Modeling: Enabler for Sustainable Water Supply & Demand Management (An Overview)

Water supply and demand management (WSDM) is only effective when tackled with holistic system understanding considering social, economic, hydrological, and economic sub-systems. System Dynamics Model (SDM), also known as System Dynamics (SD), which is a Systems Thinking Approach (STA), is actively used for this purpose by water resource analysts. This paper provides a comprehensive review of the application of SDM to water supply and demand management, with a focus on groundwater (GW) sustainability. Further, the quantitative models used in conjunction with SDM are explored. Over sixty nine papers spanning over the last 20 years were analyzed. The quantitative models complemented the SDM includes Agent-Based Modeling (ABM), Bayesian Networking (BN), Analytical Hierarchy Approach (AHP), simulation-optimization M-Objective Optimization (MOO) and solved using Genetic Algorithm (GA), Particle-Swarm-Optimization (PSO) and Non-dominated Sorting Genetic Algorithm (NSGA-II). Although Climate change significantly affects water management strategies, this study revealed that only 51% of the reviewed articles considered it, while the problem conceptualization using the Causal-Loop-Diagram (CLD) is performed by only 58% of the studies. Moreover, 70% of the reviewed articles used the Stock-Flow-Diagram (SFD) to perform the quantitative system analysis. Stakeholder engagement plays a significant role in understanding the consumers’ core issues and divergent views and needs but is incorporated by only 36% of the studies. The key findings for sustainable development in terms of water resource management included, per capita water reduction, water conservation through public awareness campaigns, usage of treated wastewater, adoption of efficient irrigation practices including drip irrigation, cultivation of low33 water consuming crops in water-stressed regions, and regulations to control groundwater over34 exploitation. In future work, developing a hybrid SDM-Optimization framework is suggested to simulate and optimize the dynamic socio-economic interactions and help policymakers devise strategic water planning and management policies that ensure sustainable development

Sustainable Water Use in Arid Agricultural Areas Based on System Dynamics and Water Footprint: a Case Study of Zhangjiakou City, China

