**1. Introduction**

The use of computer models to support the evaluation of water resources management options has grown steadily since the first hydrologic [1] and water resource computer modeling tools [2]

were described in the 1960's and 1970's. In laying out their blueprint for a physically-based, digitally simulated hydrological response model, Freeze and Harlan echoed the developers of the Stanford Watershed Model [3] in claiming that *the ability to accurately predict behavior is a severe test of the adequacy of knowledge in any subject* [Emphasis added]. As part of a review and evaluation of multi-objective programming techniques in water resources Cohon and Marks paraphrase the assertion in Loucks and Dorfman [4] that these models *should be able to predict the outcome of the decision-making process* [Emphasis added]. These early pioneers in the field of water modeling were sanguine about the power of early computers to provide this predictive power, with Freeze and Harlan even conceding that their blueprint was more of an *artist's conception*. Nonetheless, the expectation was clear, as data quality and computing power improved; it would become increasingly possible to predict outcomes related to hydrology and water management and to use these predictions to identify the best possible course of action.

This expectation related to the power of rigorous analysis, common to modern science, is consistent with a line of thinking that came to prominence in Europe during the 18th Century Enlightenment. The Enlightenment ideal, which argued for a society based on reason instead of faith and doctrine, placing rational analysis in a favored position in terms of identifying the best course for social and political evolution, emerged following more than a century of thought on the proper balance between reason and faith. In 1615, Galileo wrote in a letter to the Grand Duchess Christina of Tuscany that *nothing* ... *which necessary demonstrations prove to us, ought to be called in question* ... *upon the testimony of biblical passages which may have some different meaning beneath their words* [5]. In his work *Pensées*, published in 1670, Pascal opined that *the supreme function of reason is to show man that some things are beyond reason* [6]. In 1693, following the 1687 publication of his landmark Principia, Newton wrote in a letter to Richard Bently that *gravity may put the planets into motion, but without the divine Power, it could never put them into such a circulating motion as they have about the Sun* [7].

By the 18th Century, however, this search for a holistic balance between reason and faith faded in the face of the predominance of reason and analysis. The Scottish philosopher David Hume [8] went so far as to suggest that *there is no question of importance whose decision is not comprised in the science of man; and there is none, which can be decided with certainty, before we become acquainted with that science*. Hume would likely have included the complex water management decisions confronting society today amongst his *questions of importance*. In the decades since the publication of the early work on hydrologic and water resources computer modeling, the water management community has worked diligently to capitalize on improved data availability and computing power. This has been done in order to assess whether a particular bit of infrastructure should be built (e.g., [9]), operating rule, encoded (e.g., [10]), policy, promulgated (e.g., [11]), or behavior, incentivized (e.g., [12]), based on the application of ever more sophisticated models and analysis.

Yet in the face of this growing sophistication within the water resources practice, and the continued aspiration that better data and computing power can uniquely identify the rational water management choice, two important trends conspire to complicate matters. The first relates to the increasing reliance on participatory stakeholder processes as a forum for evaluating water management options and selecting the appropriate course of action. This trend was launched in the United States by the passage of the National Environmental Policy Act, signed into law by President Nixon in 1970, which increased the influence of stakeholders in environmental policymaking [13]. Similar laws exist elsewhere in the world. The second trend relates to the growing recognition that earlier deterministic analytical approaches to this evaluation of options may no longer be appropriate in the face of future uncertainty. For example, the weakness of the assumption of hydrologic stationarity in the face of climate change, an assumption that has underpinned most water modeling work carried out since the 1970s, has been well documented [14].

The convergence of these two trends poses questions as to the proper role of data, information, analysis, and expertise in the inherently complex social and political process of negotiating water resources management agreements and implementing water resources management interventions. The authors have encountered this convergence while working in Bolivia on the Pilot Program on Climate Resilience (PPCR) and in California working on Integrated Regional Water Management (IRWM) planning. In response, it has proven useful to look back before the Enlightenment, to the origins of the western philosophical tradition in ancient Greece, and to re-discover that still important conversations on the proper role of knowledge and expertise within systems of governance and authority took place over 2000 years ago, conversations notable for the absence of consideration of faith. This paper argues that these conversations offer insights regarding the proper design of analysis supported, stakeholder driven, participatory water resources management planning, and decision-making processes.

### **2. A Conversation during an Athenian Drought**

An article about the evolving mythical and metaphorical power of the weather in literature [15] states the obvious, we all talk about the weather, and we always have. As such, it is not impossible to imagine that two leading minds of the western philosophical tradition would have discussed the drought conditions effecting Athens around 360 BC. At that time, Plato, 67 and the leader of his own academy, and Aristotle, 24 and studying with him, were engaged in a dialogue about the proper role of the state, and coming to somewhat different conclusions. Looking back on this dialogue from the perspective of the Renaissance, Rafael, in his fresco the School of Athens (Figure 1), depicted Plato gesturing towards the sky where presumably some divine truth about society could be discovered while Aristotle gestures towards the ground where mortals walk. Assuming Rafael captured them discussing the Athenian drought of 360 BC, what might we expect them to be saying to each other?

**Figure 1.** View of the central portion of the Raphael's *School of Athens* painted between 1509 and 1511 in the Vatican's Apostolic Place, depicting a supposed conversation between Plato (left) and Aristotle (right). (Stanza della Segnatura, Palazzi Pontifici, Vatican).

Before imagining such a hypothetical exchange, some context. Writings by a contemporary of Plato and Aristotle, Demosthenes, from 361 BC, observes that his *land not only produces no crops, but that year, as you all know, the water even dried up in wells, so that not a vegetable grew in the garden* (Polykles 61) and in 357 BC, he found that *there was a universal shortage of grain* (Leptines 33), chronicling that around 360 BC Athens, with its Mediterranean climate, was indeed gripped by a severe drought. Archeological evidence [16] suggests that by 360 BC Athens had become increasingly reliant on private rainwater catchment cisterns. This water management strategy stood in stark contrast to earlier expenditures by pre-democracy autocrats, even "tyrants", in more centralized water management arrangements, most notably the 7.5 km long aqueduct constructed during the reign of Peisistratos, also known as the Tyrant of Athens, who ruled from 546 BC to 527 BC. The Peisistratos Aqueduct conveyed water from springs in the foothills of the Hymottos Mountains to a point near the Acropolis and was comprised of both tunnels hewn from the solid rock and intricate terra cotta pipelines. It is one of antiquity's early examples of hydraulic engineering [17]. Against this backdrop, a possible conversation in Plato's Academy:

**Plato:** Things are getting worse, the wells are drying up, crops are failing, and conflicts over access to the cisterns still holding water are increasing. Something needs to be done.

**Plato:** Of course. You recall how Peisistratos responded to earlier water shortages by constructing his aqueduct that filled the fountains of the Acropolis. Why are we not considering similar responses today?

**Aristotle:** Because he was only able to achieve such a system by imposing severe taxes on his subjects. Surely you are not proposing that we sacrifice our Athenian democracy simply to increase water supplies. You must know that the empowered citizens of today's Athens are loathe to fund such autocratic endeavors.

**Plato:** But such ambitious responses need not be autocratic. Even though the citizens are fixed in the shadows1, so to speak, ignorant of the real options to manage current water shortages, I am confident that someone driven by the quest for the pure drought management option2 could identify the correct response that would truly benefit the polis.

**Aristotle:** It sounds like you would consider the role of Officer of the Fountains to be one fit for your ideal Philosopher-King3.

**Plato:** I would, and that seems to be consistent with the way our democracy is heading. I have seen your notes for your pending treatise on the Athenian Democracy where you document how the position of Officer of the Fountains is no longer filled by lot4.

**Aristotle:** Indeed, but as much as we cannot let a small group of recalcitrant citizens, based on self-interest alone, reject any collective action to respond to the drought, we must also avoid the temptation to cede all authority to a small group of the elite. You know my views on the importance of a strong middle-class5. That group must ultimately arbitrate the merits of any response to the current drought.

**Plato:** That sounds to me like a recipe for paralysis. Surely something as important as the management of water during these dry times warrants ceding control to those with the knowledge and experience to discover the correct course of action6.

**Aristotle:** I am not sure that the Officer of the Fountains alone could identify such a correct course of action when each citizen brings to the decision his or her own desires and passions. Better to engage the polis in the process of deliberating on what to do. Such a process might not yield the universally perfect drought response, but it might yield something that could practically be implemented7. In addition, there is the issue of uncertainty surrounding this decision. How do we know if the drought will persist or the rains return?

**Plato:** Uncertainty is indeed tricky. While some would accuse me of being an absolutist in my pursuit for the truth, be it in terms of the proper drought response or any other issue confronting the polis, I am cognizant of my unfortunate friend Socrates who recognized the wisdom of acknowledging what he did not know8.

**Aristotle:** It seems then that perhaps you should be willing to ascribe similar wisdom regarding the unknown and uncertain to the Officer of the Fountain. Adhering to an absolute version of the true drought response is not reasonable9. Can you defer to the deliberations of the middle class?

**Plato:** I cannot. The issue of how to navigate the current drought is simply too important to the survival of the polis to be left to the middle class. I adhere to my conviction that in this case the Officer of the Fountain must indeed by granted the authority of a Philosopher-King. Given the gravity of the situation and import of our response, it would seem that we are not of a like mind as to how best to respond.

**Aristotle:** So it seems. Let us hope it rains soon, and if it does not let us hope that our political deliberation, in whatever from it takes, leads to a decision. Doing nothing does not seem like a viable option.

