Water Resources Management Model Research Articles

Water Resources Allocation Based on Complex Adaptive System Theory in the Inland River Irrigation District

Water resources are the key factors affecting the sustainable development of inland river irrigation districts. The establishment of a water resources management model is helpful to realize the coordinated development of water, society, and ecology. Aiming at the contradiction of water use and ecological vulnerability, this study was based on the method of complex adaptive system (CAS) theory, and an agent-based modeling (ABM) method was adopted. Taking Huaitoutala irrigation district as the research object, a water resource management model considering ecological balance was established, with the water resources potentially tapping in the source area as an effective constraint. This study took 2016 as the datum year; the water consumption and comprehensive benefits of four water-saving irrigation scenarios in different characteristic years were simulated and optimized under the conditions of the current water supply and 10% and 15% potential water resources tapping. The results showed that the model considering the behavior and adaptability of the agent can well optimize and simulate the water use in the irrigation district. Under the application of water resources potential tapping and high-efficiency water-saving technology; the water utilization efficiency (WUE) of the irrigation area has been significantly improved. The comprehensive benefits of the irrigation district increased the proportion of ecological water, which was conducive to the sustainable development of the irrigation district and the ecological protection of inland rivers.

Testing of Water Evaluation and Planning (WEAP) model for water resources management in the Hron River basin

Testing of Water Evaluation and Planning (WEAP) model for water resources management in the Hron River basin

A dual-randomness bi-level interval multi-objective programming model for regional water resources management

In this research, a dual-randomness bi-level interval multi-objective programming (DR-BIMP) model was developed for supporting water resources management among multiple water sectors under complexities and uncertainties. Techniques of bi-level multi-objective programming (BMOP), double-sided stochastic chance-constrained programming (DSCCP), and interval parameter programming (IPP) were incorporated into an integrated modeling framework to achieve comprehensive consideration of the complexities and uncertainties of water resources management systems. The DR-BIMP model can not only effectively deal with the interactive effects between multiple decision-makers in complex water management systems through the bi-level hierarchical strategies, but also can characterize the multiple uncertainties information expressed as interval format and probability density functions. It could thus improve upon the existing bi-level multi-objective programming through addressing discrete interval parameters and dual-randomness problems in optimization processes simultaneously. Then, the developed model was applied to a real-world case to optimally allocate water resources among three different water sectors in five sub-regions in the Dongjiang River basin, south China. The results of the model include determining values, interval values, and stochastic distribution information, which can assist bi-level decision-makers to plan future resources effectively to some extent. After comparing the variations of results, it is found that an increasing probability level can lead to higher system benefits, which is increased from [20,786.00, 26,425.92] × 108 CNY to [22,290.84, 27,492.57] × 108 CNY, while the Gini value is reduced from [0.365, 0.446] to [0.345, 0.405]. A set of increased probability levels gives rise to the lower-level objectives. Furthermore, the advantages of the DR-BIMP model were highlighted by comparing with the other models originated from the developed model. The comparison results indicated that the DR-BIMP model was a valuable tool for generating a range of decision alternatives and thus assists the bi-level decision-makers to identify the desired water resources allocation schemes under multiple scenarios.

Water Resources Management Models for Policy Assessment

Water resources management models support a variety of research applications, including the assessment of water availability [...]

