*Over the course of this century, the relationship between the human world and the planet that sustains it has undergone a profound change. /…/ When the century began, neither human numbers nor technology had the power radically to alter planetary systems. As the century closes, not only do vastly increased human numbers and their activities have that power, but major, unintended changes are occurring in the atmosphere, in soils, in waters, among plants and animals and in the relationships among all of these. /…/ The next few decades are crucial. The time has come to break out of old patterns. Attempts to maintain social and ecological stability through old approaches to development and environmental protection will increase instability. /…/ We are unanimous in our conviction that the security, well-being, and very survival of the planet depend on such changes, now.* (WCED 1987 p 22 )

Three Totally Different Environmental/GDP Curves 303

When it comes to Ozone depletion one can make a curve Kuznets-like if using a spatial parameter (see Fig 12). 'Rich' countries are overrepresented in the tempered zone around the 50th latitude with higher depletion than the low GDP's closer to the equator and where there is very little GDP creation – at the two poles – we have the highest problem and more or less no GDP. So no correlation between ozone depletion and GDP. But the origins of the causative agents were from high consuming countries. But even locking at a temporal x-axis and global values the Dobson Unit-value (an indirect measurement for the amount of ozone) is decreasing despite growing gross global product (GGP). If using the Kuznets analytic frame the curve will actually take the shape of the convex part of the letter D. But then again as NOAA says "All other things being equal, and with adherence to the international agreements, the ozone layer is expected to recover over the next 50 years or so" (NOAA Internet). One can ask if it is due to political agreements or GDPs. Porter says at least that "The ozone-protection regime is considered the most effective of all global environmental

regimes to date." (Porter 2000;15)

Fig. 12 The Ozone depletion Kuznets curve. Source: CCPO

resources for other, non-human orders, declines (Wackernagel 1996).

Another great concern for the WCED was the rate at which species were extinct. WWF has created the Living planet index (see fig 13 p 302) as a measurement for biodiversity. If one wants to be ironic it could also be called the Biodiversity Kuznets curve as it is an inverted U. But in this case it does not mean improvement. The index does not recover with increased GGP, because the temporal scale could also be translated into a GGP. As seen in fig. 9 we have had an increase from 1980 and onwards. A proponent of beneficial economic growth could argue that we haven´t reached the turning point. But then again, before the turning point we should expect a leveling off trend. And that can´t be seen. In the 1970s GGP were 2500 US\$, in the 80s 4000 US\$ and in the 90s 6000 US\$/cap in current prices (2008). So the global biodiversity seems to peak or having its negative turning point around 3-3500 US\$/cap. This is in line with the ever increasing demand from us humans on nature to satisfy our needs/wants at the expense of other species. Vitousek estimates that humans now consume something like 40% of Nature's net production and every day the space and

Below I will present some of the more well known environmental threats that we face. To start with CO2 that is a major contributor to climate change fig. 10 shows that a "normal" level seems to be around 180 to 280 ppm. The right side is about 2000 years ago and the left side roughly 400.000 years ago. The top peaks are warm periods and the lower occur during ice-times. During the period that we use to call the industrial era we have managed to increase the level by using fossil fuel to nearly 400 ppm (see below, fig 15 p 303) with most likely dramatic changes in the climate. But for the sake of this paper let's compare the emitter or country with their GDP respectively to see how income contributes to the pollution or causes environmental stress. Fig. 11 shows the increase of emissions along with increased GDP. Long-term sustainable levels (by 2100) are 0,2 – 0,7 ton CO2/capita and year for a 400 ppm and 550 ppm target respectively (Azar 2002 p 20). The chart is made up by data from 148 countries and it is only 39 who manage the lower 'limit' and 35 more if you accept the upper of 0,7 ton. I think it is fair to say that high GDP countries have an 'overproduction' of CO2 emissions and that there is no Kuznets-correlation.

Fig. 10. CO2 concentration (ppm) during last 400.000 years**.** Source: Petit et al (1999)

Fig. 11. Correlation between CO2 emissions/capita and GDP.Source: own chart with data from Explore our planet for CO2-data and UNEP 2008 for GDP numbers

Sustainable Development – Education, Business and Management – 302 Architecture and Building Construction – Agriculture and Food Security

Below I will present some of the more well known environmental threats that we face. To start with CO2 that is a major contributor to climate change fig. 10 shows that a "normal" level seems to be around 180 to 280 ppm. The right side is about 2000 years ago and the left side roughly 400.000 years ago. The top peaks are warm periods and the lower occur during ice-times. During the period that we use to call the industrial era we have managed to increase the level by using fossil fuel to nearly 400 ppm (see below, fig 15 p 303) with most likely dramatic changes in the climate. But for the sake of this paper let's compare the emitter or country with their GDP respectively to see how income contributes to the pollution or causes environmental stress. Fig. 11 shows the increase of emissions along with increased GDP. Long-term sustainable levels (by 2100) are 0,2 – 0,7 ton CO2/capita and year for a 400 ppm and 550 ppm target respectively (Azar 2002 p 20). The chart is made up by data from 148 countries and it is only 39 who manage the lower 'limit' and 35 more if you accept the upper of 0,7 ton. I think it is fair to say that high GDP countries have an

'overproduction' of CO2 emissions and that there is no Kuznets-correlation.

Fig. 10. CO2 concentration (ppm) during last 400.000 years**.** Source: Petit et al (1999)

Fig. 11. Correlation between CO2 emissions/capita and GDP.Source: own chart with data

from Explore our planet for CO2-data and UNEP 2008 for GDP numbers

When it comes to Ozone depletion one can make a curve Kuznets-like if using a spatial parameter (see Fig 12). 'Rich' countries are overrepresented in the tempered zone around the 50th latitude with higher depletion than the low GDP's closer to the equator and where there is very little GDP creation – at the two poles – we have the highest problem and more or less no GDP. So no correlation between ozone depletion and GDP. But the origins of the causative agents were from high consuming countries. But even locking at a temporal x-axis and global values the Dobson Unit-value (an indirect measurement for the amount of ozone) is decreasing despite growing gross global product (GGP). If using the Kuznets analytic frame the curve will actually take the shape of the convex part of the letter D. But then again as NOAA says "All other things being equal, and with adherence to the international agreements, the ozone layer is expected to recover over the next 50 years or so" (NOAA Internet). One can ask if it is due to political agreements or GDPs. Porter says at least that "The ozone-protection regime is considered the most effective of all global environmental regimes to date." (Porter 2000;15)

Fig. 12 The Ozone depletion Kuznets curve. Source: CCPO

Another great concern for the WCED was the rate at which species were extinct. WWF has created the Living planet index (see fig 13 p 302) as a measurement for biodiversity. If one wants to be ironic it could also be called the Biodiversity Kuznets curve as it is an inverted U. But in this case it does not mean improvement. The index does not recover with increased GGP, because the temporal scale could also be translated into a GGP. As seen in fig. 9 we have had an increase from 1980 and onwards. A proponent of beneficial economic growth could argue that we haven´t reached the turning point. But then again, before the turning point we should expect a leveling off trend. And that can´t be seen. In the 1970s GGP were 2500 US\$, in the 80s 4000 US\$ and in the 90s 6000 US\$/cap in current prices (2008). So the global biodiversity seems to peak or having its negative turning point around 3-3500 US\$/cap. This is in line with the ever increasing demand from us humans on nature to satisfy our needs/wants at the expense of other species. Vitousek estimates that humans now consume something like 40% of Nature's net production and every day the space and resources for other, non-human orders, declines (Wackernagel 1996).

Three Totally Different Environmental/GDP Curves 305

say that one can see a level off (the beginning of a decline) from the end of the 80s but it could also be explained by the fact that world economic growth also took a break during that period.

The same goes for N2O, one of the unwanted gases in the atmosphere. Then the proponents of EKC chose to measure *emissions* (not concentration) from *cities* to find the downward slope. It is easy as many producers of N2O went rural. But again, as this is a gas, it is mixed in the atmosphere quite evenly distributed after what it is produced. N2O pre-industrial levels were around 260 to 280 ppb. Again one can see a steady increase which is not surprising as the emissions from combustion processes and the use of fertilizers – activities

Fig. 15. Global atmospheric concentration of three well-mixed greenhouse gases. Source:

countries. The Kyoto protocol is perhaps the most notable. (Porter 2000)

143 countries' value of Ecological Footprint.

& World Heritage. Source GEO 4 (2007 p. 9)

When it comes to environmental agreements a great number of states have ratified 14 major global environmental treaties6 within a timeframe of about 30 years without any correlation to GDP. Poor countries as well as rich countries sign independently of their GDP. As we have around 200 independent nations it is fair to say that a large part of the international community is affected by them. And it is not so that rich countries are first in line to sign. The ones that do not sign seem to have economic reasons not to and this is mostly the rich

As a sum up I will apply the widely well known ecological footprint concept in the EKC analytic framework (fig 16 p 304). As Wackernagel (the founder of the model) says "The Ecological Footprint concept is simple, yet potentially comprehensive: it accounts for the flows of energy and matter to and from any defined economy and converts these into the corresponding land/water area required from nature to support these flows." (Wackernagel 1996:3) That area is a little bit more than 2 ha/cap on a global scale. We have then excluded the needs that all non-human species may have. The conclusion from this chart is that the turning point for an ecological sustainability measured as GDP seems to be around 8000 US\$/cap. But in reality less as there are non-human biotic orders on Earth. It is drawn from

One explanation of the failure to improve the environment could be what Stern put forward when he says that there is a risk due to the global nature of the externality gives as a result

6 Like Basel, Cartagena, CBD, CITES, CMS, Kyoto, Montreal, Stockholm, UNCCD, UNCLOS, UNFCCC

belonging to the industrial era.

Mantua (2007) p 283

*This global trend suggests that we are degrading natural ecosystems at a rate unprecedented in human history. /…/ The recent downturn in the global economy is a stark reminder of the consequences of living beyond our means. But the possibility of financial recession pales in comparison to the looming ecological credit crunch.* (WWF 2008 p 1)

Fig. 13. Global Living Planet Index 1970 – 2005. Source: WWF 2008

In the World Bank report sulphur dioxide (SO2) was one of the two substances that were empirically tested. The other one was N2O. When measuring cities there seems to be a drop in SO2 concentrations but as stated earlier it is due to political will combined with economic reasons. Industries moved out of cities, we built nuclear plants, we taxed sulphur containing oil etc. But looking at larger geographic entities the inverted U-shaped curve is hard to detect (fig 14). Concentration is correlated to emission in a limited atmosphere). An optimist might

Fig. 14. World SO2 emission (million metric tons) Source: Downing et al 1997

Sustainable Development – Education, Business and Management – 304 Architecture and Building Construction – Agriculture and Food Security

*This global trend suggests that we are degrading natural ecosystems at a rate unprecedented in human history. /…/ The recent downturn in the global economy is a stark reminder of the consequences of living beyond our means. But the possibility of financial recession pales in*

In the World Bank report sulphur dioxide (SO2) was one of the two substances that were empirically tested. The other one was N2O. When measuring cities there seems to be a drop in SO2 concentrations but as stated earlier it is due to political will combined with economic reasons. Industries moved out of cities, we built nuclear plants, we taxed sulphur containing oil etc. But looking at larger geographic entities the inverted U-shaped curve is hard to detect (fig 14). Concentration is correlated to emission in a limited atmosphere). An optimist might

*comparison to the looming ecological credit crunch.* (WWF 2008 p 1)

Fig. 13. Global Living Planet Index 1970 – 2005. Source: WWF 2008

Fig. 14. World SO2 emission (million metric tons) Source: Downing et al 1997

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1960

1962

1964

1966

1968

1970

say that one can see a level off (the beginning of a decline) from the end of the 80s but it could also be explained by the fact that world economic growth also took a break during that period.

The same goes for N2O, one of the unwanted gases in the atmosphere. Then the proponents of EKC chose to measure *emissions* (not concentration) from *cities* to find the downward slope. It is easy as many producers of N2O went rural. But again, as this is a gas, it is mixed in the atmosphere quite evenly distributed after what it is produced. N2O pre-industrial levels were around 260 to 280 ppb. Again one can see a steady increase which is not surprising as the emissions from combustion processes and the use of fertilizers – activities belonging to the industrial era.

Fig. 15. Global atmospheric concentration of three well-mixed greenhouse gases. Source: Mantua (2007) p 283

When it comes to environmental agreements a great number of states have ratified 14 major global environmental treaties6 within a timeframe of about 30 years without any correlation to GDP. Poor countries as well as rich countries sign independently of their GDP. As we have around 200 independent nations it is fair to say that a large part of the international community is affected by them. And it is not so that rich countries are first in line to sign. The ones that do not sign seem to have economic reasons not to and this is mostly the rich countries. The Kyoto protocol is perhaps the most notable. (Porter 2000)

As a sum up I will apply the widely well known ecological footprint concept in the EKC analytic framework (fig 16 p 304). As Wackernagel (the founder of the model) says "The Ecological Footprint concept is simple, yet potentially comprehensive: it accounts for the flows of energy and matter to and from any defined economy and converts these into the corresponding land/water area required from nature to support these flows." (Wackernagel 1996:3) That area is a little bit more than 2 ha/cap on a global scale. We have then excluded the needs that all non-human species may have. The conclusion from this chart is that the turning point for an ecological sustainability measured as GDP seems to be around 8000 US\$/cap. But in reality less as there are non-human biotic orders on Earth. It is drawn from 143 countries' value of Ecological Footprint.

