Socio-Environmental Systems Modelling
https://sesmo.org/
<p><em>SESMO seeks to transform society and socio-environmental decision-making through model-based research that integrates multiple issues, domain expertise and interest groups </em></p>International Environmental Modelling and Software SocietyenSocio-Environmental Systems Modelling2663-3027The Collaborative Policy Modeling Paradox: Perceptions of water quality modeling in the Chesapeake Bay Watershed
https://sesmo.org/article/view/18677
<p>The Chesapeake Assessment Scenario Tool (CAST) serves multiple key functions in meeting nutrient reduction targets across the Chesapeake Bay Watershed (CBW) and is embedded in the water quality governance system. To investigate contested perspectives regarding the model, we interviewed 59 stakeholders engaged in model governance across the CBW. We recorded statements regarding the accuracy, legitimacy, and credibility of the model, influences on its use, and on challenges and opportunities. We found skepticism regarding the legitimacy of CAST, including suggestions its role facilitates a “paper process” of policy design and that past experience has greater influence on policy decisions than model predictions. However, despite its perceived shortcomings, CAST has been central in helping stakeholders in prioritizing mitigative activities. With respect to credibility, most respondents believe the model underestimates the effects of nutrient-reduction practices, thereby underestimating progress toward TMDL-related goals. Respondents also identified opportunities for model improvement, emphasizing co-benefits of conservation practices over and above nutrient reduction. Overall, our analysis demonstrates a Collaborative Policy Modeling Paradox: collaborative model development is necessary for effective policy modeling, but the political processes of collaborative model development can negatively impact perceptions of salience, credibility, and legitimacy. Although it is important to recognize this paradox, as it is linked to dissatisfaction with the models, our findings also point to areas where improvement has occurred and to future opportunities for development.</p>
Special Issue: SES Modeling in Regulatory Contextscollaborative modellingmodel governancewater qualityPatrick BittermanD. G. Webster
Copyright (c) 2024 Patrick Bitterman, D. G. Webster
http://creativecommons.org/licenses/by-nc/4.0
2024-03-152024-03-15186771867710.18174/sesmo.18677Reflections on SES modeling: Stop me if you’ve heard this
https://sesmo.org/article/view/18658
<p>Key lessons about and limits to social-ecological systems (SES) modeling are widely available and frustratingly consistent over time. Prominent challenges include outdated perspectives about systems and models along with persistent disciplinary hegemony. The inherent complexity in SES means that an emphasis on discrete prediction is misplaced and has potentially reduced model efficacy for decision-making. Although computer models are definitely the tool to use to identify the complex relationships within SES, humans are messy and hence the ‘social’ in SES is often ignored, glossed over, or reduced to simplistic economic or demographic variables. This combination of factors has perpetuated biases in what is worth pursuing and/or publishing.</p> <p>In (re)visiting issues in SES modeling, including debates about model capabilities, data selection, and challenges in working across disciplinary lines, this reflection explores how the author’s experience aligns with extant literature as well as raises issues about what is absent from that body of work. The available lessons suggest that scholars and practitioners need to re-think how, why, and when to employ SES modeling in regulatory or other decision-making contexts.</p>
Special Issue: SES Modeling in Regulatory Contextssocial-ecological systemsmodelingboundary objectinterdisciplinarydecision-makingKristan Cockerill
Copyright (c) 2024 Kristan Cockerill
http://creativecommons.org/licenses/by-nc/4.0
2024-02-122024-02-12186581865810.18174/sesmo.18658Global sensitivity analysis of the dynamics of a distributed hydrological model at the catchment scale
https://sesmo.org/article/view/18570
<p>The PESHMELBA model simulates water and pesticide transfers at the catchment scale. Its objective is to help the process of decision making in the common management of long-term water quality. Performing the global sensitivity analysis (GSA) of this type of model is necessary to trace the output variability to the input parameters. The goal of the present work is to perform a GSA, while considering the spatio-temporal nature and the high dimensionality of the model. The output considered is the surface moisture simulated over a two-month period on a catchment of assorted mesh elements (plots). The GSA is performed on the dynamical outputs, rewritten through their functional principal components. Sobol’ indices are then estimated through polynomial chaos expansion on each principal component. The analysis differs between the two types of behaviour observed in the surface moisture outputs. The hydrodynamic properties of the surface soil have a dominant influence on the average surface moisture. Nonetheless, the parameters describing deeper soil layers influence the output dynamics of those plots where the surface moisture is saturated. We obtain Sobol’ indices with high precision while using a limited number of model estimations and considering the models spatio-temporal nature. The physical interpretation of the GSA confirms and augments our knowledge on the model.</p>
Special Issue: Sensitivity Analysis of Model OutputGlobal sensitivity analysishydrologyfunctional principal componentspolynomial chaos expansiondistributed modelKatarina RadišićEmilie RouziesClaire LauvernetArthur Vidard
Copyright (c) 2023 Katarina Radišić, Emilie Rouzies, Claire Lauvernet, Arthur Vidard
http://creativecommons.org/licenses/by-nc/4.0
2023-12-312023-12-31185701857010.18174/sesmo.18570Global sensitivity analysis of a one-dimensional ocean biogeochemical model
https://sesmo.org/article/view/18613
<p>Ocean biogeochemical (BGC) models are a powerful tool for investigating ocean biogeochemistry and the global carbon cycle. The potential benefits emanating from BGC simulations and predictions are broad, with significant societal impacts from fisheries management to carbon dioxide removal and policy-making. These models contain numerous parameters, each coupled with large uncertainties, leading to significant uncertainty in the model outputs. This study performs a global sensitivity analysis (GSA) of an ocean BGC model to identify the uncertain parameters that impact the variability of model outputs most. The BGC model Regulated Ecosystem Model 2 is used in a one-dimensional configuration at two ocean sites in the North Atlantic (BATS) and the Mediterranean Sea (DYFAMED). Variance-based Sobol' indices are computed to identify the most influential parameters for each site for the quantities of interest (QoIs) commonly considered for the calibration and validation of BGC models. The most sensitive parameters are the chlorophyll to nitrogen ratio, chlorophyll degradation rate, zooplankton grazing and excretion parameters, photosynthesis parameters, and nitrogen and carbon remineralization rate. Overall, the sensitivities of most QoIs were similar across the two sites; however, some differences emerged because of different mixed layer depths. The results suggest that implementing multiple zooplankton function types in BGC models can improve BGC predictions. Further, explicitly implementing heterotrophic bacteria in the model can better simulate the carbon export production and CO<sub>2</sub> fluxes. The study offers a comprehensive list of the most important BGC parameters that need to be quantified for future modeling applications and insights for BGC model developments.</p> <p> </p>
