Complex Water Resources Systems Research Articles

Process-based three-layer synergistic optimal-allocation model for complex water resource systems considering reclaimed water

Abstract. The increasing water demand due to human activities has aggravated water scarcity, and conflicts among stakeholders have increased the risk of unsustainable development. Ignoring the effects of trade-offs leads to misguided policy recommendations. This study highlights the concept of synergy among different aspects of the water allocation process. A process-based three-layer synergistic optimal-allocation (PTSOA) model is established to integrate the interests of stakeholders across sub-regions, decision levels, and time steps while simultaneously coupling reclaimed water to establish environmentally friendly solutions. A synergy degree index is constructed by applying network analysis for optimization. PTSOA is applied in Yiwu, southeast China, and is shown to be able to improve the contradictions among different dimensionalities in a complex system. Overall, 2.43×107–3.95×107 m3 of conventional water is saved, and notable improvements in management are achieved. The application demonstrates the efficiency and excellent performance of the PTSOA model.

An applied study of a technique incorporating machine learning algorithms to optimize water demand prediction

Abstract In water resource management, accurate water demand prediction is essential for developing effective water supply strategies and optimizing resource allocation. This study aims to investigate machine learning algorithms, particularly echo state network (ESN) models, to improve the accuracy and efficiency of water demand prediction. ESN models are selected for their excellent nonlinear time series processing capabilities, which address the challenges of traditional prediction methods when dealing with complex water resource systems. By optimizing the parameters of the ESN model, the study hopes to provide a more scientific and efficient method for residential domestic and agricultural water demand forecasting, thus supporting more refined water resources planning and management decisions. Residential water demand prediction and crop water demand prediction are the two parts of this study. In the prediction of residential water demand, based on the actual data of City Z, the optimized ESN model predicts the water demand in 2025, and the total water demand in the baseline scenario is 790.9 million m3, and the expected values of water demand in different scenarios combined with the economic growth rate and the change of water price range from 659.4708 million m3 to 730.448 million m3. The article’s accuracy analysis of crop water demand prediction indicates that the model’s relative errors in predicting the water demand of the three major crops are limited to 10%. The ESN model optimized using the machine learning algorithm in this paper has good potential for water demand prediction and is an efficient and accurate prediction tool for managing water resources.

The role of network structure in integrated water management: a case study of collaboration and influence for adopting nature-based solutions

IntroductionIntegrated water management (IWM) involves a range of policies, actions, and organizational processes that go beyond traditional hydrology to consider multifaceted aspects of complex water resource systems. Due to its transdisciplinary nature, IWM comprises input from diverse stakeholders, each with unique perceptions, values, and experiences. However, stakeholders from differing backgrounds may disagree on best practices and collective paths forward. As such, successful IWM must address key governance principles (e.g., information flow, collective decision-making, and power relations) across social and institutional scales. Here, we sought to demonstrate how network structure impacts shared decision-making within IWM.MethodsWe explored a case study in Houston, Texas, USA, where decision-making stakeholders from various sectors and levels of governance engaged in a participatory modeling workshop to improve adoption of nature-based solutions (NBS) through IWM. The stakeholders used fuzzy cognitive mapping (FCM) to define an IWM model comprising multifaceted elements and their interrelationships, which influenced the adoption of NBS in Houston. We applied grounded theory and inductive reasoning to categorize tacit belief schemas regarding how stakeholders viewed themselves within the management system. We then used FCM-based modeling to explore how unique NBS policies would translate into more (or less) NBS adoption. Finally, we calculated specific network metrics (e.g., density, hierarchy, and centrality indices) to better understand the structure of human-water relations embedded within the IWM model. We compared the tacit assumptions about stakeholder roles in IWM against the quantitative degrees of influence and collectivism embedded within the stakeholder-defined model.Results and discussionOur findings revealed a mismatch between stakeholders' external belief statements about IWM and their internal assumptions through cognitive mapping and participatory modeling. The case study network was characterized by a limited degree of internal coordination (low density index), high democratic potential (low hierarchy index), and high-efficiency management opportunities (high centrality index), which transcended across socio-institutional scales. These findings contrasted with several of the belief schemas described by stakeholders during the group workshop. We describe how ongoing partnership with the stakeholders resulted in an opportunity for adaptive learning, where the NBS planning paradigm began to shift toward trans-scale collaboration aimed at high-leverage management opportunities. We emphasize how network analytics allowed us to better understand the extent to which key governance principles drove the behavior of the IWM model, which we leveraged to form deeper stakeholder partnerships by identifying hidden opportunities for governance transformation.

