The state-of-the-art system dynamics application in integrated water resources modeling

Integrated approach to water resource management in Mashhad Plain, Iran: actor analysis, cognitive mapping, and roadmap development

Iran's Mashhad Plain faces a severe water crisis due to the excessive exploitation of groundwater, leading to the depletion of its aquifer. While water demand management is recognized as a superior solution compared to supply projects, its implementation presents notable challenges. This study addresses the urgent necessity to curtail water demand in the Mashhad Plain by alleviating conflicts among various stakeholders, including water resource managers and consumers. Initially, the research identifies key water resource actors who collaborate in devising a comprehensive roadmap and conceptual model for efficient water resource management. An analysis uncovers significant conflicts among actors, representing approximately 6% of identified issues, with minor conflicts in 30% of cases. Encouragingly, stakeholders demonstrate potential for consensus on the remaining conflict items, with specific actors emerging as pivotal in conflict resolution. Efficient water resource management in regions facing scarcity, diverse interests, and sustainability challenges demands a multifaceted strategy. Future endeavors involve developing a dynamic system model to simulate policy impacts and strengthen conflict resolution efforts. This research introduces a roadmap-driven approach aimed at resolving conflicts and implementing water demand management in the Mashhad Plain. It emphasizes the critical need to address water scarcity challenges while effectively mitigating conflicts among water resource stakeholders.

Participatory Causal Loop Diagrams Building for Supporting Decision-Makers Integrating Flood Risk Management in an Urban Regeneration Process

Several modeling tools commonly used for supporting flood risk assessment and management are highly effective in representing physical phenomena, but provide a rather limited understanding of the multiple implications that flood risk and flood risk reduction measures have on highly complex systems such as urban areas. In fact, most of the available modeling tools do not fully account for this complexity-and related uncertainty-which heavily affects the interconnections between urban systems evolution and flood risk, ultimately resulting in an ineffective flood risk management. The present research proposes an innovative methodological framework to support decision-makers involved in an urban regeneration process at a planning/strategic level, accounting for the multi-dimensional implications of flood risk and of different flood risk management strategies. The adopted approach is based on the use of System Thinking principles and participatory System Dynamics modeling techniques, and pursues an integration between scientific and stakeholder knowledge. Reference is made to one of the case studies of the CUSSH and CAMELLIA projects, namely Thamesmead (London), a formerly inhospitable marshland currently undergoing a process of urban regeneration, and perceived as being increasingly vulnerable to flooding. It represents an interesting opportunity for building a replicable modeling approach to integrate urban development dynamics with flood risk, ultimately supporting policy and decision-makers in identifying mitigation/prevention measures and understanding how they could help achieve multi-dimensional benefits (e.g., environmental, social and economic).

A study of the required sustainability-driven institutional and behavioural mechanisms to tackle the anticipated implications of agricultural water price shocks: a system dynamics approach

Economic policies for managing agricultural water use are often complicated by the challenge of using water prices as an efficient economic tool when other non-economic concerns are involved in the decision-making process. This study aims to analyse the impact of water pricing policies on preserving agricultural water resources in Iran. This study applies a system dynamics approach to simulate the system performance and behaviour of stakeholders and the economic implications. Our finding shows that water pricing policies will likely fail due to low water price elasticity and if there are lack of institutional and physical infrastructure, alternative professions, manufacturing technology, education, and training opportunities. The results also illustrate how agricultural water price increase (AWPI) fails to reduce water consumption in the absence of an adequate institutional arrangement. Also, it shows how the lack of advanced institutional infrastructure in the presence of physical infrastructure enhances pervasive overuse and destructive competition among stakeholders by increasing the area under cultivation. In the discussion, the paper portrays a way out of the decision-making body by following AWPI effects on water conservation in the agricultural sector as the most significant water consumer. It investigates the absence and subsequent presence of specific institutional conditions and evaluates training and enhancing farmers' skills and alternative career source with higher income and technology as the architecture of good environmental governance. Finally, it concludes that a series of inclusive measures must be considered to increase the elasticity of the water price. These measures must stimulate farmers towards pursuing the goals of global sustainable development and enhancing social welfare.

Scale-invariant sensitivity for multi-purpose water reservoirs management with temporal scale-dependent modeling

High-resolution temporal data (e.g., daily) is valuable for the decision-making of water resources management because it more accurately captures fine-scale processes and extremes than the coarse temporal data (e.g., weekly or monthly). However, many studies rarely consider this superior suitability for water resource modeling and management; instead, they often use whichever data is more readily available. So far, no comparative investigations have been conducted to determine if access to different time-scale data would change decision-maker perceptions or the rationality of decision making. This study proposes a framework for assessing the impact of different temporal scales on water resource management and the performance objective's sensitivity to uncertainties. We built the multi-objective operation models and operating rules of a water reservoir system based on daily, weekly, and monthly scales, respectively, using an evolution multi-objective direct policy search. The temporal scales of the input variables (i.e., streamflow) affect both the model structures and the output variables. In exploring these effects, we reevaluated the temporal scale-dependent operating rules under uncertain streamflow sets generated from synthetic hydrology. Finally, we obtained the output variable's sensitivities to the uncertain factors at different temporal scales using the distribution-based sensitivity analysis method. Our results show that water management based on too coarse resolution might give decision makers the wrong perception because the effect of actual extreme streamflow process on the performance objectives is ignored. The streamflow uncertainty is more influential than the uncertainty associated with operating rules. However, the sensitivities are characterized by temporal scale invariance, as the differences of the sensitivity between different temporal scales are not obvious over the uncertainties in streamflow and thresholds. These results show that water management should consider the resolution-dependent effect of temporal scales for balancing modeling complexity and computational cost.