Seasonal precipitation variability in mainland China based on entropy theory

AbstractPrecipitation plays a fundamental role in terrestrial modelling and is extremely vulnerable to climate change. It is particularly challenging to describe precipitation due to its intermittency and fluctuation at nearly all temporal and spatial scales. Precipitation variability represents the degree of unevenness in its distribution or its lack of uniformity over different scales. This study examined the seasonal variability of meteorological station precipitation observations during 1961–2018 over mainland China using entropy theory. The intensity disorder index (IDI) and apportionment disorder index (ADI) were used to characterize the distribution unevenness, including the number of precipitation days, and precipitation amounts. Six special regions were selected according to their geographical location and climate conditions to show the regional differences of the disorder indices. At the daily scale, the regional mean IDI was 0.4081 for the eastern Tibetan Plateau and the regional mean ADI was 0.9984 for north China, which were the largest value among the six regions investigated. The regional mean IDI was 0.1128 and the regional mean ADI was 0.4071 both for the Yangtze River Basin, which were the smallest value among the six regions investigated. Temporal variations of the DIs were also detected. The IDI have decreased not significantly in most regions, except increasing by 0.0223/decade and 0.0129/decade in southwest China during nighttime and daytime, respectively. The ADI decreased by −0.0191, −0.0275, −0.0229, and −0.0203/decade and passed the significant test at .05 level for northwest, northeast, north China, and eastern Tibetan Plateau at the daily scale, respectively. The results quantify the precipitation unevenness over mainland China, which can be treated as a reference for water resources management and land surface model evaluation.

Assessment of Water Demand in Al-Anbar Province- Iraq

The water issue has posed a great challenge in the past twenty years in most Arab countries, including Iraq in particular, due to the establishment of many dams by Turkey, which led to a decrease in the annual rate of water resources and non-compliance with international law of trans-boundary water management. The west of Iraq is considered as an arid region and suffers scarcity of rain, which has led to severe drought and seriously affected water resources in terms of quality and quantity. In this study, a numerical model of water resources management for the Euphrates River is applied by using Water Evaluation And Planning (WEAP). Anbar Province is selected to apply this model, in order to assess past trends in water resources management and to simulate current demand scenarios which must be known for the decision-makers and water resources managers, namely the reference scenario and the water tax scenario. The results showed that the demand for water in the reference scenario (2040) will be 2819.35 million cubic meters per year while the corresponding demand in the other scenario will be 2639.54 million cubic meters per year, which amounts to 179.81 million cubic meters per year saving that can be exploited.

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

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

A model integrating the system dynamic model with the risk based two-stage stochastic robust programming model for agricultural-ecological water resources management

This paper combines a risk-based two-stage stochastic robust programming (RTSRP) model into an agricultural-ecological system dynamics (AESD) to conduct agricultural-ecological water resources management. It integrates the chance- constrained programming, conditional risk-at-value, two-stage stochastic robust programming with the AESD model. The RTSRP model improves upon the TSRP model by introducing the risk control measurements. The agricultural-ecological dynamic system (AEDS) model can build water connections amid wheat, field corn, seed corn, economic crops, woodland, meadow, and city greening and farmland shelterbelts. Besides, the ecological service value is transformed into the irrigation benefit of ecological sector to guide water allocation amid sub-ecological sectors at a more applicable detailed scale. It can tradeoff relationships between economic benefit and ecological recovery by formulating two enlarging ecological areas scenarios. The combinations of the RTSRP model and the AEDS model can get optimal water allocation schemes, and simulate future sustainable degree (SD) of optimal water allocation schemes and explore relationships amid water allocation, economic benefit, and SD and risk and robustness of model. It is used to the middle reaches of the Heihe River Basin in China to verify its application. The results show that water allocation schemes have different responses on various risk scenarios. Higher water allocation corresponds to bigger water shortage risk and higher robustness of the model. The economic benefit positive with water allocation is contradictory with SD. Enlarging ecological areas contributes to improvements of economic benefit and ecological recovery, but not the SD under the condition of enough water resources.

Developing a Conceptual Model for Sustainable water Resource Management and Agricultural Development: the Case of the Breede River Catchment Area, South Africa.

The complex relationship that exists between water resources and agricultural production has been increasing constantly globally. Several factors are interacting to influence the management of water resources making the system complex and dynamic. To increase the understanding of these complex and dynamic systems, relevant tools are needed to identify the causal relationships that exist between the drivers and their influences on the system. Participatory modelling based on the system dynamics approach provides a simplistic and visualisation tool that can improve the understanding of the functioning of a complex and dynamic system. A multi-stage participatory approach was used in this study involving relevant stakeholders in the development of an integrated conceptual system dynamic model using causal loop diagrams. This approach was used because it captures the thought process and mental model of relevant stakeholders in the development of the model, making it a valuable tool for policy and decision making at government and individual levels. The integrated model built in this study used causal loop diagrams to address problems of water management and agricultural sustainability in the Breede River Catchment. The model shows major causal-relationships and feedback loops that determine the functioning of the overall system. The model demonstrates the usefulness of the participatory approach in solving problems related to water management and agricultural development in the catchment.