How Should Diverse Stakeholder Interests Shape Evaluations of Complex Water Resources Systems Robustness When Confronting Deeply Uncertain Changes?

AbstractRobustness analysis can support the design and operation of large‐scale water infrastructure projects confronting deeply uncertain futures. However, diverse actors, contextual specificities, sectoral interests, and risk attitudes make it difficult to identify an appropriate robustness metric to rank decision alternatives under deep uncertainty. Here, we clarify how methodological choices affect robustness evaluation using the multi‐actor, multi‐sector Inchampalli‐Nagarjuna Sagar water transfer megaproject in Southern India. We compare a suite of water transfer strategies discovered using evolutionary multi‐objective direct policy search (EMODPS), a strategy proposed by regional authorities and the status quo of no water transfer. We stress‐test these strategies across scenarios that capture climatic and socioeconomic uncertainties and rank them using robustness metrics representing sectoral perspectives and priorities of different actors with varying risk attitudes. Results show a considerable impact of metric choices on robustness rankings of strategies, with compromise solution discovered via EMODPS as robust. The no‐transfer strategy results in the worst water supply robustness with an average volumetric deficit of 17% of total historical demands but emerges as a robust alternative for 6 out of 12 combinations of actor‐sectors with high risk aversion. Also, changes in the amplitude of the Indian Summer Monsoon is identified as the most important uncertain factor determining the failure of strategies. Our findings highlight that the selection of robust solutions should be guided by an understanding of how assumed risk attitudes shape stakeholders' perceptions of vulnerabilities. These findings are generalizable to large infrastructure projects with diverse stakeholders and multisectoral impacts.

Navigating Water Sustainability in Mineral Mining with a Systems Thinking-Based Approach

This paper provides a comprehensive review and analysis of the sustainable management of water resources in the mining industry. It presents an overview of various sustainable development frameworks for the mining sector, emphasizing the need for a more comprehensive and integrative approach to managing water resources. The paper also highlights the critical role of water in mining operations and the increasing pressure on water resources due to mining activities. Consequently, it underscores the significance of sustainable water management practices such as stakeholder engagement, catchment-based approaches, and adequate water management strategies. The researcher combined a qualitative approach with a methodology for conducting a literature review. The majority of the articles and other sources used to compile the study's data were books and academic publications that examined relevant subjects (Water sustainability, mineral mining, system thinking-based approach). The study advocates for a shift from traditional mechanistic models and linear thinking to a more holistic systems thinking approach for addressing the complex environmental challenges associated with water resources management in mining. Furthermore, it presents system dynamics modeling as a promising tool for understanding and predicting the behavior of complex water resource systems and devising appropriate strategies for sustainable outcomes. A conceptual framework for sustainable underground mine water management is proposed through a synthesis of previous studies. The framework integrates systems thinking and sustainability principles, paving the way for socially equitable, environmentally sustainable, and economically beneficial water management strategies in the mining industry.

Optimal Implementation of Climate Change Adaptation Measures to Ensure Long-term Sustainability on Large Irrigation Systems

Observed and projected consequences of climate change on streamflow generated in the Pyrenees threatens the long-term sustainability of water resources systems downstream, especially those with high irrigation demands. To tackle this challenge, the participation of stakeholders in defining potential adaptation strategies is crucial to building awareness and capacity for the community, providing agreed solutions, and reducing conflict. However, there is also a need for a top-down approach to incorporate other, large-scale, or innovative adaptation strategies. This article describes a bottom-up-meets-top-down approach to estimate the optimal implementation intensity of adaptation strategies under different climate scenarios on a complex water resources system. Future streamflow projections were used in a water allocation model combined with a Markov Chain Monte Carlo sampling process to obtain optimal combinations of measures to meet different sustainability objectives. The methodology was applied to the Gállego-Cinca River system in NE Spain, which relies on water from the Pyrenees. A stakeholder workshop identified storage development and irrigation modernisation as the preferred adaptation options. However, the modelling results show that more storage in the basin, especially on-farm reservoirs, is not enough to maintain current sustainability levels. This will enable the adoption of demand management measures that optimise water use despite not being among stakeholder preferences.