LXGB: a machine learning algorithm for estimating the discharge coefficient of pseudo-cosine labyrinth weir

One of the practical and financial solutions to increase the efficiency of weirs is to modify the geometry of the plan and increase the length of the weir to a specific width. This increases the discharge coefficient (C_d) of the weir. In this study, a new weir referred to pseudo-cosine labyrinth weir (PCLW) was introduced. A hybrid machine learning LXGB algorithm was introduced to estimate the C_d of the PCLW. The LXGB is a combination of the linear population size reduction history-based adaptive differential evolution (LSHADE) and extreme gradient boosting (XGB) algorithm. Seven different input scenarios were presented to estimate the discharge coefficient of the PCLW weir. To train and test the proposed method, 132 data series, including geometric and hydraulic parameters from PCLW1 and PCLW2 models were used. The root mean square error (RMSE), relative root mean square error (RRMSE), and Nash-Sutcliffe model efficiency coefficient (NSE) indices were used to evaluate the proposed approach. The results showed that the input variables were the ratio of the radius to the weir height (R/W), the ratio of the length of the weir to the weir height (L/W), and the ratio of the hydraulic head to the weir height (H/W), with the average values of RMSE = 0.009, RRMSE = 0.010, and NSE = 0.977 provided better results in estimating the C_d of PCLW1 and PCLW2 models. The improvement compared to SAELM, ANFIS-FFA, GEP, and ANN in terms of R² is 2.06%, 3.09%, 1.03%, and 5.15%. In general, intelligent hybrid approaches can be introduced as the most suitable method for estimating the C_d of PCLW weirs.

System dynamics simulation and regulation of human-water system coevolution in Northwest China

The human-water system synergy in Northwest China has become more significant as the ecological civilization construction continues and the implementation of the 2030 Agenda for Sustainable Development in China proceeds. In this study, taking the Ningxia Hui Autonomous Region as a typical research region, the human–water system coevolution model was established by coupling SD (System Dynamics) model and coevolution model from the theoretical perspective of complex system synergies, to simulate the human-water system’s coevolution trends from 2010 to 2030 in this region. Five regulation schemes were then designed to enhance the synergy of the human-water system by adjusting sensitive decision variables. The results revealed that the supply to demand ratio of water and the synergy index of the human-water system obtained by the status continuation scheme would decline from 1.02 and 0.39 in 2020 to 0.81 and 0.35 in 2030, respectively, indicating the growing gap between water supply and demand and revealing the worsening human-water relationship. Under the comprehensive optimization scheme, the supply to demand ratio of water and the synergy index of the human-water system would be higher than under the other schemes, demonstrating a substantially improved human-water relationship. Hence, a comprehensive optimization regulation scheme is proposed. This scheme combines improving pro-environmental water consumption, adapting industrial structures, and carrying out water conservation and pollution prevention. This research renders a decision-making basis for regulating regional water resources and finding paths to developing a harmonious relationship between humans and water.

Modeling water inequality and water security: The role of water governance

Water Inequality, Water Security and Water Governance are fundamental parameters that affect the sustainable use of water resources. Through policy formulation and decision-making, Water Governance determines both Water Security and Water Inequality. Largely, where Water Inequality exists, Water Security is undermined through unsustainable water use practices that lead to pollution of water resources, conflicts, hoarding of water, and poor sanitation. Incidentally, the interconnectedness of Water Governance, Water Inequality and Water Security has not been investigated previously. This study modified the Gini coefficient and used a Logistics Growth of Water Resources Model (LGWR Model) to access Water Inequality and Water Security mathematically, and discussed the connected role of Water Governance. We tested the validity of both models by calculating the actual Water Inequality and Water Security of Ghana. We also discussed the implications of Water Inequality on Water Security and the overarching role of Water Governance. The results show that regional Water Inequality is widespread in some parts. The Volta region showed the highest Water Inequality (Gini index of 0.58), while the Central region showed the lowest (Gini index of 0.15). Water Security is moderately sustainable. The use of water resources is currently stress-free. It was estimated to maintain such status until 2132 ± 18 when Ghana will consume half of the current total water resources of 53.2 billion cubic meters. Effectively, Water Inequality is a threat to Water Security, results in poverty, under-development heightens tensions in water use, and causes instability. With proper Water Governance, Water Inequality can be eliminated through formulating and implementing approaches that engender equal allocation and sustainable use of water resources.

Robust optimization with equity and efficiency framework for basin-wide water resources planning

This study proposes an equitable and effective water resource planning framework that handles competing regions and conflicting water departments within water-stressed watersheds under uncertainty. To cope with uncertainty, a robust optimization method based on an ellipsoidal uncertainty set is presented to keep the best solution viable and less conservative while attempting to find a balance between the reliability and optimum goals. The comprehensive framework consists of two predominant steps: equitable initial water allocation robust optimization programming, which employs the absolute difference between the supply and demand of water resources as the objective function and the Gini coefficient as the restricted condition, given that both surface water and groundwater are random, and subsequent effective water re-allocation robust modeling, which applies cooperative game theory to achieve maximum welfare in a river basin under uncertainty of the benefit coefficient. A realistic example of the Tuojiang River Basin was conducted, and the simulation experiments showed a significant increase (79.20%) in reliability with only an 11.44% increase in objective values and 2.76% and 15.17% decreases in the amount of surface water and groundwater, respectively. The findings of the analysis reveal that robust policies achieve adaptive optimal decision-making under uncertainty at a low cost.