Representation of agriculture in water governance in São Paulo

Abstract The water resources management model in the state of São Paulo is characterized by the participation of water users from different sectors of the economy within the ambit of River Basin Committees and other organizations of the water management system. The purpose of this article is to present a survey and systematization of the performance of representatives of São Paulo’s agricultural sector in this decentralized and participatory system of water governance. To this end, this article recreates the profile of this sectoral representation in the State Water Resources Council and in the Committees for rural areas with strong agricultural dynamics in the state. The findings of this study reveal significant political and propositional differences between São Paulo’s agriculture and agroindustry sectors. Such differences have to do with the structure and capillarity of the entities that represent these sectors, as well as their divergent concept of management.

Models of management of the territorial community nature resources’ rational use

The aim of the article is to present the results of the applied research, carried out to develop a model of land and water resources management for a united territorial community. The material was prepared on the basis of the results, which had been obtained during the implementation of the project, aimed to developing a vision for the strategy of the territory development. Within the development of the vision, the strategy for the development of the territorial community has been collected in a certain way, and then, on the basis of this information, a so-called mental experiment has been carried out based on various methods of information analysis. In particular, it gave the opportunity to develop models for the use of community’s land and water resources. Local governments should rely on carefully prepared information about available resources for more effective management of territories. One of the ways to get such information is the mental experiment method used with the aim of modeling potential ways of municipal territories’ land and water resources rational use.

Selection of a Hydrological Model and Objective Function for Water Resources Management in Predominantly Rural Watershed using Criteria-Based Evaluation

Selection of a fitting up-to-date hydrological model using an evaluation of the functionality, modeler’s requirements, and modeling experiences are very important for water resources management in rural watersheds. Similarly, the selection of appropriate objective function is equally crucial in hydrological modeling processes. Accordingly, A review study was carried to select an appropriate model and objective function for water resources modeling in the predominantly rural watershed. Hydrological models namely HEC-HMS, MIKE SHE, SWAT, TOPMODEL, and SWMM, and objective functions namely NSE, RMSE, MRAE, and RAEM were reviewed. Hydrological models were reviewed under several criteria viz. temporal scale, spatial scale, hydrological processes, documentation, resources requirement, user interface and, model acquisition cost. Whereas, criteria for the review of objective functions were mathematical implication, flow regime, and modeling purpose. Each of the review criteria was comprised of several factors. The criteria-based evaluation was done to quantify the review outcome of the hydrological model and objective function. SWMM was found to be the most suitable model for simulating rural watersheds for water resources management purposes whereas, MRAE was found to be the most appropriate objective function to evaluate the performance of the model selected for rural watershed modeling.

System dynamics model of sustainable water resources management using the Nexus Water-Food-Energy approach

This research has investigated the simulation of sustainable water resources management to assess the impact of socio-economic development on water, food and energy resources security in Khuzestan Province in Iran. To achieve this goal, after simulation of the water-food-energy system dynamics model, taking into account results of the sensitivity analysis, development of water resources sustainability policy-making was elaborated in the form of four strategies of water demand, water supply, food resource and energy demand management, as well as combined policies. The simulation results of the proposed solutions were selected to be a combination of the strategies of water demand and food resources management as the best policies. Hence, 16% increase in irrigation efficiency, 10% improvement in cultivation patterns, 6% reduction in agricultural products losses, 5% decrease in food demand due to food losses, and 5% annual increase in the performance of agriculture are selected as sustainable water resources management policies.