Special Issue: Sensitivity Analysis of Model OutputOcean biogeochemical parametersRegulated Ecosystem Model 2Sobol' indicesUncertainty quantificationNabir MamnunChristoph VölkerSebastian KrumscheidMihalis VrekoussisLars Nerger
Copyright (c) 2023 Nabir Mamnun, Christoph Völker, Sebastian Krumscheid, Mihalis Vrekoussis, Lars Nerger
http://creativecommons.org/licenses/by-nc/4.0
2023-10-062023-10-06186131861310.18174/sesmo.18613Modelling agricultural innovations as a social-ecological phenomenon
https://sesmo.org/article/view/18562
<p>Agricultural innovations involve both social and social-ecological dynamics where outcomes emerge from interactions of innovation actors embedded within their ecological environments. Neglecting the interconnected nature of social-ecological innovations can lead to a flawed understanding and assessment of innovations. In this paper, we present an empirically informed, stylized agent-based model of agricultural innovation systems in Mali, West Africa. The study aimed to understand the emergence of food security and income inequality outcomes through two distinct model structures: top-down, aid-driven (exogenous) innovation and bottom-up, community-driven (endogenous) innovation. Our research questions were: i) How does the inclusion of social-ecological interactions in the model affect food security and income inequality outcomes? ii) How do exogenous and endogenous mechanisms influence food insecurity and income inequality? iii) What are the conditions under which exogenous and endogenous mechanisms would improve food security? The structural design of the model was based on a combination of theory, empirics, and mapping of social-ecological dynamics within innovation systems. Using the Social-Ecological Action Situation framework, we mapped the social, social-ecological, and ecological interactions that jointly produce food security outcomes. The exploratory model analysis reveals three key insights: i) Incorporation of social-ecological interactions influences model outcomes. Scenarios with social-ecological interactions showed a stronger relationship between income inequality and food security, lower levels of food security, and higher levels of income inequality than scenarios with social interactions. ii) Endogenous mechanism leads to higher food security and income inequality than the exogenous mechanism. iii) Bidirectional outreach is more effective than unidirectional outreach in improving food security. Inclusion of social-ecological dynamics and interactions such as the role of climate risk perception, social learning and formation of innovation beliefs and desires is key for modelling and analysis of agricultural innovations.</p>
Research Papersstylized modelssocial-ecological systemsagricultureinnovationsagent-based modelsUdita SangaJineth Berrío-MartínezMaja Schlüter
Copyright (c) 2023 Udita Sanga, Jineth Berrío-Martínez and Maja Schlüter
http://creativecommons.org/licenses/by-nc/4.0
2023-08-152023-08-15185621856210.18174/sesmo.18562Assessing the quality of land system models: moving from valibration to evaludation
https://sesmo.org/article/view/18434
<p>Reviews suggest that evaluation of land system models is largely inadequate, with undue reliance on a vague concept of validation. Efforts to improve and standardise evaluation practices have so far had limited effect. In this article we examine the issues surrounding land system model evaluation and consider the relevance of the TRACE framework for environmental model documentation. In doing so, we discuss the application of a comprehensive range of evaluation procedures to existing models, and the value of each specific procedure. We develop a tiered checklist for going beyond what seems to be a common practice of ‘valibration’ (the repeated variation of model parameter values to achieve agreement with data) to achieving ‘evaludation’ (the rigorous, broad-based assessment of model quality and validity). We propose the Land Use Change – TRACE (LUC-TRACE) model evaludation protocol and argue that engagement with a comprehensive protocol of this kind (even if not this particular one) is valuable in ensuring that land system model results are interpreted appropriately. We also suggest that the main benefit of such formalised structures is to assist the process of critical thinking about model utility, and that the variety of legitimate modelling approaches precludes universal tests of whether a model is ‘valid’. Evaludation is therefore a detailed and subjective process requiring the sustained intellectual engagement of model developers and users.</p>
Special Issue: Large-scale behavioural models of land use changevalidationevaluationCRAFTYagent-based modelland use changeCalum BrownJames MillingtonMark Rounsevell
Copyright (c) 2023 Calum Brown, James Millington, Mark Rounsevell
http://creativecommons.org/licenses/by-nc/4.0
2023-07-082023-07-08184341843410.18174/sesmo.18434Scale decisions and good practices in socio-environmental systems modelling: guidance and documentation during problem scoping and model formulation
https://sesmo.org/article/view/18563
<p>Models of socio-environmental or social-ecological systems (SES) commonly address problems requiring interdisciplinary scientific expertise and input from a heterogeneous group of stakeholders. In SES modelling multiple interactions occur on different scales among various phenomena. These scale phenomena include the technical, such as system variables, process detail, inputs and outputs, which most often require spatial, temporal, thematic and organisational choices. From a good practice and project efficiency perspective, the problem scoping and conceptual model formulation phase of modelling is the one to address well from the outset. During this phase, intense and substantive discussions should arise regarding appropriate scales at which to represent the different phenomena. Although the details of these discussions influence the path of model development, they are seldom documented and as a result often forgotten. We draw upon personal experience with existing protocols and communications in recent literature to propose preliminary guidelines for documenting these early discussions about the scale(s) of the studied phenomena. Our guidelines aim to aid modelling group members in building and capturing the richness of their rationale for scoping and scale decisions. The resulting transcripts are intended to promote transparency of modelling decisions and provide essential support for the justification of the final model for its intended use. They also facilitate adaptive modifications of the pathway of model development via retracing decisions and iterative reflection upon alternative scale options.</p>
Special Issue: Participatory & cross-scale modelling of SESs in the Anthropoceneorganisational scalespatial scaletemporal scalethematic scaleuncertaintyHsiao-Hsuan WangGeorge van VoornWilliam E. GrantFateme ZareCarlo GiupponiPatrick SteinmannBirgit MüllerSondoss ElsawahHedwig van DeldenIoannis N. AthanasiadisZhanli SunWander JagerJohn C. LittleAnthony J. Jakeman
Copyright (c) 2023 Hsiao-Hsuan Wang, George van Voorn, William E. Grant, Fateme Zare, Carlo Giupponi, Patrick Steinmann, Birgit Muller, Sondoss Elsawah, Hedwig van Delden, Ioannis N. Athanasiadis, Zhanli Sun, Wander Jager, John C. Little, Anthony J. Jakeman
