Water Resources Systems Analysis Research Articles

Evolutionary Trends and Coordinated Development Analysis of Water Resources Systems and High-Quality Economic Growth in the Yangtze River Delta

This article calculates the indices for high-quality economic development and water resource systems across 25 cities in the Yangtze River Delta from 2011 to 2021. Utilizing a multifaceted analytical framework comprising the CRITIC method, standard deviation ellipse, harmonious development coefficient, and coupling coordination coefficient, we investigate spatiotemporal evolutionary trends and overarching harmonious development states between the two systems. Results indicate: (1) Throughout the research period, mean values of high-quality economic development indices fluctuated within the range of 0.05 to 0.68, while water resource carrying capacity indices oscillated between 0.18 and 0.81. (2) The epicenter of high-quality economic development indices is situated in the periphery of Lake Tai, whereas the fulcrum of the water resource system indices is located in Huzhou City, both displaying a northwest-southeast orientation. (3) Coupling coordination development exhibits a propitious advancement trajectory, with certain locales attaining exemplary coordinated growth.

Guiding Questions for Water Resources Systems Analysis Research

Guiding Questions for Water Resources Systems Analysis Research

A Framework of Dependence Modeling and Evaluation System for Compound Flood Events

AbstractThe coincidence and superposition of flood processes from different rivers and regions tend to form compound flood events, determined by spatial relationship between diverse flood processes that cannot be accurately depicted and evaluated by existing dependence analysis methods. A framework, integrating multi‐dimensional vine copula model and dependence evaluation system, was developed with a testing‐oriented application to explore underlying dependence between two kinds of extreme runoff series (peak discharge and flood volume) extracted from the identified compound flood events in the upper reaches of the Yangtze River. Multi‐dimensional regular vine (R‐vine) copula models were established to depict the complex and diverse dependence, and corresponding vine structure was specified by the vine structure array that can reflect the sequence of tributaries flowing into the main stream and the spatial locations of different hydrometric stations. Dependence magnitude and association status were calculated and compared according to the optimal R‐vine copula models and information theory. Comparison with existing methods demonstrated that dependence evaluation system could reflect nonlinear and local dependence characteristics and eliminate the effect of extreme runoff series from other hydrometric station on the dependence. The association status between different extreme runoff series of the upper Yangtze River and its tributaries were diverse in view of the impact of tributary flood inflow. The proposed framework can be regarded as an effective way for dependence modeling and evaluation of compound floods, thus providing a scientific reference for the risk analysis of water resources systems.

Optimization of Pollutant Discharge Permits, Using the Trading Ratio System: A Case Study

Water quality management of rivers is one of the challenges in the analysis of water resource systems. The optimal operation of the pollutant carrying capacity of these systems provides significant economic value and could reduce treatment costs. In this study, the application of the trading ratio system is investigated to control the cost of pollutants in a river and make a fair deal. In this regard, transfer coefficients between pollution sources, along with the trade coefficients, are determined, considering the system limitations and each pollutant’s contaminant impact. To provide allowable limits of river water quality concentrations, the total cost of all sources and the system is minimized, using the linear programming method. Finally, the new trading discharge permits are calculated for each source. The proposed method is successfully applied to Dez River as a case study. Results show that using a trading ratio system could maintain water quality at a standard level containing economic benefits for the participants of this program.

Development of a Parametric Regional Multivariate Statistical Weather Generator for Risk Assessment Studies in Areas with Limited Data Availability

Risk analysis of water resources systems can use statistical weather generators coupled with hydrologic models to examine scenarios of extreme events caused by climate change. These require multivariate, multi-site models that mimic the spatial, temporal, and cross correlations of observed data. This study developed a statistical weather generator to facilitate bottom-up approaches to assess the impact of climate change on water resources systems for cases of limited data. While existing weather generator models have impressive features, this study suggested a simple weather generator which is straightforward to implement and can employ any distribution function for variables such as precipitation or temperature. It is based on (1) a first-order, two-state Markov chain to simulate precipitation occurrences; (2) the use of Wilks’ technique to produce correlated weather variables at multiple sites with the conservation of spatial, temporal, and cross correlations; (3) the capability to vary the statistical parameters of the weather variables. The model was applied to studies of the Diyala River basin in Iraq, which is a case with limited observed records. Results show that it exhibits high values (e.g., over 0.95) for the Nash–Sutcliffe and Kling–Gupta metric tests, preserves the statistical properties of the observed variables, and conserves the spatial, temporal, and cross correlations among the weather variables in the meteorological stations.