The water resource is an indispensable natural capital for human production and life. On the one hand, insufficient water resources and uneven temporal and spatial distribution in arid agricultural areas are the objective reasons for restricting social and economic development and fragile ecological environment. On the other hand, socio-economic development occupies a large amount of ecological water, especially the unscientific planning and unreasonable expansion of irrigated agriculture, which makes a large amount of water wasted. Therefore, in this study, Zhangjiakou, China, a city with less than 400 m3 of water per capita per year, was taken as a case study area to explore the sustainable use of water in arid agricultural areas from the perspective of blue water (surface water and groundwater) and green water (soil water). First, a complex system dynamics model, reflecting the relationships between the water resources subsystem and other socioeconomic subsystems in Zhangjiakou City, was established using Vensim PLE to simulate water demand (2015-2035) in four designed alternative development scenarios: the Current Development Scenario (CDS), the Economic Priority Scenario (EPS), the Water-saving Priority Scenario (WPS), and the Balanced Development Scenarios (BDS). Secondly, with the help of CropWat 8.0, the water footprint and its spatiotemporal characteristics and variations of the main crops in Zhangjiakou City for 2005, 2010, and 2015 were estimated. Furthermore, an in-depth analysis of blue water, green water, and food productivity and economic benefits of water footprint was further investigated by introducing three new indicators, i.e., green water footprint occupancy rate, blue water footprint deficit, and virtual water consumption per GDP. Finally, from the perspective of the ecological zone, the spatiotemporal matching characteristics of agricultural water footprint and socioeconomic factors were analyzed using the Gini coefficient and imbalance index. The main findings are as follows: The variables related to irrigation farmland are the main driving factors of water demand, especially the area and the average water consumption of irrigated land. Therefore, reducing the area of irrigated farmland and improving the efficiency of agricultural irrigation water will be the main direction of water-saving in Zhangjiakou City. But it is vital to consider various factors, e.g., agricultural GDP and farmers’ income, to determine the degree of reduction of irrigation area. Besides, in the four development scenarios, regardless of which development model is chosen, the water demand per ten thousand yuan GDP will eventually fall to around 20 m3 in 2035. Therefore, reducing water demand only by slowing down economic growth cannot improve the efficiency of water use, and even result in inefficiency of water supply capacity. Zhangjiakou City should adopt a dynamic and efficient water-saving model that not only sustains regional socio-economic development but also protects ecological security in the whole Beijing-Tianjin-Hebei region. The total water footprint requirement of Zhangjiakou City increased from 1.671 billion m3 in 2005 to 1.852 billion m3 in 2015, of which the ratio of green water to blue water was around two. The total water footprint requirement in the counties of the mountainous Bashang area is lower than those of the Baxia area, and the gap between them was further expanding. The green water footprint occupancy rate in counties of the Bashang area was 43%-49%, with an average of 44%, while it was 51%-59% in counties of the Baxia area, with an average of 54%. The highest green water footprint occupancy rate in a year was from May to August, at 58%-83%. In terms of blue water footprint deficit, in general, it was lower in the Bashang area than in the Baxia area. The changing trends in food production and economic benefits of water footprint were not always the same. Therefore, it is necessary to consider them simultaneously when developing policies from the perspective of water footprint. The agricultural water footprint of Zhangjiakou City increased from 3.61billion m3 in 2005 to 5.30 billion m3 in 2015, an increase of 1.69 billion m3, of which the water footprint of animal products increased by 1.59 billion m3. Therefore, in addition to continuing to optimize the planting structure, implement efficient water-saving irrigation measures, and control the water footprint of crops, the government needs to strictly prohibit overload grazing and develop modern animal husbandry to reduce the water footprint of animal products, especially in counties of high-altitude ecological zones I, II and IV. The Gini coefficient and the imbalance index of agricultural water footprint and socioeconomic factors indicate that the spatial distribution of agricultural water footprint and planting area, population, agricultural GDP was relatively balanced, but there were still some significant differences. It means that the adjustment of the agricultural structure in each county requires a comprehensive consideration of multiple socioeconomic factors

Assessing the Tradeoffs of Water Allocation: Design and Application of an Integrated Water Resources Model

The Bow River Basin in Southern Alberta is a semi-arid catchment, with surface water provided from the Rocky Mountains. Water resources in this basin, primarily surface water, are allocated to a variety of users- industry, municipalities, agriculture, energy and needs for the environment. The largest consumptive use is by agriculture (80%), and several large dams at the headwaters provide for over 800,000 MWhrs of hydropower. This water is managed by the 1990 Water Act, distributing water via licenses following the “first in time first in right” principle. Currently, the basin is over-allocated, and closed to any new licenses. Conflicts between different water users have consequences for the economy and the environment. By using an integrated water resources model, these conflicts can be further examined and solutions can be investigated and proposed. In this research an integrated water resources model, referred to as Sustainability-oriented Water Allocation Management and Planning Model applied to the Bow Basin (SWAMPB), is developed to emulate Alberta’s Water Resources Management Model (WRMM). While having the same allocation structure as WRMM, SWAMPB instead provides a simulation environment, linking allocation with dynamic irrigation and economic sub-models. SWAMPB is part of a much larger framework, SWAMP, to simulate the water resources systems for the entire South Saskatchewan River Basin (SSRB). SWAMPB integrates economics with a water resources allocation model as well as an irrigation model- all developed using the system dynamics approach. Water is allocated following the allocation structure provided in WRMM, through operation rules of reservoirs and diversions to water users. The irrigation component calculates the water balance of farms, determining the crop water demand and crop yields. An economic valuation is provided for both crops and hydropower generation through the economic component. The structure of SWAMPB is verified through several phases. First, the operation of reservoirs with fixed (known) inflows, and modeled releases, are compared against WRMM for a historical simulation period (1928-2001). Further verifications compare the operation of SWAMPB as a whole without any fixed flows but fixed demands to identify errors in the system water allocation. A final verification then compares both models against historical flows and reservoir levels to assess the validity of each model. SWAMPB, although found to have some minor differences in model structure due to the system dynamics modeling environment, is to be evaluated as an acceptable emulator. SWAMPB is applied to assess a variety of management and policy solutions to mitigating environmental flow deficit. Solutions include increasing irrigation efficiency (S1), requiring more summer release from hydropower reservoirs at the headwaters (S2), a combination of the previous two (S3), implementing the In-Stream Flow Needs (S4) and implementing Water Conservation Objectives (S5). The solutions are not only examined by their ability to restore river flows, but also with respect to the economic consequences and effect on hydropower, irrigation, and municipalities. It is found that the three technical solutions (S1, S2, and S3) provide economic gains and allow more efficient water use, but do little to restore streamflows. Conversely, the two policy solutions (S4 and S5) are more effective at restoring river flow, but have severe consequences on the economy and water availability for irrigation and municipal uses. This analysis does not recommend a particular solution, but provides a quantification of the tradeoffs that can be used by stakeholders to make decisions. Further work on the SWAMP methodology is foreseen, to link SWAMPB with other models, enabling a comprehensive analysis across the entire SSRB