One explanation of the failure to improve the environment could be what Stern put forward when he says that there is a risk due to the global nature of the externality gives as a result

6 Like Basel, Cartagena, CBD, CITES, CMS, Kyoto, Montreal, Stockholm, UNCCD, UNCLOS, UNFCCC & World Heritage. Source GEO 4 (2007 p. 9)

Three Totally Different Environmental/GDP Curves 307

which spewed 11 million gallons of crude oil over the pristine shores of Alaska in 1989, also

We use PPP (a cost-of-living adjustment between different countries) or McDonald index to make GDP figures more comparable. Inflation is also excluded to make figures from different years analogous. But shouldn't we also implement a quality factor? Before the time of mass consumption I think we can agree that dairies were more 'natural'. Industrial efficiency had not at that time influenced the quality with artificial additives to speed up production or allow for longer transportation and/or shelf-life in the store. Is a small farm chicken from 1920 in quality comparable to an industrial chemically stuffed chicken from the 21th century? GDP is supposed to measure the production, how much we can consume. The work we have to put in to get a chicken is much less today – so we are richer. But GDP will not be adjusted for the quality change. A friend of order might say that we are paying more for the 'bio-chicken'. Yes that is true, but should we then compare the 1920s chicken

The reason for doing the GDP/Environmental stress relation curve is that GDP is considered a measure of standard of living. But is it? The Human Development Index, which also includes life span expectation, literacy and provisions of schools and the Genuine Progress Index aggregate something like 15 different parameters to measure human wellbeing, suggest otherwise. Other scholars like Maslow, Max-Neff and Dodds (Dodds 1997) argue that the quality of life is much more intricate to measure than to reduce it to the

In the case of environmental curves it could be argued that what has been measured to create the inverted U-shape curve is *urban* concentrations/emission of pollutants. These have been compared to a parameter that measures the performance for a whole country. So by moving out production sites from cities to rural areas one can decrease urban pollution and at the same time keep the high GDP. This movement was quite profound in the 1960s and 70s due to very high prices for real estates in central city areas of high income countries. The numbers in GDP are *sales-figures*. When the producer sells a liter of gasoline for say 1,5 € that will be added to the GDP. But at the same time when we consume the gas we lose the resource (the capital valued 1,5 ) and that is not counted for. When it is used it will also add to the CO2-concentration in the atmosphere (environmental costs) and that is not either reduced from the GDP. When looking at corporations' key performance indicators, the normal thing is to read the balance-sheet to find the value of different assets and debts. The most common markers are liquidity and solidity. Only sales figures are not the primary source of information when we want to know the status of a company's economic situation. At least we need a consolidated statement of income with both sales *and* costs. We want to see if we have made a profit. It is the balance-sheet that gives us the information about the amount of resources (capital) we have and over time tells us if these are growing or decreasing. On the debt side we have the value of how much we owe the suppliers. To make a comparison with the global world, an environmentalist could argue that this is the same as the value humans have taking out of the environment without "paying" back. And if we don't pay our suppliers the will stop to deliver. In this world it is the Nature that delivers the needed resources to society. Companies without suppliers are impossible to run and it is

led to a short GDP increase due to the costs of the massive clean-up operation.

with the bio-chicken to see how much richer we really have become?

pecuniary value of the industrial production.

that individuals find very little incentives to act (Stern 2007). It is a similar approach that Harding (Harding 1968) presents in his widely cited article *The tragedy of the commons.*

Fig. 16. Ecological Footprint for different countries vs their GDP. Source: own drawing by data from WWF 2008:32-4 and UNDP 2008

#### **4. The problems with the GDP-parameter**

Adam Smith's renowned book *Wealth of Nations* (Smith 1776) starts with this paragraph

*The annual labour of every nation is the fund which originally supplies it with all the necessaries and conveniences of life which it annually consumes, and which consist always either in the immediate produce of that labour, or in what is purchased with that produce from other nations.*

This is the foundation for the idea of GDP, to measure the value of the work the inhabitants of a nation is producing during a year. To know how much they could spend. The x-axis in this survey has mostly been GDP (if not it could be translated to GDP) but that is a very dynamic parameter. It could be measured in 3 different ways,

But it is only transactions that are registered that counts. We do not know the proportions of expenditures or as in the case of China's production and internal consumption as they lend part of the result for someone else to consume (USA). We do not know the Gini-coefficient or division between profit and salary and at what time the money is consumed. We have both a temporal and spatial displacement of GDP and environmental consequences. A paradox is also that ecological disasters create GDP. As an example, the Exxon Valdez tanker disaster, Sustainable Development – Education, Business and Management – 306 Architecture and Building Construction – Agriculture and Food Security

that individuals find very little incentives to act (Stern 2007). It is a similar approach that

Fig. 16. Ecological Footprint for different countries vs their GDP. Source: own drawing by

Adam Smith's renowned book *Wealth of Nations* (Smith 1776) starts with this paragraph

*produce of that labour, or in what is purchased with that produce from other nations.*

dynamic parameter. It could be measured in 3 different ways,

savings + government spending + (exports – imports)

*The annual labour of every nation is the fund which originally supplies it with all the necessaries and conveniences of life which it annually consumes, and which consist always either in the immediate*

This is the foundation for the idea of GDP, to measure the value of the work the inhabitants of a nation is producing during a year. To know how much they could spend. The x-axis in this survey has mostly been GDP (if not it could be translated to GDP) but that is a very

1. GDP as value added of goods and services (or the value of production at the consumer

3. GDP as supply balance or expenditures (GNP = (private) consumption + investments/

But it is only transactions that are registered that counts. We do not know the proportions of expenditures or as in the case of China's production and internal consumption as they lend part of the result for someone else to consume (USA). We do not know the Gini-coefficient or division between profit and salary and at what time the money is consumed. We have both a temporal and spatial displacement of GDP and environmental consequences. A paradox is also that ecological disasters create GDP. As an example, the Exxon Valdez tanker disaster,

data from WWF 2008:32-4 and UNDP 2008

2. GDP as the sum of profits and salaries

level)

**4. The problems with the GDP-parameter**

Harding (Harding 1968) presents in his widely cited article *The tragedy of the commons.*

which spewed 11 million gallons of crude oil over the pristine shores of Alaska in 1989, also led to a short GDP increase due to the costs of the massive clean-up operation.

We use PPP (a cost-of-living adjustment between different countries) or McDonald index to make GDP figures more comparable. Inflation is also excluded to make figures from different years analogous. But shouldn't we also implement a quality factor? Before the time of mass consumption I think we can agree that dairies were more 'natural'. Industrial efficiency had not at that time influenced the quality with artificial additives to speed up production or allow for longer transportation and/or shelf-life in the store. Is a small farm chicken from 1920 in quality comparable to an industrial chemically stuffed chicken from the 21th century? GDP is supposed to measure the production, how much we can consume. The work we have to put in to get a chicken is much less today – so we are richer. But GDP will not be adjusted for the quality change. A friend of order might say that we are paying more for the 'bio-chicken'. Yes that is true, but should we then compare the 1920s chicken with the bio-chicken to see how much richer we really have become?

The reason for doing the GDP/Environmental stress relation curve is that GDP is considered a measure of standard of living. But is it? The Human Development Index, which also includes life span expectation, literacy and provisions of schools and the Genuine Progress Index aggregate something like 15 different parameters to measure human wellbeing, suggest otherwise. Other scholars like Maslow, Max-Neff and Dodds (Dodds 1997) argue that the quality of life is much more intricate to measure than to reduce it to the pecuniary value of the industrial production.

In the case of environmental curves it could be argued that what has been measured to create the inverted U-shape curve is *urban* concentrations/emission of pollutants. These have been compared to a parameter that measures the performance for a whole country. So by moving out production sites from cities to rural areas one can decrease urban pollution and at the same time keep the high GDP. This movement was quite profound in the 1960s and 70s due to very high prices for real estates in central city areas of high income countries.

The numbers in GDP are *sales-figures*. When the producer sells a liter of gasoline for say 1,5 € that will be added to the GDP. But at the same time when we consume the gas we lose the resource (the capital valued 1,5 ) and that is not counted for. When it is used it will also add to the CO2-concentration in the atmosphere (environmental costs) and that is not either reduced from the GDP. When looking at corporations' key performance indicators, the normal thing is to read the balance-sheet to find the value of different assets and debts. The most common markers are liquidity and solidity. Only sales figures are not the primary source of information when we want to know the status of a company's economic situation. At least we need a consolidated statement of income with both sales *and* costs. We want to see if we have made a profit. It is the balance-sheet that gives us the information about the amount of resources (capital) we have and over time tells us if these are growing or decreasing. On the debt side we have the value of how much we owe the suppliers. To make a comparison with the global world, an environmentalist could argue that this is the same as the value humans have taking out of the environment without "paying" back. And if we don't pay our suppliers the will stop to deliver. In this world it is the Nature that delivers the needed resources to society. Companies without suppliers are impossible to run and it is

Three Totally Different Environmental/GDP Curves 309

Meadows' *Limits to Growth* (Meadows et al 1972) where the conclusion is that we *might* run out of vital resources if humanity continues to exploit the nature at current exponential pace and finally the reports about Ozone depletion ( Molina, M. 1974, Rowland, F 1994) and part

If we scrutinize the debate within the scientific community regarding these three examples, I am convinced we will find that that the academic world is invested with values and that an ideology orientation is a partial compass when we do research. Scholars are guided by what Söderbaum (2008) calls a mental map and Schumpeter (1954) a preanalytic cognitive act. Daly puts it this way; "One might say that vision is the pattern or shape of the reality in question that the right hemisphere of the brain abstracts from experience. Whatever is omitted from the preanalytic vision cannot be recaptured by subsequent analysis"(Daly 2004 p 23). In my opinion we should start to more openly discuss if it is time to include the

When it comes to opinions about environmental curves it is easiest to find pro and contra arguments for the EKC as this is the one where establishment and environmentalists clash. When we look the other way around, towards the EDC it seems that industrialists and producers use the tactic of silence. One has to go back to the beginning of the 1970s after the publication of *Limits to Growth* to find any substantial attack on the environmentalists idea of limits to growth. The Brundtland world-view on environmental curves is not as controversial as 'she' has a solution for the high income countries – eco modernization. Although the moral dilemma with transnational displacement of 'dirty' production to developing countries and keeping the high GDP generating high-tech 'clean' production in the West is a question of fair distribution. But then who is going to produce the commodities

The EKC seems to be a time limited success in a local jurisdiction. And the reason for its appearance does not seem to be environmental consciousness but economic consequences. The losses for forest owners in Northern Europe due to the so called 'acid rain' triggered the political community to action. After Rachel Carsons book *Silent Spring* and that her qualms were verified in Minamata, and Itai-itai, (chemical poisoning) the Club of Rome's *Limits to Growth* and other environmental publications forced the politicians to act with more legislation to satisfy local opinion. This was amplified by the first so called oil crisis in the

It is hard to find environmental stock/GDP-curves of 'catches' from Nature (i.e. mines, forests or fisheries) that shows a long run sustainability. Instead 'The Newfoundland Cod fishing environmental Curve' could be a good example. For over five centuries the Grand Banks off the coast of the Canadian island of Newfoundland were the richest fishing grounds in the world. The moral of the Newfoundland cod collapse is simple: overexploiting natural resources such as fisheries, forests or raw materials is good for short term GDP growth but disastrous for ecosystems, economies and communities in the long term. When it comes to EBC there has been no debate as it is my own invention. One can albeit say that it gets support from UNEP, but the arguments again is deforestation, desertification. And for these arguments Brundtland is very inconsistent, to say the least,

of the argumentations that followed their publications.

writer's values in the scientific method to make it credible.

we in the west want for a low price is a question that is not answered.

**6. Conclusion**

beginning of the 1970s.

quite obvious that society without the Nature as provider of de natural resources we cannot continue to run Mother Earth.

Could it be that institutional stability both enhance growth and environmental benefits and that the GDP itself is not the mainspring to environmental improvements? So when there is growth we can sometimes see local improvements not because of the growth *per se,* but due to responsible politicians who both creates stability (for growth) and take sustainability a little bit more seriously than in countries with less developed institutions? As said in Brunetti's work *Politics and economic growth* at least "that a political system that include transparent, orderly, incremental law-making process" and a broad citizens participation via a strong party system, is needed to be growth enhancing. (Brunetti 1997) The World Bank itself in the report from 1992 states that it is politics, not the GDP-level, that determines the environmental outcome.

#### **5. Discussion**

Can we afford every country to develop economically and pass the "turning point"? What will happen to the environment on the journey up to the top of the curve? It seems that the environmental negative trespassing point – when we consume more than we have – lays around 8.000 US\$ (see fig. 17, footprint/GDP-diagram) with current global population. If everybody is going to have that income and keep present consumption patterns we need 4 to 5 planets Earth ???? If the Earth we have has a limited capacity and sustainable development is about satisfying everyone's needs and if we want to lift the low GDP countries towards a decent standard of living it has to be at the expense of the 'Rich'.

Another way to do it, is to slowly and in an orderly way take low income countries, one by one in a pace that the ecosphere can stand, over the 'hill' to the 'blessed' high income, low environmental impact countries. But that could only be good policy if you believe in the Kuznets curve. The empiric evidence has shown that this is not the case, at least not for global problems. It seems that they get worse with increased GDP. So we have a paradox. What could be the guideline if locally perceived problems are solved with increased GDP but global real, but unperceived, stresses get worse by the same economic growth?

