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

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).

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.

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.

Circular Economy in the Construction Industry: A Step towards Sustainable Development

Construction is a resource-intensive industry where a circular economy (CE) is essential to minimize global impacts and conserve natural resources. A CE achieves long-term sustainability by enabling materials to circulate along the critical supply chains. Accordingly, recent research has proposed a paradigm shift towards CE-based sustainability. However, uncertainties caused by fluctuating raw material prices, scarce materials, increasing demand, consumers’ expectations, lack of proper waste infrastructure, and the use of wrong recycling technologies all lead to complexities in the construction industry (CI). This research paper aims to determine the enablers of a CE for sustainable development in the CI. The system dynamics (SD) approach is utilized for modeling and simulation purposes to address the associated process complexity. First, using content analysis of pertinent literature, ten enablers of a CE for sustainable development in CI were identified. Then, causality among these enablers was identified via interviews and questionnaire surveys, leading to the development of the causal loop diagram (CLD) using systems thinking. The CLD for the 10 shortlisted enablers shows five reinforcing loops and one balancing loop. Furthermore, the CLD was used to develop an SD model with two stocks: “Organizational Incentive Schemes” and “Policy Support.” An additional stock (“Sustainable Development”) was created to determine the combined effect of all stocks. The model was simulated for five years. The findings show that policy support and organizational incentive schemes, among other enablers, are critical in implementing a CE for sustainable development in CI. The outcomes of this study can help CI practitioners to implement a CE in a way that drives innovation, boosts economic growth, and improves competitiveness.

Analyzing and Assessing Dynamic Behavior of a Physical Supply and Demand System for Sustainable Water Management under a Semi-Arid Environment

The extensive interest in sustainable water management reflects the extent to which the global water landscape has changed in the past twenty years, which is a natural development of changes in water resources and an increase in the level of imbalance between water supply and demand. In this paper, a simulation model based on system dynamics (SD) methodology was developed to aid sustainable water management efforts in a semi-arid region. Six policy scenarios were used to study, analyze, and assess water management trends in the Southeast region of New Mexico, USA. The modeling process included two phases: calibration (2000–2015) and future prediction (2016–2050). Several statistical criteria were applied to assess the developed model performance. The findings revealed that the simulated outputs were in excellent agreement with the historical data, indicating accurate model simulation. The SD model’s determination coefficients ranged from 0.9288 to 0.9936 and the index of agreement values ranged from 0.9397 to 0.9958. Findings for the business-as-usual scenario indicated that total water withdrawals and total population will continue to rise, whereas groundwater storage, agricultural consumptive water use, and total consumptive water use will decrease over the simulated period. Sensitivity analysis using Monte Carlo simulation indicated that cultivated irrigated land change is the most influential parameter affecting groundwater storage, water supply storage change (total withdrawals), agricultural consumptive water use, and total consumptive water use. The changes occurring in the agricultural cultivated area had a great influence on controlling the groundwater system. Overall, the results showed that our SD model has been successful in capturing the system’s dynamic behavior, and confirmed its capability in modeling water management issues for policy and decision makers under semi-arid conditions.

Sustainability Assessment Model of the Buriganga River Restoration Project in Bangladesh: A System Dynamics and Inclusive Wealth Study

The Bangladesh government initiated the Buriganga River Restoration Project in 2010 to clean the heavily polluted Turag-Buriganga River. This study assessed the dynamic impact of the project on intergenerational well-being and developing a sustainable river system. The project outcomes were modeled for three future scenarios—varying waste control, streamflow, and migration control levels. System dynamics modeling—based on Streeter-Phelps’ water quality model and inclusive wealth (IW) index—was applied to secondary data (including remotely sensed data). The simulation model indicated that the project (with increasing streamflow up to 160 m3/s) will not ensure sustainability because dissolved oxygen (DO) is meaningfully decreasing, biological oxygen demand (BOD) is increasing, and IW is declining over time. However, sustainability can be achieved in scenario 3, an integrated strategy (streamflow: 160 m3/s, waste control: 87.78% and migration control: 6%) that will ensure DO of 8.3 mg/L, BOD of 3.1 mg/L, and IW of 57.5 billion USD in 2041, which is equivalent to 2.22% cumulative gross domestic product by 2041. This study is the first to use combined modeling to assess the dynamic impacts of a river restoration project. The findings can help policymakers to achieve sustainability and determine the optimal strategy for restoring polluted rivers.