Water Resource Systems Analysis for Water Scarcity Management: The Thames Water Case Study

Optimisation tools are a practical solution to problems involving the complex and interdependent constituents of water resource systems and offer the opportunity to engage with practitioners as an integral part of the optimisation process. A multiobjective genetic algorithm is employed in conjunction with a detailed water resource model to optimise the “Lower Thames Control Diagram”, a set of control curves subject to a large number of constraints. The Diagram is used to regulate abstraction of water for the public drinking water supply for London, UK, and to maintain downstream environmental and navigational flows. The optimisation is undertaken with the aim of increasing the amount of water that can be supplied (deployable output) through solely operational changes. A significant improvement of 33 Ml/day (1% or £59.4 million of equivalent investment in alternative resources) of deployable output was achieved through the optimisation, improving the performance of the system whilst maintaining the level of service constraints without negatively impacting on the amount of water released downstream. A further 0.2% (£11.9 million equivalent) was found to be realisable through an additional low-cost intervention. A more realistic comparison of solutions indicated even larger savings for the utility, as the baseline solution did not satisfy the basic problem constraints. The optimised configuration of the Lower Thames Control Diagram was adopted by the water utility and the environmental regulators and is currently in use.

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.

State-of-art of genetic programming applications in water-resources systems analysis.

Evolutionary algorithms (EAs) have become competitive solvers of a wide variety of water-resources optimization problems. Genetic programming (GP) has become a leading EA since its inception in 1985. This paper reviews the state-of-the-art of GP and its applications in water-resources systems analysis. A comprehensive knowledge about GP's theory and modeling approach is essential for its successful application in water-resources systems analysis. This review presents variants of GP that have been proven useful in various applications to water resources problems. Several examples of applications of GP in water-resources systems analysis are herein presented. This review reveals GP's capability and superiority compared to other conventional methods, which makes it suitable for solving a wide variety of water-related problems including rainfall-runoff modeling, streamflow sediment prediction, flood prediction and routing, evaporation and evapotranspiration forecasting, reservoir operation, groundwater modeling, water quality modeling, water demand forecasting, and water distribution systems.

Copula-based method for stochastic daily streamflow simulation considering lag-2 autocorrelation

Daily stochastic streamflow simulation is widely used for the design of reservoirs, evaluation of reservoir operation rules, and risk evaluation of operation of water resources systems. The major difficulties and challenges of daily streamflow are that there are 365 days that need to be simulated, which entails much more calculation than does monthly streamflow simulation. Since lag-2 auto-correlation is usually large, the lag-2 correlations should be considered. This paper therefore proposes a copula-based method for daily stochastic streamflow simulation. The contribution and novelty of this paper are that: (a) the proposed method can consider lag-2 correlations, compared with the currently used copula based method; (b) the conditional copulas are used to build high dimensional copulas, which make calculations easier; and (c) the method can be used for daily streamflow simulation because of the simplified model structure and effective parameter estimation method. Seven gauging stations on the upper Yangtze River and Pearl River in China were selected as case studies. Results demonstrated that the proposed method preserved the basic statistics (including mean daily flow, standard deviation, and coefficient of skewness) of observed data of each day well. Comparison with the currently used seasonal autoregressive model (SAR(2)) and bivariate copula-based method considering lag-1 autocorrelation indicated that the proposed method produced smaller relative errors and was better overall. Therefore, the proposed method can be regarded as an effective way for stochastic daily streamflow simulation, and can be used for the design of reservoirs and risk analysis of water resources systems.

Defining the Role of Water Resources Systems Analysis in a Changing Future

Defining the Role of Water Resources Systems Analysis in a Changing Future

Real-time reservoir operation using data mining techniques.