http://creativecommons.org/licenses/by-nc/4.0
2023-03-272023-03-27185631856310.18174/sesmo.18563Kernel-based sensitivity indices for any model behavior and screening
https://sesmo.org/article/view/18566
<p>Complex models are often used to understand interactions and drivers of human-induced and/or natural phenomena. It is worth identifying the input variables that drive the model output(s) in a given domain and/or govern specific model behaviors such as contextual indicators based on socioenvironmental models. Using the theory of multivariate weighted distributions to characterize specific model behaviors, we propose new measures of association between inputs and such behaviors. Our measures rely on sensitivity functionals (SFs) and kernel methods, including variance-based sensitivity analysis. The proposed ℓ1-based kernel indices account for interactions among inputs, higher-order moments of SFs, and their upper bounds are somehow equivalent to the Morris-type screening measures, including dependent elementary effects. Empirical kernel-based indices are derived, including their statistical properties for the computational issues, and numerical results are provided.</p>
Special Issue: Sensitivity Analysis of Model Outputclusteringdependency modelsRHKSMultivariate weighted distributionsreducing uncertaintiesMatieyendou Lamboni
Copyright (c) 2023 Matieyendou Lamboni
http://creativecommons.org/licenses/by-nc/4.0
2023-12-122023-12-12185661856610.18174/sesmo.18566Control variate Monte Carlo estimators based on sparse polynomial chaos expansions
https://sesmo.org/article/view/18568
<p>We introduce two control variate Monte Carlo estimators where the control is based on the truncated sparse polynomial chaos expansion of the function in hand. We use the control variate estimators to estimate the lower and upper Sobol' indices in some applications, and compare them numerically with some of the best Monte Carlo estimators in the literature. The results suggest that in computationally expensive problems where a low-order polynomial chaos expansion is not an accurate approximation of the model but highly correlated with it, the control variate estimators are either the best or among the best in terms of efficiency.</p>
Special Issue: Sensitivity Analysis of Model Outputcontrol variateMonte CarloBayesian polynomial chaosSobol' sensitivity indicesHui DuanGiray Okten
Copyright (c) 2023 Hui Duan, Giray Okten
http://creativecommons.org/licenses/by-nc/4.0
2023-12-042023-12-04185681856810.18174/sesmo.18568Science-design loop for the design of resilient urban landscapes
https://sesmo.org/article/view/18543
<p>Urban landscapes face significant challenges, as they must transform towards sustainability while remaining resilient. Urban landscape transformation is a complex task for landscape designers. They must not only create new solutions for landscapes but also ensure that their proposals are capable to deliver and maintain key ecosystems services over time and especially after shocks. In practice, designers must increase their dialogue with scientists and engineers to include expertise on ecosystems functions and services. Through science-design feedback loops, designers can be challenged by scientists’ models and simulations and thus create informed designs. Lastly, stakeholders also catalyse key steps of such a process, in particular by providing local expertise as well as co-constructing and validating the informed designs. In this paper, we introduce a roadmap, centred on an intensive interdisciplinary dialogue – a science-design loop. We illustrate the relevance of this roadmap with the analysis of five case studies about flood management and blue-green infrastructures. We analyse them according to the main steps of our roadmap and with the support of key interviews with experienced practitioners. First, this analysis provides an overview of best practices and challenges in the current urban landscape design world. But above all, we show the relevance of the proposed roadmap to muster science and design in a balanced manner in urban transformations.</p>
Research Papersurban landscape transformationscience-design loopinterdisciplinary dialogueblue-green infrastructuresflood managementNicolas SalliouTony ArborinoJoan Iverson NassauerDiego SalmeronPhilipp UrechDerek VollmerAdrienne Grêt-Regamey
Copyright (c) 2023 Nicolas Salliou, Tony Arborino, Joan Iverson Nassauer, Diego Salmeron, Philipp Urech, Derek Vollmer, Adrienne Grêt-Regamey
http://creativecommons.org/licenses/by-nc/4.0
2023-02-142023-02-14185431854310.18174/sesmo.18543Recognizing political influences in participatory social-ecological systems modeling
https://sesmo.org/article/view/18509
<p>Stakeholder participation in social-ecological systems (SES) modeling is increasingly considered a desirable way to elicit diverse sources of knowledge about SES behavior and to promote inclusive decision-making in SES. Understanding how participatory modeling processes function in the context of long-term adaptive management of SES may allow for better design of participatory processes to achieve the intended outcomes of inclusionary knowledge, representativeness, and social learning, while avoiding unintended outcomes. Long-term adaptive management contexts often include political influences -- attempts to shift or preserve power structures and authority, and efforts to represent the political and economic interests of stakeholders -- in the computer models that are used to shape policy making and implementation. In this research, we examine a period that included a major transition in the watershed model used for management of the Chesapeake Bay in the United States. The Chesapeake Bay watershed model has been in development since the 1980s, and is considered by many to be an exemplary case of participatory modeling. We use documentary analysis and interviews with participants involved in the model application and development transition to reveal a variety of ways in which participatory modeling may be subject to different kinds of political influences, some of which resulted in unintended outcomes, including: perceptions of difficulty updating the model in substantive ways, “gaming” of the model/participatory process by stakeholders, and increasing resistance against considering uncertainty in the system not captured by the model. This research suggests unintended or negative outcomes may be associated with both participatory decision-making and stakeholder learning even though they are so often touted as the benefits of participatory modeling. We end with a hypothesis that further development of a theory of computer model governance to bridge model impact and broader theories of environmental governance at the science-policy interface may result in improved SES modeling outcomes.</p>
Special Issue: Participatory & cross-scale modelling of SESs in the Anthropoceneparticipatory modelingscience policyevidence-based policyboundary objectswatershed managementTheodore C. LimPierre D. GlynnGary W. ShenkPatrick BittermanJoseph H. A. GuillaumeJohn C. LittleD. G. Webster
Copyright (c) 2023 Theodore C. Lim, Pierre D. Glynn, Gary W. Shenk, Patrick Bitterman, Joseph H. A. Guillaume, John C. Little, D. G. Webster
http://creativecommons.org/licenses/by-nc/4.0
2023-05-182023-05-18185091850910.18174/sesmo.18509Applications of GIS and remote sensing in public participation and stakeholder engagement for watershed management
https://sesmo.org/article/view/18149