An information theory-based approach to characterize drivers of upstream salmon migration

The migration timing of Pacific salmon in the Columbia River basin is subject to multiple influences related to climate, human water resource management, and lagged effects such as oceanic conditions. We apply an information theory-based approach to analyze drivers of adult Chinook salmon migration within the spring and fall spawning seasons and between years based on salmon counts at dams along the Columbia and Snake Rivers. Time-lagged mutual information and information decomposition measures, which characterize lagged and nonlinear dependencies as reductions in uncertainty, are used to detect interactions between salmon counts and lagged streamflows, air and water temperatures, precipitation, snowpack, climate indices and downstream salmon counts. At a daily timescale, these interdependencies reflect migration timing and show differences between fall and spring run salmon, while dependencies based on variables at an annual resolution reflect long-term predictability. We also highlight several types of joint dependencies where predictability of salmon counts depends on the knowledge of multiple lagged sources. This study illustrates how co-varying human and natural drivers could propagate to influence salmon migration timing or overall returns, and how nonlinear types of dependencies between variables enhance predictability of a target. This information-based framework is broadly applicable to assess driving factors in other types of complex water resources systems or species life cycles.

Evaluation method of regional water resources carrying capacity based on semipartial connection number and dynamic subtraction set pair potential

为准确和客观地评价区域水资源承载力，从水资源承载力评价样本与评价等级标准这一集对的复杂系统结构角度，应用集对分析半偏联系数和减法集对势方法，构造了定量反映和刻画集对联系数系统结构中联系数分量间微观运动的迁移率矩阵，提出了一种联系数分量值的修正方法，同时基于减法集对势和三角模糊数方法动态确定了差异度系数，构建了区域水资源承载力定量评价方法. 该方法在安徽省淮北市的应用结果表明：2011—2019年水资源承载力介于2~3级之间，承载力较差，系统态势总体上由偏反势向均势过渡，逐渐向好发展；在判别系统态势发展方面，基于普通减法集对势的联系数值由2011年的-0.279变化到2018年的-0.037，再到2019年的-0.218，基于半偏减法集对势的联系数值由2011年的-0.267变化到2018年的-0.035，再到2019年的的-0.207，说明两种方法均适用，但在确定评价等级值方面，评价效果后者更优，相对误差在1 % 以内，这与半偏减法集对势的物理解释意义更为深刻有关. 联系数系统结构中联系数分量间的微观运动结果表明，原联系数中最大分量的值会减小，其他两个分量的变化情况与该分量本身的大小、半偏联系数表示的增量与原联系分量的比例、被迁移的原联系分量的大小有关. 基于半偏联系数和动态减法集对势法可实现联系数的修正更新和差异度系数的动态确定，方法物理解释性强、评价结果准确可靠，为从系统结构成因机理角度准确判别水资源复杂系统所处状态及总体发展趋势提供了新的有效途径.;In order to accurately and objectively evaluate the level of regional water resources carrying capacity (WRCC), from the perspective of WRCC evaluation samples and evaluation level standards, set pair analysis semipartial connection number (SCN) and subtraction set pair potential (SSP) method were applied in this study. A mobility matrix which quantitatively reflects and describes the micro movement between the connection number components (CNCs) in the connection number system structure was constructed, along with a correction method on CNC values. Meanwhile, the difference coefficient was dynamically determined based on SSP and triangular fuzzy number method, and the quantitative evaluation method of regional WRCC was constructed. The application of this method in Huaibei City, Anhui Province showed that WRCC in 2011-2019 was between level 2-3, and the carrying capacity was relatively poor. The overall system situation transited from partial inverse potential to equilibrium potential, and gradually developed for the better. In judging the development of system situation, the connection number value based on SSP changed from -0.279 in 2011 to -0.037 in 2018 and then to -0.218 in 2019, and connection number value based on SSP changed from -0.267 in 2011 to -0.035 in 2018 and then to -0.207 in 2019. Results indicated that both methods were applicable, with the latter one better in determining the evaluation grade value and relative error < 1 %, which was related to the more profound physical interpretation of the semipartial SSP. The micro motion results between the CNCs in the structure of the connection number system showed that the value of the largest component in the original connection coefficient will decrease, and the changes of the other two components are related to the size of the component itself, the proportion of the increment represented by the SCN to the original CNCs, and the size of the migrated original CNCs. Based on the SCN and dynamic SSP method, the correction and updating of connection number and the dynamic determination of difference coefficient can be realized. The method has strong physical interpretation and accurate and reliable evaluation results, which provides a new and effective way to accurately distinguish the state and overall development trend of complex water resources system from the perspective of system structure and genetic mechanism.