The optimal operation of hydropower reservoirs is essential for the planning and efficient management of water resources and the production of hydroelectric energy. Various techniques such as the genetic algorithm (GA), artificial neural networks (ANN), support vector machine (SVM), and dynamic programming (DP) have been employed to calculate reservoir operation rules. This paper implements the data mining techniques SVM and ANN to calculate the optimal release rule of hydropower reservoirs under "forecasting" and "non-forecasting" scenarios. The employment of data mining techniques accounting for data uncertainty to calculate optimal hydropower reservoir operation is novel in the field of water resource systems analysis. The optimal operation of the Karoon 3 reservoir, Iran, serves as a test of the proposed methodology. The upstream streamflow, storage records, and several lagged variables are model inputs. Data obtained from solving the reservoir optimization problem with nonlinear programming (NLP) are applied to train (calibrate) the SVM, and ANN, SVM, and ANN are executed in the "non-forecasting" scenario based on all inputs along with their time-lagged variables. In contrast, current parameters are removed from the set of inputs in the "forecasting" scenario. The results of the SVM model are compared with those of the ANN model with the correlation coefficient (R), the mean error (ME), and the root mean square error (RMSE). This paper's results indicate performance of the SVM is better than that of the ANN model by 1.5%, 400%, and 10% with respect to the R, ME, and RMSE diagnostic statistics, respectively. In addition, SVM and ANN overcome data uncertainty ("forecasting" scenario) to produce optimal reservoir operation.

Seasonal Hydrological and Meteorological Time Series

Time series models are often used in hydrology and meteorology studies to model streamflows series in order to make forecasting and generate synthetic series which are inputs for the analysis of complex water resources systems. In thispaper we introduce a new modeling approach for hydrologic and meteorological time series assuming a continuous distribution for the data, where both the conditional mean and conditional varianceparameters are modeled. Bayesian methods using standard MCMC (Markov Chain Monte Carlo Methods) are used to simulate samples for the joint posterior distribution of interest. Two applications to real data sets illustrate the proposedmethodology, assuming that the observations come from a normal, a gamma or a beta distribution. A first example is given by a time series of monthly averages of natural streamflows, measured in the year period ranging from1931 to 2010 in Furnas hydroelectric dam, Brazil. A second example is given with a time series of 313 air humidity data measured in a weather station of Rio Claro, a Brazilian city located in southeastern of Brazil. These applications motivate us to introduce new classes of models to analyze hydrological and meteorological time series

More Integrated Formal Education and Practice in Water Resources Systems Analysis

More Integrated Formal Education and Practice in Water Resources Systems Analysis

Developed Swarm Optimizer: A New Method for Sizing Optimization of Water Distribution Systems

AbstractThe introduction of metaheuristic algorithms in water resources engineering has greatly raised the need for continued development of appropriate optimization methodologies for analysis, planning, design, and operation of water resources systems. This paper proposes a novel developed swarm-based optimization algorithm named DSO, which integrates the accelerated particle swarm optimization (PSO) with the big bang-big crunch algorithm (BB-BC) to optimize the design of water distribution systems (WDSs). Traditional PSO is easy to fall into stagnation when no particle explores a position that is better than its previous best position for several iterations. To deal with the problem of maintaining diversity within the swarm and to enhance the exploration in the search, the concepts of the Big Crunch and Big Bang strategies from the BB-BC algorithm are incorporated into the global and local searching steps of the accelerated PSO, respectively. In addition, a harmony search–based strategy is used to contr...

Managing Water Resources Conflicts: Modelling Behavior in a Decision Tool

While technical tools for analysis of water resources systems have advanced, the major issue in resolving problems focuses on the interaction of human and natural systems. Agent-based modeling (ABM) has recently been used as an effective tool to develop integrated human-environmental models. One of the main challenges of ABM application in water resources management is to identify and characterize key agents. We provided recommendations to characterize agents normally involved in water decisions, and developed a framework for a conflict management tool, comprised of three models: a watershed simulation, an optimization, and a behavioral simulation model. The optimization-simulation model determined tradeoffs between the objective functions. The behavioral simulation model, developed based on ABM, simulated stakeholders interactions and their reactions to water allocation decisions. This model evaluated the applicability of different management scenarios to achieve specific rates of reduction in agricultural water allocations, selected from the tradeoffs. To develop and adjust this model, key stakeholders were identified in the San Joaquin River (SJR) watershed, California, and a survey was administered. The proposed recommendations and framework provides a new and innovative way to identify institutional interconnections, formulate and simulate their interactions, and create a hydrologic-environmental-human interface to support powerful decision-support tools to manage conflicts and make informed, practical decisions in water resources.

