Evaluating water resources management scenarios considering the hierarchical structure of decision-makers and ecosystem services-based criteria

Behboudian, Massoud; Kerachian, Reza; Motlaghzadeh, Kasra; Ashrafi, Saeed

doi:10.1016/j.scitotenv.2020.141759

Cited by 36 publications

(17 citation statements)

References 35 publications

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“…In (9), α and β are gradient coefficients, and γ is the correlation coefficient. Obviously, the pixel value in the 3×3 neighborhood of the current pixel is:…”

Section: Plos Onementioning

confidence: 99%

“…It is a long-term strategy to alleviate the contradiction between water supply and demand and realize the sustainable use of water resources [8]. Controlling pollution refers to that at areas with severe water pollution, the wastewater utilization rate, the discharge rate of production and domestic sewage, and current water quality can be improved by strengthening environmental awareness, increasing water pollution control efforts, building sewage treatment equipment, improving [9]. Managing water resources refers to the organization, coordination, supervision, and dispatch of water resources development and utilization.…”

Section: Introductionmentioning

confidence: 99%

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Application of edge computing and GIS in ecological water requirement prediction and optimal allocation of water resources in irrigation area

Xie

Jiang

et al. 2021

PLoS ONE

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The purposes are to use water resources efficiently and ensure the sustainable development of social water resources. The edge computing technology and GIS (Geographic Information Science) image data are combined from the perspective of sustainable development. A prediction model for the water resources in the irrigation area is constructed. With the goal of maximizing comprehensive benefits, the optimal allocation of water quality and quantity of water resources is determined. Finally, the actual effect of the model is verified through specific instance data in a province. Results demonstrate that the proposed irrigation area ecological prediction model based on edge computing and GIS images can provide better performance than other state of the art models on water resources prediction. Specifically, the accuracy can remain above 90%. The proposed model for ecological water demand prediction in the irrigation area and optimal allocation of water resources is based on the principle of quality water supply. The optimal allocation of water resources reveals the sustainable development ideas and the requirements of the optimal allocation model, which is very reasonable. The improvement of the system is effective and feasible, and the optimal allocation results are reasonable. This allocation model aims at the water quality and quantity conditions, water conservancy project conditions, and specific water demand requirements in the study area. The calculation results have great practicability and a strong guiding significance for the sustainable utilization and management of the irrigation area.

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“…In (9), α and β are gradient coefficients, and γ is the correlation coefficient. Obviously, the pixel value in the 3×3 neighborhood of the current pixel is:…”

Section: Plos Onementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of edge computing and GIS in ecological water requirement prediction and optimal allocation of water resources in irrigation area

Xie

Jiang

et al. 2021

PLoS ONE

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show abstract

“…Subsequent studies explored ways of combining sophisticated hydrologic modeling with measures of demand (e.g., Nedkov and Burkhard 2012;Karabulut et al 2016;Momblanch et al 2017;Lin et al 2021), while others expanded the scope of assessments to include a larger set of services and suite of models to measure them (e.g., Vollmer et al 2016;Grizzetti et al 2019). Methods have also been developed to incorporate expert opinion, both in rapid field assessments (McInnes and Everard 2017;Walters et al 2021) and in tradeoff assessments at the basin scale (Forio et al 2020;Behboudian et al 2021). At a minimum, ecosystem service assessments should capture both supply and demand (Boerema et al 2017), but additional information on pressures, underlying ecological condition, spatial flow of services, and their impacts on human well-being can also be useful in evaluating tradeoffs between services and the sustainability of meeting multiple demands (Villamagna et al 2013;Grizzetti et al 2016;Sutherland et al 2018;Czúcz et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Integrating Ecosystem Services Into Water Resource Management: An Indicator-Based Approach

Shaad

Souter²,

Vollmer

et al. 2022

Environmental Management

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Natural ecosystems are fundamental to local water cycles and the water ecosystem services that humans enjoy, such as water provision, outdoor recreation, and flood protection. However, integrating ecosystem services into water resources management requires that they be acknowledged, quantified, and communicated to decision-makers. We present an indicator framework that incorporates the supply of, and demand for, water ecosystem services. This provides an initial diagnostic for water resource managers and a mechanism for evaluating tradeoffs through future scenarios. Building on a risk assessment framework, we present a three-tiered indicator for measuring where demand exceeds the supply of services, addressing the scope (spatial extent), frequency, and amplitude for which objectives (service delivery) are not met. The Ecosystem Service Indicator is measured on a 0–100 scale, which encompasses none to total service delivery. We demonstrate the framework and its applicability to a variety of services and data sources (e.g., monitoring stations, statistical yearbooks, modeled datasets) from case studies in China and Southeast Asia. We evaluate the sensitivity of the indicator scores to varying levels data and three methods of calculation using a simulated test dataset. Our indicator framework is conceptually simple, robust, and flexible enough to offer a starting point for decision-makers and to accommodate the evolution and expansion of tools, models and data sources used to measure and evaluate the value of water ecosystem services.

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“…However, for the exact determination of consequences of management policies, the distribution and scattering of demand sites at the basin level should be considered (Ashrafi & Dariane 2017). Numerous studies have been conducted on modeling water resources systems by focusing on quality flow parameters (Emamgholizadeh et al 2014;Keshavarzi et al 2015;Jafari et al 2019;Khorasani et al 2020;Shirnezhad et al 2020;Behboudian et al 2021). Multiple studies have been conducted on Iranian basins to investigate the effect of climate changes on water resources and to analyze their results (Marofi et al 2012;Jamali et al 2013;Dehghani et al 2014;Moazami et al 2016;Adib et al 2018).…”

Section: Introductionmentioning

confidence: 99%

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

Ashrafi

Mahmoudi

2021

Journal of Hydroinformatics

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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.

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Evaluating water resources management scenarios considering the hierarchical structure of decision-makers and ecosystem services-based criteria

Cited by 36 publications

References 35 publications

Application of edge computing and GIS in ecological water requirement prediction and optimal allocation of water resources in irrigation area

Application of edge computing and GIS in ecological water requirement prediction and optimal allocation of water resources in irrigation area

Integrating Ecosystem Services Into Water Resource Management: An Indicator-Based Approach

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

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