Correction to: Analysis of Water Quantity and Quality Trade‑Offs to Inform Selective Harvesting of Inflows in Complex Water Resource Systems

Correction to: Analysis of Water Quantity and Quality Trade‑Offs to Inform Selective Harvesting of Inflows in Complex Water Resource Systems

Improving Indicators of Hydrological Alteration in Regulated and Complex Water Resources Systems: A Case Study in the Duero River Basin

Assessing the health of hydrological systems is vital for the conservation of river ecosystems. The indicators of hydrologic alteration are among the most widely used parameters. They have been traditionally assessed at the scale of river reaches. However, the use of such indicators at the basin scale is relevant for water resource management since there is an urgent need to meet environmental objectives to mitigate the effects of present and future climatic conditions. This work proposes a methodology to estimate the indicators of hydrological alteration at the basin scale in regulated systems based on simulations with a water allocation model. The methodology is illustrated through a case study in the Iberian Peninsula (the Duero River basin), where different minimum flow scenarios were defined, assessing their effects on both the hydrological alteration and the demand guarantees. The results indicate that it is possible to improve the hydrological status of some subsystems of the basin without affecting the water demand supplies. Thus, the methodology presented in this work will help decision makers to optimize water management while improving the hydrological status of the river basins.

Analysis of Water Quantity and Quality Trade-Offs to Inform Selective Harvesting of Inflows in Complex Water Resource Systems

Analysis of Water Quantity and Quality Trade-Offs to Inform Selective Harvesting of Inflows in Complex Water Resource Systems

Comprehensive analysis of water carrying capacity based on wireless sensor network and image texture of feature extraction

This article takes the complex uncertainty in the carrying process of water resources system as the research object. Firstly, the water resources carrying capacity system is divided into three sub-systems: bearing support capacity, bearing pressure and bearing regulation capacity. System analysis methods based on wireless sensor network and image texture of feature extraction for correlation analysis, gray correlation analysis, and multi-dimensional conditional cloud algorithm are introduced into the field of water resources carrying capacity evaluation research. Moreover, combine it with the subtraction set opposition, the effect partial bias connection number, and the risk matrix. Finally, three types of models for water resource carrying capacity evaluation and trend analysis were constructed. The evaluation results of water resources carrying capacity are consistent with the actual process, and the overall development trend is gradually improving. The application results of the evaluation model of water resource carrying capacity are established. The calculation results of the image texture feature of extraction model are similar to the overall change trend of the model before the improvement. The trend of change is more obvious. It can not only describe the water resource carrying level as a whole, but also characterize the reliability of the calculation results and the bearing risk caused by the uncertainty of the water resource carrying system. The water resources carrying capacity evaluation and trend analysis of calculation results are reasonable and feasible. The research results can provide a reasonable and effective decision-making basis for the systematic analysis of the bearing boundary issues between regional complex water resources systems and human water activities, and then propose adaptive risk prevention and control strategies for water resources carrying capacity.