Analyzing the wastewater treatment facility location/network design problem via system dynamics: Antalya, Turkey case

Wastewater treatment facility location selection and network design issues have become attractive topics in the field of wastewater management due to increasing human population, resource scarcity, environmental concerns, and rise of necessity for sustainable solutions for future policy designs. Especially in areas where the demand for wastewater treatment increases dramatically over the years because of reasons such as high migration levels, rapid industrialization, and tourism activities, the problem turns out to be more critical and dynamic. The existing studies try to deal with the issue through mathematical modeling approaches based on optimization perspectives, which require significant computational effort. In this study, an alternative approach based on system dynamics (SD) method is proposed to examine the complex dynamic and nonlinear structure of wastewater treatment facility location selection and network design problems. The proposed SD simulation model is designed for a densely populated industrial and tourism spot, the city of Antalya, located on the Mediterranean coast of Turkey. The model is capable of determining where and when to build a new wastewater treatment facility as well as generating the generic wastewater network structure to be built for the five districts situated in the city center based on cost issues for 2015-2040 period. In addition, the impacts of demand level changes for wastewater treatment due to population variations are analyzed via several scenarios to help decision makers to develop sustainable and cost-efficient management policies. Although SD is a frequently utilized approach in the water/wastewater management arena, to the best of our knowledge, this study is the first attempt to examine the complex and dynamic nature of wastewater treatment facility location selection and network design problems through SD approach.

A Framework to Support the Selection of an Appropriate Water Allocation Planning and Decision Support Scheme

Water is becoming a scarce resource in many parts of the world, leading to increased competition amongst water users. Optimized water allocation is increasingly important to balance the growing demand for water and the limited supply of accessible clean water. The literature on water allocation schemes and decision support systems, developed for application in specific water management areas or watersheds, was critically reviewed. Although the literature is rich in studies on the application of a broad range of water allocation schemes, there is a lack of information available on the methodology and process of selecting the most applicable scheme that balances the local realities and requirements of stakeholders while considering the local context with regard to the economic, social and environmental impact of water usage. In this article, a framework is presented that water management practitioners can use to select applicable water allocation planning schemes and associated decision support systems based on the characteristics and requirements of the specific water management situation. The framework was used to analyse the water supply situation in South Africa (SA), taking broader factors into account. Based on this, a generic conceptualized water allocation planning and decision support framework for a typical SA water management area is proposed.

Distributed Hydrological Model Based on Machine Learning Algorithm: Assessment of Climate Change Impact on Floods

Rapid population growth, economic development, land-use modifications, and climate change are the major driving forces of growing hydrological disasters like floods and water stress. Reliable flood modelling is challenging due to the spatiotemporal changes in precipitation intensity, duration and frequency, heterogeneity in temperature rise and land-use changes. Reliable high-resolution precipitation data and distributed hydrological model can solve the problem. This study aims to develop a distributed hydrological model using Machine Learning (ML) algorithms to simulate streamflow extremes from satellite-based high-resolution climate data. Four widely used bias correction methods were compared to select the best method for downscaling coupled model intercomparison project (CMIP6) global climate model (GCMs) simulations. A novel ML-based distributed hydrological model was developed for modelling runoff from the corrected satellite rainfall data. Finally, the model was used to project future changes in runoff and streamflow extremes from the downscaled GCM projected climate. The Johor River Basin (JRB) in Malaysia was considered as the case study area. The distributed hydrological model developed using ML showed Nash–Sutcliffe efficiency (NSE) values of 0.96 and 0.78 and Root Mean Square Error (RMSE) of 4.01 and 5.64 during calibration and validation. The simulated flow analysis using the model showed that the river discharge would increase in the near future (2020–2059) and the far future (2060–2099) for different Shared Socioeconomic Pathways (SSPs). The largest change in river discharge would be for SSP-585. The extreme rainfall indices, such as Total Rainfall above 95th Percentile (R95TOT), Total Rainfall above 99th Percentile (R99TOT), One day Max Rainfall (R × 1day), Five-day Max Rainfall (R × 5day), and Rainfall Intensity (RI), were projected to increase from 5% for SSP-119 to 37% for SSP-585 in the future compared to the base period. The results showed that climate change and socio-economic development would cause an increase in the frequency of streamflow extremes, causing larger flood events.

A scenario analysis-based optimal management of water resources supply and demand balance: A case study of Chengdu, China

Water resources scarcity has threatened the coordinative development of demographics, society and economy. As a typical rapidly urbanizing area and an emerging megacity in China, Chengdu is confronting the pressure of inadequate water supply. The present study divides the macroeconomic factors that affect the water resource supply and demand balance into six major subsystems: water resources supply, water demand, water drainage, population, ecological environment and economy. The combining variable interaction description and predictive simulation models are applied to simulate the water supply and demand ratio (S:D) from 2005 to 2035. Further, this study designs different development scenarios to simulate the change of S:D ratios by altering the parameter values of driving factors. The results show that: (1) the S:D ratio will decline if the current development scenario continues, implying the serious water resources shortage and the severe water supply-demand conflict in Chengdu; (2) socio-economic water demand and wastewater/rainwater reuse are the key driving parameters of S:D ratio, especially the water consumption per ten thousand yuan of industrial value-added; (3) the S:D ratio will increase from 0.92 in the current baseline scenario to 1.06 in the integrated optimization scenario in 2025, and the long-term planning brings 2035 from 0.71 to 1.03, with the proportion of unconventional water supply rise to 38% and 61%, respectively. This study can provide a decision-making tool for policy-makers to explore plausible policy scenarios necessary for bridging the gap between the water supply and demand in megacities.

System dynamics model for intra-city multimodal transportation considering behavioral indicators and demand under uncertainty conditions

Purpose

By designing a system dynamics model in the form of a multimodal transportation system, this study for the first time seeks to reduce costs and time, and increase customer satisfaction by considering uncertainties in the intra city transit system, especially demand uncertainty and provide a prototype system to prove the capability of the dynamical system.

Design/methodology/approach

The paper tried to model the factors affecting the intra city multimodal transportation system by defining different scenarios in the cause-and-effect model. The maps and results developed according to system dynamics modeling principles are discussed.

Findings

Four scenarios were considered given the factors affecting the urban transportation system to implement the transportation information system for reducing the material and non-material costs of wrong planning of the intra city transit system. After implementing the scenarios, scenario two was selected under the following conditions: advertising for cultural development, support of authorities by efforts such as street widening to reduce traffic, optimize infrastructure, increase and optimize public transport and etc.