1In the Allegory of the Cave (Republic, VII 514 a, 2 to 517 a, 7) Plato wrote of individuals chained in a cave, convinced that the shadows on the wall in front of them are reality. He goes on to speculate how someone freed from the cave would come to see both (i) the real world, *he would be able to view the things themselves, the beings, instead of the dim reflections* and (ii) his or her responsibility to those remaining in the cave because *If he again recalled his first dwelling, and the "knowing" that passes as the norm there, and the people with whom he once was chained, don't you think he would consider himself lucky and, by contrast, feel sorry for them?* 2In his Theory of Forms, Plato (Republic 477a-478e) asserts that there is a difference between knowledge (*epistémé*) and *doxa*, translated as opinion. *Knowledge is infallible—you cannot know what is false. Opinion, however, can be mistaken. So opinion cannot be knowledge*. As Plato applies the Theory of Forms to all things and ideas, he would argue that knowledge about the perfect drought response existed to be discovered. 3Plato (Republic V.473c11-d6) asserts that those with the ability to distinguish between knowledge and opinion should be endowed with authority because *unless philosophers become kings or those whom we now call kings and rulers philosophize and there is a conjunction of political power and philosophy there can be no cessation of evils*. While there is some debate as to whether Plato felt that all decision should be under the purview of his Philosopher-King, or simply the constitutional decisions, he does make reference to laws and institutions, which are related to the implementation of a constitution, stating that *knowledge of what justice is, which requires knowledge of the definition of its essence (form), will in some cases improve judgments about how far possible or actual laws or institutions are just* (Republic VI.484cd, VII.520cd). Major water management decisions would seem to be one such case. 4From Aristotle (Athenaion Politeia, 43.1) we learn that among the leadership positions on the Athenian Democracy, *the Officer of Fountains was one of the few that were elected by vote whereas most other officers were chosen by lot; so important was this position within the governance system of classical Athens*. As such, the citizens of the Athenian Democracy seemed to have already identified the need for a "professional" class of water managers. 5Aristotle (Politics 1296b-1297a 4.12) argues that a large and strong middle class is essential to the stability of a democracy as a stabilizing force against the conflict between the autocratic elite and the disgruntled masses. He writes that the *lawgiver in his constitution must always take in the middle class* and that *everywhere it is the arbitrator that is most trusted, and the man in the middle is an arbitrator*. The assumption here is that Plato would not agree that this middle class possessed the sort of training that he ascribed to his Philosopher-King. 6Plato (Republic, Book 6, lines 487d-488e), describing the state of affairs aboard a ship at sea, writes that sailors *have no idea that the true navigator must study the seasons of the year, the sky, the stars, the winds and all the other subjects appropriate to his profession if he is to be really fit to control a ship*. The inference is that the true captain is in a better position to steer the "Ship of State". 7Aristotle who wrote that sensation, reason and desire all contribute to action, stressed the difference between scientific knowledge and practical wisdom. Of the latter he wrote (Nicomachean Ethic, Book VI) it is *concerned with things human and things about which it is possible to deliberate; for we say this is above all the work of the man of practical wisdom, to deliberate well. Nor is practical wisdom concerned with universals only-it must also recognize the particulars; for it is practical, and practice is concerned with particulars*. This suggests that unlike Plato, Aristotle would not expect that a perfect, context independent, drought response to be available to be discovered. 8In his recounting of the trial of his mentor (Apology 21d), Plato suggested that in describing one of his accusers Socrates said *I am wiser than this man; for neither of us really knows anything fine and good, but this man thinks he knows something when he does not, whereas I, as I do not know anything, do not think I do either. I seem, then, in just this little thing to be wiser than this man at any rate, that what I do not know I do not think I know either*. 9Aristotle (Nicomachean Ethic, Book I) acknowledged uncertainty in the setting of public policy by stating that *we must therefore be content if, in dealing with subjects and starting from premises thus uncertain, we succeed in presenting a broad outline of the truth: when our subjects and our premises are merely generalities, it is enough if we arrive at generally valid conclusions for it is the mark of an educated mind to expect that amount of exactness in each kind which the nature of the particular subject admits.*

History records that in 346 BC, and again in 333 BC, Kephisodoros of Hagnous and Pytheas of Alopeke, respectively, were named in decrees commending their efforts as Officers of the Fountains to restore the public water system of Athens. The archeological evidence also points to increased investment in public water supply in the third quarter of the 4th Century BC [16]. As such, it seems that the citizens of Athens did take collective action in response to the drought of 360 BC. We can only imagine the conversations between the Officers of the Fountains and the citizens of Athens that took place in the Agora in more than a decade between 360 and 346 BC, leading to this apparent change in water policy. One can surmise, however, that they may have been contentious.

### **3. Implications for Water Management for the 21st Century**

This hypothetical dialogue is offered in order to suggest that, as in antiquity, the current efforts by a group of water management professionals to convince, through analysis, the wider body politic that a particular course of action is in its collective best interest, is rooted in a longstanding philosophical

debate. Thanks to the early pioneers in the field of water modeling, today's water management professionals have access to powerful tools as they seek to discover the best water management option in the face of uncertainty related to climate change, demography, economic development, and regulatory reform. New approaches to decision making under uncertainty based on rigorous analysis [18,19] have been proposed to assist in this effort. However, the fundamental question of whether the "perfect" option, the Platonic form, even exists to be discovered remains, motivating new questions as to the proper role of data and analysis in the creation of knowledge (epistemology from Plato's reference to *episteme*) that will guide society towards more sustainable patterns of water use and conservation as pressure on this vital resource grows.

This paper will argue that the proper response to these questions lies not in rejecting either the view of Plato, with his focus on the quest for the perfect form, or that of Aristotle, with his recognition of the importance of human desires in shaping decisions, but in their integration. Based on that argument, this paper reports on an attempt to translate recent academic work on decision making under uncertainty into a structured, analysis-supported, stakeholder-driven participatory process focused on river basin planning and management that includes the sustained participation of the full spectrum of stakeholders in a river basin and not simply interactions between the decision makers themselves. The process has been designed to facilitate negotiations amongst water managers and stakeholders holding distinct opinions as to the definition of a successful outcome, analogous to Plato's Philosopher-Kings" and Aristotle's "middle-class", respectively, leading, hopefully, to broad and stable agreements.

In presenting this process, the authors acknowledge that there is a rich literature pertaining to the use of participatory processes in water management, including literature on the use of models to inform these processes. Vionov et al. [20], presented the current state of the practice of modeling with stakeholders, identifying seven components of potential stakeholder participation in the environmental modeling process. Basco-Carrera et al. [21] proposed a framework for distinguishing between participatory and collaborative modeling in water resources management. Halbe et al. [22] propose a framework for initiating, designing, and institutionalizing participatory modeling in water resources management. The work presented here might reasonably be considered a single case within the general frameworks that these papers propose. What distinguishes this approach is the bottom up manner in which it has been developed and improved based on our experience as water modelers, trained to aspire to the Platonic role of Philosopher-King, yet working with stakeholders as members of the Aristotelian middle class, in a number of diverse settings over a number of years. While the approach may conform with more general frameworks, it is distinguished by its intentional design references to philosophical discourse.

It could be argued that the initial seeds of this approach were sown during the same period of time as the origins of water modeling. A recent review of the seminal psychological research related to decision making [23] referenced experiments conducted in the 1970s where individual subjects refused to apply accepted axioms from rational choice theory while playing games of chance, even after these axioms were fully explained to them [24]. Extrapolating these findings into the broader realm of decision-making, Slovic suggested that:

*An analysis which fails to appreciate the concern for regret and ambiguity is likely to violate the decision maker's preferences. Therefore we must work to devise methods for incorporating such psychological variables into the decision analysis, despite the aesthetic and practical complications that will arise when utilities and preferences are context-dependent*. [Emphasis added]

This conclusion, backed up by volumes of subsequent research in the fields of psychology and behavioral economics, suggests that no single "right" answer will be independently discovered by every player confronting the same game of chance, as suggested by the rational choice model. Gintis [25], demonstrated that counter to rational choice theory, when facing individual decisions game players are variably more averse to loss than attracted to gain, with some individuals placing greater value on what they possess than on what they could acquire. In public goods games, where freeriding is

the rational choice, Lopes [26], reported that participants demonstrated notions of fairness, cooperation, reciprocity, and social pressure that led to non-rational decisions. Finally, Henrich et al. [27] found that the degree of pre-existing social cohesion and market integration within a group of players of a public good game largely explained the degree of cooperation expressed.

Slovic's conclusion that the distinct preferences that individuals bring to a decision-making challenge will uniquely shape their notion of the correct course of action, has been repeatedly confirmed. The conclusion strongly evokes Aristotle's suggestion that in addition to reason, sensation and desire also contribute to action. The challenge is to create an intentional space for this sensation and desire in the water management decision-making process, which heretofore has been structured more along technical and analytical lines. Moreover, the suggestion that the degree of social cohesion contributes to higher levels of cooperation implies that a process that actually contributes to the creations of such cohesion can better harmonize the distinct sensations and desires of individual stakeholders. The practice described in this paper has been structured so that the distinct preferences held by individual stakeholders in a particular river basin remain the central focus, with each stakeholder taking responsibility for articulating and defending his or her own interests or values, as the group collectively seeks to define a mutually acceptable course of action.

This focus is consistent with the conclusions of the National Research Council [28], which in a useful review of models of decision-making, draws a distinction between the more common "predict-then-act" framework and an alternative "analysis with deliberation" approach. As its name implies, the first framework imagines a sequential progression of gathering information, using this information to construct knowledge, leading to decisions. This is how Plato imagined the path towards knowledge in his Theory of Forms. The second approach imagines a more iterative process, which begins with the stakeholders and decision makers participating in a joint problem formulation based on their particular preferences that guides data gathering and analytical design. This analysis will produce intermediate results that are collectively reviewed by these same participants leading to new cycles of data gathering and analysis, and ultimately to a decision. Aristotle's model of the deliberating middle class corresponds well with this approach.