And another matter of concern is the question, what will happen to the credibility of the academic world if we with our scientific methods (that are legitimizing us) can deliver answers or theories to totally different world views, that logically cannot co-exist?

An additional unease is the issue of finding a mutual or joint solution to begin the journey on the path towards sustainable development if different paradigms like business as usual that believe in the free market, the eco-modernist who believes in indefinite human creativity to solve problems and the doomsday prophets who are totally convinced about the ecosphere's absolute limits, can get answers from the scientific society that make them feel confident that they are themselves right respectively and the others are wrong.

Due to lack of space it is not possible to expand this perspective of different actorgroups (including scientists) trying to influence the interpretation of research results. I have read Coase's. *The Problem of Social Cost* (Coase 1960), which was the background paper for what was later created as the so called Coaese theorem, which states that there are possibilities to find a free-market solution to environmental stress (Coase himself has the opposite opinion). Meadows' *Limits to Growth* (Meadows et al 1972) where the conclusion is that we *might* run out of vital resources if humanity continues to exploit the nature at current exponential pace and finally the reports about Ozone depletion ( Molina, M. 1974, Rowland, F 1994) and part of the argumentations that followed their publications.

If we scrutinize the debate within the scientific community regarding these three examples, I am convinced we will find that that the academic world is invested with values and that an ideology orientation is a partial compass when we do research. Scholars are guided by what Söderbaum (2008) calls a mental map and Schumpeter (1954) a preanalytic cognitive act. Daly puts it this way; "One might say that vision is the pattern or shape of the reality in question that the right hemisphere of the brain abstracts from experience. Whatever is omitted from the preanalytic vision cannot be recaptured by subsequent analysis"(Daly 2004 p 23). In my opinion we should start to more openly discuss if it is time to include the writer's values in the scientific method to make it credible.

#### **6. Conclusion**

Sustainable Development – Education, Business and Management – 308 Architecture and Building Construction – Agriculture and Food Security

quite obvious that society without the Nature as provider of de natural resources we cannot

Could it be that institutional stability both enhance growth and environmental benefits and that the GDP itself is not the mainspring to environmental improvements? So when there is growth we can sometimes see local improvements not because of the growth *per se,* but due to responsible politicians who both creates stability (for growth) and take sustainability a little bit more seriously than in countries with less developed institutions? As said in Brunetti's work *Politics and economic growth* at least "that a political system that include transparent, orderly, incremental law-making process" and a broad citizens participation via a strong party system, is needed to be growth enhancing. (Brunetti 1997) The World Bank itself in the report from 1992 states that it is politics, not the GDP-level, that determines

Can we afford every country to develop economically and pass the "turning point"? What will happen to the environment on the journey up to the top of the curve? It seems that the environmental negative trespassing point – when we consume more than we have – lays around 8.000 US\$ (see fig. 17, footprint/GDP-diagram) with current global population. If everybody is going to have that income and keep present consumption patterns we need 4 to 5 planets Earth ???? If the Earth we have has a limited capacity and sustainable development is about satisfying everyone's needs and if we want to lift the low GDP

countries towards a decent standard of living it has to be at the expense of the 'Rich'.

but global real, but unperceived, stresses get worse by the same economic growth?

answers or theories to totally different world views, that logically cannot co-exist?

feel confident that they are themselves right respectively and the others are wrong.

Another way to do it, is to slowly and in an orderly way take low income countries, one by one in a pace that the ecosphere can stand, over the 'hill' to the 'blessed' high income, low environmental impact countries. But that could only be good policy if you believe in the Kuznets curve. The empiric evidence has shown that this is not the case, at least not for global problems. It seems that they get worse with increased GDP. So we have a paradox. What could be the guideline if locally perceived problems are solved with increased GDP

And another matter of concern is the question, what will happen to the credibility of the academic world if we with our scientific methods (that are legitimizing us) can deliver

An additional unease is the issue of finding a mutual or joint solution to begin the journey on the path towards sustainable development if different paradigms like business as usual that believe in the free market, the eco-modernist who believes in indefinite human creativity to solve problems and the doomsday prophets who are totally convinced about the ecosphere's absolute limits, can get answers from the scientific society that make them

Due to lack of space it is not possible to expand this perspective of different actorgroups (including scientists) trying to influence the interpretation of research results. I have read Coase's. *The Problem of Social Cost* (Coase 1960), which was the background paper for what was later created as the so called Coaese theorem, which states that there are possibilities to find a free-market solution to environmental stress (Coase himself has the opposite opinion).

continue to run Mother Earth.

the environmental outcome.

**5. Discussion**

When it comes to opinions about environmental curves it is easiest to find pro and contra arguments for the EKC as this is the one where establishment and environmentalists clash. When we look the other way around, towards the EDC it seems that industrialists and producers use the tactic of silence. One has to go back to the beginning of the 1970s after the publication of *Limits to Growth* to find any substantial attack on the environmentalists idea of limits to growth. The Brundtland world-view on environmental curves is not as controversial as 'she' has a solution for the high income countries – eco modernization. Although the moral dilemma with transnational displacement of 'dirty' production to developing countries and keeping the high GDP generating high-tech 'clean' production in the West is a question of fair distribution. But then who is going to produce the commodities we in the west want for a low price is a question that is not answered.

The EKC seems to be a time limited success in a local jurisdiction. And the reason for its appearance does not seem to be environmental consciousness but economic consequences. The losses for forest owners in Northern Europe due to the so called 'acid rain' triggered the political community to action. After Rachel Carsons book *Silent Spring* and that her qualms were verified in Minamata, and Itai-itai, (chemical poisoning) the Club of Rome's *Limits to Growth* and other environmental publications forced the politicians to act with more legislation to satisfy local opinion. This was amplified by the first so called oil crisis in the beginning of the 1970s.

It is hard to find environmental stock/GDP-curves of 'catches' from Nature (i.e. mines, forests or fisheries) that shows a long run sustainability. Instead 'The Newfoundland Cod fishing environmental Curve' could be a good example. For over five centuries the Grand Banks off the coast of the Canadian island of Newfoundland were the richest fishing grounds in the world. The moral of the Newfoundland cod collapse is simple: overexploiting natural resources such as fisheries, forests or raw materials is good for short term GDP growth but disastrous for ecosystems, economies and communities in the long term.

When it comes to EBC there has been no debate as it is my own invention. One can albeit say that it gets support from UNEP, but the arguments again is deforestation, desertification. And for these arguments Brundtland is very inconsistent, to say the least,

Three Totally Different Environmental/GDP Curves 311

http://www.ccpo.odu.edu/~lizsmith/SEES/ozone/class/Chap\_9/index.htm

Coase, R. (1960) The Problem of Social Cost. *Journal of Law and Economics*, 3(1) pp 1-44 Daly, H. (2007) *Ecological Economics and Sustaiable Development.* Edgar Elgar Cheltenham, UK. Daly, H., Farley, J. (2004) *Ecological Economics. Principles and applications*. Island Press, London Dasgupta, P. and Mäler, K.-G. (1994): *Poverty, Institutions, and the Environmental-Resource*

Dearing, J.A. (2007) Human-Environment interaction: learning from the past. In Costanza, R,

Dodds, S. (1997) Towards a 'science of sustainability': Improving the way ecological economics understands human well-being. *Ecological Economics* 23 (1997) 95-111 Downing, R., R. Ramankutty, J. Shah, (1997) *RINS-ASIA: An Assessment Model for Acid*

Dryzek, J.S. (1997) *The Politics of the Earth – Environmental Discources*. Oxford University

http://exploreourpla.net/climate-change/co2-emissions-historical [2011-06-15) Friman, E. (2002) *No Limits, the 20th Century Discourse of Economic Growth* Skrifter från

ESI (2005*) Environmental Sustainability* Index. http://www.yale.edu/esi/ [2011-09-25]

GEO4 (2007) *Environment for development*. UNEP http://www.unep.org/geo/geo4.asp Grossman, G. Krueger, A. (1995): Economic Growth and the Environment, *Quarterly Journal*

Humphreys, D. (2006) *Logjam: deforestation and the crisis of global governance*. Earthscan, London

Lambin, E., et al . (2007) Integrated Human Environment Approaches of Land Degradation

Mankiw, G. (2008) *Principles of economics 5th ed. South-Western Cengage Learning*. Mason, Ohio,

Mantua, N. (2007) Decadal Chronolgy of 20th-Century Changes. In Costanza, R, Graumlich,

Molina, M., Rowland, F. (1974) Stratospheric sink for chloroflouromethanes: chlorine atom-

Mäler, K-G. (1993) Growth and environment. In SOU 1993:16 *Nya villkor för ekonomi och politik*  Mäler, K-G. (1994) *Economic Growth and the Environment*. Beijer Reprint Series No. 37 NASA, http://earthobservatory.nasa.gov/Features/Arrhenius/ [2011-06-15]

in Drylands. In Costanza, R, Graumlich, L. and Steffen, W. (ed.) *Sustainability or Collapse? An intergrated history and future of people on Earth*. The MIT Press, London,

L. and Steffen, W. (ed.) *Sustainability or Collapse? An intergrated history and future of*

Graumlich, L., and Steffen, W. (ed) *Sustainability or Collapse? An intergrated history*

CCPO (Center for Coastal Physical Oceanography, Old Dominion University)

Cherni,J. (2002) *Economic growth versus the Environment*. Palgrave, Basingstoke.

*and future of people on Earth*.The MIT Press, London, U.K.

*Deposition in Asia*. The World Bank, Washington, D.C.

institutionen för historiska studier 2, Umeå universitet.

Harding, G. ( 1968) The tragedy of the commons. *Science* 162(1968):1243-1248

Kahn, H. et al (1976) *The Next 200 Years*. William Morrow, New York.

Hermele, K. 1995. *Ekonomerna, tillväxten och miljön*. Stockholm: Carlsson Bokförlag.

Lindmark, M. (1998) *Towards Environmental Historical National Accounts for Sweden*.

*people on Earth.* The MIT Press, London, U.K. p. 277-299 Meadows, et al (1972*) The limits to growth*. Universe Books, New York

catalysed destruction of ozone. *Nature* 1974:249, pp 810-812

*of Economics*, vol. 110, pp. 353-377

IMF (2008) World *Economic Outlook*, April 2008 Ed.

Clark, M. (2002) *In search of Human Nature*. Routledge, London.

*Base*, World Bank Environment Paper no. 8,

[2011-06-15]

Press, Oxford

U.K. p. 337-352

USA

Explore our planet

and UNEP doesn't show any empirical evidence. It is just an opinion. When it comes to deforestation there are a lot of other factors influencing the outcome. And as deforestation also is a cause for desertification, it follows that neither WCED nor UNEP can state that low income countries are the cause. The arguments for the poor to be a major cause of environmental deterioration are very 'poor'.

The critique against the environmentalist is that they forget to include technical innovations and human creativity. They are normally doomsday prophets. Another argument is that the Business as usual group can show improvements in richer countries – they can afford to clean up. What they forget is displacement or the rucksack.

One must keep in mind that EKC deals with waste, (emission or concentration), EBC deals with production as an agent for environmental degradation at least in poor countries whereas EDC and ecological footprints look at consumption as the parameter to measure. But as Marx already said, production is at the same time consumption – consumption of natural resources.

If one concentrates the global environmental problems to the ones defined by WCED and tries to find empiric evidence, it is quite obvious that there is no decoupling between GDP and environmental problems. Instead it seems that there is a positive monotonic relationship between economic growth and environmental problems.

#### **7. Acknowledgment**

I wish to thank the editorial board of InTech for finding interest in my studies and that they publish my thoughts. Because writing, without readers has very limited value.

#### **8. References**

Beckerman, W. (1974), *In Defense of Economic Growth*. London: Cape.

Brunetti, A. (1997) *Politics and economic growth*. OECD, Paris

Brännlund, K., Kriström, B. (1998) *Miljöekonomi* Studentlitteratur, Lund

Sustainable Development – Education, Business and Management – 310 Architecture and Building Construction – Agriculture and Food Security

and UNEP doesn't show any empirical evidence. It is just an opinion. When it comes to deforestation there are a lot of other factors influencing the outcome. And as deforestation also is a cause for desertification, it follows that neither WCED nor UNEP can state that low income countries are the cause. The arguments for the poor to be a major cause of

The critique against the environmentalist is that they forget to include technical innovations and human creativity. They are normally doomsday prophets. Another argument is that the Business as usual group can show improvements in richer countries – they can afford to

One must keep in mind that EKC deals with waste, (emission or concentration), EBC deals with production as an agent for environmental degradation at least in poor countries whereas EDC and ecological footprints look at consumption as the parameter to measure. But as Marx already said, production is at the same time consumption – consumption of natural resources. If one concentrates the global environmental problems to the ones defined by WCED and tries to find empiric evidence, it is quite obvious that there is no decoupling between GDP and environmental problems. Instead it seems that there is a positive monotonic

I wish to thank the editorial board of InTech for finding interest in my studies and that they

Andrén, S. (2004) *Hållbar tillväxt - möjlighet eller motsägelse?: En granskning av EU:s Lissabonstrategi ur ett humanekologiskt perspektiv.* Master thesis, Lunds Universitet Arrow, K. (1995) Economic Growth, Carrying Capacity and the Environment. *Science vol 268*

Azar, C., Holmberg, J., Karlsson, S., (2002). Decoupling - past trends and prospects for the

Beckerman, W. (1995) *Small is Stupid: Blowing the Whistle on the Greens*. London: Duckworth. Booth, D. (2004) *Hooked on growth – economic addictions and the environment.* Rowman &

Bratt, L. (2006) Ecological economics – worldviews of the initiators and their conclusions. In

Bratt, L. (2009) The Brundtland link between poverty and environmental degradation, and

future. Paper commissioned by the Swedish Environmental Advisory Council (Miljövårdsberedningen). http://www.sou.gov.se/mvb/pdf/decoupling.pdf Barnett, H., Morse, C (1963) *Scarcity and Growth: The Economics of Natural Resource*

*Availability.* Baltimore: lohns Hopkins University Press for Resources for the Future.