<p>The use of Geographic Information Systems (GIS) and remote sensing technologies for the development of water quality management programs and for post-implementation assessments has increased dramatically in the past decade. This increase in adoption has been made more accessible through the interfaces of many popular software tools used in the regulation and assessment of water quality. Customized applications of these tools will increase, as ease of access and affordability of directly monitored and remotely sensed datasets improve over time. Concurrently, there is a need for inclusive participatory engagement with stakeholders to achieve solutions to current watershed management challenges. This paper explores the potential of these GIS and remote sensing datasets, tools, models, and immersive engagement technologies from other domains, for improving public participation and stakeholder engagement throughout the watershed planning process. To do so, an initial review is presented about the use of GIS and remote sensing in watershed management and its role in impairment identification, model development, and planning and implementation. Then, ways in which GIS and remote sensing can be integrated with stakeholder engagement through (1) leveraging GIS and remote sensing datasets, and (2) stakeholder engagement approaches including outreach and education, modeler-led development, and stakeholder-led involvement and feedback, are discussed. Finally, future perspectives on the potential for transforming public participation and stakeholder engagement in the watershed management process through applications of GIS and remote sensing are presented.</p>
Research Papersgeographic information systemsremote sensingmodellingwater qualitystakeholder engagementNigel W. T. QuinnVamsi SridharanJohn Ramirez-AvilaSanaz ImenHuilin GaoRocky TalchabhadelSaurav KumarWalter McDonald
Copyright (c) 2022 Nigel Quinn, Vamsi Sridharan, John Ramirez-Avila , Sanaz Imen, Huilin Gao, Rocky Talchabhadel, Saurav Kumar, Walter McDonald
http://creativecommons.org/licenses/by-nc/4.0
2022-10-172022-10-17181491814910.18174/sesmo.18149Investigating the micro-level dynamics of water reuse adoption by farmers and the impacts on local water resources using an agent-based model
https://sesmo.org/article/view/18148
<p>Agricultural water reuse is gaining momentum to address freshwater scarcity worldwide. The main objective of this paper was to investigate the micro-level dynamics of water reuse adoption by farmers at the watershed scale. An agent-based model was developed to simulate agricultural water consumption and socio-hydrological dynamics. Using a case study in California, the developed model was tested, and the results showed that agricultural water reuse adoption by farmers is a gradual and time-consuming process. In addition, results also showed that agricultural water reuse could significantly decrease the water shortage (by 57.7%) and groundwater withdrawal (by 74.1%). Furthermore, our results suggest that recycled water price was the most influential factor in total recycled water consumption by farmers. Results also showed how possible freshwater shortage or groundwater withdrawal regulations could increase recycled water use by farmers. The developed model can significantly help assess how the current water reuse management practices and strategies would affect the sustainability of agricultural water resources.</p>
Research Paperswater reuseagent-based modellingagricultural water managementrecycled water for irrigationFarshid ShoushtarianMasoud Negahban-AzarAndrew Crooks
Copyright (c) 2022 Farshid Shoushtarian, Masoud Negahban-Azar, Andrew Crooks
http://creativecommons.org/licenses/by-nc/4.0
2022-10-202022-10-20181481814810.18174/sesmo.1814818 Politically relevant solar geoengineering scenarios
https://sesmo.org/article/view/18127
<p>Solar geoengineering, also known as Solar Radiation Modification (SRM), has been proposed to alter Earth’s radiative balance to reduce the effects of anthropogenic climate change. SRM has been identified as a research priority, as it has been shown to effectively reduce surface temperatures, while substantial uncertainties remain around side effects and impacts. Global modeling studies of SRM have often relied on idealized scenarios to understand the physical processes of interventions and their widespread impacts. These extreme or idealized scenarios are not directly policy-relevant and are often physically implausible (such as imposing global solar reduction to counter the warming of an instantaneous quadrupling of CO<sub>2</sub>). The climatic and ecological impacts of politically relevant and potentially plausible SRM approaches have rarely been modeled and assessed. Nevertheless, commentators and policymakers often falsely assume that idealized or extreme scenarios are proposed solutions to climate change. This paper proposes 18 scenarios that appear to be broadly plausible from political and Earth System perspectives and encompass futures that could be both warnings or perhaps desirable. We place these scenarios into four groups following broader strategic contexts: (1) Global Management; (2) Regional Emergencies; (3) Coordinated Regional Interventions; and (4) Reactive Global Interventions. For each scenario, relevant model experiments are proposed. Some may be performed with existing setups of global climate models, while others require further specification. Developing and performing these model experiments – and assessing likely resulting impacts on society and ecosystems – would be essential to inform public debate and policymakers on the real-world issues surrounding SRM.</p>
Research Papersgeoengineeringscenariossolar radiation modificationmarine cloud brighteningAndrew LockleyYangyang XuSimone TilmesMasahiro SugiyamaDale RothmanAdrian Hindes
Copyright (c) 2022 Andrew Lockley, Yangyang Xu, Simone Tilmes, Masahiro Sugiyama, Dale Rothman, Adrian Hindes
http://creativecommons.org/licenses/by-nc/4.0
2022-07-222022-07-22181271812710.18174/sesmo.18127RICE50+: DICE model at country and regional level
https://sesmo.org/article/view/18038
<p>Benefit-cost Integrated Assessment Models (IAMs) have been largely used for optimal policies and mitigation pathways countering climate change. However, the available models are relatively limited in the representation of regional heterogeneity. This is despite strong evidence of significant variation of local mitigation costs and benefits, institutional capacity, environmental and economic priorities. Here, I introduce RICE50+, a benefit-cost optimizing IAM with more than 50 independently deciding regions or countries. Its core foundation is the DICE model, improved with several original contributions. These include new calibrations on actual mitigation cost data, full integration of recent empirically based impact functions, alternative socioeconomic reference projections as well as normative preferences, including welfare specifications explicitly featuring inequality aversion. Due to its high level of regional detail, the model can support researchers in better investigating the role of heterogeneity in international cooperation, cross-country inequalities, and climate change impacts under a variety of mitigation pathways and scenarios.</p>
Research Papersclimate changeintegrated assessment modelbenefit-cost analysisclimate policyPaolo Gazzotti
Copyright (c) 2022 Paolo Gazzotti
http://creativecommons.org/licenses/by-nc/4.0
2022-04-132022-04-13180381803810.18174/sesmo.18038Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses
https://sesmo.org/article/view/18155