Un acercamiento institucional a la gestión del agua ante el cambio climático en la Ciudad de México

This paper presents an analysis of the policy instruments that Mexico City’s government has built in the water sector to achieve adaptation to climate change. It seeks to investigate the institutional facilitators and barriers that have allowed or prevented to the city government to achieve an effectiveness of policy instruments. Climate change is initially presented as a problem that contributes to a global environmental change and some indicators of the effects in Mexico are exposed, with an emphasis on water ones in Mexico City. Subsequently, the barriers and facilitators that some studies have identified as contributing mainly to the effectiveness of policy instruments are presented as a frame of reference. Thirdly, the analisis of the policy instruments that the government of Mexico City has built in the water sector is carried out, for which the barriers and facilitators identified in the reference framework are taken as reference. The research is fundamentally qualitative and makes use of techniques such as document review and systematization. The findings of this research suggest that the actions implemented by the government of Mexico City in the water sector to achieve adaptation to climate change are limited by institutional barriers that are common with other sectoral policies, as is the case of human and economic resources, and also by barriers that are associated with the dominant of integrated water resources management model and that affect the type of actions that are designed to achieve an adaptation to climate change.

Water supply failure probability under influence of climate change—Balsillas river basin case study

This project assesses the risk of water supply failure for the agricultural sector under climate change conditions by implementing hydrological models that support decision-making for satisfying consumptive demands in times of scarcity. This project was developed using hydrological modeling tools such as the HydroBID software and the SIMGES and SIMRISK water resource management models of AQUATOOL DSS. The flow series for a current scenario were obtained for different climate change scenarios from a Global Climate Model (GCM) and the Coordinated Regional Experiment on Climate Reduction (CORDEX) by downscaling the results from the global scale to basin-scale using a statistical method based on chaos theory. These projections show that under conditions of climate change, the agricultural sector of the Balsillas basin will not suffer significant impacts since they will be able to satisfy most demand points.

An inexact multi-stage interval-parameter partial information programming model for water resources management under uncertainties

Abstract The urban water shortage crisis around the world is increasing. In this study, an inexact multi-stage interval-parameter partial information programming model (IMIPM) is proposed for urban water resources planning and management under uncertainties. Optimization techniques of two-stage stochastic programming (TSP), interval-parameter programming (IPP), linear partial information theory (LPI) and multistage stochastic programming (MSP) are combined into one general framework. IMIPM is used to tackle uncertainties like interval numbers, water inflow probabilities expressed as linear partial information, dynamic features in a long planning time and joint probabilities in water resources management. It is applied to Harbin where the manager needs to allocate water from multi-water sources to multi-water users during multi-planning time periods. Four water flow probability scenarios are obtained, which are associated with uncertainties of urban rainfall information. The results show that the dynamics features and uncertainties of system parameters (such as water allocation targets and shortage) are considered in this model by generating a set of representative scenarios within a multistage context. The results also imply that IMIPM can truly reflect the actual urban water resources management situation, and provide managers with decision-making space and technical support to promote the sustainable development of economics and the ecological environment in cities.

Validation of the SMOS Level 1C Brightness Temperature and Level 2 Soil Moisture Data over the West and Southwest of Iran

The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission with the MIRAS (Microwave Imaging Radiometer using Aperture Synthesis) L-band radiometer provides global soil moisture (SM) data. SM data and products from remote sensing are relatively new, but they are providing significant observations for weather forecasting, water resources management, agriculture, land surface, and climate models assessment, etc. However, the accuracy of satellite measurements is still subject to error from the retrieval algorithms and vegetation cover. Therefore, the validation of satellite measurements is crucial to understand the quality of retrieval products. The objectives of this study, precisely framed within this mission, are (i) validation of the SMOS Level 1C Brightness Temperature (TBSMOS) products in comparison with simulated products from the L-MEB model (TBL-MEB) and (ii) validation of the SMOS Level 2 SM (SMSMOS) products against ground-based measurements at 10 significant Iranian agrometeorological stations. The validations were performed for the period of January 2012 to May 2015 over the Southwest and West of Iran. The results of the validation analysis showed an RMSE ranging between 9 to 13 K and a strong correlation (R = 0.61–0.84) between TBSMOS and TBL-MEB at all stations. The bias values (0.1 to 7.5 K) showed a slight overestimation for TBSMOS at most of the stations. The results of SMSMOS validation indicated a high agreement (RMSE = 0.046–0.079 m3 m−3 and R = 0.65–0.84) between the satellite SM and in situ measurements over all the stations. The findings of this research indicated that SMSMOS shows high accuracy and agreement with in situ measurements which validate its potential. Due to the limitation of SM measurements in Iran, the SMOS products can be used in different scientific and practical applications at different Iranian study areas.