Frostell B. ed*. Science for Sustainable Development*. Proceedings 1th VHU conference,

other questionable opinions. *Int. J. Innovation and Sustainable Development*, Vol. 4,

environmental deterioration are very 'poor'.

**7. Acknowledgment**

**8. References**

*1995*

Västerås

No. 1, pp. 74–92.

clean up. What they forget is displacement or the rucksack.

relationship between economic growth and environmental problems.

Beckerman, W. (1974), *In Defense of Economic Growth*. London: Cape.

Littlefield Publisher Inc, Oxford

Brunetti, A. (1997) *Politics and economic growth*. OECD, Paris

Brännlund, K., Kriström, B. (1998) *Miljöekonomi* Studentlitteratur, Lund

publish my thoughts. Because writing, without readers has very limited value.

	- http://exploreourpla.net/climate-change/co2-emissions-historical [2011-06-15)

**16**

*China*

**Temporal-Spatial Changes of the Oasis in**

Yaowen Xie, Linlin Li, Xiaojiong Zhao and Chunxia Yuan *College of Earth and Environmental Sciences, Lan Zhou University*

**the Heihe River Basin over the Past 25 Years**

In China, the arid area occupies a quarter of the total area of the land. It mainly distributes in five provinces: Gansu, Ningxia, Qinghai, Xinjiang and Inner Mongolia. In the arid area, oasis is the special landscape on the background of deserts. It is not only the most centralized area of human activities but also the largest area where human disturbances happen at the regional scale. Oasis covers only 4%–5% of the area of the arid region, whereas they load over 90% of the population and 95% of the social wealth in this area (Li et al., 2007). Therefore, oasis plays very important roles in the economic and social development. In recent 60 years, the articial oasis of this region kept expanding, as a result, living space of human beings became larger, and the overall productivity and capability were improved as well, which made great contribution to the development of regional economy. However, the ecological environment of the arid area is fragile due to the dry climate, scarce rainfall and short water resource. Consequently, over exploitation on oasis led to imbalanced and unreasonable reallocation of water resource, which further make the local water cycle process changed and finally results in salinization, desertification and wind erosion in other parts (Wang, 2009). If no effective measures are taken, stability of the oasis and sustainable development of the economy in arid area of China will face serious threats. Britannica Concise Encyclopedia defines oasis as fertile tract of land on the background of a desert where a perennial supply of fresh water is available. Oases vary in size, ranging from about 2.5 acres (1 hectare) around small springs to vast areas of naturally watered or irrigated land (Britannica Concise Encyclopedia, 2006); Wikipedia considers oasis as an isolated area of vegetation in a desert. In this study the oasis particularly refers to the dominated vegetation coverage growing in oasis area in view of the value of ecosystem

Remote sensing images have been used as a source of information for detecting land-use and land-cover changes at local, regional, and global scales in recent decades. Many scientists have investigated oasis ecosystem of western China using satellite data and some valuable results have been obtained. Luo (2003) constructed the process of land use/land cover change in the oasis of the arid region using remote sensing imagery data of 1979, 1987 and 1998; Tian (2011) studied the spatial-temporal processes of oasis development in the middle reaches of the Heihe River based on a time series of the normalized difference vegetation index (NDVI) derived from the 16-day composite MOD13A2 data with a spatial

**1. Introduction**

services and research conveniences.

NOAA http://www.ozonelayer.noaa.gov/science/basics.htm [2011-09-25]

## **Temporal-Spatial Changes of the Oasis in the Heihe River Basin over the Past 25 Years**

Yaowen Xie, Linlin Li, Xiaojiong Zhao and Chunxia Yuan *College of Earth and Environmental Sciences, Lan Zhou University China*

#### **1. Introduction**

Sustainable Development – Education, Business and Management – 312 Architecture and Building Construction – Agriculture and Food Security

Panayotou, T. (1993) *Emperical Tests and policy analysis of environmental degradation at different*

Pearce, D. (1993) *Sustainable Development and developing countries economies*. In Turner, R. ed.

Perman, R., Stern, D. (2003) Evidence from panel root and cointegration tests that the

Perrings, C. (1989) Environmental bonds and environmental research in innovative activites.

Petit et al. (1999) Climate and atmospheric history of the past 400.000 years from Vostok ice

Radetzki, M. (1992): Economic Growth and the Environment, in: P. Low, (ed*.): International*

Radetzki, M. (2001): *Den gröna myten – ekonomisk tillväxt och miljöns kvalitet*. SNS Förlag,

Rowland, F., Molina, M. (1994) Ozone depletion: 20 years after the alarm. *Chemical and*

Simon, J., Kahn, H. (1984) *The Resourceful Earth: A Response to the Global 2000 Report.*New

Smith, A. (1776) *An Inquiry into the Nature and Causes of the Wealth of Nations*. 5th ed. 1904.

Stern, D. (Internet) *The Environmental Kuznets Curve* . http://www.ecoeco.org/pdf/stern.pdf

Stern, N. (2007) *The Economics of Climate Change: The Stern Review*. Cambridge University Press. Söderbaum, P. (2008) *Understanding Sustainability Economics – towards pluralism in economics*.

Wackernagel, M., Rees, W.(1996) *Our ecological footprint – reducing human impact on the Earth.*

World Bank (1992) *World Development Report 1992: Development and the Environment*

Schumpeter, J. (1954) *History of economic analysis*. Oxford University Press, Oxford.

SOU 2000:7 *App. 2 Långtidsutredningen Miljö och ekonomi – scenarier fram till 2015*

*Trade and the Environment World Bank Discussion* Paper no. 159, Washington D.C.,

*stages of economic development*. Working paper 238, Technology and employment

(1993) Sustainable Environmental economics and management. Belhaven Press,

environmental Kuznets curve does not exist. *Australian Journal of Agricultural and*

NOAA http://www.ozonelayer.noaa.gov/science/basics.htm [2011-09-25]

program. International Labour Office, Geneva

core, Antartica. *Nature* vol. 399 (6735), pp, 429-436 Porter, G. (2000) *Global Environmental Politics*. Westview Press, Oxford

Radetzki, M. (1991) *Tillväxt och Miljö*. SNS förlag, Stockholm

OECD (1991) *The State of the Environment*

London. p. 72-105

pp. 121-136

Stockholm.

[2011-06-15]

Earthscan, London.

*Resource* Economicsvol 47

*Ecological economics* 1(1989) 95-110

*Engeneering* News 1994:72 pp 8-13

York: Basil Blackwell.

Methuen & Co., Ltd. London SOU 2000:7 *The long-term survey1999/2000*

UNDP (2008) *Human Development Report 2007/2008*

SOU 2000:*7 App. 7 Långtidsutredningen Vad är hållbar utveckling*

Vogel, M. (1999) *Environmental Kuznets Curves Springer Berlin*

UNEP (1999) *GEO2000, UNEP's Millennium Report on the Environment*

New Society Publishers, Gabriola Island, Canada. WCED (1987) *Our Common Future*. Oxford University Press, Oxford

WWF (2008) *Living Planet Report 2008*. World Wildlife Foundation

In China, the arid area occupies a quarter of the total area of the land. It mainly distributes in five provinces: Gansu, Ningxia, Qinghai, Xinjiang and Inner Mongolia. In the arid area, oasis is the special landscape on the background of deserts. It is not only the most centralized area of human activities but also the largest area where human disturbances happen at the regional scale. Oasis covers only 4%–5% of the area of the arid region, whereas they load over 90% of the population and 95% of the social wealth in this area (Li et al., 2007). Therefore, oasis plays very important roles in the economic and social development. In recent 60 years, the articial oasis of this region kept expanding, as a result, living space of human beings became larger, and the overall productivity and capability were improved as well, which made great contribution to the development of regional economy. However, the ecological environment of the arid area is fragile due to the dry climate, scarce rainfall and short water resource. Consequently, over exploitation on oasis led to imbalanced and unreasonable reallocation of water resource, which further make the local water cycle process changed and finally results in salinization, desertification and wind erosion in other parts (Wang, 2009). If no effective measures are taken, stability of the oasis and sustainable development of the economy in arid area of China will face serious threats.

Britannica Concise Encyclopedia defines oasis as fertile tract of land on the background of a desert where a perennial supply of fresh water is available. Oases vary in size, ranging from about 2.5 acres (1 hectare) around small springs to vast areas of naturally watered or irrigated land (Britannica Concise Encyclopedia, 2006); Wikipedia considers oasis as an isolated area of vegetation in a desert. In this study the oasis particularly refers to the dominated vegetation coverage growing in oasis area in view of the value of ecosystem services and research conveniences.

Remote sensing images have been used as a source of information for detecting land-use and land-cover changes at local, regional, and global scales in recent decades. Many scientists have investigated oasis ecosystem of western China using satellite data and some valuable results have been obtained. Luo (2003) constructed the process of land use/land cover change in the oasis of the arid region using remote sensing imagery data of 1979, 1987 and 1998; Tian (2011) studied the spatial-temporal processes of oasis development in the middle reaches of the Heihe River based on a time series of the normalized difference vegetation index (NDVI) derived from the 16-day composite MOD13A2 data with a spatial

Temporal-Spatial Changes of the Oasis in the Heihe River Basin over the Past 25 Years 315

free images covering the whole basin acquired every 3 or 4 years from 1986 to 2009 were

Fig. 1. The location of the Heihe River Basin and the approximate range of its oasis

133/033 134/031 134/032 134/033 135/032

Landsat ETM 07/07/1999 14/06/2000 30/07/1999 30/07/1999 21/07/1999

Atmospheric correction of multiple-date remote sensor data is required when the individual data images used in the change analysis algorithm are based on linear transformations of the data. A set of normalized difference vegetation index images were produced for each date in this study, atmospheric correction of multiple-date imageries was performed before image-to-image rigorous registration being conducted. According to the differences on

09/06/1986 03/08/1986 03/08/1986 18/07/1986 25/07/1986 23/06/1991 15/09/1990 27/06/1990 27/06/1990 18/06/1990 12/06/1993 08/06/1993 08/06/1993 08/06/1993 25/07/1992 23/06/1997 15/09/1996 15/09/1996 15/09/1996 22/09/1996 23/07/2006 11/09/2006 23/06/2006 23/06/2006 17/08/2006 24/06/2009 19/09/2009 17/07/2009 17/07/2009 09/08/2009

13/06/2002 24/09/2002 23/08/2002 23/08/2002 14/08/2002

selected and analyzed (Table 1).

Landsat TM

Table 1. A list of Selected TM/ETM images

resolution of 1km. These studies used either a few phases' imageries or low spatial resolution data to detect changes of the oasis, but few of them reflected the detailed process of dynamic changes in complete time series.

This chapter selected 8 phases of Landsat TM/ETM images that cover a period of 23 years from 1986 to 2009 to reconstruct the process of temporal and spatial changes of the Heihe oasis in northwest China. In order to separate and extract study object directly and accurately, an improved threshold method was proposed for vegetation extraction, and the characteristics and development laws of oasis were further analyzed and discussed.

#### **2. Study area**

The Heihe River is the second largest continental river in China .The Heihe River Basin is the representative in the arid area of northwestern China. It is located between 96°42'-102°00' E and 37°41'-42°42' N, with an area of 128,000 km2 approximately. It is one of the areas with the earliest development of irrigating agriculture in the arid area of China, and supports a population more than 1.9×106 nowadays. The main stream, with a length of 821 km, originates from the Qilian Mountains of Qinghai Province, flowing through the middle basin called the Hexi Corridor of Gansu Province, and ends in the Juyan Lake, a terminal lake in the desert in the Inner Mongolia Autonomous Region. The runoff from thousands of glaciers, snow and permafrost in the mountainous catchment basically constructs the water resources of the Heihe river basin. Because of its relatively abundant water resource (mean annual runoff is 37.3×108 m3), the Heihe River Basin was developed as the important commodity grain base in north-west China. Additionally, it has experienced rapid socioeconomic development and an increase in population density. 95 percent people of the basin are living in agricultural area of the oasis, and approximately 80 percent of them are engaged in husbandry production. However, the extensive exploitation of the water and land resources in the upper and middle parts of the basin has led to a sharp decrease in the water resource in the lower reaches.

Due to the influence of the water resource distribution and human activities, the oasis of Hehei River Basin distributes mainly on the piedmont lower alluvial fan and fluvial plain in the middle reaches of the river. Administratively, this study area includes Zhangye Prefecture-level City (governs six counties named Ganzhou, Shandan, Minle, Gaotai, Linze, and Sunan Yugur Autonomous County), part of Jiuquan Prefecture-level City (governs Suzhou and Jinta County), Jia Yuguan Prefecture-level City and part of Alxa League (governs Ejin Banner) of the Inner Mongolia Autonomous Region. The location of the Heihe River Basin and the approximate range of its oasis are illustrated in Figure 1.