As part of a research program on the "analysis with deliberation" approach, researchers at the RAND Corporation proposed a decision-making model called Robust Decision Making (RDM) that attempts to formalize this approach (Figure 2). A novel problem formulation framework referred to as XLRM initiates the iterative process. In the XLRM framework, a decision making challenge is divided into four component parts. The first corresponds to uncertain e**x**ogenous (X) factors that are outside the control of stakeholders and decision makers but which have the potential to influence outcomes (e.g., climate change, population growth). The second component relates to the **l**evers (L) or options that decision makers can implement in order to improve outcomes (e.g., new infrastructure, new regulations), with the option of maintaining the current system configuration (Business as Usual) always being considered. The R in the framework corresponds to the analytical tools deployed to **r**elate the articulated uncertainties to the identified management options so that values of stakeholder specific **m**etrics (M) of performance used to evaluate and compare potential outcomes can be produced. These different performance metrics can be equated to the different human sensations and desires that Aristotle referred to in the Nocomachean Ethic and the context-dependent preferences that Slovic discovered during his research on the validity of rational choice theory.

It is worth noting, however, that the iterative process shown in Figure 2 and described in Lempert et al [18] suggests that the "analysis with deliberation" approach will ultimately lead to the identification of the "Robust Strategy", which is one that will perform "well" over a range of possible future conditions. This strategy is presumably discovered by moving through a series of steps focused on case generation, scenario discovery, and tradeoff analysis leading to the identification of the robust approach. There are, however, several potential pathways that the analysis can follow after the XLRM participatory scoping has been completed which do not lead directly to the robust strategy. These include:

**Figure 2.** The Robust Decision Making framework, an example of the Analysis with Deliberation Approach to decision making under uncertainty. [18].

The figure is not explicit, however, in defining what constitutes a too poor performance, a too high vulnerability, or a too extreme tradeoff. In fact, in many applications of RDM in the water sector [29,30], efforts have been made to inform the definition of these thresholds through some algorithmic procedure. When taken to the extreme, this would render the process defined in Figure 2 a more complex version of predict-then-act, in effect reducing efforts to reconcile the different desires and preferences held by the stakeholders to simply add another deterministic step in an analytical procedure.

The participatory process described in this paper, referred to as the Robust Decision Support (RDS) practice attempts to operationalize the process described in Figure 2 while avoiding the inclination towards the Platonic inherent in overly algorithmic assignment of thresholds of performance, vulnerability, and tradeoff. Here is it important to be clear that the proposed RDS practice fully adopts the analytical framework within RDM (Figure 2), with its rigorous combination of uncertainties and strategies within model runs designed to produce values of a range of performance metrics. What is novel is the manner in which this analytical framework is embedded within a broadly subscribed participatory process, where the participating stakeholders, not algorithms, drive the decision to return to the participatory scoping step. These decisions are made based on the desires of individual or groups of stakeholders involved in a particular river basin planning exercise, desires that Slovic showed may have little relation to rational choice. While RDS should be considered a derivative of RDM, it is distinct in how it understands the motivations of individual stakeholders within a decision making process, and the importance it places on these distinct motivations.

While developing the RDS practice in the context of water management planning and decision making, the authors have spent five years working in collaboration with water management stakeholders and decision makers in Latin America, the United States, Southeast Asia, and Africa in order to test, refine, and formalize this analysis-supported participatory process. In developing this practice, the research team sought to recognize the unique preferences of each stakeholder engaged a decision-making process. The result is a formal process for accompanying stakeholders and decision makers through a series of modules, as shown in Figure 3.

**Figure 3.** Steps within the Robust Decision Support (RDS) practice designed to lead stakeholders representing different water management constituencies though a process of highly participatory negotiations beginning with a problem formulation and culminating with a joint commitment to implement a consensus program of action. Potential iterative loops back to the initial problem formulation can follow model results exploration. Adjustments in the assumed future uncertainties will require a new system vulnerability assessment, while adjustments to the management options under consideration can be accommodated without generating a new vulnerability baseline. The timing of stakeholder workshops within the process is indicated.

More complete descriptions of each of modules, in Figure 3, which are implemented in two phase Preparation and Formulation followed by Evaluation and Agreement, are included below, including some justification for their inclusion in the RDS practice in terms of managing stakeholder dynamics.

and perspectives they will bring to the process. The results are used to produce a map of social networks that highlight potential conflicts and coalitions, as well as a plan to encourage the contribution of information and insights to the process.

The entire process, from the initial definition of the decision space to the identification of the preferred integrated program of actions can take anywhere from 9 to 18 months to complete and requires stakeholder participation in up to five all-day workshops. The RDS practice should not be viewed as a quick effort that will miraculously lead to the identification of the perfect management option. The goal is not to create a common vision of what constitutes the true best outcome, rather, the RDS practice is a sustained effort to create a stable agreement between disparate parties, each of whom expresses and advocates for his or her own desired outcome within a process that fosters social cohesion.

We cannot know exactly what conversations took place in the Athenian Agora between the height of the 360 BC drought and the recognition of the Kephisodoros of Hagnous in 346 BC for his efforts to restore the fountains of Athens. Nonetheless it is clear that the process leading to the restoration of the fountains took years to complete. The great contribution of the early pioneers in the development of hydrologic and water resources model is that they provided the tools required to accelerate the complex social and political process leading to improved policy setting and decision-making around water resources. A decision that took more than a decade to reach in Ancient Athens can now be completed in a little more than a year.

### **4. Implementing the RDS Practice in the Andes**

Water managers across the tropical Andean Region must plan for an uncertain future prompted by climate change [31]. These changes are already being felt in high elevations. The glaciated area of Peru's Cordillera Blanca—which represents 35% of all glaciers in the country—have retreated from 728 km2 in 1960 to 536 km2 in 2003 [32]. In Bolivia's Cordillera Real, the glaciated area shrank 43% by volume between 1963 and 2006 [33]. Colombia has lost more than 50% of its glaciers, with only six glacier capped mountains remaining as of 2012 [34]. Also vulnerable to climatic changes are the Andean páramos (high altitude moorlands) and bofedales (high altitude marshes), which with their high infiltration and soil moisture storage capacities provide crucial water production for downstream users, particularly during low flow periods. The unique biodiversity of páramos and bofedales underscores their fragility, with climate change compromising their ability to supply water [35], as well as reducing their total area [36]. For the 40 million people that depend directly on Andean ecosystems (glaciers, páramos, and bofedales) for their water resources [37], such changes can have far-reaching consequences, creating water management challenges in terms of meeting urban and agricultural demands, capturing hydropower generation potential, and preserving important ecosystems.

One Andean region where these consequences are already being felt is the La Paz/El Alto Region of Bolivia (Figure 4). These neighboring cities possess very different histories and geographies that have translated in to very different levels of water service provision. The historical city of La Paz lies in a canyon to which several glaciated watersheds drain providing the city with reasonable levels of water supply, albeit one at risk to future retreat and disappearance of these glaciers. El Alto situated on the western edge of La Paz lies atop a 4000 meter high altiplano that drains to Lake Titicaca. Only one watershed draining the Cordillera Real has been tapped to provide water to El Alto, complemented by a groundwater pumping plant in the southern part of the city. The water quality in the Tuni watershed is also threatened by contamination associated with relic mining activity. While the two cities are actually served by the same water utility, the residents of El Alto typically rely heavily on water procured from private tanker trucks that ply the streets of the city. Based on its own analysis, the utility developed ambitious plans for increased water sharing between La Paz and El Alto and expansion of the El Alto capture zone far to the north. These plans encountered extreme skepticism and strong resistance from both the City of La Paz and existing irrigators in the targeted watersheds.

In 2012, in order to build trust and resolve the conflict between the stakeholders in La Paz and in rural areas to the north of El Alto, the Ministry of the Environment and Water convened a focal group of key stakeholders and decision makers to plan for new water management investments in the region. Over the course of a year, these stakeholders participated in an RDS process, beginning with the problem formulation workshop that produced the XLRM matrix shown in Table 1. Two of the articulated uncertainties merit further explanation. To a large extent, the current government in Bolivia draws its political power from indigenous communities, which are more present in rural areas and in El Alto than in historic La Paz. There was an interest in exploring the implications of a possible shift away from the current policy related to historical water rights in La Paz and/or the lower priority assigned to agricultural water use as against potable supply. Also, the uncertainty related to further expansion of irrigated areas had a particular local character as it was tied strongly to a global quinoa boom that was underway when the problem formulation was completed. In total, the definition of the five dimension of planning uncertainty resulted in the definition of an ensemble of 192 different future scenarios.

Using a widely available water resources systems model [38] as an analytical engine, a model of the pertinent region of the Cordillera Real was constructed and calibrated to simulate glacier evolution, bofedal dynamics, and rainfall-runoff hydrology in existing and potential source watersheds. The current urban and agricultural demand and supply systems were also represented, along with several strategies to expand the urban water supply system to several watersheds to the north along the Cordillera Real and to invest in watershed protection. To explore the six identified strategies across the full range of articulated uncertainties required an ensemble of 1152 WEAP model runs (192 future

scenarios × 6 management strategies), each producing a time series output for each of the metrics of performance. The challenge of exploring the large database of model output associated with such an ensemble is to develop a shared conceptual model amongst the RDS participants regarding the interpretation of results associated with each unique combination of scenario and strategy. It is in the development of this shared conceptual model that advanced data exploration and visualization tools proved particularly useful. Forni et al. [2016] reports on how advanced visualization was used in Bolivia to guide the RDS participants in the construction of a shared conceptual model and in the extraction of shared insights and knowledge from the ensemble of model output.