Evaluation of Seasonal, Drought, and Wet Condition Effects on Performance of Satellite-Based Precipitation Data over Different Climatic Conditions in Iran

The Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) are the most important and widely used data sources in several applications—e.g., forecasting drought and flood, and managing water resources—especially in the areas with sparse or no other robust sources. This study explored the accuracy and precision of satellite data products over a span of 18 years (2000–2017) using synoptic ground station data for three regions in Iran with different climates, namely (a) humid and high rainfall, (b) semi-arid, and (c) arid. The results show that the monthly precipitation products of GPM and TRMM overestimate the rainfall. On average, they overestimated the precipitation amount by 11% in humid, by 50% in semi-arid, and by 43% in arid climate conditions compared to the ground-based data. This study also evaluated the satellite data accuracy in drought and wet conditions based on the standardized precipitation index (SPI) and different seasons. The results showed that the accuracy of satellite data varies significantly under drought, wet, and normal conditions and different timescales, being lowest under drought conditions, especially in arid regions. The highest accuracy was obtained on the 12-month timescale and the lowest on the 3-month timescale. Although the accuracy of the data is dependent on the season, the seasonal effects depend on climatic conditions.

System dynamics approaches to assess the impacts of climate change on surface water quality and quantity: case study of Karoun River, Iran

The aim of this research is to gain a better understanding of the effects of climate change with a comprehensive and dynamic perspective. Therefore, by using the System Dynamics (SD) approach to simulate the effects of climate change on the quality and quantity of the Karoun River and regarding the water supply and demand systems in the region and their feedback relations, a model was developed in Vensim. CGCM3 outputs under A2, B1, and A1B emission scenarios have been used to investigate the effects of climate change on both the quality/quantity of the water resources system. Also, to determine the effects of climate change on agricultural demand, the water requirement of selected crops for the next period (2015-2050) has been calculated via CROPWAT model. The results show that the maximum and minimum temperature and evaporation will increase. The results of the developed SD model show that if the current development process continues under all three climate change scenarios, the system will be able to meet the domestic, industrial, and environmental demand. However, the supply of agricultural demand will be deficient. Also, the average EC value in Ahvaz station under three emission scenarios has increased more than 21%, compared to the 15-year average. The average pH value did not change much. Then, several proposed management scenarios were evaluated to improve system performance. The results show that the scenario of optimal operation of upstream dams has the best performance. However, due to the unrealistic growing trend, despite applying this scenario, the development of the agricultural sector will fail down after a few years. Therefore, to reach a long-term solution to the problem of water shortage, the growth trend of this sector for the next period should be reviewed in light of the effects of climate change.

The Use of Artificial Neural Networks to Predict the Physicochemical Characteristics of Water Quality in Three District Municipalities, Eastern Cape Province, South Africa

Reliable prediction of water quality changes is a prerequisite for early water pollution control and is vital in environmental monitoring, ecosystem sustainability, and human health. This study uses Artificial Neural Network (ANN) technique to develop the best model fits to predict water quality parameters by employing multilayer perceptron (MLP) neural network and the radial basis function (RBF) neural network, using data collected from three district municipalities. Two input combination models, MLP-4-5-4 and MLP-4-9-4, were trained, verified, and tested for their predictive performance ability, and their physicochemical prediction accuracy was compared by using each model's observed data with the predicted data. The MLP-4-5-4 model showed a better understanding of the data sets and water quality predictive ability giving an MSE of 39.06589 and a correlation coefficient (R²) of the observed and the predicted water quality of 0.989383 compared to the MLP-4-9-4 model (R² = 0.993532, MSE = 39.03087). These results apply to natural water resources management in South Africa and similar catchment systems. The MLP-4-5-4 system can be scaled up for future water quality prediction of the Waste Water Treatment Plants (WWTPs), groundwater, and surface water while raising awareness among the public and industry on future water quality.

A Dynamic Modeling Framework to Evaluate the Efficacy of Control Actions for a Woody Invasive Plant, Hakea sericea

Invasive alien species (IAS) are a significant component of global changes, causing severe economic and biodiversity damage. In this regard, Hakea sericea is one of the most widespread IAS throughout the Mediterranean region, including Portugal. The difficulty surrounding its management is exacerbated by post-fire situations, signifying a challenging task for managers. To assist in this effort, we used a system dynamic approach to model the population dynamics of Hakea sericea regarding the combinations of wildfire risk and control scenarios, which differ in periodicity, type of interventions, and cohort age. The ultimate goal of this study was to assess the effectiveness and costs of control efforts at reducing the abundance of this IAS. A Natura 2000 site Alvão/Marão (code PTCON0003) in northern Portugal, severely invaded by Hakea sericea, served as the study site. The modeling results demonstrate that Hakea sericea is likely to continue spreading if left uncontrolled. Although it may not be possible to ensure eradication of Hakea sericea from the study, repeated control actions aimed at the entire IAS population could be very effective in reducing its area. From a practical standpoint, removing all plants 24 months after each fire event followed by subsequent monitoring appears to be the most cost-effective strategy for managing Hakea sericea. Considering the modeling results, the dynamic modeling framework developed is a versatile, instructive tool that can support decision-making aimed at effective management of Hakea sericea.