Originality/value

The value of this paper is considering uncertainty in traffic optimization; taking into account behavioral and demand indicators such as cultural promotion, official support, early childhood learning, traffic hours and the impact of traveler social status; investigating the factors affecting the system under investigation and the reciprocal effects of these factors and real-world simulation by considering the factors and effects between them.

Current solid waste management strategies and energy recovery in developing countries - State of art review

Solid waste generation has rapidly increased due to the worldwide population, urbanization, and industrialization. Solid waste management (SWM) is a significant challenge for a society that arises local issues with global consequences. Thus, solid waste management strategies to recycle waste products are promising practices that positively impact sustainable goals. Several developed countries possess excellent solid waste management strategies to recycle waste products. Developing countries face many challenges, such as municipal solid waste (MSW) sorting and handling due to high population density and economic instability. This mismanagement could further expedite harmful environmental and socioeconomic concerns. This review discusses the current solid waste management and energy recovery production in developing countries; with statistics, this review provides a comprehensive revision on energy recovery technologies such as the thermochemical and biochemical conversion of waste with economic considerations. Furthermore, the paper discusses the challenges of SWM in developing countries, including several immediate actions and future policy recommendations for improving the current status of SWM via harnessing technology. This review has the potential of helping municipalities, government authorities, researchers, and stakeholders working on MSW management to make effective decisions for improved SWM for achieving sustainable development.

Scope, trends and opportunities for socio-hydrology research in Africa: A bibliometric analysis

Socio-hydrology research is concerned with the understanding of how humanity interacts with water resources. The purpose of this study was to assess the disparity between global and African trends as well as developments in the research domain of socio-hydrology. From the viewpoint of a multitude of research themes, multi-author collaborations between African and international researchers and the number of publications produced globally, the results reveal that the field of socio-hydrology is still underdeveloped and yet nascent. At a global level, the USA, China, and the Netherlands have the highest number of scientific publications, while in Africa, South Africa dominates, although these scientific publications are significantly much lower than the global output. The output of scientific publications on socio-hydrology research from Africa increased from 2016, with significant output reached in 2019. Water management and supply, hydrological modelling, flood monitoring as well as policies and decision-making, are some of the dominant themes found through keywords co-occurrence analysis. These main keywords may be considered as the foci of research in socio-hydrology. Although socio-hydrology research is still in the early stages of development in Africa, the cluster and emerging themes analysis provide opportunities for research in Africa that will underpin new frontiers of the research agenda encompassing topics such as the (1) impacts of climate change on socio-hydrology; (2) influence of socio-hydrology on water resources such as surface water and groundwater; (3) benefits of socio-hydrological models on river basins and (4) role of socio-hydrology in economic sectors such as agriculture. Overall, this study points to a need to advance socio-hydrology research in Africa in a bid to address pressing water crises that affect sustainable development as well as to understand the feedback mechanisms and linkages between water resources and different sectors of society.

Nature-based solutions efficiency evaluation against natural hazards: Modelling methods, advantages and limitations

Nature-based solutions (NBS) for hydro-meteorological risks (HMRs) reduction and management are becoming increasingly popular, but challenges such as the lack of well-recognised standard methodologies to evaluate their performance and upscale their implementation remain. We systematically evaluate the current state-of-the art on the models and tools that are utilised for the optimum allocation, design and efficiency evaluation of NBS for five HMRs (flooding, droughts, heatwaves, landslides, and storm surges and coastal erosion). We found that methods to assess the complex issue of NBS efficiency and cost-benefits analysis are still in the development stage and they have only been implemented through the methodologies developed for other purposes such as fluid dynamics models in micro and catchment scale contexts. Of the reviewed numerical models and tools MIKE-SHE, SWMM (for floods), ParFlow-TREES, ACRU, SIMGRO (for droughts), WRF, ENVI-met (for heatwaves), FUNWAVE-TVD, BROOK90 (for landslides), TELEMAC and ADCIRC (for storm surges) are more flexible to evaluate the performance and effectiveness of specific NBS such as wetlands, ponds, trees, parks, grass, green roof/walls, tree roots, vegetations, coral reefs, mangroves, sea grasses, oyster reefs, sea salt marshes, sandy beaches and dunes. We conclude that the models and tools that are capable of assessing the multiple benefits, particularly the performance and cost-effectiveness of NBS for HMR reduction and management are not readily available. Thus, our synthesis of modelling methods can facilitate their selection that can maximise opportunities and refute the current political hesitation of NBS deployment compared with grey solutions for HMR management but also for the provision of a wide range of social and economic co-benefits. However, there is still a need for bespoke modelling tools that can holistically assess the various components of NBS from an HMR reduction and management perspective. Such tools can facilitate impact assessment modelling under different NBS scenarios to build a solid evidence base for upscaling and replicating the implementation of NBS.

Evaluating the efficacy of targeting options for conservation practice adoption on watershed-scale phosphorus reductions

Conservation identities of farmers in the Maumee River watershed, derived from farmer surveys, were embedded into a SWAT watershed model. This was done to improve the representation of the heterogeneity among farmers in the decision-making process related to the adoption of conservation practices. Modeled farm operations, created with near field-level Hydrologic Response Units (HRUs) within the SWAT model, were assigned a modeled primary operator. Modeled primary operators held unique conservation identities driven by their spatial location within the watershed. Five pathways of targeting the adoption of subsurface placement of phosphorus and buffer strips to HRUs within the watershed were assessed. Targeting pathways included targeting by HRU-level phosphorus losses, conservation identity of model operators, a hybrid approach combining HRU-level phosphorus losses and conservation identity of the model primary operator managing the HRU, and a proxy measure for random placement throughout the watershed. Targeting the placement of subsurface phosphorus application to all agricultural HRUs resulted in the greatest reduction in total phosphorus losses (32%) versus buffer strips (23%). For both conservation practices, targeting by HRU-level total phosphorus losses resulted in the most efficient rate of phosphorus reduction as measured by the ratio of phosphorus reduction to conservation practice adoption rates. The hybrid targeting approach closely resembled targeting by phosphorus losses, indicating near optimal results can be obtained even when constraining adoption by farmer characteristics. These results indicate that by developing management strategies based on a combination of field-level information and human-operator characteristics, a more efficient use of limited resources can be used while achieving near-maximal environmental benefits as compared to managing environmental outcomes solely based on field-level information.