<p>Sensitivity analysis is now considered a standard practice in environmental modeling. Several open-source libraries, such as the Sensitivity Analysis Library (SALib), have been published in the recent past aimed at simplifying the application of sensitivity analyses. Still, there remain issues in software usability and accessibility, as well as a lack of guidance in the interpretation of sensitivity analysis results. This paper describes the changes made and planned to SALib to advance the ease with which modelers may conduct sensitivity analysis and interpret results. We further offer our perspectives from the past 7 years of maintaining SALib for the consideration of those aspiring to launch their own software for sensitivity analysis, develop methodology, or those otherwise interested in becoming involved in a project like SALib. These include the value of a community of practice to foster best practices for sensitivity analysis, the potential for collaboration across different software (for sensitivity analysis) platforms, and the need to specifically support the software development that underpins computational science.</p>
Advances in Modelling Practicesensitivity analysiscommunity of practicesoftware accessibilityTakuya IwanagaWilliam UsherJonathan Herman
Copyright (c) 2022 Takuya Iwanaga, Will Usher, Jon Herman
http://creativecommons.org/licenses/by-nc/4.0
2022-05-312022-05-31181551815510.18174/sesmo.18155Upscaling in socio-environmental systems modelling: Current challenges, promising strategies and insights from ecology
https://sesmo.org/article/view/18112
<p>Sustainability challenges in socio-environmental systems (SES) are inherently multiscale, with global-level changes emerging from socio-environmental processes that operate across different spatial, temporal, and organisational scales. Models of SES therefore need to incorporate multiple scales, which requires sound methodologies for transferring information between scales. Due to the increasing global connectivity of SES, upscaling – increasing the extent or decreasing the resolution of a modelling study – is becoming progressively more important. However, upscaling in SES models has received less attention than in other fields (e.g., ecology or hydrology) and therefore remains a pressing challenge. To advance the understanding of upscaling in SES, we take three steps. First, we review existing upscaling approaches in SES as well as other disciplines. Second, we identify four main challenges that are particularly relevant to upscaling in SES: 1) heterogeneity, 2) interactions, 3) learning and adaptation, and 4) emergent phenomena. Third, we present an approach that facilitates the transfer of existing upscaling methods to SES, using two good practice examples from ecology. To describe and compare these methods, we propose a scheme of five general upscaling strategies. This scheme builds upon and unifies existing schemes and provides a standardised way to classify and represent existing as well as new upscaling methods. We demonstrate how the scheme can help to transparently present upscaling methods and uncover scaling assumptions, as well as to identify limits for the transfer of upscaling methods. We finish by pointing out research avenues on upscaling in SES to address the identified upscaling challenges.</p>
Special Issue: Large-scale behavioural models of land use changemultiscaleupscaling schemetransferabilityregionalizationmeta-modelGunnar DresslerJurgen GroeneveldJessica HetzerAnja JanischewskiHenning NolzenEdna RodigNina SchwarzFranziska TaubertJule ThoberMeike WillTim WilliamsStephen Bjorn WirthBirgit Muller
Copyright (c) 2022 Gunnar Dressler, Jürgen Groeneveld, Jessica Hetzer, Anja Janischewski, Henning Nolzen, Edna Rödig, Nina Schwarz, Franziska Taubert, Jule Thober, Meike Will, Tim Williams, Stephen Björn Wirth, Birgit Müller
http://creativecommons.org/licenses/by-nc/4.0
2022-07-282022-07-28181121811210.18174/sesmo.18112Towards a global behavioural model of anthropogenic fire: The spatiotemporal distribution of land-fire systems
https://sesmo.org/article/view/18130
<p>Landscape fire regimes are created through socio-ecological processes, yet in current global models the representation of anthropogenic impacts on fire regimes is restricted to simplistic functions derived from coarse measures such as GDP and population density. As a result, fire-enabled dynamic global vegetation models (DGVMs) have limited ability to reproduce observed patterns of fire, and limited prognostic value. At the heart of this challenge is a failure to represent human agency and decision-making related to fire. This paper outlines progress towards a global behavioural model that captures the categorical differences in human fire use and management that arise from diverse land use objectives under varying socio-ecological contexts. We present a modelled global spatiotemporal distribution of what we term ‘land-fire systems’ (LFSs), a classification that combines land use systems and anthropogenic fire regimes. Our model simulates competition between LFSs with a novel bootstrapped classification tree approach that performs favourably against reference multinomial regressions. We evaluate model outputs with the human appropriation of net primary production (HANPP) framework and find good overall agreement. We discuss limitations to our methods, as well as remaining challenges to the integration of behavioural modelling in DGVMs and associated model-intercomparison protocols.</p>
Special Issue: Large-scale behavioural models of land use changefireDGVMbehavioural modelHANPPOliver PerkinsSarah MatejKarlheinz ErbJames Millington
Copyright (c) 2022 Oliver Perkins, Sarah Matej, Karlheinz Erb, James Millington
http://creativecommons.org/licenses/by-nc/4.0
2022-05-232022-05-23181301813010.18174/sesmo.18130Integrated modelling of social-ecological systems for climate change adaptation
https://sesmo.org/article/view/18161
<p>Analysis of climate change risks in support of policymakers to set effective adaptation policies requires an innovative yet rigorous approach towards integrated modelling (IM) of social-ecological systems (SES). Despite continuous advances, IM still faces various challenges that span through both unresolved methodological issues as well as data requirements. On the methodological side, significant improvements have been made for better understanding the dynamics of complex social and ecological systems, but still, the literature and proposed solutions are fragmented. This paper explores available modelling approaches suitable for long-term analysis of SES for supporting climate change adaptation (CCA). It proposes their classification into seven groups, identifies their main strengths and limitations, and lists current data sources of greatest interest. Upon that synthesis, the paper identifies directions for orienting the development of innovative IM, for improved analysis and management of socio-economic systems, thus providing better foundations for effective CCA.</p>
Research Papersintegrated modellingsocial-ecological systemclimate change adaptationintegrated assessment modelagent-based modelCarlo GiupponiAnne-Gaelle AusseilStefano BalbiFabio CianAlexander FeketeAnimesh K. GainArthur Hrast EssenfelderJavier Martinez-LopezVahid MojtahedCelia NorfHelder RelvasFerdinando Villa
Copyright (c) 2021 Carlo Giupponi, Anne-Gaelle Ausseil, Stefano Balbi, Fabio Cian, Alexander Fekete, Animesh K. Gain, Arthur Hrast Essenfelder, Javier Martínez-López, Vahid Mojtahed, Celia Norf, Hélder Relvas, Ferdinando Villa
http://creativecommons.org/licenses/by-nc/4.0
2022-01-312022-01-31181611816110.18174/sesmo.18161Perspectives on confronting issues of scale in systems modeling