**Figure 4.** The La Paz/El Alto Region of Bolivia depicting current sources of water supply for La Paz and El Alto (solid outlines), along with potential new source watersheds (dashed outlines), existing reservoirs (triangles), conveyance facilities (solid lines), and points of urban (hexagons) and agricultural (pentagons) demand. The wellfield (circular cross hatch) providing water to El Alto is also shown. (Data source: Ministry of Environment and Water).

**Table 1.** Initial XLRM problem formulation matrix developed by a focal group of stakeholders representing various constituencies convened by the Bolivian Ministry of the Environment and Water during a one-day problem formulation workshop held in La Paz, Bolivia.

At this point it is sufficient to say that once this shared model was available it became increasingly easy to add additional layers of complexity to the data visualizations, without overwhelming the participants in the process. In spite of the complexity of the system, the RDS participants were able to grasp the implications of the information presented, co-creating knowledge about the performance of the system under various future scenarios and management strategies. At the end of the 9-month process a consensus was reached that the capture zone for the El Alto water supply system should be extended north to include new watersheds, but only in combination with investments to improve the performance of existing irrigation systems in these watershed. This decision was subsequently refined through engineering design and costing and submitted to the PPCR for funding. By 2018, the realization of these new investments was nearing completion.

### **5. Implementing the RDS Practice in California**

California has one of the most complex engineered water resource systems in the world. More than a century of water resources development has deeply impacted the environment. Most of California's historical wetlands are gone, water quality is impaired, habitats for salmonid fish are severely reduced, and close to 90% of riparian woodlands have been lost [39]. Much of this development occurred over the 20th century, from a combination of local, state, and federal infrastructure projects that invariably sourced water from a distance after local sources failed to keep up with demand. Since the 1970's, environmental demands have come to the forefront, and state and federal government's role has shifted a bit, from supporting infrastructure development, to protecting environmental needs [40]. Nonetheless, today, close to 80% of human water use in California is for irrigated agriculture, supporting a 40+ billion dollar industry and making California, especially the Central Valley, a globally important agricultural producer [41].

In California, the RDS practice has been applied to support local efforts to complete an Integrated Regional Water Management (IRWM) planning process in order to propose specific projects for financial support from the State of California. In Yuba County (Figure 5), at the downstream end of the Yuba River basin, which originates upstream in the Sierra Nevada, a stakeholder group representing municipal water supply, irrigation, hydropower, flood management, and environmental interests worked together over a period of 18 months to define the uncertainties, objectives and management options required to create an XLRM problem formulation matrix and to explore the potential performance of various management options contained within the Yuba County Integrated Regional Water Management Plan. To support the analysis a model was calibrated to represent the hydrology of the Yuba River Basin and the North and South Sub-Basins of the Yuba County Groundwater Aquifer. Within this hydrologic context, the operations of the major hydropower, flood control, and water supply infrastructure in the basin were simulated along with the allocation of water to meet municipal, irrigation, and ecological water needs.

**Figure 5.** The Yuba River Watershed in Northern California, depicting the source water region in the Sierra Nevada as well as the water management infrastructure located within Yuba County in the western portion of the watershed. Red dashed lines show the position of irrigation districts with access to some portion of the flow in the Yuba River Watershed, yellow dots show the location of population centers where drinking water is supplied by a public utility. (Data source: California Spatial Information Library).

The final XLRM matrix, co-created over several rounds of ensemble analysis, is shown in Table 2. It contains two dimensions of planning uncertainty, climate change, and regulatory reform associated with current efforts to update the Bay-Delta Water Quality Control Plan that contemplate requiring the tributaries in the Sacramento and San Joaquin River Basin to constantly contribute a percentage of their full natural flow to ensure the health of the Bay Delta system. Four climate projections of critical interest were formulated based on the concerns articulated by the stakeholders. Two corresponded to end members extracted from the IPCC database (hot-dry and warm-wet) and two were constructed to contain climate attributes of particular concern to stakeholders (repeating extended drought and dry-fall/wet spring). Two Delta regulation futures were also formulated, the first corresponding to the current regulatory regime and the second representing a 50% of full natural flow contribution to Delta health, meaning that in the final round of analysis, a total of eight future scenarios were ultimately explored.

**Table 2.** Final XLRM problem formulation matrix developed by a focal group of stakeholders representing various constituencies convened by the Yuba County Water Agency in Marysville, California. The initial problem formulation contained two additional dimensions of uncertainty associated with hydropower relicensing and land use change, but these were eliminated from consideration due to the discovery of their relatively small impact, relative to climate change and the eventual Delta regulatory regime, on the vulnerability of the system.

As in the case of Bolivia, a widely available water resource systems model was used as the primary analytical engine to produce values for the metrics of performance and innovative data visualization techniques [42] were used to create a shared conceptual model of the results of the ensemble analysis. The RDS analysis showed that the Yuba system is highly vulnerable in a drought scenario, combined with a new 50% of full natural flow Delta regulatory regime. The analysis of strategies, drawn from the IRWM plan, showed that most of the individual strategies proposed did not broadly reduce the regional vulnerabilities of the system as it relates to the metrics of performance posited by the full spectrum of stakeholders. In particular, urban conservation projects, while helping local constituencies, would not significantly decrease system level vulnerabilities because of the very small proportion of total water used by the non-agricultural sector. In this setting standalone urban water management actions, while helping to improve overall water use awareness, cannot produce broad benefits. However, an ambitious combination of multiple discrete strategies—a portfolio of infrastructure and river restoration action—could create positive cross-sectoral regional impact. Based on this exercise in negotiation, the participants in the Yuba RDS process were able to prioritize and combine discrete actions into a package for which they have sought financial support from the State of California. While there is no guarantee that this application will prove successful, it does represent the sort of integrated package of broadly supported actions that the IRWM planning process was intended to promote, but which has proved elusive over California's decade-long experiment with Integrated Regional Water Management Planning [43].


*Article* **Impacts of Urbanization on the Muthurajawela Marsh and Negombo Lagoon, Sri Lanka: Implications for Landscape Planning towards a Sustainable Urban Wetland Ecosystem**

**Darshana Athukorala 1,\*, Ronald C. Estoque 2, Yuji Murayama 3 and Bunkei Matsushita 3**

**Abstract:** Urban wetland ecosystems (UWEs) play important social and ecological roles but are often adversely affected by urban landscape transformations. Spatio-temporal analyses to gain insights into the trajectories of landscape changes in these ecosystems are needed for better landscape planning towards sustainable UWEs. In this study, we examined the impacts of urbanization on the Muthurajawela Marsh and Negombo Lagoon (MMNL), an important UWE in Sri Lanka that provides valuable ecosystem services. We used remote sensing data to detect changes in the land use/cover (LUC) of the MMNL over a two-decade period (1997–2017) and spatial metrics to characterize changes in landscape composition and configuration. The results revealed that the spatial and socio-economic elements of rapid urbanization of the MMNL had been the main driver of transformation of its natural environment over the past 20 years. This is indicated by a substantial expansion of settlements (+68%) and a considerable decrease of marshland and mangrove cover (−41% and −21%, respectively). A statistical analysis revealed a significant relationship between the change in population density and the loss of wetland due to settlement expansion at the Grama Niladhari division level (*n* = 99) (where wetland includes marshland, mangrove, and water) (1997–2007: *R2* = 0.435, *p* = 0.000; 2007–2017: *R2* = 0.343, *p* = 0.000). The findings also revealed that most of the observed LUC changes occurred in areas close to roads and growth nodes (viz. Negombo, Ja-Ela, Wattala, and Katana), which resulted in both landscape fragmentation and infill urban expansion. We conclude that, in order to ensure the sustainability of the MMNL, there is an urgent need for forward-looking landscape and urban planning to promote environmentally conscious urban development in the area which is a highly valuable UWE.

**Keywords:** wetland; muthurajawela marsh and negombo lagoon; socio-ecological; spatio-temporal analysis; urban ecology; remote sensing

## **1. Introduction**

Although wetlands account only for 4–6% of the world's surface area [1], they are regarded as one of the most productive ecosystems [2,3]. A wetland ecosystem includes marsh, fen, peatland, shallow water areas, as well as natural and human-made areas with evidence of intermittent and permanent waterlogged areas between natural wet aquatic habitats and dry terrestrial ecosystems [4,5]. Wetlands provide valuable social and ecological benefits, e.g., coastal protection, flood control, carbon sequestration and biodiversity conservation, among other ecosystem services [6–9]. As such, wetlands play important roles in the context of the United Nations' sustainable development goals (SDGs) and targets [10–12]. Unfortunately, almost 64–71% of the world's wetlands have been

**Citation:** Athukorala, D.; Estoque, R.C.; Murayama, Y.; Matsushita, B. Impacts of Urbanization on the Muthurajawela Marsh and Negombo Lagoon, Sri Lanka: Implications for Landscape Planning towards a Sustainable Urban Wetland Ecosystem. *Remote Sens.* **2021**, *13*, 316. https://doi.org/10.3390/rs13020316

Received: 25 November 2020 Accepted: 12 January 2021 Published: 18 January 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

transformed, degraded or have disappeared in recent decades as a result of anthropogenic activities, including industrialization, agriculture, and urbanization [1,13–15].

In 2018, more than 55% of the world's population lived in urban areas, and this proportion is projected to reach 68% by 2050 [16]. Such a development would exert tremendous pressure on the natural environment across urban areas in the world as large areas transform to impervious surfaces. Studies have shown that rapid, uncontrolled, and unplanned urbanization has been impacting the quality of urban ecological environments across the world [17–22], including urban wetland ecosystems (UWEs) [23–27].