Complex Socio-Ecological Systems: Translating Narratives into Future Land Use and Land Cover Scenarios in the Kilombero Catchment, Tanzania

The Kilombero wetland in Tanzania is affected by advancing land use and land cover changes (LULCC), where we observe a conflict between development interests and the necessity of conservation measures to maintain the functionalities of the ecosystem. Thus, assessing patterns of LULCC is crucial to foresee potential future developments and to develop sustainable future management strategies. In this study, we use a multi-method scenario approach to assess the spatial implications and underlying driving forces of potential change by (1) developing a System Dynamics Causal Loop Diagram (CLD) to disentangle the underlying socio-economic and ecologic driving forces, (2) deriving a qualitative business-as-usual (BAU) and a conservation scenario from participatory narratives elaborated during a stakeholder workshop, and (3) quantifying the spatial implications of these scenarios with the Land Change Modeler (LCM). Results indicate that under the BAU assumption only 37% of the natural vegetation is expected to persist until 2030 in the wetland. In contrast, strict enforcement of protected areas (conservation scenario) halts further conversion of the wetland. However, both scenarios pinpoint considerable expansions of cropland in the western highlands with potentially serious impacts on catchment-wide hydrological processes. The produced qualitative and quantitative outputs reveal hotspots of possible future change and starting points for advisable further research and management interventions.

System Dynamics-Multiple Objective Optimization Model for Water Resource Management: A Case Study in Jiaxing City, China

Predicting and allocating water resources have become important tasks in water resource management. System dynamics and optimal planning models are widely applied to solve individual problems, but are seldom combined in studies. In this work, we developed a framework involving a system dynamics-multiple objective optimization (SD-MOO) model, which integrated the functions of simulation, policy control, and water allocation, and applied it to a case study of water management in Jiaxing, China to demonstrate the modeling. The predicted results of the case study showed that water shortage would not occur at a high-inflow level during 2018–2035 but would appear at mid- and low-inflow levels in 2025 and 2022, respectively. After we made dynamic adjustments to water use efficiency, economic growth, population growth, and water resource utilization, the predicted water shortage rates decreased by approximately 69–70% at the mid- and low-inflow levels in 2025 and 2035 compared to the scenarios without any adjustment strategies. Water allocation schemes obtained from the “prediction + dynamic regulation + optimization” framework were competitive in terms of social, economic and environmental benefits and flexibly satisfied the water demands. The case study demonstrated that the SD-MOO model framework could be an effective tool in achieving sustainable water resource management.

Causal Loop Diagrams for supporting Nature Based Solutions participatory design and performance assessment

The contribution of Nature Based Solutions (NBSs) for supporting climate change adaptation and water-related risks reduction is becoming increasingly relevant for policy and decision-makers, compared to 'grey infrastructures', thanks to their capability to jointly deal with a multiplicity of societal and environmental challenges, producing several co-benefits besides limiting the impacts of water-related risks. Nevertheless, their mainstreaming is still limited by several barriers, which are often related to socio-institutional (e.g. limited cooperation and stakeholders' involvement, limited awareness about NBSs impacts) rather than to technical aspects. In this context, innovative tools for NBSs planning, design, implementation and assessment are required, along with effective processes capable of supporting stakeholders' participation. The present research aims to propose a shift in the approach to NBSs design, based on the early stakeholders' involvement in the identification, modelling and performance assessment in terms of benefits and, particularly, co-benefits production. A multi-step methodology was implemented for the purpose, combining both individual and participatory activities. Reference is made to one of the case studies of the NAIAD project, namely the Balta Potelu Pond Area (Lower Danube, Romania). Causal Loop Diagrams (CLDs) were used to describe the system in terms of causal connections and mutual influences, incorporating stakeholders' views and ideas. Inputs from both institutional (e.g. ministries and municipalities) and non-institutional stakeholders (e.g. NGOs and members of the local communities) were integrated. This allowed a comparative assessment of multiple NBSs, based on the analysis of benefits and co-benefits produced, as well as the identification of trade-offs among different stakeholders (e.g. the increase of agricultural production versus biodiversity conservation) and potential side effects. CLDs were then coupled with a Performance Matrix (a basic feature of Multi-Criteria Decision Analysis) and fuzzy logic to help decision-makers identify the most suitable NBSs for the area. The whole process was aimed at facilitating the process of NBSs selection and analysis, while considering the multiple impacts associated with their implementation.

An Integrated Modeling System for the Evaluation of Water Resources in Coastal Agricultural Watersheds: Application in Almyros Basin, Thessaly, Greece

This study presents an integrated modeling system for the evaluation of the quantity and quality of water resources of coastal agricultural watersheds. The modeling system consists of coupled and interrelated models, including (i) a surface hydrology model (UTHBAL), (ii) a groundwater hydrology model (MODFLOW), (iii) a crop growth/nitrate leaching model (REPIC, an R-ArcGIS-based EPIC model), (iv) a groundwater contaminant transport model (MT3DMS), and (v) a groundwater seawater intrusion model (SEAWAT). The efficacy of the modeling system to simulate the quantity and quality of water resources has been applied to the Almyros basin in Thessaly, Greece. It is a coastal agricultural basin with irrigated and intensified agriculture facing serious groundwater problems, such as groundwater depletion, nitrate pollution, and seawater intrusion. Irrigation demands were estimated for the main crops cultivated in the area, based on precipitation and temperature from regional weather stations. The models have been calibrated and validated against time-series of observed crop yields, groundwater table observations, and observed concentrations of nitrates and chlorides. The results indicate that the modeling system simulates the water resources quantity and quality with increased accuracy. The proposed modeling system could be used as a tool for the simulation of water resources management and climate change scenarios.