The future of water resources systems analysis: Toward a scientific framework for sustainable water management

AbstractThis paper presents a short history of water resources systems analysis from its beginnings in the Harvard Water Program, through its continuing evolution toward a general field of water resources systems science. Current systems analysis practice is widespread and addresses the most challenging water issues of our times, including water scarcity and drought, climate change, providing water for food and energy production, decision making amid competing objectives, and bringing economic incentives to bear on water use. The emergence of public recognition and concern for the state of water resources provides an opportune moment for the field to reorient to meet the complex, interdependent, interdisciplinary, and global nature of today's water challenges. At present, water resources systems analysis is limited by low scientific and academic visibility relative to its influence in practice and bridled by localized findings that are difficult to generalize. The evident success of water resource systems analysis in practice (which is set out in this paper) needs in future to be strengthened by substantiating the field as the science of water resources that seeks to predict the water resources variables and outcomes that are important to governments, industries, and the public the world over. Doing so promotes the scientific credibility of the field, provides understanding of the state of water resources and furnishes the basis for predicting the impacts of our water choices.

Network Analysis and Visualizations of Water Resources Infrastructure in California: Linking Connectivity and Resilience

AbstractConnectivity is important to the structure and function of systems. In water infrastructure systems, connections between components determine flow patterns and operational flexibility. Network theory can provide tools to assess and view connectivity in water resource networks that augment current methods in water resource systems analysis. This paper presents an analysis of connectivity and resilience in the network of California’s water resources infrastructure using network theory visualization and metrics. Applying these techniques to a link-node network used in a statewide hydroeconomic model of water management in California, the analysis shows how such metrics are useful to describe aspects of connectivity and identify important system components. Both the entire system and the San Francisco Bay Area subsystem are analyzed using measures of centrality, spacing, and linkage. The analysis also assesses the effects of network degradation by removing selected components, revealing complex relati...

Network structure, complexity, and adaptation in water resource systems

Infrastructure systems are often complex. Many have both natural and built components. For such systems, including water resource networks, resilience is a common policy goal. In the formalised study of complex systems, the structure and function of networks can contribute directly to system resilience. One branch of complex systems studies, network science, describes how connectivity between individual components can explain some system-wide properties of growth and reliability. Water resource systems analysis has only begun to apply techniques from network theory and complexity science to assess adaptability and resilience. We present an analysis of connectivity in a network model of California's water infrastructure system using several network science techniques. Results indicate that nodes in California's water system are clustered but without scale-free properties. The network originates from a mixture of top-down (centralised) and bottom-up (dispersed interactions of parties) planning. This structure provides managers greater flexibility to use local and distant water sources. We use the analysis to illustrate how several disciplinary notions of resilience apply to civil infrastructure planning. We also explore how adaptability, not just complexity, influences resilience in planning. Creating systems that can respond to future changes must be an important policy goal in planning civil infrastructure.

Spatiotemporal variation of long‐term drought propensity through reliability‐resilience‐vulnerability based Drought Management Index