Simulation Of Reservoir Operation In A Multi Reservoir System

The present study aims to apply simulation software MIKE Basin for the operation of reservoirs of Mahanadi Reservoir Project (MRP) Complex. MRP complex is a multipurpose multi reservoir system. Simulation is a technique by which we emulate the behavior of a system. Simulation is a very powerful technique in analyzing most complex water resource system in detail for performance evaluation. Reservoir operation study has been done for data of 34 years. The results extracted from the study indicated that the performance of simulation model MIKE Basin is satisfactory.

Dynamic long-term streamflow probabilistic forecasting model for a multisite system considering real-time forecast updating through spatio-temporal dependent error correction

Long-term streamflow forecasting for a multisite river basin system can experience oscillation of spatio-temporal dependent forecast errors. Characterizing the dependent information and conducting spatio-temporal dependent forecast error correction can reduce the total uncertainty in real-time forecasting. On the basis of a single-site martingale model of forecast evolution (MMFE), which can simulate forecast uncertainty evolution over the temporal scale, this study developed a dynamic long-term streamflow probabilistic forecasting model that addresses spatio-temporal dependent error correction for a multisite system. Error characteristics and hybrid spatio-temporal forecast improvements with complex dependencies are captured by Copula function, which describes the systemwide evolution of forecast uncertainty. The proposed model was verified by forecasting the streamflow of the Hongze Lake–Luoma Lake system in China. The results revealed the following. 1) The spatio-temporal dependent error correction based on MMFE can refine the spatio-temporal dimension hybrid error information, which is helpful in improving forecast accuracy. 2) As the spatio-temporal dependence of forecast uncertainty is described using a Copula function, selection of the marginal distribution and connection function is flexible through combining statistical and informational characteristics of the errors, which is helpful in improving the fittedness of complex system error simulation. 3) Compared with the benchmark forecast model without correction, the proposed model greatly decreased forecast uncertainty by reducing the standard deviation of the errors, continuous ranked probability score (CRPS), and Brier score (BS) by nearly 40%, 11.4%, and 34.6%, respectively, and further reduce the CRPS by 2.1% on average (highest value: 3.7%) and reduce the BS by 1.2% on average (highest value: 2.0%) in comparison with only temporal correction. The results demonstrate that the proposed model improves the accuracy and reliability of probabilistic streamflow forecasting for complex water resource systems by reducing uncertainty.

Decentralized calibration process for distributed water resources systems using the self-adaptive multi-memory melody search algorithm

Abstract Having systematic simulation and optimization models with high computational accuracy is one of the most important problems in developing decision support systems. In the present research, a specific methodology was proposed for decentralized calibration of complex water resources system models by using the structural capabilities of the melody search algorithm. This methodology was implemented in the framework of a self-adaptive simulation–optimization model that helps fine-tune complex water resources models by introducing a new definition of the way sub-memories are related to each. The introduced structure aims to achieve the highest possible level of consistency, which is estimated by using different criteria, between model results and observed data at several control points of surface flows. The introduced strategy was put to the test in developing a water resources model for the Great Karun Watershed, Iran, and was found to produce accurate results compared to some other well-known optimization algorithms such as GA, HS, PSO, SGHS, EMPSO, and SaMeS. In an attempt to determine the effect of calibration on water resources system modeling, 16 calibration models of different dimensions are developed and their computational costs are compared in terms of their computation time and effects on the accuracy of the results.

Robust climate change adaptation pathways in agricultural water management

Analysis of climate change impacts as well as conscious decision-making and long-term planning in complex water resources systems require use of innovative approaches under conditions of deep climate uncertainty. This research aims to design and evaluate robust adaptable plans under deep climate uncertainties in the agricultural sector. For this purpose, a combination of the Adaptation Pathways (AP) approach in conjunction with the Soil and Water Assessment Tool (SWAT) model is used to evaluate the robustness of adaptation actions and to design robust adaptation pathways under future climate uncertainties in the Hablehroud River Basin, Iran. Deep climate uncertainties are specified as plausible climate scenario combinations according to the average precipitation and temperature changes in Representative Concentration Pathways (RCPs) 4.5 and 8.5, 2020–2080. According to the results, changes in cropping patterns represent the most robust adaptation action across various combinations of climate scenarios. Other adaptation actions, including deficit irrigation, changes in crop planting dates, and improving irrigation efficiency, are fairly robust in the specific time period from 2020 to 2080. Sequencing of these adaptation actions based on their robustness and expiry date results in designing adaptation pathway maps under RCPs 4.5 and 8.5. Finally, different preferred pathways are identified based on the expiry date of each robust adaptation action. Changes in cropping patterns can be selected as the most robust adaptation pathway (robustness greater than 80) under deep climate uncertainty among these different pathways. Suggesting other preferred pathways can be helpful to select reasonable pathways for implementation.