The Dynamics of Sustainability Risks in the Global Coffee Supply Chain: A Case of Indonesia–UK

Indonesia is one of the leading global coffee producers, and the sustainability of its coffee supply chains is therefore of crucial importance, not only for the coffee sector, but also for the thousands of livelihoods involved. Recognising sustainability risks within supply chains is an important component of understanding logistics. This research investigated the sustainability risks in the Indonesia–UK coffee supply chain by using System Dynamics (SD), a simulation modeling paradigm commonly used to assess complex systems. The model parameters and other components of the dynamic model were extracted through interviews with key stakeholders in the coffee supply chain, supported by evidence from a literature review. The model was then verified and validated in different stages, before being used to investigate five different what-if scenarios to consider changes to parameters in the system. The results of this investigation demonstrate the importance of improving agricultural productivity to support a sustainable coffee supply chain. This research also confirms that by combining the SD model and the multiple criteria decision-making technique, it is possible to achieve a more practical and accurate solution than by the individual tool alone, thus ensuring a better understanding of the whole issues affecting the coffee supply chain.

Water Resource Carrying Capacity Based on Water Demand Prediction in Chang-Ji Economic Circle

In view of the large spatial difference in water resources, the water shortage and deterioration of water quality in the Chang-Ji Economic Circle located in northeast China, the water resource carrying capacity (WRCC) from the perspective of time and space is evaluated. We combine the gray correlation analysis and multiple linear regression models to quantitatively predict water supply and demand in different planning years, which provide the basis for quantitative analysis of the WRCC. The selection of research indicators also considers the interaction of social economy, water resources, and water environment. Combined with the fuzzy comprehensive evaluation method, the gray correlation analysis and multiple linear regression models to quantitatively and qualitatively evaluate the WRCC under different social development plans. The developmental trends were obtained from 2017 to 2030 using four plans designed for distinct purposes. It can be seen that the utilization of water resource is unreasonable now and maintains a poor level under a business-as-usual Plan I. Plan II and Plan III show that resource-based water shortage is the most critical issue in this region, and poor water quality cannot be ignored either. Compared with Plan I, the average index of WRCC in Plan IV increased by 51.8% and over 84% of the regions maintain a good level. Strengthening sewage treatment and properly using transit water resources are more conducive to the rapid development of Chang-Ji Economic Circle.

Using a system thinking approach to assess the contribution of nature based solutions to sustainable development goals

Climate change and the overexploitation of natural resources increase the need to integrate sustainable development policies at both national and international levels to fit the demands of a growing population. In 2015 the United Nations (UN) established the 2030 Agenda for sustainable development with the aim of eradicating extreme poverty, reducing inequality and protecting the planet. The Agenda 2030 highlights the importance of biodiversity and the functioning of ecosystems to maintain economic activities and the well-being of local communities. Nature Based Solutions (NBS) support biodiversity conservation and the functioning of ecosystems. NBS are increasingly seen as innovative solutions to manage water-related risks while transforming natural capital into a source of green growth and sustainable development. In this context, NBS could potentially contribute to the achievement of several Sustainable Development Goals (SDGs) by promoting the delivery of bundles of ecosystem services together generating various social, economic and environmental co-benefits. However, to achieve the full potential of NBS, it is necessary to recognize the trade-offs and synergies of the co-benefits associated with their implementation. To this aim, we have adopted a system perspective and a multi-sectoral approach to analyse the potential of NBS to deliver co-benefits while at the same time reducing the negative effects of water-related hazards. Using the case study of Copenhagen, we have analysed the relationships between the co-benefits associated with the scenario of the restoration of the Ladegaardsaa urban river. Our hypothesis is that enhancing the understanding of the social, economic and environmental factors of the system, including mutual influences and trade-offs, could improve the decision-making process and thereby enhance the capability of NBS to contribute to the achievement of the SDGs.

Analysis of the potential of reclaimed water utilization in typical inland cities in northwest China via system dynamics

Located in the hinterland of the Eurasian continent, the inland areas of northwestern China have an arid climate and are confronted with continuing challenges in water resources quantity and quality. Reclaimed water plays an important role in maintaining the sustainable use of urban water resources, especially in arid regions. In this paper, a system dynamics urban reclaimed water model (SDURWM) considering the status of arid regions in northwestern China was constructed. The supply and demand balance index (RWB) and the utilization efficiency index (RWUE) of reclaimed water were proposed as evaluation indicators. The potential of reclaimed water utilization (2016-2025) in three typical cities with similar natural environments and population sizes but with large economic differences were estimated by the SD model. Then the relevant values of reclaimed water quota, supply and resident awareness were adjusted within the range of 10%-20%. The predicted results from intervention demonstrate that the RWB of three cities will be closer or maintain to the ideal value, and that the RWUE will increase by about 0.1, compared with the non-intervention results. This indicates that a minor change of the targeted policies can invigorate the capacity of reclaimed water use in droughty cities. This paper provides some effective solutions for the government's planning of developing the potential of reclaimed water.

FACTORS INFLUENCING URBAN INVESTMENT ATTRACTIVENESS: AN FCM-SD APPROACH

The increasing concentration of populations in urban areas in recent decades has strengthened the interest in – and the importance given to – these zones. Cities have become quite attractive from investors’ point of view because of the wide array of opportunities and growing need for investment in urban areas. Thus, city strategic planning quite often requires an understanding of the determinants that attract investment to urban zones. This study sought to identify the factors that strengthen urban investment based on the knowledge of a panel of experts. Fuzzy cognitive mapping techniques were applied to understand the concepts and decision criteria included in the decision-support model and their cause-and-effect relationships. The results provide insights into which determinants most strongly influence urban investment, namely, infrastructure, supporting services, and political-administrative factors. Diverse scenarios at the intra- and inter-cluster levels were created to clarify the impacts of variable changes on the model developed. The findings were validated by both the expert panel members and the vice-president of the Portuguese Association of Real Estate Developers and Investors. Advantages and limitations of the proposed framework are presented, as well as recommendations for future research.