A System Dynamics Model for Risk Assessment of Strategic Customer Performance Perspective in Power Plants

YesThe energy sector is a dynamic business environment, power plants have to deal with several complex risks, including both technical and non-technical risks. Thus, unexpected risks can disrupt the energy generation processes, with a negative long-term impact. Furthermore, these risks are not isolated, as their impact may affect a series of interrelated risks. To add to this complexity, the assessment of those risks may change with time in a dynamic business environment. This situation makes strategic decision making less effective regarding the successful design of a risk management system. Understanding the dynamic behaviour of a complex system of interrelated risks in the energy sector is very important to achieve a more sustainable overall performance of the power plants. This paper presents a System Dynamics (SD) approach to capture the interdependencies of strategic non-technical risks associated to the customer performance perspective in a risk management system for the energy sector. Several approaches for risk assessment focus on technical risks related to equipment but fail to consider the complex interactions with other risks and neither consider the dynamic nature of the business environment. A system dynamics model with 15 risk factors was built to assist decision makers in understanding the behaviour for such risks affecting the customer performance perspective. The model was validated in a power plant in the Middle East. The model allowed to highlight the impact of mitigating the risk of policy and regulations on the availability risk of the power plant and on the risk factor related to operational and maintenance cost

A system dynamics simulation model for environmental risk assessment at strategic level in power plants

YesIn a constantly changing business environment, a systematic approach is needed for risk assessment in order to allow for a more long-term strategic view. The System Dynamics (SD) modelling technique can be applied as an effective approach to understand the dynamic behaviour of a system over time. This understanding can be subsequently explicitly reflected on policies, strategic plans and operational procedures. This paper presents a SD model to assess environmental risks in power plants. The model helps to understand the long-term behaviour of the system under study. A questionnaire and focus group interviews have been conducted to understand the relationship among various risks. The SD model has been validated with two power plants in the Middle East. The developed model highlighted the impact of environmental risks on the performance of power plants. Although the SD model focuses on risk assessment in power plants, it can be easily adapted to other industry sectors

Uncertainty Modeling in The Assessment of Climate Change Impacts on Water Resources Management