Water resources management – towards performance based approach.

Global change that results from population growth, global warming, and land use change (especially rapid urbanization) directly affects the complexity of water resources management problems and the uncertainty they are exposed to. Both, the complexity and the uncertainty, are the result of dynamic interactions of innumerable system parts within three major systems: (i) the physical environment; (ii) the social and demographic characteristics of the region under consideration; and (iii) the pipes, roads, bridges, buildings, and other components of the constructed environment (infrastructure). Recent trends in dealing with complex water resources systems include consideration of the entire region being affected, explicit consideration of all costs and benefits, elaboration of a large number of alternative solutions, and the greater participation of all stakeholders in the decision-making. Systems approaches based on simulation, optimization, and multi-objective analyses, in deterministic, stochastic and fuzzy forms, demonstrated in the last 50 years, an excellent potential for providing appropriate support for effective water resources management. This paper explores the future opportunities based on the advances in systems theory that can, on a broader scale, majorly transform the management of water resources. The paper identifies performance-based water resources engineering as a methodological framework to improve water resources management in the face of rapid climate destabilization so that sustainability becomes the norm, not the occasional success story.

Application of the Systems Approach to the Management of Complex Water Systems

This paper provides an introduction to, and an overview of, the Special Issue on the application of systems approach to the management of complex water systems. The main motivation in proposing this Special Issue was that today, more than ever, we need a systems approach to assist in dealing with the difficulties introduced by the increase in the complexity of water resource problems, consideration of environmental impacts, and the introduction of the principles of sustainability. This issue offers an opportunity to review applications of the systems approach to water resource management and draw lessons from worldwide experience relevant to future water problems. The Special Issue includes 15 contributions that offer an interesting view into contemporary problems, approaches, and issues related to management of complex water resources systems. It will be presumptuous to say that these 15 contributions characterize the success or failure of the systems approach to support water resources decision-making. However, these contributions offer some interesting lessons from the current experience and trace possible future work directions.

Rule-Based Object-Oriented Water Resource System Simulation Model for Water Allocation

Simulation is a basic method to analyze water resources system and provide information for decision-making. In this study, a framework is presented that describes the basic elements in a water resource system and a modelling technique integrating conceptual simulation and rule control. To formulate the process of the water cycle and water exploitation with a mathematical model, the water system is described based on adjustable relevant rules and respective parameters with experiences and pragmatic demands in the framework. The rule set describes the principles required to design conceptual networks and control the concrete processes of movement and conversion of different water flows. Combined with object-oriented programming, different calculation functional modules are classified based on the characteristics of water source layers, and the processes that occur in the networks are realised in the computation. The influence of the South-to-North Water Diversion project on the Haihe River basin is analysed by the rule-based object-oriented water resource allocation simulation model. According to the simulation results, groundwater extraction will be reduced by 6,181 million m3. The relationship between water source replacement and water layer exchange in the Haihe River basin is analysed, and the feasibility of the model is verified. Based on the rule-based model, the user requirements can be taken into account conveniently, and the rules are flexible to adjust with experiences and real conditions. This model can be used to simulate complex water resource systems.

Study on water cycle simulation model of multi-source and multi-functional irrigation area based on SWAT model (I): Principles and construction methods

Aiming at the water cycle simulation of multi-sources and multi-functional irrigation area, the coupling relationship between natural water cycle and social water cycle was established based on SWAT model. The methods of sub basins divisions in SWAT model were improved, which were incorporated into the improved SWAT model. The water cycle process of complex water resource system and the response to various human activities in irrigation area were simulated accurately and quantitatively to meet the needs of accurate water resource management.