Advances in geospatial technology, including geographic information systems (GIS) and remote sensing, have greatly improved the monitoring of landscape changes over space and time. Today, information derived from these advancements provides important input to landscape planning and decision-making in many contexts, biodiversity conservation [28–31], and sustainable urbanization [32–34]. In fact, Earth observation technologies, particularly remote sensing, play important roles in the monitoring of various social and ecological indicators related to the United Nations' SDGs and targets [35], including those that are associated with wetlands [11,36,37].

With changes in land use/cover (LUC) due to urbanization, natural landscapes suffer from irreversible transformation [38]. The monitoring of landscape status over space and time is hence an essential endeavor. Scholars have shown the usefulness of geospatial techniques for characterizing landscape patterns, including those of UWEs [27,39,40], and their changes over time [41–43]. Such information that facilitates impact analysis on ecosystem services and biodiversity [44–46] can be used to direct landscape and urban development planning towards sustainable UWEs [45,47,48].

The Muthurajawela Marsh and Negombo Lagoon (MMNL), the biggest coastal saltwater peat bog in Sri Lanka, is located on the western coastal belt between the Kelani River and Negombo Lagoon lying inland to Katana, Wattala, Ja-Ela, and Negombo in the Gampaha District of the Western Province. The Muthurajawela Marsh, together with the lagoon, creates an integrated coastal wetland ecosystem. The complex development of this landscape during the Holocene period (Circa 6000–5000 years) progressed after the final glacial period (Figure 1) [49–51]. The MMNL has been, and is still today, an important UWE in the country. Its estimated monetary value is around Rs 726.5 million per year, including benefits from flood prevention, treatment of wastewater, and shallow coastal fisheries [52].

**Figure 1.** Geological evolution of the Muthurajawela Marsh and Negombo Lagoon (MMNL), Sri Lanka, from the Holocene period to the present. (**a**) The MMNL in the mid-Holocene period, marked with a marine regression, exposing a wider coastal area; (**b**) Wetland started to form (c. 7000); (**c**) Formation of wetland from south to north and clay deposits continued (c. 6500); (**d**) Marshland and lagoon started to form as an interdependent ecological system (c. 6500–6300); (**e**) Formation of marshland and lagoon continued at the final stage, forming one contiguous wetland (c. 6000); and (**f**) The present condition in which the MMNL is an important urban wetland ecosystem (UWE) in the Colombo Metropolitan Region with high socio-ecological significance. The images were sourced from the MMNL's master plan and MMNL's conservation management plan [49,50].

The Colombo Metropolitan Region (CMR), the country's capital and the location of the MMNL, has grown very rapidly over the recent decades. For example, CMR's population grew from 3.9 million in 1981 to 5.8 million in 2012 [53]. Consequently, the area of builtup lands in the CMR also expanded dramatically from 11,165 ha in 1992 to 35,876 ha in 2014 [54]. There have been several studies on MMNL [55,56], but a study that focuses on the impacts of urbanization on this highly valuable UWE is still lacking.

Hence, the focus in this study is specifically on detecting changes in the LUC and examining the landscape composition and configuration of the MMNL over the past two decades (1997–2017) by using remote sensing data and spatial metrics respectively. The loss of wetland (water, mangrove, and marshland) due to urbanization (settlement expansion) was quantified and the influence of population growth to this LUC transition was investigated. The implications of the findings for landscape and urban planning towards sustainable UWEs are discussed.

#### **2. Materials and Methods**

#### *2.1. The MMNL, Sri Lanka*

The MMNL, extending over roughly 134 km2 (Figure 2), consists of the Gampaha District's four Divisional Secretariats (DS). This area has been experiencing rapid urbanization and economic growth over the past three decades. The landscape of the MMNL encompasses various land surface features, including the lagoon and marsh and mangrove areas, as well as some highly and moderately urbanized lands.

The MMNL receives freshwater from the eastward direction via two channels (viz. lower Aththanagalu Oya and lower Kelani Ganga). The area has a gentle slope, with an elevation range of 0–30 m. According to the geological timetable, the MMNL belongs to the Quaternary soil group, which is composed of soil deposits from wind-blown sands, river deposits, and lacustrine sediments [57]. The area has a tropical monsoon climate as per the Koppen classification [58]. The wet season is from May to September, and the dry season is from December to early March. Mean annual rainfall is between 2000 mm and 2500 mm, with mean annual daytime temperatures ranging from 22.5 ◦C to 25.0 ◦C [59].

Demographically, the MMNL contains urban and rural settlements. However, due to a rising population and rapid urban expansion, many parts of this valuable UWE have become highly vulnerable to the impacts of urbanization, including the Muthurajawela Marsh, which contains two protected areas (Figure 2). The lagoon is a shallow-water coastal water body and a highly productive fish area [52]. It is joined to the Indian Ocean by a single narrow opening in the north. This, too, will continue to be affected if the rapid urbanization of the area is not controlled and carefully planned.

In fact, the lagoon had initially been utilized by the fishing industry and the neighboring area had been occupied by settlements and industries [51,60]. However, over the past 60 years, parts of the lagoon have been reclaimed for various purposes, including illegitimate settlements that have extended to intertidal sands along the channel segments of the estuary [51,52]. Unlawful activities, such as illegal settlements, illegal fishing, and illegal cutting of trees, as well as waste dumping and water pollution, are among the important current concerns with regard to the management of the MMNL [51,52].

#### *2.2. LUC Mapping*

We used three Landsat images for this study, viz. two TM (Thematic Mapper) images captured in 1997-02-07 and 2007-01-02, and one OLI/TIRS (Operational Land Imager/ Thermal Infrared Sensor) image captured in 2017-01-31. They were sourced from the USGS (https://earthexplorer.usgs.gov/). The images have a spatial resolution of 30 m. Only one Landsat scene was needed for the study area. Temporal consistency and cloud cover were considered in the selection of the images. All the images were acquired during the cloud-free, dry season.

Before LUC classification, we first created a wetland classification scheme comprising four classes: settlement, marshland, mangrove, and water (Table 1). These LUC classes

reflect the physical characteristics of the study area and have been widely used in previous studies [61–63].

**Figure 2.** Location of the MMNL. (**a**) Map of Sri Lanka, (**b**) Gampaha District, and (**c**) a 3D map of the MMNL produced using a 30 m digital elevation model (ASTER). The Google Earth image was acquired on 17 February 2017.

The three Landsat images were classified using a hybrid classification method, i.e., a combination of unsupervised and supervised classification techniques [64,65], which was performed in ArcGIS 10.6. First, we used the ISODATA clustering algorithm, an unsupervised classification algorithm, to produce 14 clusters for each image. We used bands 5, 4, and 3 for the TM images and bands 6, 5, and 4 for the OLI/TIRS image. Second, we performed a supervised classification using the maximum likelihood algorithm and the result of the first step as input. For the training sites, we digitized 15 training samples for each class, where the number of pixels per sample ranged from 20 to 782. In total, we digitized 60 samples per image. We assessed the accuracy of the classified 1997, 2007, and 2017 LUC maps using 400 random points. Google Earth was the source of reference data

for 2007 and 2017. For 1997, we used topographic maps from the Survey Department of Sri Lanka [66].

**Table 1.** Wetland classification scheme used in this study.

*2.3. Assessment of LUC Changes in the MMNL*

We calculated the loss and gain areas and rates for each LUC class using Equations (1) and (2), respectively [67].

$$\text{L/G area} \, := A\_b - A\_a \tag{1}$$

$$L/G\text{ rate } (\%) \;= (A\_b - A\_a)/A\_a \times 100\tag{2}$$

where *L*/*G* area refers to the area that each class lost or gained (ha) between two time points. *L*/*G* rate refers to the percentage of loss or gain (%) of each class area. *Aa* and *Ab* are the beginning and the end values of each class, respectively.

#### *2.4. Assessment of Wetland Loss Across Grama Niladhari (GN) Divisions*

Due to rapid urbanization, there is a high likelihood of the wetland area and its surrounding areas being converted to urban land use. Here, we identified the top wetlandlosing GNs susceptible to urbanization (settlement expansion) over the study period. Currently, there are 99 GN divisions in the study area. To do this, we calculated the density of wetland loss due to urbanization across the GNs during the first time period (TP1) (1997– 2007) and second time period (TP2) (2007–2017) using Equations (3) and (4), respectively.

$$WLD\_{TP1}(\%) = \frac{WL\_{TP1}}{A} \times 100\tag{3}$$

$$WLD\_{TP2}(\%) = \frac{WL\_{TP2}}{A} \times 100\tag{4}$$

where *WLDTP*1(%) and *WLDTP*2(%) refer to the density of wetland loss density in a particular GN due to urbanization (settlement expansion) during the two time periods (first and second, respectively). *WLTP*1 and *WLTP*2 are the areas of wetland loss in a particular GN due to urbanization during the two time periods (first and second, respectively). *A* refers to the area of a particular GN. Wetland includes water, mangrove, and marshland.

#### *2.5. Relationship between Urbanization and Wetland Loss*

We examined the relationship between urbanization as proxied by the change in population density (CPD) (Equations (5) and (6)) and density of wetland loss due to settlement expansion (WLD) at the GN division level. Since the 1997, 2007, and 2017 population data at the GN division level were not available, we extrapolated such data based on the average population growth rate (APGR) of Katana Wattala, Ja-Ela, and Negombo DS divisions for 1981, 2001, and 2012 census years. Each of these DS divisions consisted of a number of GN divisions. Thus, for those GN divisions that belonged to a particular DS division, only one APGR was used. Finally, scatter plots were produced between CPD (x) and WLD (y) for both periods (TP1 and TP2) to examine the relationship between urbanization and wetland loss.

$$\text{CPD}\_{TP1}(\%) = \frac{PD\_{2007} - PD\_{1997}}{PD\_{1997}} \times 100\tag{5}$$

$$\text{CPD}\_{TP2}(\%) = \frac{PD\_{2017} - PD\_{2007}}{PD\_{2007}} \times 100\tag{6}$$

where *CPDTP*1(%) and *CPDTP*2(%) refer to the change in population density in a particular GN during the two time periods (first and second, respectively). *PD* refers to the population density of a particular GN.