#### **3. Data and methodology**

#### **3.1 Data acquisition and processing**

Data selection is very important in a spatial-temporal change analysis: the imagery must completely cover the whole study area; the time period should be suitable to capture the change; the images should be obtained during vigorous growing seasons of the vegetation given oases' phenological differences. Therefore, Landsat TM/ETM dataset was selected to detect the oases change, considering its advantages of multi-bands, high spatial resolution, high temporal resolution especially the continuity over years and free availability. 40 cloudSustainable Development – Education, Business and Management – 314 Architecture and Building Construction – Agriculture and Food Security

resolution of 1km. These studies used either a few phases' imageries or low spatial resolution data to detect changes of the oasis, but few of them reflected the detailed process

This chapter selected 8 phases of Landsat TM/ETM images that cover a period of 23 years from 1986 to 2009 to reconstruct the process of temporal and spatial changes of the Heihe oasis in northwest China. In order to separate and extract study object directly and accurately, an improved threshold method was proposed for vegetation extraction, and the

The Heihe River is the second largest continental river in China .The Heihe River Basin is the representative in the arid area of northwestern China. It is located between 96°42'-102°00' E and 37°41'-42°42' N, with an area of 128,000 km2 approximately. It is one of the areas with the earliest development of irrigating agriculture in the arid area of China, and supports a population more than 1.9×106 nowadays. The main stream, with a length of 821 km, originates from the Qilian Mountains of Qinghai Province, flowing through the middle basin called the Hexi Corridor of Gansu Province, and ends in the Juyan Lake, a terminal lake in the desert in the Inner Mongolia Autonomous Region. The runoff from thousands of glaciers, snow and permafrost in the mountainous catchment basically constructs the water resources of the Heihe river basin. Because of its relatively abundant water resource (mean annual runoff is 37.3×108 m3), the Heihe River Basin was developed as the important commodity grain base in north-west China. Additionally, it has experienced rapid socioeconomic development and an increase in population density. 95 percent people of the basin are living in agricultural area of the oasis, and approximately 80 percent of them are engaged in husbandry production. However, the extensive exploitation of the water and land resources in the upper and middle

characteristics and development laws of oasis were further analyzed and discussed.

parts of the basin has led to a sharp decrease in the water resource in the lower reaches.

River Basin and the approximate range of its oasis are illustrated in Figure 1.

Due to the influence of the water resource distribution and human activities, the oasis of Hehei River Basin distributes mainly on the piedmont lower alluvial fan and fluvial plain in the middle reaches of the river. Administratively, this study area includes Zhangye Prefecture-level City (governs six counties named Ganzhou, Shandan, Minle, Gaotai, Linze, and Sunan Yugur Autonomous County), part of Jiuquan Prefecture-level City (governs Suzhou and Jinta County), Jia Yuguan Prefecture-level City and part of Alxa League (governs Ejin Banner) of the Inner Mongolia Autonomous Region. The location of the Heihe

Data selection is very important in a spatial-temporal change analysis: the imagery must completely cover the whole study area; the time period should be suitable to capture the change; the images should be obtained during vigorous growing seasons of the vegetation given oases' phenological differences. Therefore, Landsat TM/ETM dataset was selected to detect the oases change, considering its advantages of multi-bands, high spatial resolution, high temporal resolution especially the continuity over years and free availability. 40 cloud-

of dynamic changes in complete time series.

**2. Study area**

**3. Data and methodology**

**3.1 Data acquisition and processing**

free images covering the whole basin acquired every 3 or 4 years from 1986 to 2009 were selected and analyzed (Table 1).

Fig. 1. The location of the Heihe River Basin and the approximate range of its oasis

Table 1. A list of Selected TM/ETM images

Atmospheric correction of multiple-date remote sensor data is required when the individual data images used in the change analysis algorithm are based on linear transformations of the data. A set of normalized difference vegetation index images were produced for each date in this study, atmospheric correction of multiple-date imageries was performed before image-to-image rigorous registration being conducted. According to the differences on

Temporal-Spatial Changes of the Oasis in the Heihe River Basin over the Past 25 Years 317

A new method - the edge weighting method is developed in this study. Normally, the image threshold is supposed to exist in the transition region from the target object to the background. If the gray value in the edge area is obtained, it would become easy to find a suitable threshold according to these gray values. As the edge detective operators are based on differential, they are easily affected by noise or point features (such as outlier). Sometimes the result contains pseudo edges (Li et al., 2006; Yi & Du, 2005), which have a further influence on binarization processing. The fundamental ideas of edge weighting method are as follows: the optimal threshold is supposed to subjectively exist. The average of all gray values obtained by edge detection is set as the critical threshold. Pixels with distinct gray values in the image make different contribution to the optimal threshold: the greater the value of | i θ - θ |, the smaller its weight. Therefore, we took the inverse of| i θ - θ |as the coefficient of weight to obtain the binarization threshold of the entire image. The steps

First, edge detection is implemented by using different non-directional operators to obtain the intermediate image. The selected operator is not only helpful for obtaining the position of the edge with easy and good accuracy, but also can largely avoid the loss of interior feature of the objects. Tracking the intermediate image, the position of edge pixels were obtained, and all gray values in the original image of these edge pixels could be found out based on which the mean value marked as θ was calculated. The normalization coefficient

> ∑ m

S =

i

optimal threshold will be obtained based on statistical characteristic of the image.

1 W =

values. The weighting coefficient of each pixel is defined as:

i=0 i

Where i θ denotes the gray value on the edge; m represents the number of the different gray

1

i

Finally, add up each different gray value of edge pixels with weighting coefficient and the

Using the edge weighting method described above, the oases of sample years were reconstructed. The current oases distribution of the Heihe River Basin is showed in Figure 2. The oases consist of two main parts: the middle reach oases and the low reach oases .They are located in the midst of Hexi Corridor and in Ejin Banner in Inner Mongolia respectively. The oases are distributed in zones along the two sides of the main stream of the Heihe River. According to the administration boundary, the spatial distribution of oases in the Heihe River Basin can be divided into 3 parts: ① Zhangye oasis. The oases are located in the middle of the Heihe River. From the south to the north, the oases include three topographic regions: Qilian Mountain, the central corridor plain and north mountain. The Minle and

|θ - θ| (1)

S|θ - θ| (2)

can be described as following:

can be expressed as:

**4. Oasis reconstruction**

**4.1 Distribution status of oasis**

biophysical and phenological characteristic of the vegetation among the upper, middle and lower reaches of the Heihe River Basin, the images were divided into three parts. 133/033 and 134/033 were combined into a single composite image, 134032 and 135032 were combined into another single composite image.

#### **3.2 Vegetation Index calculation**

Since 1960s, scientists have extracted and modeled various biophysical variables of vegetation to provide vegetation information using remotely sensed data. Much of this effort has involved the use of vegetation indices that indicate relative abundance and activity of green vegetation. NDVI (Normalized Difference Vegetation Index) is the most popular vegetation index used to evaluate the variation of surface vegetation at regional and global scales across a range of temporal scales. It is calculated as: NDVI = (infrared - red) / (infrared + red). The ratio reduces many forms of multiplicative noise presenting in multiple bands of multiple-data imagery, such as sun illumination differences, cloud shadows, some atmosphere attenuation and topographic distortions. Seasonal and inter-annual changes in vegetation growth and activity can be monitored using NDVI (John, 2005). The standard MODIS land products include the global 16-day composite NDVI products with a spatial resolution of 500m and 1km respectively (Huete et al., 2002a). Many applications and studies have proven the value of NDVI for vegetation information analysis. Therefore, in this study, NDVI database based on the selected images was constructed for further monitoring vegetation status and dynamic change.

#### **3.3 Threshold method for vegetation extraction**

Threshold method is a simple and important form of image segmentation to be widely used in the field of pattern recognition by computer and image processing for gray-level image. It is particularly suitable for specific information and parts of interest extraction. This method takes the difference of gray value between the target objects and the background into account, and determines one or several thresholds of the image on basis of certain principle functions, which each pixel is assigned to one class if its gray value is greater than the determined threshold and otherwise to the other class (Chen & Li, 2006). For remotely sensed images, determining the optimal threshold is a critical task for a large amount of information of the data. At the meantime, this method not only compresses a great amount of data, but also greatly simplifies the analysis and processing steps of the images (Du et al., 2002a).

A great variety of threshold algorithms have been developed in the last few decades (Kittler et al., 2009; Lee & Chung, 1990; Sahoo et al., 1988; Sezgin & Sankur, 2004; Weszka, 1978; Waston, 1987; Yin, 1999). These algorithms can be classified into two types: edge-based algorithms and area-based algorithms (John, 2005), but selecting an appropriate one is difficult. The problem is that independent criteria definition in different algorithms typically produces different results with distinct precision for these algorithms since they make different assumptions about the image. For instance, the famous Otsu's method (Otsu, 1979) is based on a linear discriminant analysis and the recent Kwon's threshold selection method is another technique based on a clustering criterion (Kwon, 2004). These aforementioned typical, simple and relatively effective methods based on criteria pay attention to both the foreground object(s) and the background, and they are affected greatly by proportion of the foreground account in the entire image. At the same time, these methods fail to partially remove noise existing in the background (Chen & Li, 2006).

A new method - the edge weighting method is developed in this study. Normally, the image threshold is supposed to exist in the transition region from the target object to the background. If the gray value in the edge area is obtained, it would become easy to find a suitable threshold according to these gray values. As the edge detective operators are based on differential, they are easily affected by noise or point features (such as outlier). Sometimes the result contains pseudo edges (Li et al., 2006; Yi & Du, 2005), which have a further influence on binarization processing. The fundamental ideas of edge weighting method are as follows: the optimal threshold is supposed to subjectively exist. The average of all gray values obtained by edge detection is set as the critical threshold. Pixels with distinct gray values in the image make different contribution to the optimal threshold: the greater the value of | i θ - θ |, the smaller its weight. Therefore, we took the inverse of| i θ - θ |as the coefficient of weight to obtain the binarization threshold of the entire image. The steps can be described as following:

First, edge detection is implemented by using different non-directional operators to obtain the intermediate image. The selected operator is not only helpful for obtaining the position of the edge with easy and good accuracy, but also can largely avoid the loss of interior feature of the objects. Tracking the intermediate image, the position of edge pixels were obtained, and all gray values in the original image of these edge pixels could be found out based on which the mean value marked as θ was calculated. The normalization coefficient can be expressed as:

$$\mathbf{S} = \sum\_{i=0}^{m} \frac{1}{|\; \Theta\_i \; \mathbf{\cdot} \; \Theta|} \tag{1}$$

Where i θ denotes the gray value on the edge; m represents the number of the different gray values. The weighting coefficient of each pixel is defined as:

$$\mathbf{W}\_{i} = \frac{1}{\mathbf{S} \, |\, \boldsymbol{\theta}\_{i} \, \cdots \, |} \, \tag{2}$$

Finally, add up each different gray value of edge pixels with weighting coefficient and the optimal threshold will be obtained based on statistical characteristic of the image.

#### **4. Oasis reconstruction**

Sustainable Development – Education, Business and Management – 316 Architecture and Building Construction – Agriculture and Food Security

biophysical and phenological characteristic of the vegetation among the upper, middle and lower reaches of the Heihe River Basin, the images were divided into three parts. 133/033 and 134/033 were combined into a single composite image, 134032 and 135032 were

Since 1960s, scientists have extracted and modeled various biophysical variables of vegetation to provide vegetation information using remotely sensed data. Much of this effort has involved the use of vegetation indices that indicate relative abundance and activity of green vegetation. NDVI (Normalized Difference Vegetation Index) is the most popular vegetation index used to evaluate the variation of surface vegetation at regional and global scales across a range of temporal scales. It is calculated as: NDVI = (infrared - red) / (infrared + red). The ratio reduces many forms of multiplicative noise presenting in multiple bands of multiple-data imagery, such as sun illumination differences, cloud shadows, some atmosphere attenuation and topographic distortions. Seasonal and inter-annual changes in vegetation growth and activity can be monitored using NDVI (John, 2005). The standard MODIS land products include the global 16-day composite NDVI products with a spatial resolution of 500m and 1km respectively (Huete et al., 2002a). Many applications and studies have proven the value of NDVI for vegetation information analysis. Therefore, in this study, NDVI database based on the selected images was constructed for further

Threshold method is a simple and important form of image segmentation to be widely used in the field of pattern recognition by computer and image processing for gray-level image. It is particularly suitable for specific information and parts of interest extraction. This method takes the difference of gray value between the target objects and the background into account, and determines one or several thresholds of the image on basis of certain principle functions, which each pixel is assigned to one class if its gray value is greater than the determined threshold and otherwise to the other class (Chen & Li, 2006). For remotely sensed images, determining the optimal threshold is a critical task for a large amount of information of the data. At the meantime, this method not only compresses a great amount of data, but also

A great variety of threshold algorithms have been developed in the last few decades (Kittler et al., 2009; Lee & Chung, 1990; Sahoo et al., 1988; Sezgin & Sankur, 2004; Weszka, 1978; Waston, 1987; Yin, 1999). These algorithms can be classified into two types: edge-based algorithms and area-based algorithms (John, 2005), but selecting an appropriate one is difficult. The problem is that independent criteria definition in different algorithms typically produces different results with distinct precision for these algorithms since they make different assumptions about the image. For instance, the famous Otsu's method (Otsu, 1979) is based on a linear discriminant analysis and the recent Kwon's threshold selection method is another technique based on a clustering criterion (Kwon, 2004). These aforementioned typical, simple and relatively effective methods based on criteria pay attention to both the foreground object(s) and the background, and they are affected greatly by proportion of the foreground account in the entire image. At the same time, these methods fail to partially

greatly simplifies the analysis and processing steps of the images (Du et al., 2002a).

combined into another single composite image.

monitoring vegetation status and dynamic change.