https://sesmo.org/article/view/18156
<p>Issues of scale pervade every aspect of socio-environmental systems (SES) modeling. They can stem from the context of both the modeling process, and the purpose of the integrated model. A webinar hosted by the National Socio-Environmental Synthesis Center (SESYNC), The Integrated Assessment Society (TIAS) and the journal Socio-Environmental Systems Modelling (SESMO) explored how model stakeholders can address issues of scale. Four key considerations were raised: (1) being aware of our influence on the modeling pathway, and developing a shared language to overcome cross-disciplinary communication barriers; (2) that localized effects may aggregate to influence behavior at larger scales, necessitating the consideration of multiple scales; (3) that these effects are “patterns†that can be elicited to capture understanding of a system (of systems); and (4) recognition that the scales must be relevant to the involved stakeholders and decision makers. Key references in these four areas of consideration are presented to complement the discussion of confronting scale as a grand challenge in socio-environmental modeling. By considering these aspects within the integrated modeling process, we are better able to confront the issues of scale in socio-environmental modeling.</p>
Reviews and Reflectionssocio-environmental modelingintegrated modelinginterdisciplinary scalepatternsTakuya IwanagaPatrick SteinmannAmir SadoddinDerek RobinsonVal SnowVolker GrimmHsiao-Hsuan Wang
Copyright (c) 2022 Takuya Iwanaga, Patrick Steinmann, Amir Sadoddin, Derek T. Robinson, Val Snow, Volker Grimm, Hsiao-Hsuan Wang
http://creativecommons.org/licenses/by-nc/4.0
2022-04-272022-04-27181561815610.18174/sesmo.18156Understanding smallholder farmer decision making in forest land restoration using agent-based modeling
https://sesmo.org/article/view/18036
<p>Success of forest restoration at farm level depends on the farmer's decision-making and the constraints to farmers' actions. There is a gap between the intentions and the actual behavior towards restoration in Sub-Saharan Africa and the Global South. To understand this discrepancy, our study uses empirical household survey data to design and parameterize an agent-based model. WEEM (Woodlot Establishment and Expansion Model) has been designed based on household socio-demographics and projects the temporal dynamics of woodlot numbers in Uganda. The study contributes to a mechanistic understanding of what determines the current gap between farmer's intention and actual behavior. Results reveal that an increase in knowledge of the current forest policies laws and regulations (PLRs) from 18% to 50% and to 100% reduces the average number of woodlots by 18% and 79% respectively. Lack of labor reduces the number of woodlots by 80%. Increased labor requirement from 4 to 8 and to 12 man-days, reduces the number of woodlots by 26% and 61% respectively. WEEM indicates that absence of household labor and de facto misconception of PLRs "perceived tenure insecurity" constrains the actual behavior of farmers. We recommend forest PLRs to provide full rights of use and ownership of trees established on private farmland. Tree fund in the case of Uganda should be operationalized to address the transaction costs and to achieve the long-term targets of forest land restoration.</p>
Research Papersforest restorationland-use changeagent-based modeldecision-makinglaborVianny AhimbisibweJurgen GroeneveldMelvin LippeSusan Balaba TumwebazeEckhard AuchUta Berger
Copyright (c) 2021 Vianny Ahimbisibwe, Melvin Lippe, Eckhard Auch, Jürgen Groeneveld, Susan Balaba Tumwebaze, Uta Berger
http://creativecommons.org/licenses/by-nc/4.0
2021-11-252021-11-25180361803610.18174/sesmo.2021a18036Synergising decision making and interventions across human health and environment: concepts for designing a model for infectious diseases
https://sesmo.org/article/view/18126
<p>The impact of environmental factors on human health outcomes is well established. It is therefore not surprising that interventions aimed at improving human health are often environmental-based, such as restoring riparian vegetation for flood mitigation, with a view to reducing associated infectious disease transmission. Yet the risks and benefits of these interventions on the environment itself are rarely measured, or weighed up against potential health gains. One of the challenges with such an evaluation is the requirement for cross-sectoral support from decision makers in both the health and environmental sectors. To facilitate this support, cross-sectoral models are required that simultaneously estimate the impact of proposed environmental interventions on both sectors. Despite their obvious value, a systematic search of the peer-reviewed literature did not identify any model that concurrently models the impact of environmental intervention on <em>both</em> environmental and human infectious disease related outcomes. In this paper, we conceptually explore potential approaches for designing such a model, using leptospirosis as a case study to highlight the various data sources, spatial scales, temporal scales and required system behaviour that would need to be integrated for a cross-sectoral model of this complexity. By comparing these system requirements against the strengths and limitations of individual modelling techniques, we demonstrate the potential benefits of a hybrid-ensemble approach that uses component models from different frameworks. By combining the strengths of the different techniques to tackle this wicked problem, such a modelling approach supports the prioritisation of environmental interventions that optimise the overall benefit by considering impacts on both human health and the environment.</p>
Research Paperscross-sectoral modelenvironmental modellinginfectious diseaseecohealthenvironmental healthJessica StanhopeHelen J. MayfieldJoseph H. A. GuillaumeOz SahinPhilip WeinsteinColleen Lau
Copyright (c) 2021 Jessica Stanhope, Helen Mayfield, Joseph Guillaume, Oz Sahin, Philip Weinstein, Colleen Lau
http://creativecommons.org/licenses/by-nc/4.0
2022-03-162022-03-16181261812610.18174/sesmo.18126A situated agent-based model to reveal irrigators' options behind their actions under institutional arrangements in Southern France
https://sesmo.org/article/view/17893
<p>There has been little exploration of the explicit simulation of the set of options of actors in agent-based models and its evolution over time. This study proposes to use affordances as intermediate entities between agents' environment and agent actions. We illustrated the approach on a typical gravity-fed network in the South-East of France to explore how the abandonment of traditional sharing of water changes the irrigators' options to irrigate. We simulated a typical dry year irrigation season under two institutional arrangements (i.e. traditional coordination through daily slots and its abandonment). Simulation results are consistent with field surveys, and reveal an increase in the number of internal conflicts among irrigators as the counterpart of the abandonment of traditional sharing of water. They also highlight the consequences of the heterogeneity of the irrigators' interests within the collective institution. The sensitivity analysis of the model allowed identification of optimal modalities of coordination, and a potential compromise between past and current institutional arrangements. The key benefits of using affordances in ABM lie in the study of their population dynamics for characterizing the interaction situations between actors and their environment and for better understanding the model dynamics.</p>