Sustainable resource optimization under water-energy-food-carbon nexus

Pressures from growing demands and shrinking supplies have reached a critical junction in major global resources, particularly water, energy, and food (WEF). Recognizing the complex interaction across those highly interconnected resources, the nexus concept evolved to boost efficiencies across all nexus pillars. Several modeling efforts tried to capture the complexity of this problem, but most attempts captured only one or two nexus pillars, remained localized to fixed case-studies or applications, or used simulations to assess pre-defined scenarios rather than solving for optimum solutions under defined objective function and constraints. Here, we present an optimization model for water, energy, and food nexus resource management and allocation at a regional scale. The model was successfully validated using a hypothetical case study to test its efficiency under several resource availability scenarios and different policy targets. The results enhanced the understanding of the interlinkages among the nexus sectors by demonstrating the sensitivity of the WEF nexus to adopted strategies. For example, imposing food variety constraints changed water consumption by an order of magnitude and more than doubled energy requirements. Moreover, adopting renewable energy may cause increased demands for land, but can significantly cut CO2 emissions. The model serves as an effective decision-making tool that enables policy makers to assess multiple WEF sources and recommends the optimum resource allocation under various policy, technology, and resource constraints.

Data Duration Options of a Practicing Water Manager when Developing a Model for Sustainable Water Resources Development

Water scarcity emphasizes the importance of water resources planning and management. Monthly hydrologic models are commonly used because in practice, monthly time step is the choice for planning activities. Reliability of the model simulations depends upon the nature of the data. Data quality is important and data should be representative of the watershed processes. The information contained in the data and careful extraction is also important. A detailed review of available guidelines and research findings to identify the best data duration option available for water managers to calibrate and verify a monthly streamflow estimation model for sustainable water resources management was carried out. The data length selection for monthly water resources models varies between 12 and 780 months and the reasons for selection is mostly individual preference. This study exhibits a qualitative evaluation using five key criteria. Data length use in research and guidelines indicates that 20 to 40 year long data sets are the most favoured for monthly model applications. A total data length of range 20-30 years or greater should be utilized for monthly water resources model development. It may be prudent to select at least a 20-year data period for model calibration based on the analysis.

Uncertainty Quantification in Water Resource Systems Modeling: Case Studies from India

Regional water resource modelling is important for evaluating system performance by analyzing the reliability, resilience and vulnerability criteria of the system. In water resource systems modelling, several uncertainties abound, including data inadequacy and errors, modeling inaccuracy, lack of knowledge, imprecision, inexactness, randomness of natural phenomena, and operational variability, in addition to challenges such as growing population, increasing water demands, diminishing water sources and climate change. Recent advances in modelling techniques along with high computational capabilities have facilitated rapid progress in this area. In India, several studies have been carried out to understand and quantify uncertainties in various basins, enumerate large temporal and regional mismatches between water availability and demands, and project likely changes due to warming. A comprehensive review of uncertainties in water resource modelling from an Indian perspective is yet to be done. In this work, we aim to appraise the quantification of uncertainties in systems modelling in India and discuss various water resource management and operation models. Basic formulation of models for probabilistic, fuzzy and grey/inexact simulation, optimization, and multi-objective analyses to water resource design, planning and operations are presented. We further discuss challenges in modelling uncertainties, missing links in integrated systems approach, along with directions for future.