**3.3 Threshold method for vegetation extraction**

remove noise existing in the background (Chen & Li, 2006).

**3.2 Vegetation Index calculation**

#### **4.1 Distribution status of oasis**

Using the edge weighting method described above, the oases of sample years were reconstructed. The current oases distribution of the Heihe River Basin is showed in Figure 2. The oases consist of two main parts: the middle reach oases and the low reach oases .They are located in the midst of Hexi Corridor and in Ejin Banner in Inner Mongolia respectively. The oases are distributed in zones along the two sides of the main stream of the Heihe River. According to the administration boundary, the spatial distribution of oases in the Heihe River Basin can be divided into 3 parts: ① Zhangye oasis. The oases are located in the middle of the Heihe River. From the south to the north, the oases include three topographic regions: Qilian Mountain, the central corridor plain and north mountain. The Minle and

Temporal-Spatial Changes of the Oasis in the Heihe River Basin over the Past 25 Years 319

Shandan oasis are in the alluvial and pluvial fan and the natural conditions is relative suitable, hence the oasis is widely distributed with relative large area. The Linze and Gaotai oasis are mainly distributed along the two sides of the Heihe River. ② Jiuquan and Jiayuguan oasis. The oases are located in flat open area in north of Qinlian Mountain, which belong to higher position oasis (Zhang, 2002). ③ Ejin oasis in the low reaches. The oases are located in the west part of Inner Mongolia. It has a transitional zone with desert areas, as a result the distribution of the oasis is scattered. More importantly, it is an important line of ecological defense in the leading edge of West China.

The oases distribution of different years can be seen from Figure3, and it shows the main location of oases changed little since 1986.

#### **4.2 Validation on reconstruction of oasis**

The results of oasis reconstruction need to be validated after the work have been finished. According to related studies, different methods were used to verify the accuracy of the interpretation of remote sensing. In this study, field validation was used to verify the oasis reconstruction. The specific process is as following: 1) based on the extracted oasis in 2009, the uncertainty regions of 10%-20% were chosen to validate in the fields; 2) according to the results of the validation, the results of reconstruction were further modified. The points of verification in the Heihe River Basin are shown as Figure 2.

Fig. 2. The validation points in the Heihe River Basin

Sustainable Development – Education, Business and Management – 318 Architecture and Building Construction – Agriculture and Food Security

Shandan oasis are in the alluvial and pluvial fan and the natural conditions is relative suitable, hence the oasis is widely distributed with relative large area. The Linze and Gaotai oasis are mainly distributed along the two sides of the Heihe River. ② Jiuquan and Jiayuguan oasis. The oases are located in flat open area in north of Qinlian Mountain, which belong to higher position oasis (Zhang, 2002). ③ Ejin oasis in the low reaches. The oases are located in the west part of Inner Mongolia. It has a transitional zone with desert areas, as a result the distribution of the oasis is scattered. More importantly, it is an important line of

The oases distribution of different years can be seen from Figure3, and it shows the main

The results of oasis reconstruction need to be validated after the work have been finished. According to related studies, different methods were used to verify the accuracy of the interpretation of remote sensing. In this study, field validation was used to verify the oasis reconstruction. The specific process is as following: 1) based on the extracted oasis in 2009, the uncertainty regions of 10%-20% were chosen to validate in the fields; 2) according to the results of the validation, the results of reconstruction were further modified. The points of

ecological defense in the leading edge of West China.

verification in the Heihe River Basin are shown as Figure 2.

Fig. 2. The validation points in the Heihe River Basin

location of oases changed little since 1986.

**4.2 Validation on reconstruction of oasis**

Temporal-Spatial Changes of the Oasis in the Heihe River Basin over the Past 25 Years 321

Based on the results of oasis reconstruction, oasis areas of the total watershed and each county or district were counted using GIS in each period as shown in Table2, and the change curve of area was drawn according to data in Table2 as shown in figure4. As illustrated in Table 2 and Figure 4, oasis expansion is the main trend from 1986 to 2009 in this area, except 1996 and 2002 that had two periods of short-term oasis atrophy. The smallest oasis area was 4526.16 km2 in 2002, while the oasis area reached the maximum value of 5581.44 km2 in 2009. The change trend of area presented slow decline from 1986 to 2002 in this area, during which a decrease was followed by a trend of increase. The oasis area increased rapidly since

According to Table 2 and Figure 4, the oasis areas are large in Ganzhou district and Suzhou district, but small in Minle County, Jiayuguan City and Sunan County, and the oasis areas of the rest counties is at an intermediate level. The changes trend is not exactly the same between oasis area in each county / district and total area. The changes of area are acute in Ejin oasis. Overall, the trend of decreasing, shrinking and expansion of oases run concurrently. There is slight change of oasis area in Minle County, Jiayuguan city and Sunan County. The oasis areas in other counties have some fluctuations in some years, but

In order to understand the rate of regional oasis changes and their characteristic differences, the dynamic degree is calculated for each county and district.  Analysis of the oasis changes in the Heihe River Basin**

generally the trend of change is consistent with the overall trends.

could be mathematically expressed as the following function (Liu, 2000b):

**5.1 Analysis of the area changes**

2002, reaching a maximum in 2009.

City County/

Ganzhou

Suzhou

Ejin

Table 2. The oasis area in the Heihe River Basin (unit: km2)

Zhangye

Jiuquan

Inner Mongolia

Fig. 3. The oases distribution in the Heihe River Basin from 1986 to 2009

#### **5. Analysis of the oasis changes in the Heihe River Basin**

#### **5.1 Analysis of the area changes**

Sustainable Development – Education, Business and Management – 320 Architecture and Building Construction – Agriculture and Food Security

Fig. 3. The oases distribution in the Heihe River Basin from 1986 to 2009

Based on the results of oasis reconstruction, oasis areas of the total watershed and each county or district were counted using GIS in each period as shown in Table2, and the change curve of area was drawn according to data in Table2 as shown in figure4. As illustrated in Table 2 and Figure 4, oasis expansion is the main trend from 1986 to 2009 in this area, except 1996 and 2002 that had two periods of short-term oasis atrophy. The smallest oasis area was 4526.16 km2 in 2002, while the oasis area reached the maximum value of 5581.44 km2 in 2009. The change trend of area presented slow decline from 1986 to 2002 in this area, during which a decrease was followed by a trend of increase. The oasis area increased rapidly since 2002, reaching a maximum in 2009.

According to Table 2 and Figure 4, the oasis areas are large in Ganzhou district and Suzhou district, but small in Minle County, Jiayuguan City and Sunan County, and the oasis areas of the rest counties is at an intermediate level. The changes trend is not exactly the same between oasis area in each county / district and total area. The changes of area are acute in Ejin oasis. Overall, the trend of decreasing, shrinking and expansion of oases run concurrently. There is slight change of oasis area in Minle County, Jiayuguan city and Sunan County. The oasis areas in other counties have some fluctuations in some years, but generally the trend of change is consistent with the overall trends.

In order to understand the rate of regional oasis changes and their characteristic differences, the dynamic degree is calculated for each county and district. The dynamic degree model could be mathematically expressed as the following function (Liu, 2000b):

$$\mathbf{k} = \frac{\mathbf{U}\_{\text{b}} \cdot \mathbf{U}\_{\text{a}}}{\mathbf{U}\_{\text{a}}} \ast \frac{\mathbf{1}}{\mathbf{T}} \ast \mathbf{1}00\% \tag{3}$$

Table 2. The oasis area in the Heihe River Basin (unit: km2)

Temporal-Spatial Changes of the Oasis in the Heihe River Basin over the Past 25 Years 323

1993- 1996

Shandan 9.83 -4.92 6.01 3.78 -1.82 1.67 5.28 Minle 22.74 -6.28 7.10 2.80 -4.10 1.67 4.94

District 2.96 0.79 -0.50 1.60 -1.75 2.05 1.07 Linze 4.63 6.13 -3.38 3.48 -3.4 4.82 -1.31 Gaotai -1.66 6.77 -3.42 -1.24 2.12 4.32 -2.26 Sunan -18.56 22.02 -5.45 -6.17 9.81 19.67 5.43

Districr -2.49 1.69 -7.36 4.51 -2.19 5.43 1.58 Jinta -3.76 -0.46 -7.68 6.38 3.72 5.89 5.24

Banner -7.52 10.87 -1.16 -14.78 -3.80 0.15 13.48

0.73 1.45 -2.00 0.43 -1.78 3.38 2.88

Jiayuguan Jiayuguan -5.10 4.45 -20.39 33.06 -2.32 8.37 5.79

Table 3. The dynamic degree of the oasis change in the Heihe River Basin from 1986 to 2009

A: Shandan County; B: Minle County; C: Ganzhou District; D: Linze County; E: Gaotai County; F: Sunan County; G: Suzhou District; H: Jiayuguan City; I: Jinta County; J: Ejin Banner; K: Total Dynamic Degree

1999-2002, the oasis dynamic degree kept at lower level in all counties, which indicates that the degree of increase or decrease was more gently, and the oasis remained a steady state in a short period. The oasis dynamic degree also kept at lower level in the counties except Sunan County in 2002-2006. From 2006 to 2009, the oasis dynamic degree reached 13.48 with abrupt increase in Ejin oases, while it remained at lower level in other counties or districts.

Fig. 5. The net changes of oasis in the Heihe River Basin from 1986 to 2009

1996- 1999

1999- 2002

2002- 2006 2006- 2009

1990- 1993

City County/

Zhangye

Jiuquan

Inner Mongolia

(unit:%)

District

Ganzhou

Suzhou

Ejin

Total Dynamic Degree

1986- 1990

Fig. 4. The oasis area in the Heihe River Basin from 1986 to 2009

Where K is the oasis change rate over time T, Ua is the oasis area at the beginning of the monitoring period, and Ub is the oasis area at the end of the monitoring period .The dynamic degree is thus defined as the time rate of the oasis change that oasis is converted into the desert and that part of the oasis area at the beginning of the monitoring period subjects to change. The dynamic degree represents, in a comprehensive manner, the change of oasis in a given region. The oasis dynamic degree is shown in Table3 and Figure5.

Table 3 and Figure5 indicate that the oasis dynamic degrees are greatly different in different periods. The oasis dynamic degree of Jiayuguan City was the largest compared with that of other counties or districts, which had been increased from -20.39 in 1993-1996 to 33.06 in 1996-1999, indicating that the oasis had severely decreased and increased in these periods respectively. In addition, the oasis dynamic degree was larger in Sunan County, which was - 18.56 in 1986-1990 with severe decreasing, and 22.02 in 1990-1993 with severe increase. On the whole, the oasis dynamic degree kept at an intermediate level in other counties, but larger in individual periods. For the whole basin, the oasis dynamic degree maintained a less difference in the Heihe River Basin in all periods, with a gently increase or decrease. Taking the oasis as a complete system, not only the whole oasis system but also part of the oasis should be concerned, because the individual changes which constitute oasis system, could be researched to understand exactly the inner factors of the oasis change. On the other hand, the oasis dynamic degree in the same period remained great difference in all counties. The oasis dynamic degree was up to 22.74 with an extreme increase in Minle County, and - 18.56 in Sunan County with an extreme decrease in 1986-1990. The oasis dynamic degree reached the maximum of 22.02 with extreme increase in Sunan County in 1993-1996. The oasis dynamic degree in Jiayuguan city was the largest among all counties in 1996-1999. In Sustainable Development – Education, Business and Management – 322 Architecture and Building Construction – Agriculture and Food Security

Minle County Total Area

Shandan County Ganzhou District Linze County Gaotai County Sunan County Suzhou District Jiayuguan City Jinta County Ejina Banner

1986 1990 1993 1996 1999 2002 2006 2009

Where K is the oasis change rate over time T, Ua is the oasis area at the beginning of the monitoring period, and Ub is the oasis area at the end of the monitoring period .The dynamic degree is thus defined as the time rate of the oasis change that oasis is converted into the desert and that part of the oasis area at the beginning of the monitoring period subjects to change. The dynamic degree represents, in a comprehensive manner, the change

Table 3 and Figure5 indicate that the oasis dynamic degrees are greatly different in different periods. The oasis dynamic degree of Jiayuguan City was the largest compared with that of other counties or districts, which had been increased from -20.39 in 1993-1996 to 33.06 in 1996-1999, indicating that the oasis had severely decreased and increased in these periods respectively. In addition, the oasis dynamic degree was larger in Sunan County, which was - 18.56 in 1986-1990 with severe decreasing, and 22.02 in 1990-1993 with severe increase. On the whole, the oasis dynamic degree kept at an intermediate level in other counties, but larger in individual periods. For the whole basin, the oasis dynamic degree maintained a less difference in the Heihe River Basin in all periods, with a gently increase or decrease. Taking the oasis as a complete system, not only the whole oasis system but also part of the oasis should be concerned, because the individual changes which constitute oasis system, could be researched to understand exactly the inner factors of the oasis change. On the other hand, the oasis dynamic degree in the same period remained great difference in all counties. The oasis dynamic degree was up to 22.74 with an extreme increase in Minle County, and - 18.56 in Sunan County with an extreme decrease in 1986-1990. The oasis dynamic degree reached the maximum of 22.02 with extreme increase in Sunan County in 1993-1996. The oasis dynamic degree in Jiayuguan city was the largest among all counties in 1996-1999. In

of oasis in a given region. The oasis dynamic degree is shown in Table3 and Figure5.