Identifying Capabilities and Potentials of System Dynamics in Hydrology and Water Resources as a Promising Modeling Approach for Water Management

Agriculture is the most important sector with regard to water resources management due to its social, economic, hydrological, and environmental aspects, and many scholars and researchers have been driven to investigate the dynamic interrelationships among hydrological, environmental, and socioeconomic factors affecting agriculture. The system dynamics (SD) approach has become widely used because of its merits and benefits as a tool to deal with complex, dynamic problems and systems with many aspects and components that are involved and must be understood to ensure sound decisions regarding water and hydrological systems. Although agricultural water management needs to be studied as a main part of water management, socioeconomic management, and environmental management requiring the use of SD, this review shows that SD is currently used to a limited extent in terms of agricultural water management. This paper sheds light on the studies and investigations on the use of SD in the water sector and highlights the strengths of SD in order to encourage researchers to use this promising method to manage such a vital resource. Accordingly, this review seeks to include a comprehensive and up-to-date survey of existing publications and scholarly papers on the use of SD modeling as an effective technique for dealing with different problems associated with planning, management, and analysis of hydrology and water resources systems. Recent trends in the integration of SD with other modeling systems, such as artificial intelligence systems, are discussed along with the limitations and challenges facing application. This article makes a new contribution by giving a foundation of references and studies for scholars, researchers, and academics which encourages future investigation in employing the SD approach to hydrology and water resources management and planning, especially with agricultural water.

Sensitive Factors Identification and Scenario Simulation of Water Demand in the Arid Agricultural Area Based on the Socio-Economic-Environment Nexus

Water scarcity has seriously threatened the sustainable development of Zhangjiakou City, an arid agricultural area in North China, and the ecological security of its neighboring areas. In this study, a system dynamics model is established based on variable sensitivity analysis and is employed to simulate water demand (2015–2035) in four designed alternative development scenarios in Zhangjiakou City. The results show that: (1) the variables related to irrigation farmland are the main driving factors of water demand, especially the area and water use quota. (2) The total water demand will rise continually in the current development scenario and economic priority scenario, and the proportion of agricultural water demand will drop to 67% and 63%, respectively. It will decline continually in the water-saving priority scenario and balanced development scenario, and the proportion of agricultural water demand will drop to 56% and 57%, respectively. (3) Water consumption per ten thousand yuan of GDP will fall to around 20 m3 in 2035 in each scenario, indicating that the reduction of water demand only by slowing down economic growth cannot improve the efficiency of water use. The research results will be beneficial to extract feasible strategies and policies for balancing economic development and water conservation.

Analyzing the Effectiveness of a Multi-Purpose Dam Using a System Dynamics Model

The increasing frequency of extreme droughts and flash floods in recent years due to climate change has increased the interest in sustainable water use and efficient water resource management. Because the water resource sector is closely related to human activities and affected by interactions between the humanities and social sciences, there is a need for interdisciplinary research that can consider various elements, such as society and the economy. This study elucidates relationships within the social and hydrological systems and quantitatively analyzes the effects of a multi-purpose dam on the target society using a system dynamics model. A causal loop was used to identify causal relationships between the social and hydrological components of the target area, and a simulation model was constructed using the system dynamics technique. Additionally, climate change and socio-economic scenarios were applied to analyze the future effects of the multi-purpose dam on population change, the regional economy, water use, and flood damage prevention in the target area. The model proved reliable in predicting socio-economic changes in the target area and can be used to make decisions about efficient water resource management and water-resource-related facility planning.

A new model framework for sponge city implementation: Emerging challenges and future developments

Sponge City concept is emerging as a new kind of integrated urban water systems, which aims to address urban water problems. However, its implementation has encountered a variety of challenges. The lack of an integrated comprehensive model to assist Sponge City planning, implementation and life cycle assessment is one of the most challenging factors. This review briefly analyses the opportunity of existing urban water management models and discusses the limitation of recent studies in the application of current integrated models for Sponge City implementation. Furthermore, it proposes a new Sponge City model framework by integrating four main sub-models including MIKE-URBAN, LCA, W045-BEST, and MCA in which environmental, social, and economic aspects of Sponge City infrastructure options are simulated. The new structure of Sponge City model that includes the sub-model layer, input layer, module layer, output layer, and programing language layer is also illustrated. Therefore, the proposed model could be applied to optimize different Sponge City practices by not only assessing the drainage capacity of stormwater infrastructure but also pays attention to multi-criteria analysis of urban water system (including the possibility of assessing Sponge City ecosystem services for urban areas and watershed areas) as well. Balancing between simplification and innovation of integrated models, increasing the efficiency of spatial data sharing systems, defining the acceptability of model complexity level and improving the corporation of multiple stakeholders emphasizing on possible future directions of a proper Sponge City design and construction model.