Research Paperscollective irrigationagent-based modelsituated actionaffordanceinstitutional arrangementBastien RichardBruno BonteOlivier BarreteauIsabelle Braud
Copyright (c) 2021 Bastien Richard, Bruno Bonté, Olivier Barreteau, Isabelle Braud
http://creativecommons.org/licenses/by-nc/4.0
2022-02-242022-02-24178931789310.18174/sesmo.17893Containerization for creating reusable model code
https://sesmo.org/article/view/18074
<p>Will you be able to run your computational models in the future? Even with well-documented code, this can be difficult due to changes in the software frameworks and operating systems that your code was built on. In this paper we discuss the use of containers to preserve code and their software dependencies to reproduce simulation results in the future. Containers are standalone lightweight packages of the original model software and their dependencies that can be run independent of the platform. As such they are suitable for reuse and sharing results. However, the use of containers is rare in the field of modeling social-environmental systems. We provide an introduction to the basic principles of containerization, argue why it would be beneficial if this tool became common practice in the field, describe a conceptual walkthrough to the process of containerizing a model, and reflect on near future directions of containerization workflows.</p>
Advances in Modelling Practicecomputational modelscontainersresearch softwarereproducibilitymodel portabilityManuela Vanegas FerroAllen LeeCalvin PritchardC. Michael BartonMarco A. Janssen
Copyright (c) 2021 Manuela Vanegas Ferro, Allen Lee, Calvin Pritchard, C. Michael Barton, Marco A. Janssen
http://creativecommons.org/licenses/by-nc/4.0
2022-03-142022-03-14180741807410.18174/sesmo.18074Editorial: SESMO Special Issues
https://sesmo.org/article/view/18040
<p>As the journal nears the end of its second official year, we are pleased to start accepting submissions to our first two Special Issues. The first Special Issue is on <a href="https://sesmo.org/announcement/view/20"><em>Resilience of complex coupled Socio-Technical-Environmental systems through the modeling lens</em></a> with guest editors Tatiana Filatova, Tina Comes (4TU Resilience Engineering Centre), Christoph Hoelscher (ETH Zurich) and Juliet Mian (Resilence Shift). This Special Issue aims to bring together cutting-edge research and international practice to offer insights into the latest scientific modelling methods, gaps, challenges and opportunities and best practice examples relating to operationalising resilience across a range of socio-technical-environmental applications. The second Special Issue is on <a href="https://sesmo.org/announcement/view/21"><em>Large-scale behavioural models of land use change</em></a> with guest editors Calum Brown (Karlsruhe Institute of Technology), Tatiana Filatova (University of Twente), Birgit Müller (Helmholtz Centre for Environmental Research – UFZ), and Derek Robinson (University of Waterloo). This Special Issue is focussed on better understanding and modelling of temporal or spatial scales in land use dynamics.</p> <p> </p> <p>We invite new proposals for Special Issues that fit within SESMO’s <a href="https://sesmo.org/about">aims and scope</a>. Our Special Issues are cohesive collections of articles focussed on a specific contemporary theme related to socio-environmental systems modelling. The Special Issue can build on previous work and research gaps, but can also explore new and emerging terrain relevant to our aims. Although the conceptualisation of a Special Issue may be initiated in a conference or workshop, it is critical that such a proposal also builds on the original dialogue. Articles should also be canvassed from across the globe. SESMO is an open access journal with no article processing or publication charges for authors. If you have a topic to propose, please contact us to discuss further.</p>
EditorialTony JakemanIoannis AthanasiadisSerena Hamilton
Copyright (c) 2021 Tony Jakeman, Ioannis Athanasiadis, Serena Hamilton
2021-02-052021-02-05180401804010.18174/sesmo.2020a18040An agent-based model to support community forest management and non-timber forest product harvesting in northern Thailand
https://sesmo.org/article/view/17894
<p>Agent-based models are popular in common-pool resource management to represent complex systems and stimulate collective action and management, where they are used to evaluate scenarios of stakeholders' choice in participatory simulations. We developed the "CoComForest" (COllaborative COMmunity FOREST management) model to support community forest management (CFM) and non-timber forest product (NTFP) harvesting in Nan Province, northern Thailand. The model was used as a computer-based role-playing game to support sharing of perceptions and knowledge among stakeholders, and in participatory simulations to explore future CFM scenarios. The Unified Modelling Language was used to build the conceptual model, subsequently implemented under the CORMAS (COmmon-pool Resource and Multi-Agent System) simulation platform. Several tests were conducted in the laboratory for verification and calibration before using this tool with 21 diverse stakeholders during a field workshop. Three different participatory gaming and simulation sessions were organized. The first one focused on the co-validation of the model with participants. They accepted most of the model functionalities and the scheduling of the rounds of play. The model was used in the subsequent two sessions to simulate the scenarios of firebreak establishment and introduction of outsiders intensively harvesting NTFPs, respectively. The results showed that the intensive harvesting practices of outsiders accelerated the depletion of resources, whereas the prevention of wildfire by establishing firebreaks could increase the resource availability in the landscape. The debriefing session at the end of the workshop focused on the analysis of simulation results and the relationships between the players' decision-making and their actual circumstances. Individual in-depth interviews conducted after the workshop helped to evaluate the use of this model with local stakeholders. Most participants considered the model as a useful common representation of the system they manage collectively. Its use in participatory simulations facilitated communication among the stakeholders searching for an adapted and acceptable collective action plan to improve CFM at the sub-district level in order to prevent the overharvesting of NTFPs by outsiders.</p>
Research Papersparticipatory agent-based simulationcomputer-assisted role-playing gameCompanion Modelling (ComMod)CORMASknowledge exchangeThailandWuthiwong WimolsakcharoenPongchai DumrongrojwatthanaChristophe Le PageFrancois BousquetGuy Trebuil
Copyright (c) 2021 Wuthiwong Wimolsakcharoen, Pongchai Dumrongrojwatthana, Christophe Le Page, François Bousquet, Guy Trébuil
http://creativecommons.org/licenses/by-nc/4.0
2021-04-212021-04-21178941789410.18174/sesmo.2021a17894Combining social network analysis and agent-based modelling to explore dynamics of human interaction: A review
https://sesmo.org/article/view/16325