System Dynamics Modeling for Evaluating Regional Hydrologic and Economic Effects of Irrigation Efficiency Policy

Exploring the dynamic mechanisms of coupled sociohydrologic systems is necessary to solve future water sustainability issues. This paper employs system dynamics modeling to determine hydrologic and economic implications of an irrigation efficiency (IE) policy (increased conveyance efficiency and field efficiency) in a coupled sociohydrologic system with three climate scenarios. Simulations are conducted within the lower Rio Grande region (LRG) of New Mexico for the years 1969 to 2099, including water, land, capital, and population modules. Quadrant analysis is utilized to compare the IE policy outcomes with the base case and to categorize results of simulations according to hydrologic and economic sustainability. The four categories are beneficial, unacceptable, unsustainable agricultural development, and unsustainable hydrology. Simulation results for the IE policy analyzed here fall into the categories of unsustainable agricultural development or unacceptable, suggesting there are long-term negative effects to regional economies in all scenarios with mixed results for hydrologic variables. IE policy can yield water for redistribution as increased unit water supply in the field produces more deep percolation; however, IE policy sacrifices regional connectivity. Specifically, simulation results show that the policy increases abundance by 4.7–74.5% and return flow by −3.0–9.9%. These positive results, however, come at the cost of decreased hydrologic connectivity (−31.5 to −25.1%) and negative economic impacts (−32.7 to −5.7%). Long-term net depletions in groundwater are also observed from loss of hydrologic connectivity and increased agricultural water demand from projections of increased consumptive use of crops. Adaptive water management that limits water use in drought years and replenishes groundwater in abundant years as well as economic incentives to offset the costs of infrastructure improvements will be necessary for the IE policy to result in sustainable agriculture and water resources.

Delving into the Divisive Waters of River Basin Planning in Bolivia: A Case Study in the Cochabamba Valley

River basin planning in Bolivia is a relatively new endeavor that is primed for innovation and learning. One important learning opportunity relates to connecting watershed planning to processes within other planning units (e.g., municipalities) that have water management implications. A second opportunity relates to integrating watershed management, with a focus on land-based interventions, and water resources management, with a focus on the use and control of surface and groundwater resources. Bolivia’s River Basin Policy and its primary planning instrument, the River Basin Master Plan (PDC in Spanish), provide the relevant innovation and learning context. Official guidance related to PDC development lacks explicit instructions related to the use of analytical tools, the definition of spatially and temporally dis-aggregated indicators to evaluate specific watershed and water management interventions, and a description of the exact way stakeholders engage in the evaluation process. This paper describes an effort to adapt the tenets of a novel planning support practice, Robust Decision Support (RDS), to the official guidelines of PDC development. The work enabled stakeholders to discern positive and negative interactions among water management interventions related to overall system performance, hydrologic risk management, and ecosystem functions; use indicators across varying spatial and temporal reference frames; and identify management strategies to improve outcomes and mitigate cross-regional or inter-sectorial conflicts.

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.

CHNS Modeling for Study and Management of Human–Water Interactions at Multiple Scales

This paper presents basic definitions and challenges/opportunities from different perspectives to study and control water cycle impacts on society and vice versa. The wider and increased interactions and their consequences such as global warming and climate change, and the role of complex institutional- and governance-related socioeconomic-environmental issues bring forth new challenges. Hydrology and integrated water resources management (IWRM from the viewpoint of an engineering planner) do not exclude in their scopes the study of the impact of changes in global hydrology from societal actions and their feedback effects on the local/global hydrology. However, it is useful to have unique emphasis through specialized fields such as hydrosociology (including the society in planning water projects, from the viewpoint of the humanities) and sociohydrology (recognizing the large-scale impacts society has on hydrology, from the viewpoint of science). Global hydrological models have been developed for large-scale hydrology with few parameters to calibrate at local scale, and integrated assessment models have been developed for multiple sectors including water. It is important not to do these studies with a silo mindset, as problems in water and society require highly interdisciplinary skills, but flexibility and acceptance of diverse views will progress these studies and their usefulness to society. To deal with complexities in water and society, systems modeling is likely the only practical approach and is the viewpoint of researchers using coupled human–natural systems (CHNS) models. The focus and the novelty in this paper is to clarify some of these challenges faced in CHNS modeling, such as spatiotemporal scale variations, scaling issues, institutional issues, and suggestions for appropriate mathematical tools for dealing with these issues.