#### *2.6. Landscape Pattern Analysis*

Many scholars have discussed the usefulness of spatial metrics for landscape pattern analysis [68,69]. Landscape-level metrics provide general information about landscape patterns in the study area. On the other hand, class-level metrics include more detailed descriptions of landscape patterns based on class-level information. Using FRAGSTATS V4.2, landscape-level and class-level metrics were computed to gain insights into the changes in the landscape pattern of the MMNL (Table 2).

Where: i = any LUC patch; *ni* = number of patches of LUC category i; A = total area of LUC (m2); *eik is sum o f* edge total (m) in LUC class I—counting landscape boundary and segments; j = 1,2, 3, ... , n sum of the specific patch area; *aij* = patch area ij in number of the pixel ; *pi* = proportion of the i—any LUC area of the total landscape; *pij* = circumference of patch ij regarding the sum of cell surface; Z = total pixel in the landscape; m = total patch in the entire area, without landscape border. Patch number was determined based on the eight-cell neighborhood rule.

#### **3. Results**

#### *3.1. Classification Accuracy and LUC Changes*

The overall accuracy of the three classified LUC maps was 83.0% in 1997, 84.5% in 2007, and 84.8% in 2017 (Appendix A Table A1). The primary cause of the classification errors was spectral confusion because some of the pixels of the LUC classes had similar spectral reflectance due to soil moisture levels and vegetation types [71,72]. We found that some mangrove pixels were misclassified as marsh, and some marsh pixels were misclassified as settlements and mangroves, and so on (Appendix A Table A1). Nevertheless, the accuracy levels of the classified LUC maps of the MMNL are adequate for this study. Other related studies have reported overall accuracies ranging from 69% to 82% [73–75].

The LUC change analysis revealed that marshland in the MMNL had been drastically shrinking due primarily to the expansion of settlements. For example, of the 1767 ha and 2282 ha total loss of the marshland class in TP1 and TP2, respectively, 820.89 ha (43%) and 691.92 ha (42%) were lost from the mangrove class (Figure 3 and Table 3). During TP1, the settlement class gained a total area of 1464 ha, whereas during TP2, it gained a total area 1880.91 ha.

**Figure 3.** LUC maps of the MMNL in 1997, 2007, and 2017 derived from Landsat data (see Methods).

**Table 3.** LUC transitions in the MMNL (ha).

The mangrove class experienced considerable losses to both the marshland and settlement classes in the two periods. There were some gains in the area of the mangrove class, but its total loss outweighed its total gain, resulting in net losses during both periods. Nevertheless, the gain of mangrove from marshland in both periods (520 ha in TP1 and 538 ha in TP2) is a positive sign. This could have been due to the government's efforts to conserve the MMN by conducting mangrove reforestation activities in previous years.

Table 4 shows the L/G of the LUC classes in the MMNL in terms of area and rate. The results revealed that the mangrove class had a net decrease of 266 ha (14%) and 126 ha (8%) in TP1 and TP2, respectively. The marshland class had a net reduction of 539 ha (11%) and 1406 ha (33%). By contrast, the settlement class had a net increase of 883 ha (25%) and 1528 ha (35%).

**Table 4.** Losses and gains of the LUC classes in the MMNL.

Figure 4 shows the spatial distribution of wetland loss due to urbanization (settlement expansion) in both periods, i.e., the loss of marshland, mangrove, and water. The results revealed that the central part (south of the lagoon) and the east part of the MMNL became more fragmented due to road construction. During the 2007–2017 period, the area exhibited a ribbon type of development. Another pattern that emerged is the settlement cluster in the middle, western part of the MMNL. In general, settlements consumed mostly the marshland and mangrove areas in the northern, eastern, and southern parts of the MMNL.

**Figure 4.** Spatial distribution of wetland loss in the MMNL due to urbanization (settlement expansion). (**left**) 1997 to 2007; and (**right**) 2007 to 2017. Wetland includes water, mangrove, and marshland.

#### *3.2. Change in Population Density and Loss of Wetland Due to Urbanization*

The maps of the GN-level change in population density (CPD) and density of wetland loss due to urbanization (settlement expansion) (WLD) are shown in Figure 5. The top five GNs in terms of WLD during TP1 were Thimbirigasyaya, Nayakakanda South, Kurunduhena, Welikadamulla, Telangapatha; those during TP2 were Thalahena, Palliyawatta South, Maha Pamunugama, Pitipana North, Udammita South. A more exhaustive list of the top GNs in terms of WLD is given in Appendix A Table A2.

The statistical analysis revealed a positive, significant correlation between CPD and WLD in both time periods (TP1: *R2* = 0.435, *p* = 0.000; TP2: *R2* = 0.343, *p* = 0.000) (Figure 6), indicating that as the CPD increased, the WLD also increased. This suggests that urbanization was, indeed, an important factor or a driver of wetland loss in the MMNL.

#### *3.3. Changes in Landscape Composition and Configuration*

At the class-level, the results revealed that between 1997 and 2017, the marshland class had become more fragmented, as indicated by the overall increase in its number of patches (NP), patch density (PD), edge density (ED), and the decline in its largest patch index (LPI), landscape shape index (LSI), and COHESION due to conversions to settlement marshland and water classes (Figure 7). On the other hand, the mangrove class had become less fragmented, as indicated by the overall decrease in its NP, PD, and ED. While its COHESION decreased during the first period, it increased during the second period. This suggests that the mangrove class, with the loss of some of its fragmented patches, had become more contiguous from 2007 to 2017. The decrease in LPI and LSI during the 1997–2017 period was due to mangrove gains, especially those resulting from the conversion of marshland, suggesting the development of more regular shapes at the edges of the mangrove. Conversely, the analysis results showed that LPI and LSI in marshland had fewer regular shapes at the edges, and the patches were more adjoining compared to the mangrove class. Therefore, the overall result of the mangrove showed less fragmentation than the marshland class. The settlement class had also become less

fragmented, as indicated by the overall decrease in its NP, PD, and ED, and the overall increase in its COHESION. The expansion of settlements to adjacent areas resulted in an infilling pattern of urban growth, and eventually in a more contiguous and aggregated configuration of the settlement class. This observation is also supported by the increasing pattern of the settlement class' LPI.

**Figure 5.** GN-level change in population density (CPD) (**a**,**b**) and density of wetland loss due to urbanization (settlement expansion) (WLD) (c and d) in the MMNL. Wetland includes water, mangrove, and marshland. The numbers on maps (**c**,**d**) refer to the numbers of the GNs in Appendix A Table A2.

**Figure 6.** Relationship between change in population density (CPD) and density of wetland loss due to settlement expansion (WLD) in the MMNL during (**a**) 1997–2007 (TP1) and (**b**) 2007–2017 (TP1). Each point is a GN division.

**Figure 7.** Class-level spatial metrics for the MMNL (1997–2017).

At the landscape level, the results revealed that SHDI and SHEI had gradually declined from 1997 to 2017 (Table 5). This indicates that the landscape of MMNL had tended to be less fragmented, clustering, and aggregating. Moreover, the overall decrease in patch richness at the class-level had resulted in an overall decrease in SHDI and SHEI at the landscape-level in the study area.

**Table 5.** Landscape-level spatial metrics for the MMNL (1997–2017).

#### **4. Discussion**

*4.1. Landscape Transformation of the MMNL*

The MMNL is an important UWE in Sri Lanka owing to its biodiverse ecosystem that is home to numerous wildlife, water habitat species, and migratory birds [50], besides the various ecosystem services it provides [52]. Our findings showed that the landscape of this highly valuable UWE had been transformed dramatically over the past two decades, losing considerable expanses of its marshland and mangrove cover due to rapid, unplanned and uncontrolled urbanization (settlement expansion) (Figures 3 and 4; Table 3).

Urbanization, led by socio-economic and biophysical factors, has altered and is still altering the MMNL landscape. If this wetland change trend continues, it may adversely impact the ecosystem services, biodiversity and aesthetic value of the area. There are indications of an infilling urban growth pattern in the MMNL (Figure 3) and clear signs of illegal settlements inside the wetland area. The uncontrolled urban expansion of the CMR and its effects on landscape changes have caused many socio-economic and ecological problems, as well as an overall degradation of the natural environment in the study area.

Today, the MMNL has been fragmented into four parts owing to settlements, the construction of the main road and the Colombo-Katunayake Expressway [76], and the area experiencing a ribbon type-development during the 2007–2017 period. This expressway runs along the marshland, and a small piece of the Negombo lagoon can be clearly identified in our classified maps, especially in 2007 and 2017 (Figures 3 and 4). Using urban wetland modelling, Zubair et al. (2017) [77] found that two of the main watersheds had increased, but subsequently decreased in one due to urban expansion. These findings generally support our results on the effects of human intervention, as indicated in previous research [78].

Availability and reclamation of natural wetland areas according to environmentfriendly policies and enforcement of regulations are crucial to the protection and conservation of the MMNL. Restoration of wetland vegetation is vital, particularly in the highly populated areas of the GN divisions. A top-to-bottom approach should be adopted to ensure judicious use of wetland to ensure its protection and sustainability. Generally, wetland areas play an essential role in mitigating the urban heat island effect [79]. The MMNL is situated in the CMR which covers a considerable area. Conserving this highly valuable wetland will promote the cooling effect for better living conditions for the city dwellers of the CMR. Therefore, the protection and sustainability of the wetland should be promoted systematically by policymakers and urban planners.