Fig. 4. The oasis area in the Heihe River Basin from 1986 to 2009

0

200

400

The Change of Area/km2

600

800

1000

1200

0

1000

2000

The Change of Total Area/km2

3000

4000

5000

6000

Table 3. The dynamic degree of the oasis change in the Heihe River Basin from 1986 to 2009 (unit:%)

A: Shandan County; B: Minle County; C: Ganzhou District; D: Linze County; E: Gaotai County; F: Sunan County; G: Suzhou District; H: Jiayuguan City; I: Jinta County; J: Ejin Banner; K: Total Dynamic Degree

Fig. 5. The net changes of oasis in the Heihe River Basin from 1986 to 2009

1999-2002, the oasis dynamic degree kept at lower level in all counties, which indicates that the degree of increase or decrease was more gently, and the oasis remained a steady state in a short period. The oasis dynamic degree also kept at lower level in the counties except Sunan County in 2002-2006. From 2006 to 2009, the oasis dynamic degree reached 13.48 with abrupt increase in Ejin oases, while it remained at lower level in other counties or districts.

Fig. 6. The maps of oasis change in the Heihe River Basin from 1986 to 2009

Fig. 6. The maps of oasis change in the Heihe River Basin from 1986 to 2009

Temporal-Spatial Changes of the Oasis in the Heihe River Basin over the Past 25 Years 327

From the point of spatial distribution of oasis changes during the last 25 years, the expansion and shrink of oasis have occurred alternately in all counties in the Heihe River Basin. In addition, the intensity of expansion and shrink varied sharply in different periods. Both of expansion and shrink had a distinct regional distribution between 1986 and 1990. The expanding regions mainly concentrated in Minle County, Shandan County, yet more or less expansion appeared in other counties. The shrunk regions mainly concentrated in Suzhou District, Jinta County and Ejin Banner. From 1990 to 1993, both expansion and shrink of oasis presented scattered, the expanding regions were located in Linze County, northern of Gaotai County and Ejin Banner, while the shrink regions were located in Minle County, Shandan County and Jinta County. From 1993 to 1996, the most serious decline of the oasis occurred in Linze County, south of Gaotai County, Suzhou District and Ejin Banner, while little expanding regions presented in Minle County and south of Shandan County. From 1996-1999, the expansion of oasis was the smallest, and its distribution was scattered. There was a little expansion of oasis distribution in all counties except Ejin Banner. The shrunk regions distributed in Gaotai County, north of Jinta County and Ejin Banner, and the shrinking of oasis was most severe in Ejin Banner. From 1999-2002, the shrinking of oasis widely occurred in the Heihe River Basin, but the expansion of oasis only sporadically took place in Shandan County, Gaotai County and Jinta County. The expanding area of oasis in 2002-2006 was the largest of all periods, and the expanding regions were widely located in the whole basin; correspondingly, there were few atrophied regions. From 2006-2009, the expanding area of oasis was also larger and the expanded oases widely distributed in Minle County, Shandan County, Jinta County and Ejina Banner, while the shrinking of oasis mainly took place in Linze County, Gaotai County and the

In the whole study area, the regions that the oasis area changes greater mainly distributed at the border of the oasis. For instance, through artificial cultivation, improvement of irrigation system, a large number of deserts with relatively good natural conditions were converted into farmland, woodland, etc. Meanwhile, grassland degradation and desert formation occurred as a result of water shortage and other undesirable condition. In addition, some areas that have no or are short of surface water began to pump groundwater to irrigate the reclaimed wasteland. Disorder exploitation led to rapid decline of groundwater level and strengthened the drought of soil, yet increased abandoned land. Furthermore, the grassland severely degraded due to over-grazing. The factors mentioned above recurred in different research periods. As a result, oasis changes dynamically between expansions and shrink in

This study discussed the spatial and temporal processes and characteristics of oasis changes in the Heihe River Basin between 1986 and 2009. The following conclusions can be

First, expansion was the main trend of oasis change in the Heihe River Basin from 1986 to 2009, except the period from 1996 to 2002 in which the oasis shrunk shortly. From 1986 to 2002, the oasis area experienced a process of gentle increasing and then decreasing

south of Sunan County.

the study area.

**6. Conclusion**

obtained:

#### **5.2 Analysis of spatial pattern change of the Heihe oasis**

Eight maps of oasis distribution between 1986 and 2009 were made using change detection in ArcMap (Figure 6). The areas of changed part were calculated as shown in Table 4 and Figure 7. Table 4 shows that the most outstanding increase of area occurred in 1986-1990 as much as 968.84 km2. The most outstanding decreasing area of 935.96 km2 occurred in 1993- 1996. From 1999 to 2002, the increased area is the smallest (389.38 km2), and between 2002 and 2006 the decreased area is the smallest (313.99 km2). From the point of change trends of the oasis area in the study period, the increase and decrease of area are alternately present as undulate. The decreased area is much larger than the increased oasis area between 1993- 1996 and 1999-2002, indicating that the oasis shrunk in both periods. It is clear that the shrinking regions are far more than the expanding regions from the change maps of oasis. The increased areas are greater than the decreased area in other periods, indicating that the oasis expanded in these periods.

Table 4. The change of oasis area in each periods in the Heihe River Basin (unit:km2)

Fig. 7. The change of oasis area in each period in the Heihe River Basin (unit:km2)

From the point of spatial distribution of oasis changes during the last 25 years, the expansion and shrink of oasis have occurred alternately in all counties in the Heihe River Basin. In addition, the intensity of expansion and shrink varied sharply in different periods. Both of expansion and shrink had a distinct regional distribution between 1986 and 1990. The expanding regions mainly concentrated in Minle County, Shandan County, yet more or less expansion appeared in other counties. The shrunk regions mainly concentrated in Suzhou District, Jinta County and Ejin Banner. From 1990 to 1993, both expansion and shrink of oasis presented scattered, the expanding regions were located in Linze County, northern of Gaotai County and Ejin Banner, while the shrink regions were located in Minle County, Shandan County and Jinta County. From 1993 to 1996, the most serious decline of the oasis occurred in Linze County, south of Gaotai County, Suzhou District and Ejin Banner, while little expanding regions presented in Minle County and south of Shandan County. From 1996-1999, the expansion of oasis was the smallest, and its distribution was scattered. There was a little expansion of oasis distribution in all counties except Ejin Banner. The shrunk regions distributed in Gaotai County, north of Jinta County and Ejin Banner, and the shrinking of oasis was most severe in Ejin Banner. From 1999-2002, the shrinking of oasis widely occurred in the Heihe River Basin, but the expansion of oasis only sporadically took place in Shandan County, Gaotai County and Jinta County. The expanding area of oasis in 2002-2006 was the largest of all periods, and the expanding regions were widely located in the whole basin; correspondingly, there were few atrophied regions. From 2006-2009, the expanding area of oasis was also larger and the expanded oases widely distributed in Minle County, Shandan County, Jinta County and Ejina Banner, while the shrinking of oasis mainly took place in Linze County, Gaotai County and the south of Sunan County.

In the whole study area, the regions that the oasis area changes greater mainly distributed at the border of the oasis. For instance, through artificial cultivation, improvement of irrigation system, a large number of deserts with relatively good natural conditions were converted into farmland, woodland, etc. Meanwhile, grassland degradation and desert formation occurred as a result of water shortage and other undesirable condition. In addition, some areas that have no or are short of surface water began to pump groundwater to irrigate the reclaimed wasteland. Disorder exploitation led to rapid decline of groundwater level and strengthened the drought of soil, yet increased abandoned land. Furthermore, the grassland severely degraded due to over-grazing. The factors mentioned above recurred in different research periods. As a result, oasis changes dynamically between expansions and shrink in the study area.

#### **6. Conclusion**

Sustainable Development – Education, Business and Management – 326 Architecture and Building Construction – Agriculture and Food Security

Eight maps of oasis distribution between 1986 and 2009 were made using change detection in ArcMap (Figure 6). The areas of changed part were calculated as shown in Table 4 and Figure 7. Table 4 shows that the most outstanding increase of area occurred in 1986-1990 as much as 968.84 km2. The most outstanding decreasing area of 935.96 km2 occurred in 1993- 1996. From 1999 to 2002, the increased area is the smallest (389.38 km2), and between 2002 and 2006 the decreased area is the smallest (313.99 km2). From the point of change trends of the oasis area in the study period, the increase and decrease of area are alternately present as undulate. The decreased area is much larger than the increased oasis area between 1993- 1996 and 1999-2002, indicating that the oasis shrunk in both periods. It is clear that the shrinking regions are far more than the expanding regions from the change maps of oasis. The increased areas are greater than the decreased area in other periods, indicating that the

> 1993- 1996

Table 4. The change of oasis area in each periods in the Heihe River Basin (unit:km2)

Fig. 7. The change of oasis area in each period in the Heihe River Basin (unit:km2)

of Area 968.84 735.41 634.52 757.65 389.38 925.23 772.45

of Area 832.20 525.68 935.96 696.62 645.05 313.99 328.54

1996- 1999

1999- 2002

2002- 2006

2006- 2009

**5.2 Analysis of spatial pattern change of the Heihe oasis**

oasis expanded in these periods.

Increase

Decrease

1986- 1990

1990- 1993

> This study discussed the spatial and temporal processes and characteristics of oasis changes in the Heihe River Basin between 1986 and 2009. The following conclusions can be obtained:

> First, expansion was the main trend of oasis change in the Heihe River Basin from 1986 to 2009, except the period from 1996 to 2002 in which the oasis shrunk shortly. From 1986 to 2002, the oasis area experienced a process of gentle increasing and then decreasing

Temporal-Spatial Changes of the Oasis in the Heihe River Basin over the Past 25 Years 329

Lee, S. U. & Chung, S. Y. (1990). A Comparative Performance Study of Several Global

Luo, G.P., Zhou, C. H. & Chen, X. (2003). Process of Land Use/ Land Cover Change in the

Li, Z., Jia, Y.H. & Cheng, G. (2006). Edge Detection Algorithm for Remote Sensing Image

Li, W. D., Li, Z. Z. & Wang, J. Q. (2007). Evaluation of Oasis Ecosystem Risk by

Otsu, N. (1979). A Threshold Selection Method from Gray-level Histograms. *IEEE Trans.*

Sahoo, P. K., Soltani, S. & Wong, A. K. C. (1988). A Survey of Thresholding Techniques.

Sezgin, M. & Sankur, B. (2004). Survey over Image Thresholding Techniques and

Tucker, C. J. (1979). Red and Photographic Infrared Linear Combinations for Monitoring

Tian, J., Su, H. B. & Chen, S. H. (2011). Spatial-Temporal Processes of Desertification

Weszka, J. S. (1978). A Survey of Threshold Selection Techniques. *Computer Graphics and Image Process*, Vol. 7, No.2, (April 1978), pp. 259-265, ISSN 0615-1486 Waston, A. L. (1987). New Method of Classification for Landsat Data Using 'Watershed'

Wang, T. (2009). Review and Prospect of Research on Oasification and Desertification in

Yin, P.Y. (1999). A Fast Scheme for Optimal Thresholding Using Genetical Gorithms. *Signal*

Yi, H. & Du,Y. (2005). Reash of Image Segmentation Technique Based on Edge Information. *Mode Electronic Technology*, Vol. 5, (August 2005), pp. 116-120, ISSN 1004-373X

*Processing*, Vol. 72, No.2, (January 1999), pp. 85-95, ISSN 0615-1486

*Syst. Man Cybern*, Vol. 9, No.1, (January 1979), pp. 62-66

*Process*, Vol. 52, No.2, (November 1990), pp. 171-190, ISSN 0734-189X Liu, J. Y. & Buhe, A. S. (2000b). Study on Spatial-temporal Feature of Modern Land Use

No. 3, (May, 2000), pp.229-239, ISSN 1001-7410

72, ISSN 0375-5444

0742

2006), pp. 52-54, ISSN 1672-4623

233-260, ISSN 0734-189X

ISSN 0034-4257

7588

0167-8655

1000-694X

2004), pp. 146–165, ISSN 0030-8277

Thresholding Techniques for Segmentation. *Computer Vision, Graphics and Image*

Change in China: Using Remote Sensing Techniques. *Quaternary Sciences*, Vol. 20,

Oasis of Arid Region. *Acta Geographica Sinica*, Vol. 58, No. 1, (January 2003), pp. 63-

Based on Mathematical Morphology. *Geospatial Information*, Vol. 4, No.4, (August

Reliability Theory in an Arid Area: A Case Study in the Shiyang River Basin, China. *Journal of Environmental Sciences,* Vol. 19, No. 4, (May 2007), pp. 508–512, ISSN 1001-

*Computer Vision, Graphics, and Image Processing*, Vol. 41, No.2, (February 1988), pp.