Water allocation and governance in multi-stakeholder environments: Insight from Axios Delta, Greece

This article deals with stakeholders' interactions and institutional capacity influencing water resource management where competitive demands co-exist. For the case study area of Axios Delta, Northern Greece, a water deficit in the agricultural sector, an unmet environmental flow and a reduced capacity for urban supply during drought conditions are observed. An egocentric network analysis based on desk-study and a series of semi-structured stakeholder interviews reveals how weak stakeholder ties lead to ineffective multilevel governance and, as a result, low water efficiency practices. There is a lack of understanding of other users' priorities as well as of the risks related to climate change and/or seasonal variability. This is reflected in the flat rate abstraction licence for agricultural purposes which reduces environmental flow to below acceptable standards. There is no transboundary cooperation between Greece and the Republic of North Macedonia which hinders an integrated management approach. A limited exchange of information to support an evidence-based allocation plan is observed. Suitable interventions identified through a DPSIR approach are evaluated in a multi-criteria analysis considering cost effectiveness, delivered benefits as well as ease of implementation. Suitable technical practices include the development of a local and catchment-scale monitoring network for surface water and groundwater, climate-adaptive agriculture and treated-water reclamation. Updated management policies involve the institutional prioritisation of environmental flow through an adaptive allocation plan as well as the strengthening of transboundary cooperation. This research shows how the coordination of aggregated diverging interests in multilevel multi-stakeholder environments appears to be key in supporting positive water budgets in an uncertain climate future.

Engaging stakeholders in the assessment of NBS effectiveness in flood risk reduction: A participatory System Dynamics Model for benefits and co-benefits evaluation

There is an imperative worldwide need to identify effective approaches to deal with water-related risks, and mainly with increasingly frequent floods, as well as with severe droughts. Particularly, policy and decision-makers are trying to identify systemic strategies that, going beyond the mere risk reduction, should be capable to deal simultaneously with multiple challenges (such as climate resilience, health and well-being, quality of life), thus providing additional benefits. In this direction, the contribution of Nature Based Solutions (NBS) is relevant, although their wider implementation is still hampered by several barriers, such as the uncertainty and lack of information on their long-term behavior and the difficulty of quantitatively valuing their multidimensional impacts. The activities described in the present paper, carried out within the EU funded project NAIAD, mainly aim at developing a participatory System Dynamic Model capable to quantitatively assess the effectiveness of NBS to deal with flood risks, while producing a multiplicity of co-benefits. The adoption of a participatory approach supported both to increase the available knowledge and the awareness about the potential of NBS and hybrid measures (e.g. a combination of NBS and socio-institutional ones). Specific reference is made to one of the demos of the NAIAD project, namely the Glinščica river case study (Slovenia).

Urban Hydroinformatics: Past, Present and Future

Hydroinformatics, as an interdisciplinary domain that blurs boundaries between water science, data science and computer science, is constantly evolving and reinventing itself. At the heart of this evolution, lies a continuous process of critical (self) appraisal of the discipline’s past, present and potential for further evolution, that creates a positive feedback loop between legacy, reality and aspirations. The power of this process is attested by the successful story of hydroinformatics thus far, which has arguably been able to mobilize wide ranging research and development and get the water sector more in tune with the digital revolution of the past 30 years. In this context, this paper attempts to trace the evolution of the discipline, from its computational hydraulics origins to its present focus on the complete socio-technical system, by providing at the same time, a functional framework to improve the understanding and highlight the links between different strands of the state-of-art hydroinformatic research and innovation. Building on this state-of-art landscape, the paper then attempts to provide an overview of key developments that are coming up, on the discipline’s horizon, focusing on developments relevant to urban water management, while at the same time, highlighting important legal, ethical and technical challenges that need to be addressed to ensure that the brightest aspects of this potential future are realized. Despite obvious limitations imposed by a single paper’s ability to report on such a diverse and dynamic field, it is hoped that this work contributes to a better understanding of both the current state of hydroinformatics and to a shared vision on the most exciting prospects for the future evolution of the discipline and the water sector it serves.

A Scenario-Based Optimization Model for Planning Sustainable Water-Resources Process Management under Uncertainty

Discrepancies between water demand and supply are intensifying and creating a need for sustainable water resource process management associated with rapid economic development, population growth, and urban expansion. In this study, a scenario-based interval fuzzy-credibility constrained programming (SIFCP) method is developed for planning a water resource management system (WRMS) that can handle uncertain information by using interval values, fuzzy sets, and scenario analysis. The SIFCP-WRMS model is then applied to plan the middle route of the South-to-North Water Diversion Project (SNWDP) in Henan Province, China. Solutions of different water distribution proportion scenarios and varied credibility levels are considered. Results reveal that different water-distribution proportion scenarios and uncertainties used in the SIFCP-WRMS model can lead to changed water allocations, sewage discharges, chemical oxygen demand (COD) emissions, and system benefits. Results also indicate that the variation of scenarios (i.e., from S2 to S3) can result in a change of 9% over the planning horizon for water allocation in the industrial sector. Findings can help decision-makers resolve conflicts among economic objective, water resource demand, and sewage discharge, as well as COD emissions.

Network model-based analysis of the goals, targets and indicators of sustainable development for strategic environmental assessment

Strategic environmental assessment is a decision support technique that evaluates policies, plans and programs in addition to identifying the most appropriate interventions in different scenarios. This work develops a network-based model to study interlinked ecological, economic, environmental and social problems to highlight the synergies between policies, plans, and programs in environmental strategic planning. Our primary goal is to propose a methodology for the data-driven verification and extension of expert knowledge concerning the interconnectedness of the sustainable development goals and their related targets. A multilayer network model based on the time-series indicators of the World Bank open data over the last 55 years was assembled. The results illustrate that by providing an objective and data-driven view of the correlated variables of the World Bank, the proposed layered multipartite network model highlights the previously not discussed interconnections, node centrality measures evaluate the importance of the targets, and network community detection algorithms reveal their strongly connected groups. The results confirm that the proposed methodology can serve as a data-driven decision support tool for the preparation and monitoring of long-term environmental policies. The developed new data-driven network model enables multi-level analysis of the sustainability (goals, targets, indicators) and will make it possible to plan long-term environmental strategic planning. Through relationships among indicators, relationships among targets and goals can be modelled. The results show that sustainable development goals are strongly interconnected, while the 5th goal (gender equality) is linked mostly to 17th (partnerships for the goals) goal. The analysis has also highlighted the importance of the 4th (quality education).