In this study, we used a hybrid method (unsupervised and supervised) to classify the LUC of the MMNL from Landsat imagery (see Section 2.2). The method minimized classification errors. Overall, this hybrid classification provides comprehensive classifications of natural plant vegetation and soil moisture levels in urban wetland areas [80]. The overall accuracy of our three classified LUC maps was 83.0% in 1997, 84.5% in 2007, and 84.8% in 2017. Similar findings were reported by reference [64] in their small wetlands mapping in Kenya and Tanzania, where using unsupervised and supervised approaches, the overall classification accuracy was 83%. Lane et al. (2014) [81] reports an overall accuracy of 86.5% in wetland classification using eight-band high-resolution satellite data and a hybrid mapping approach in the Selenga River Delta in southeastern Siberia, Russia.

In general, settlement expansion can be correlated with rapid population growth in the MMNL. It is important to note that the MMNL is located in the Gampaha District of Sri Lanka, the second most populous district in Sri Lanka after the Colombo District. Rural-urban migration due to the establishment of Export Processing Zones (viz. Biyagama, Katunayake) in the Gampaha District [82] contributed to the higher population growth during the 1990s. Job opportunities in these Export Processing Zones provided better living conditions for migrants. Given the decline in agricultural productivity in the country's dry regions, the government encouraged rural-urban migration to reduce poverty [83]. In particular, post-war policies and development projects in the CMR resulted in the country's industrial capital becoming an important driver of rapid urban growth of the CMR after 2009 [84].

Figure 8 projects continuous growth in four DS divisions in the study area from 1981 to 2051. The dramatic increase in the urban population of four DS divisions in the study area is expected to continue in the future. From 1997 to 2017, the population of the study area increased by 15.51%. The population density of the Wattala and Ja-Ela DS divisions was higher than that of Katana and Negombo, indicating high urban pressure radiating from the capital of Colombo and the core of the Gampaha District (Figures 2, 3 and 5). However, the Negombo DS division should not be ignored because this DS division has a significant effect on the wetland's northern part (Figure 2), which has been impacted

by rapid population growth leading to residential (including illegal settlements) and non-residential developments in industrial and commercial sectors.

**Figure 8.** Projected population trend for Wattala, Ja-Ela, Katana and Negombo DSDs of Gampaha District: The population data for 1981, 2001 and 2012 were sourced from the Department of Census and Statistics, Sri Lanka [85]. The 1991 population was projected using growth rates of 5.1%, 2.6%, 2.1%, and 6.9% for Wattala, Ja-Ela, Katana, and Negombo, respectively. From 2021 to 2051, growth rates were projected using rates of 0.87%, 0.83%, 0.51%, and −0.13% for Wattala, Ja-Ela, Katana, and Negombo, respectively.

In wetland change analyses, researchers have identified some implications of wetland landscape pattern changes due to urbanization [86,87]. There is evidence that environmental degradation is very much related to economic growth, as reflected particularly in per capita income [88]. A spatial metrics analysis shows that the MMNL settlement areas have become less fragmented (Figure 7) due to the decrease in the number of settlement patches along the roads and the dispersion of newly established patches from existing settlement areas around growth nodes (i.e., Negombo, Ja Ela, and Wattala) (Figure 2) and administrative centers. Furthermore, current settlement patches have become more extensive, and the gaps between settlement patches have diminished. While the expansion process has led to the development of settlement patches, there is a reduction in the distance between settlement patches due to the impact of dispersion in the MMNL. This rapid urban development of the MMNL and its subsequent wetland landscape changes have created many socio-ecological problems (Figure 9).

The MMNL has already been encroached upon by the urban sprawl; further infilling patterns are anticipated. Several factors can cause further fragmentation of the MMNL's landscape and dispersed growth. The MMNL is located in the western coastal plain of Sri Lanka (Figure 2), and there are no significant physical restrictions, such as high altitudes and steep slopes, which promote fragmentation of the landscape. In the past two decades, a significant expansion of road networks (Figure 3) has shortened travel time from the urban center (capital city of Colombo and the core of the Gampaha District) to the suburbs (Negombo, Katana, Wattala, and Ja Ela) and Katunayake Bandaranaike International Airport. While people moving to the suburbs facilitate the fragmentation of the wetland landscape, the lagoon fishing industry and its settlements, as well as illegal wetland reclamation, also contribute to wetland degradation and land fragmentation. Wetland areas along the roads have progressively been turned into settlements (Figure 4). Moreover, push factors, such as high housing costs and service value and land prices in urban core areas have facilitated the fragmentation of wetland areas, including marshland and mangrove areas, over the last two decades in the MMNL. Accordingly, such issues

concerning future wetland landscape and urban planning activities in and around the MMNL must be addressed.

**Figure 9.** Some fieldwork photos of the MMNL: (**a**) Human encroachment in Negombo Lagoon area, (**b**) Illegal settlements of the study area, (**c**) Dumping of garbage into the lagoon, and (**d**) Human activities inside the Muthurajawela marshland. Source: First author (D. A.), 2017.

#### *4.2. Implications for Wetland Sustainability*

A variety of environmental and socio-economic problems have arisen as a result of the rapid urbanization process in the MMNL, such as extensive degradation of wetland ecosystems and loss of important wetland ecosystem services that affect flood control, carbon sequestration, wetland productivity, the quantity of fish in the lagoon, urban poverty, and slum development. Besides the ongoing urbanization process that has led to the loss of wetland areas, current policies and regulations have not adequately addressed increasing land fragmentation and scattered settlements in the MMNL. Land fragmentation is threatening the sustainability of this urban wetland.

This study was performed on 4 DS divisions and 99 GN divisions in the Gampaha District (Figures 2 and 5). Local government authorities should consider stricter enforcement of protection and conservation measures for wetland areas that have become increasingly degraded. It would be useful for the Department of Wildlife Conservation, the Ministry of Environment, the Central Environmental Authority, and the Urban Development Authority to undertake wetland conservation projects, in particular, wetland restoration projects and community-based approaches with judicious use of wetland. While local NGOs and communities are also involved in implementing the Muthurajawela Wetland Management Plan [49,50,89], the aims of their management plan have yet to be achieved. Time is of the essence. Therefore, it is strongly recommended that city planners and local policymakers implement new laws and legislation without further delay to protect this wetland.

RS data and GIS techniques are useful for spatial analysis [90]. The above study could be useful in determining how much of the future landscape changes (e.g., the spatial extent of urban areas towards natural environment and urban wetland areas) could be compensated by comprehensive land-use practices and environmental rehabilitation activities such as reforestation programs in mangrove and also natural areas. The recovery of the wetland has significant potential to reduce the pressure on the carrying capacity of the MMNL by human activity. Once the MMNL has been changed into a settlement, it would be difficult to reverse the conversion.

Against this backdrop, it is evident that scientifically sound knowledge is needed to help urban landscape planners and policymakers tackle socio-ecological issues and achieve the essential SDGs [35] to ensure wise and sustainable use of the MMNL. Indeed, wetlands provide multiple services and benefits to people and are vital to attaining the SDGs [91] and Aichi Targets of the Convention on Biological Diversity [92]. The fourth Strategic Plan (2016–2024) of the Ramsar Convention has identified four major objectives and 19 specific objectives in this regard. Therefore, the authorities should aim to implement the Ramsar Convention's Strategic Plans and attain the Aichi Targets so as to mitigate socio-ecological problems associated with urbanization and protect wetland landscapes.

#### *4.3. Limitations and Prospects for Future Wetland Study*

This study used three satellite images captured in 1997, 2007, and 2017. More satellite images taken at different time points would provide valuable details, leading to a better spatial-temporal analysis. We need to point out that this investigation was limited by the lack of other clear and accessible satellite images temporarily compatible with the three satellite images employed. Another limitation was the unavailability of actual socioeconomic data of the study area. Simultaneous and direct measurements are required to understand effective wetland conservation and protection strategies. Direct observations of urban wetlands can provide valuable knowledge for potential wetland management over the next few decades. We propose that future studies use much higher-resolution remote sensing images to investigate wetlands (at least for Sri Lanka). We need contemporary and long-term observations to appreciate the challenges in ensuring urban wetland sustainability.

#### **5. Conclusions**

We examined the impacts of urbanization on the Muthurajawela Marsh and Negombo Lagoon (MMNL), an important urban wetland ecosystem (UWE) in Sri Lanka owing to the valuable ecosystem services it provides. We found a substantial expansion of its settlements (+68%) and a considerable decrease in the extent of its marshland and mangrove forests (−41% and −21%, respectively). A statistical analysis revealed a positive, significant relationship between the change in population density and the loss of wetland due to settlement expansion, indicating that urbanization had indeed played a major role in the landscape transformation of the MMNL. The findings also revealed that most of the observed LUC changes occurred in areas close to roads and growth nodes (viz. Negombo, Ja-Ela, Wattala, and Katana), resulting in landscape fragmentation and infill urban expansion. The results indicated that the spatial and socio-economic elements of rapid urbanization of the MMNL had been the main driver of the transformation of its natural environment over the past 20 years. The study also showed that a hybrid mapping approach (unsupervised and supervised) can improve urban wetland mapping accuracy from remote sensing satellite imagery.

Overall, we conclude that, in order to ensure the sustainability of the MMNL, which is a highly valuable UWE, there is an urgent need for forward-looking landscape and urban planning that could promote environmentally-conscious urban development in the area.