Quantitative Performance Evaluation. *Electronic Imaging*. Vol. 13, No.1, (January

Vegetation. *Remote Sensing of Environment*, Vol. 8, No.2, (May 1979), pp. 127-150,

and Oasification in the Middle Reaches of the Heihe River Based on Remote Sensing, *Resources Science*, Vol. 33, No. 2, (February 2011), PP. 347-355, ISSN 1007-

Algorithm, *Pattern Recognition Letters*, Vol.6, No. 1, (June 1987), pp.15-19, ISSN

Arid Regions. *Journal of Desert Research*, Vol.29, No.1, (January 2009), pp. 1-9, ISSN

process. After 2002, an abrupt increase appeared and reached the top in 2009. The oasis area reached the maximum value as 5581.44 km2 in 2009 and minimum value as 4526.16 km2 in 2002.

Second, the changes of oasis dynamic degree were great different in all counties over the past 23 years. The oasis expanding and shrinking occurred in all counties, and both of them alternatively occurred in each county.

Third, the intensity of expansion and shrinking varied in different periods. It indicates that the all oases in the Heihe River Basin are a whole and there is interrelationship existed. However, there are still questions such as the change reasons remaining unclear and further analysis is expected to be made in the future.

Final, the edge weighting method is an efficient way to reconstruct the oasis changes over past decades, which not only makes the reconstruction easier, quick, automatic, but also the results more objective and accurate.

#### **7. Acknowledgment**

The authors would like to acknowledge the support from 973 Program of China (2009CB421306) and the National Natural Science Foundation of China (91025010). Some image data used are downloaded from the Earth Resources Observation and Science Center (EROS). Thanks lecturer Lei LU and student Hong ZHAO, both from Lanzhou University for improving English.

#### **8. References**

*Britannica Concise Encyclopedia*. Encyclopedia Britannica, Inc, ISBN 978-1-59339-492-9, 2006, Available from

http://www.britannica.com/EBchecked/topic/423497/oasis

Sustainable Development – Education, Business and Management – 328 Architecture and Building Construction – Agriculture and Food Security

process. After 2002, an abrupt increase appeared and reached the top in 2009. The oasis area reached the maximum value as 5581.44 km2 in 2009 and minimum value as 4526.16 km2

Second, the changes of oasis dynamic degree were great different in all counties over the past 23 years. The oasis expanding and shrinking occurred in all counties, and both of them

Third, the intensity of expansion and shrinking varied in different periods. It indicates that the all oases in the Heihe River Basin are a whole and there is interrelationship existed. However, there are still questions such as the change reasons remaining unclear and further

Final, the edge weighting method is an efficient way to reconstruct the oasis changes over past decades, which not only makes the reconstruction easier, quick, automatic, but also the

The authors would like to acknowledge the support from 973 Program of China (2009CB421306) and the National Natural Science Foundation of China (91025010). Some image data used are downloaded from the Earth Resources Observation and Science Center (EROS). Thanks lecturer Lei LU and student Hong ZHAO, both from Lanzhou University

*Britannica Concise Encyclopedia*. Encyclopedia Britannica, Inc, ISBN 978-1-59339-492-9, 2006,

Chen, S. C. & Li, D. H. (2006). Image Binarization Focusing on Objects, *Neurocomputing,* Vol.

Du,Q, Xiang J.Y. & Yuan S.C. (2004). Study on Threshold Segmentation for infrared image

Huete, A. R., Didan, K. & Miura, T. (2002). Overview of the Radiometric and Biophysical

John, R. J. (2005). *Introductory Digital Image Processing: A Remote Sensing Perspective*(3rd

Kittler,J., Illingworth, J & Foglein, J. (1985). Threshold Selection Based on a Simple Image

Kwon, S. H. (2004). Threshold Selection Based on Cluster Analysis, *Patten Recognition Lett*,

based on edge detection. *Infrared and Laser Engineering*, Vol. 33, No. 3, (June, 2004),

Performance of the MODIS Vegetation Indices. *Remote Sensing of Environment*, Vol.

Statistic. *Computer Vision, Graphics and Image Processing*, Vol. 30, No.2, (May 1985),

http://www.britannica.com/EBchecked/topic/423497/oasis

69, No.16-18, (October 2006), pp. 2411-2415, ISSN 0925-2312

83, No.1-2, (November 2002), pp. 195-213, ISSN 0034-4257

edition), Pearson Education, Inc, ISBN 0-13-145361-0

Vol. 25, No.9, (July 2004), pp. 1045-1050, ISSN 0167-8655

in 2002.

alternatively occurred in each county.

results more objective and accurate.

**7. Acknowledgment**

for improving English.

Available from

pp.288-291, ISSN 1007-2276

pp. 125-147, ISSN 0734-189X

**8. References**

analysis is expected to be made in the future.

**17**

*Italy*

**Saving the World's Most Precious Resource**

Water is probably the world's most precious natural resource. Without it, there would be no life. It's sad then to think that so many people already live with less than their daily needs and that this situation is predicted to get even worse. In fact, according to an UN assessment, by 2025, around two-thirds of the world's population will have insufficient

The traditional solution to a water shortage problem has been to develop new sources. But as the easily extractable ones have already been exploited, this quest is becoming increasingly difficult. Little wonder then, that even London, the capital city of what is considered to be one of the wettest countries in the world, is turning to desalination as a solution. Not only is this very expensive, but it is has a huge environmental impact. Furthermore, it addresses just the consequence of the problem and not its root cause, which

So why then, has such a disastrous situation arisen in the first place, particularly when the water utility personnel is amongst the most dedicated of any industry? The answer lies in the traditional approach to water network management, where the objective was not necessarily to improve efficiency, but to ensure that the customers had some supply for a part of the time. Unknowingly, the leakage level was increasing, probably because only a small proportion of leaks ever come to the surface. As the reservoirs ran dry, water was rationed, making things even worse. In some cities water supply is counted in just a few days of the week. The answer appears obvious: reduce the losses. So why is this not done?

In its simplest definition, water loss is the difference between the total production and total consumption. However, there is a lot more to it than this, as the International Water

The loss is composed of two main components: commercial (or apparent) and physical (or real). The former comprises inaccurate measurement and illegal use, whilst the latter includes leakage from the reservoirs and from the supply and distribution network,

Association's (IWA) standard water balance, (reproduced below in Figure 1), shows.

Probably because the solution is not as easily defined as the problem itself.

**1. Introduction**

invariably relates to inefficiencies.

**2. Water balance**

including service pipes.

supply.

Dewi Rogers1 and Alessandro Bettin2

*2SGI – Studio Galli Ingegneria SpA, Sarmeola di Rubano (PD)*

*1DEWI Srl, Perugia (PG)*

Zhang, B. & Zhang, K. (2002). Study on the Spatial Differentiation and the Evolution in Arid Regions-A Case Study for Oases in the Heihe River Basin. *Journal of Glaciology and Geocryology*,Vol. 4, No. 24, (August, 2002)pp.414-420, ISSN 1000-0240

## **Saving the World's Most Precious Resource**

Dewi Rogers1 and Alessandro Bettin2

*1DEWI Srl, Perugia (PG) 2SGI – Studio Galli Ingegneria SpA, Sarmeola di Rubano (PD) Italy*

#### **1. Introduction**

Sustainable Development – Education, Business and Management – 330 Architecture and Building Construction – Agriculture and Food Security

Zhang, B. & Zhang, K. (2002). Study on the Spatial Differentiation and the Evolution in Arid

*Geocryology*,Vol. 4, No. 24, (August, 2002)pp.414-420, ISSN 1000-0240

Regions-A Case Study for Oases in the Heihe River Basin. *Journal of Glaciology and*

Water is probably the world's most precious natural resource. Without it, there would be no life. It's sad then to think that so many people already live with less than their daily needs and that this situation is predicted to get even worse. In fact, according to an UN assessment, by 2025, around two-thirds of the world's population will have insufficient supply.

The traditional solution to a water shortage problem has been to develop new sources. But as the easily extractable ones have already been exploited, this quest is becoming increasingly difficult. Little wonder then, that even London, the capital city of what is considered to be one of the wettest countries in the world, is turning to desalination as a solution. Not only is this very expensive, but it is has a huge environmental impact. Furthermore, it addresses just the consequence of the problem and not its root cause, which invariably relates to inefficiencies.

So why then, has such a disastrous situation arisen in the first place, particularly when the water utility personnel is amongst the most dedicated of any industry? The answer lies in the traditional approach to water network management, where the objective was not necessarily to improve efficiency, but to ensure that the customers had some supply for a part of the time. Unknowingly, the leakage level was increasing, probably because only a small proportion of leaks ever come to the surface. As the reservoirs ran dry, water was rationed, making things even worse. In some cities water supply is counted in just a few days of the week. The answer appears obvious: reduce the losses. So why is this not done? Probably because the solution is not as easily defined as the problem itself.

#### **2. Water balance**

In its simplest definition, water loss is the difference between the total production and total consumption. However, there is a lot more to it than this, as the International Water Association's (IWA) standard water balance, (reproduced below in Figure 1), shows.

The loss is composed of two main components: commercial (or apparent) and physical (or real). The former comprises inaccurate measurement and illegal use, whilst the latter includes leakage from the reservoirs and from the supply and distribution network, including service pipes.

Saving the World's Most Precious Resource 333

A more detailed study, rather than a subjective observation, has shown otherwise, with leakage representing around 80% of total water loss. This is not surprising when it is considered that a typical leak is between 500 and 1000 times greater than the average consumption of a domestic property. Furthermore, the cost of recovering much of the

Leakage from reservoirs is usually visible and as the number of such structures in a network is limited, it is considered less problematic and more easily checked and recovered. Leakage from the network on the other hand, is a different proposition, not only because the pipes extend for hundreds and thousands of kilometres and are almost all buried, but mainly because only a small proportion of leaks are visible. This is due to many factors, including the ground conditions and the location of other services such as sewers, in the vicinity. So finding leaks in such circumstances is quite literally a needle in a haystack problem and probably explains why leakage is so high all over the world, with values often exceeding

It is clear that to undertake a proper water balance, it is first necessary to collect a lot of detailed information about the flows and consumptions. Unfortunately this is not always available. Even if it were, such an assessment inevitably ends up being a long term one, normally annual, which means that an invisible leak might run for a long time before its consequence is detected. What is needed then, is a more immediate and precise way of quantifying leakage – one that is not subject to measurement errors. This is precisely the reason the minimum night flow approach was developed. It is based on the principle that as the customer consumption is usually very low at night, the flow into a network at that time corresponds almost entirely to the leakage. Not only does this allow a more accurate assessment, but it also enables a daily check to be performed. As headloss and consequently the operating pressures, are directly related to the flow, it follows that at night, the pressures will tend to be higher, causing leakage to increase. Care is therefore needed when

Having derived the leakage level from the water balance, it is necessary to interpret the result. Traditionally, leakage is expressed as a percentage of the inflow. However this gives no indication of the quantity being lost, the area it covers nor how difficult it will be to recover. To overcome this, it has been suggested that leakage is expressed either in terms of the customer connections (l/connection/day) or in proportion to the extension of the network (l/km/hour). The former is better suited to urban areas, whereas the latter is more universally applicable and has the advantage of being directly related to the effort needed to recover it. The IWA Water Loss Specialist Group also propose the ILI (International Leakage Index) as a performance indicator, which relates the existing leakage to a minimum or unavoidable value, with 1.0 representing the optimum. There are some doubts though over the validity of accepting a minimum level for leakage other than zero, and how this is value

The real answer though, lies in considering leakage not as a technical parameter, but as an economic loss, caused by treating and pumping water that never reaches the final customer. To recover it requires an economic investment, which increases significantly if very low leakage levels are to be attained. If follows therefore that there will be an optimum balance between investment on the one hand and savings on the other, which will vary from

commercial loss is often uneconomic.

extrapolating the night time value to an average one.

50% of production.

is defined.

Commercial losses is often thought to be the main cause of water loss, probably because of the impression given by images such as the one in Figure 2, where numerous customer service pipes are illegally tapped into the distribution network.

Fig. 1. IWA Water Balance

Fig. 2. Illegal customer connections

Sustainable Development – Education, Business and Management – 332 Architecture and Building Construction – Agriculture and Food Security

Commercial losses is often thought to be the main cause of water loss, probably because of the impression given by images such as the one in Figure 2, where numerous customer

> Revenue w ater

Nonrevenue w ater (NRW)

Unauthorised consumption Customer metering inaccuracies

Unbilled unmetered consumption

Billed metered consumption (including w ater exported)

Billed unmetered consumption

Unbilled metered consumption

Leakage on transmission and/or distribution mains Leakage and overflow s at utility's storage tanks

Leakage on service connections up to point of customer metering

service pipes are illegally tapped into the distribution network.

Billed authorised consumption

Unbilled authorised consumption

Apparent losses

Real losses

Authorised consumption

Water losses

Fig. 1. IWA Water Balance

System input volume (corrected for know n errors)

Fig. 2. Illegal customer connections

A more detailed study, rather than a subjective observation, has shown otherwise, with leakage representing around 80% of total water loss. This is not surprising when it is considered that a typical leak is between 500 and 1000 times greater than the average consumption of a domestic property. Furthermore, the cost of recovering much of the commercial loss is often uneconomic.