AbstractThis paper characterizes the long‐term, spatiotemporal variation of drought propensity through a newly proposed, namely Drought Management Index (DMI), and explores its predictability in order to assess the future drought propensity and adapt drought management policies for a location. The DMI was developed using the reliability‐resilience‐vulnerability (RRV) rationale commonly used in water resources systems analysis, under the assumption that depletion of soil moisture across a vertical soil column is equivalent to the operation of a water supply reservoir, and that drought should be managed not simply using a measure of system reliability, but should also take into account the readiness of the system to bounce back from drought to a normal state. Considering India as a test bed, 5 year long monthly gridded (0.5° Lat × 0.5° Lon) soil moisture data are used to compute the RRV at each grid location falling within the study domain. The Permanent Wilting Point (PWP) is used as the threshold, indicative of transition into water stress. The association between resilience and vulnerability is then characterized through their joint probability distribution ascertained using Plackett copula models for four broad soil types across India. The joint cumulative distribution functions (CDF) of resilience and vulnerability form the basis for estimating the DMI as a five‐yearly time series at each grid location assessed. The status of DMI over the past 50 years indicate that drought propensity is consistently low toward northern and north eastern parts of India but higher in the western part of peninsular India. Based on the observed past behavior of DMI series on a climatological time scale, a DMI prediction model comprising deterministic and stochastic components is developed. The predictability of DMI for a lead time of 5 years is found to vary across India, with a Pearson correlation coefficient between observed and predicted DMI above 0.6 over most of the study area, indicating a reasonably good potential for drought management in the medium term water resources planning horizon.

Analysis of projected water availability with current basin management plan, Pajaro Valley, California

Summary The projection and analysis of the Pajaro Valley Hydrologic Model (PVHM) 34 years into the future using MODFLOW with the Farm Process (MF-FMP) facilitates assessment of potential future water availability. The projection is facilitated by the integrated hydrologic model, MF-FMP that fully couples the simulation of the use and movement of water from precipitation, streamflow, runoff, groundwater flow, and consumption by natural and agricultural vegetation throughout the hydrologic system at all times. MF-FMP allows for more complete analysis of conjunctive-use water-resource systems than previously possible with MODFLOW by combining relevant aspects of the landscape with the groundwater and surface-water components. This analysis is accomplished using distributed cell-by-cell supply-constrained and demand-driven components across the landscape within “water-balance subregions” (WBS) comprised of one or more model cells that can represent a single farm, a group of farms, watersheds, or other hydrologic or geopolitical entities. Analysis of conjunctive use would be difficult without embedding the fully coupled supply-and-demand into a fully coupled simulation, and are difficult to estimate a priori. The analysis of projected supply and demand for the Pajaro Valley indicate that the current water supply facilities constructed to provide alternative local sources of supplemental water to replace coastal groundwater pumpage, but may not completely eliminate additional overdraft. The simulation of the coastal distribution system (CDS) replicates: 20 miles of conveyance pipeline, managed aquifer recharge and recovery (MARR) system that captures local runoff, and recycled-water treatment facility (RWF) from urban wastewater, along with the use of other blend water supplies, provide partial relief and substitution for coastal pumpage (aka in-lieu recharge). The effects of these Basin Management Plan (BMP) projects were analyzed subject to historical climate variations and assumptions of 2009 urban water demand and land use. Water supplied directly from precipitation, and indirectly from reuse, captured local runoff, and groundwater is necessary but inadequate to satisfy agricultural demand without coastal and regional storage depletion that facilitates seawater intrusion. These facilities reduce potential seawater intrusion by about 45% with groundwater levels in the four regions served by the CDS projected to recover to levels a few feet above sea level. The projected recoveries are not high enough to prevent additional seawater intrusion during dry-year periods or in the deeper aquifers where pumpage is greater. While these facilities could reduce coastal pumpage by about 55% of the historical 2000–2009 pumpage for these regions, and some of the water is delivered in excess of demand, other coastal regions continue to create demands on coastal pumpage that will need to be replaced to reduce seawater intrusion. In addition, inland urban and agricultural demands continue to sustain water levels below sea level causing regional landward gradients that also drive seawater intrusion. Seawater intrusion is reduced by about 45% but it supplies about 55% of the recovery of groundwater levels in the coastal regions served by the CDS. If economically feasible, water from summer agricultural runoff and tile-drain returnflows could be another potential local source of water that, if captured and reused, could offset the imbalance between supply and demand as well as reducing discharge of agricultural runoff into the National Marine Sanctuary of Monterey Bay. A BMP update (2012) identifies projects and programs that will fund a conservation program and will provide additional, alternative water sources to reduce or replace coastal and inland pumpage, and to replenish the aquifers with managed aquifer recharge in an inland portion of the Pajaro Valley.