<p>Agent-based modelling (ABM) and social network analysis (SNA) are both valuable tools for exploring the impact of human interactions on a broad range of social and ecological patterns. Integrating these approaches offers unique opportunities to gain insights into human behaviour that neither the evaluation of social networks nor agent-based models alone can provide. There are many intriguing examples that demonstrate this potential, for instance in epidemiology, marketing or social dynamics. Based on an extensive literature review, we provide an overview on coupling ABM with SNA and evaluating the integrated approach. Building on this, we identify current shortcomings in the combination of the two methods. The greatest room for improvement is found with regard to (i) the consideration of the concept of social integration through networks, (ii) an increased use of the co-evolutionary character of social networks and embedded agents, and (iii) a systematic and quantitative model analysis focusing on the causal relationship between the agents and the network. Furthermore, we highlight the importance of a comprehensive and clearly structured model conceptualization and documentation. We synthesize our findings in guidelines that contain the main aspects to consider when integrating social networks into agent-based models.</p>
Research Papersagent-based modellingsocial network analysishuman behaviourreviewMeike WillJurgen GroeneveldKarin FrankBirgit Muller
Copyright (c) 2020 Meike Will, Jürgen Groeneveld, Karin Frank, Birgit Müller
http://creativecommons.org/licenses/by-nc/4.0
2020-02-282020-02-28163251632510.18174/sesmo.2020a16325Tracing resilience, social dynamics and behavioral change: a review of agent-based flood risk models
https://sesmo.org/article/view/17938
<p>Climate change and rapid urbanization exacerbate flood risks worldwide. The recognition of the crucial role that human actors play in altering risks and resilience of flood-prone cities triggers a paradigm shift in climate risks assessments and drives the proliferation of computational models that include societal dynamics. Yet, replacing a representative rational actor dominant in climate policy models with a variety of behaviorally-rich agents that interact, learn, and adapt is not straightforward. Focusing on the costliest climate-exacerbated hazard, flooding, we review computational agent-based models that include behavioral change and societal dynamics. We distinguish between two streams of literature: one stemming from economics & behavioral sciences and another from hydrology. Our findings show that most studies focus on households while representing decisions of other agents (government, insurance, urban developers) simplistically and entirely overlooking firms' choices in the face of risks. The two communities vary in the extent they ground agents' rules in social theories and behavioral data when modeling boundedly-rational decisions. While both aspire to trace feedbacks that agents collectively instigate, they employ different learning and interactions when computing societal dynamics in the face of climate risks. Dynamics of hazard, exposure, and vulnerability components of flood risks driven by incremental adaptation of agents are well represented. We highlight that applying a complex adaptive system perspective to trace the evolution of resilience can lead to a better understanding of transformational adaptation. The methodological advances in computational models with heterogeneous behaviorally-rich adaptive agents are relevant for adaptation to different climate-driven hazards beyond flooding.</p>
Research PapersAgent-based modelingclimate changeadaptationurbanbehaviorfloodsresilienceAlessandro TabernaTatiana FilatovaDebraj RoyBrayton Noll
Copyright (c) 2020 Alessandro Taberna, Tatiana Filatova, Debraj Roy, Brayton Noll
2020-12-082020-12-08179381793810.18174/sesmo.2020a17938Learning across disciplines in socio-environmental problem framing
https://sesmo.org/article/view/17895
<p>Modelling complex socio-environmental problems requires integration of knowledge across disparate fields of expertise. A key challenge is understanding how social learning across disciplines occurs in scientific research teams, in order that integrated knowledge is co-created. This article introduces a new framework for training researchers to integrate their knowledge across disciplines, based on current understanding of how inter- and transdisciplinary learning in research teams occurs. The framework was generated from a synthesis of learning, cognitive, and social science theories, and combines facilitated, structured negotiation processes with co-creation of boundary objects. It was used in two, 9 to 10-day intensive training workshops for doctoral students. This article describes the framework, workshop design, analysis of data collected during the workshops related to knowledge integration processes, what has been learned from the results, and the impact on participants. All participants indicated the experience was transformative, provided knowledge and skills unavailable elsewhere, filled gaps in their graduate education programs, and improving confidence in their capacity for inter- and transdisciplinary research. Pre- and post-workshop surveys confirm that the framework changed participants’ knowledge, behaviors, and competencies for engaging across disciplines. Many students have reported they have used the framework in a variety of other research and education settings, indicating they are able to transfer their new competencies to other contexts. Findings contribute to understanding of how to more effectively train researchers to integrate knowledge across disciplines for complex societal problem solving.</p>
Research Papersinterdisciplinaryknowledge integrationmodel-based reasoningboundary objectscomplex problem solvingDeana PenningtonShirley VincentDavid GosselinKate Thompson
Copyright (c) 2021 Deana Pennington, Shirley Vincent, Dave Gosselin, Kate Thompson
http://creativecommons.org/licenses/by-nc/4.0
2021-05-242021-05-24178951789510.18174/sesmo.2021a17895Building trust in SWAT model scenarios through a multi-institutional approach in Uruguay
https://sesmo.org/article/view/17892
<p>The inherent complexity of numerical models and the diversity of stakeholders in integrated water resources management (IWRM) create challenges in achieving credibility, salience and legitimacy to develop trust in model-based scenarios. In Uruguay, there has been significant debate on increasing agricultural production while managing agriculture’s environmental impacts (e.g., on water quality and environmental flows). This paper reports on the evolution of a stakeholder process in a case study with a multi-institutional participatory modelling group, supported by researchers. This specific participatory modelling (PM) project is unique in that the active stakeholders are the actual hydrological modellers, and the role of “experts†is mainly in facilitation and capacity building. The results highlight the different bottlenecks and the factors that enabled effective collaboration in this PM project. The main bottlenecks were related to: different views on representation of the watershed, the quality and usability of different input data, the public information for the technical implementation of the model, and the priority of output scenarios. The factors that enhanced collaboration were: a focus on a single basin problem, strong support from upper management, and support from experts in coordination and capacity building. The detailed documentation provided with this project can inspire similar approaches in the future.</p>
Research PapersIntegrated Water Resource Managementhydrological modellingstakeholder modellingcapacity buildingFlora MerWalter BaethgenR. Willem Vervoort
Copyright (c) 2020 Flora Mer, Rutger Willem Vervoort, Walter Baethgen
2020-12-152020-12-15178921789210.18174/sesmo.2020a17892