**Author Contributions:** Conceptualization, D.A.; methodology, D.A. and R.C.E.; software, D.A. and R.C.E.; validation D.A., R.C.E., and Y.M.; formal analysis, D.A. and R.C.E.; investigation, D.A. and R.C.E.; resources, D.A.; data curation, D.A.; writing—original draft preparation, D.A.; writing review and editing, R.C.E., Y.M., and B.M.; visualization, D.A.; supervision, Y.M. and B.M.; project administration, Y.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data that support the findings of this study are available from the corresponding author on reasonable request.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Abbreviations**

#### **Appendix A**

#### **Table A1.** Confusion matrices of the classified LUC maps of the MMNL.

**Table A2.** Top 20 GNs in the MMNL in terms of density of wetland loss due to urbanization (settlement expansion) (WLD) (%) (see Equations (3) and (4)).

#### **References**


**5. Dependencies of the diagnostic parameters**

The structural dependencies of the tan, the relative permittivity *r* and the conductivity are shown in Figure 6. A temperature increase results in an increase of the mobility of the (polarized) molecules, the charge carriers and the number of electrons having at least the necessary energy to overcome the potential barrier or in other words the activation energy *a E* , (Küchler, 2009). Therefore, there is a constant rise of conductivity, (Bayer, Boeck, Möller, & Zaengl, 1986):

$$\tan \delta\_{\rm con} = \mathbf{A} \mathbf{e}^{-E\_s/\mathbf{k}T} \tag{9}$$

Empiric Approach for Criteria Determination of Remaining Lifetime Estimation of MV PILC Cables 263

)

increases with rising test voltages, and

on voltage.

PILC cables (viscosity of 50 mm2/s by 100°C) reaches its maximum in the vicinity of -8°C and the minimum in the region of 30°C. It was shown and discussed in (Mladenovic & Weindl, Influence of the thermal stress on the diagnostic parameters of PILC cables, 2010) that temperatures around 30°C are also not optimal for diagnostic measurements of MV PILC

Unlike to the temperature, the test voltage can be adjusted and is therefore used as a parameter for some diagnostic methods. According to equation (1), the differential tan(

Theoretically, it is to be expected that the dissipation factor raises with an increase of the voltage since these means an injection of more energy, enhancing the energy of the charge carriers and a multiplication of the ions. Therefore, the conductivity and in this way the tan

is principally rising with increasing test voltages. It was shown in (Bayer, Boeck, Möller, &

The dominating ageing process in paper-mass insulation systems is a degradation of the cellulose which results in a higher moisture content. Since the conductivity and permanent resistivity of the water is much higher than of cellulose-mass it can be expected that cables

The behavior of PD activity with varied test-voltage is already well known and widely used as a diagnostic criterion for the detection of numerous failures that can occur in cables and

Moreover, a stepwise increase of the dissipation factor with the test-voltage is often interpreted as a result of increased PD activities within the insulation. Anyway, the rate of the losses caused by PD activity in the total dissipation losses is very indistinct, since it is defined by the cable length, the number of weaknesses, the PD intensity, etc., (Mladenovic & Weindl, Comparison of the parametric Partial Discharges and Dissipation factor

For a successful development of reliable ageing models, it is of prime importance to have different but constant ageing conditions and access to the regularly measured and monitored parameters up to the failure events. Therefore the characteristic key-values of the

artificial ageing period of two years. Beside the main field of thermo-electrically aged cable samples, selected cables were set under thermal stress only, while another group cables was electrically aged. In this way it should be possible to determine the parameters in the ageing models and the influence of each stress type on the ageing rapidity. The thermal ageing can principally be modeled by Arrhenius law, the electrical ageing by e.g. the inverse power law. When concurrent stress conditions are applied combined and complex ageing models

were acquired selectively for each cable at least daily over the complete

measured at two times the nominal voltage *U*2 and the nominal voltage *U*1 are

cables based on the dissipation factor.

Zaengl, 1986) on the example of epoxy resin, that *r*

that the gradient is steeper for higher temperatures.

Characteristics of MV PILC Cables, 2012).

**6. Artificial ageing experiment**

with higher moisture content show stronger dependency of the tan

values-tan

cable garnitures.

PD and tan

partially used for this purpose.

where are: A - the pre-exponential factor, *T* is the absolute temperature and k Boltzmann constant.

**Figure 6.** Structural dependencies of the dissipation factor tan, relative permittivity *r* , and conductivity on temperature with three different polarization mechanisms (dashed blue line)

On the other hand, the polarization processes show different resonant phenomena over a wider temperature range. Appropriate temperatures drive different polarization processes. Even one polarization process like the orientational polarization can have e.g. two resonant temperatures due to the presence of different molecular structures, like e.g. moisture in the paper-mass insulation system. Therefore, with an increasing temperature the relative permittivity rises stepwise at discrete temperatures as a consequence of increased dipole mobility. Finally, with higher temperatures *r* decreases again due to the thermal agitation which results in a partial disorganization of the dipole arrangements caused by the field. The activity of PD, if any, will change according to ideal gas and Paschen's law, (Mladenovic, Determination of the Remaining Lifetime of PILC cables based on PD and tan(δ) diagnostics, 2012, to be published). Also, conductive channels within insulation, if present, will develop faster leading to the complete breakdown of the insulation.

Since the temperature cannot be adjusted in field measurements, the temperature dependency of tanδ is inappropriate to be used as a diagnostic criteria directly. Although, it is very important to know its characteristic behavior for different ageing situations and to have reference tan-temperature-condition profiles, so that the measured parameters can be evaluated correctly. According to (Bayer, Boeck, Möller, & Zaengl, 1986) the tanof MV PILC cables (viscosity of 50 mm2/s by 100°C) reaches its maximum in the vicinity of -8°C and the minimum in the region of 30°C. It was shown and discussed in (Mladenovic & Weindl, Influence of the thermal stress on the diagnostic parameters of PILC cables, 2010) that temperatures around 30°C are also not optimal for diagnostic measurements of MV PILC cables based on the dissipation factor.

Unlike to the temperature, the test voltage can be adjusted and is therefore used as a parameter for some diagnostic methods. According to equation (1), the differential tan() values-tan measured at two times the nominal voltage *U*2 and the nominal voltage *U*1 are partially used for this purpose.

Theoretically, it is to be expected that the dissipation factor raises with an increase of the voltage since these means an injection of more energy, enhancing the energy of the charge carriers and a multiplication of the ions. Therefore, the conductivity and in this way the tan is principally rising with increasing test voltages. It was shown in (Bayer, Boeck, Möller, & Zaengl, 1986) on the example of epoxy resin, that *r* increases with rising test voltages, and that the gradient is steeper for higher temperatures.

The dominating ageing process in paper-mass insulation systems is a degradation of the cellulose which results in a higher moisture content. Since the conductivity and permanent resistivity of the water is much higher than of cellulose-mass it can be expected that cables with higher moisture content show stronger dependency of the tanon voltage.

The behavior of PD activity with varied test-voltage is already well known and widely used as a diagnostic criterion for the detection of numerous failures that can occur in cables and cable garnitures.

Moreover, a stepwise increase of the dissipation factor with the test-voltage is often interpreted as a result of increased PD activities within the insulation. Anyway, the rate of the losses caused by PD activity in the total dissipation losses is very indistinct, since it is defined by the cable length, the number of weaknesses, the PD intensity, etc., (Mladenovic & Weindl, Comparison of the parametric Partial Discharges and Dissipation factor Characteristics of MV PILC Cables, 2012).


**4. Discussion**

A lot of progress was made in this scientific field during 1980–2000. Both packed columns and capillary columns were used for this purpose. Moreover, various detection systems such as NPD, FID, SID, MS, were adopted. Liquid–liquid extraction was the most frequent sample preparation technique, while various solvents were tested. Derivatization with various reagents, resulting in di fferent trifluoroacetyl, heptafluorobutyryl or carbethoxyhexafluorobutyryl, were also employed. Other conventional sample preparation techniques including protein precipitation and solid phase extraction have also been used.

However, due to the rapid development of high-performance liquid chromatography, the application of gas chromatography was significantly reduced after 2000. This can be attributed to the fact that HPLC, especially when coupled with mass spectrometry, can provide highly sensitive methods and extremely low limits of detection. Until today, HPLC is a well-established technique for the determination of various drugs (antidepressants, antipsychotics, antiepileptics, etc.).

The recent advances in the use of gas chromatography for the determination of TCAs in biofluids focus on the implementation of novel sample preparation techniques, such as LPME, SPME, EME, etc. Additionally, novel materials have been synthesized and tested for the extraction of tricyclic antidepressants from biofluids. These techniques follow the principles of "green chemistry" and have numerous advantages compared to conventional sample preparation methods.

The reported GC methods can be classified into the more sensitive GC-MS methods and the GC methods coupled with other detection systems (mostly ECD, NPD, and FID). The GC-MS methods combine the resolution ability of gas chromatography with the highly sensitive detection ability of mass spectrometry. Therefore, highly sensitive methods can be developed and low LODs can be obtained. Satisfactory LOQ values can be obtained both with GC-FID and with GC-NPD techniques. As shown in Table 1, by using a preconcentration method in combination with GC-MS, limits of quantification can be reduced to 0.2 ng/mL, while, with GC-FID and GC-NPD, they are more than 0.5 ng/mL and 44 ng/mL, respectively. This is of high importance especially for forensic toxicology applications in which highly sensitive and specific GC-MS (or LC-MS, LC-MS/MS) are required.


Author details

Edmundo Lozoya-Gloria\*, Xochitl Morales-de la Cruz and Takehiro A. Ozawa-Uyeda Genetic Engineering Department, CINVESTAV-IPN Irapuato Unit, Irapuato, Guanajuato, México

\*Address all correspondence to<EMAIL_ADDRESS>
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