Climate change has significant impacts on water resource systems. The objective of this study is to assess climate change impacts on water resource management. The methodology includes (a) the assessment of uncertainty introduced by choice of precipitation downscaling methods; (b) uncertainty assessment and quantification of the impact of climate change on projected streamflow; and (c) uncertainty in and impact of climate change on the management of reservoirs used for hydropower production. The assessment is conducted for two future time periods (2036 to 2065 and 2066 to 2095). The study area, Campbell River basin, British Columbia, Canada, consists of three reservoirs (Strathcona, Ladore and John Hart). A new multisite statistical downscaling method based on beta regression (BR) is developed for generating synthetic precipitation series, which can preserve temporal and spatial dependence along with other historical statistics (e.g. mean, standard deviation). To account for different uncertainty sources, four global climate models (GCMs), three greenhouse gas emission scenarios (RCPs), six downscaling models (DSMs), are considered, and the differences in projected variables of interest are analyzed. For streamflow generation a hydrologic model is used. The results show that the downscaling models contribute the highest amount of uncertainty to future streamflow predictions when compared to the contributions by GCMs or RCPs. It is also observed that the summer (June, July & August) and fall (September, October & December) flows into Strathcona dam (British Columbia) will decrease, while winter (December, January & February) flows will increase in both future time periods. In addition, the flow magnitude becomes more uncertain for higher return period flooding events in the Campbell River system under climate change than the low return period flooding events. To assess the climate change impacts on reservoir operation, in this study a system dynamics model is used for reservoir flow simulation. Results from system dynamics model show that as the inflow decreases in summer and fall, it also affects reservoir release and power production. It is projected that power production from downstream reservoirs (LDR & JHT) will decrease more drastically than the upstream reservoir (SCA) in both future time periods considered in this study

Land Use Conflict Detection and Multi-Objective Optimization Based on the Productivity, Sustainability, and Livability Perspective

Land use affects many aspects of regional sustainable development, so insight into its influence is of great importance for the optimization of national space. The book mainly focuses on functional classification, spatial conflict detection, and spatial development pattern optimization based on productivity, sustainability, and livability perspectives, presenting a relevant opportunity for all scholars to share their knowledge from the multidisciplinary community across the world that includes landscape ecologists, social scientists, and geographers. The book is systematically organized into the optimization theory, methods, and practices for PLES (production–living–ecological space) around territorial spatial planning, with the overall planning of PLES as the goal and the promotion of ecological civilization construction as the starting point. Through this, the competition and synergistic interactions and positive feedback mechanisms between population, resources, ecology, environment, and economic and social development in the PLES system were revealed, and the nonlinear dynamic effects among subsystems and elements in the system identified. In addition, a series of optimization approaches for PLES is proposed

Spatio-temporal evolution and driving factors of regulating ecosystem service value: a case study of Poyang Lake Area, China

Clarifying the driving mechanisms of spatial and temporal changes in the regulating ecosystem service value (RESV) is an important part of realizing the goal of sustainable development. Existing studies have focused on specific factors, ignoring the complex interactions between factors and their regional differences. In this regard, the spatial and temporal changes of RESV and its driving mechanisms in the different zones (core area, fringe area, and peripheral area) were explored in the Poyang Lake Area, China. The results showed that RESV spatially showed the distribution characteristics of fringe area > core area > peripheral area, while the lakes influenced the provision of regulating ecosystem services, showing that RESV per unit area was higher in the core area, and gradually declined with the increase of distance from the lakes, presenting the decreasing trend of fringe area > peripheral area. From 2000 to 2020, the study area lost 70.5988 billion CNY for RESV, in which the core area was the most affected. Further analysis of the driving mechanism of RESV in different areas found that there are regional differences in the paths of the driving factors: Population density mainly affects the core area, precipitation mainly affects the fringe area, and GDP per land mainly affects the peripheral area

A Systems Approach for River and River Basin Restoration

Communities increasingly find that the water quality, water levels, or some other resource indicator in their river basins do not meet their expectations. This discrepancy between the desired and actual state of the resource leads to efforts in river basin restoration. River basins are complex systems, and too often, restoration efforts are ineffective due to a lack of understanding of the purpose of the system, defined by the system structure and function. The river basin structure includes stocks (e.g., water level or quality), inflows (e.g., precipitation or fertilization), outflows (e.g., evaporation or runoff), and positive and negative feedback loops with delays in responsiveness, all of which function to change or stabilize the state of the system (e.g., the stock of interest, such as water level or quality). External drivers on this structure, together with goals and rules, contribute to how a river basin functions. This book reviews several new research projects to identify and rank the twelve most effective leverage points to address discrepancies between the desired and actual state of the river basin system. This book demonstrates that river basin restoration is most likely to succeed when we change paradigms rather than try to change the system elements, as the paradigm will establish the system goals, structure, rules, delays, and parameters