Special Issue "Water Resources Management Strategy Under Global Change"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Resources Management, Policy and Governance".

Deadline for manuscript submissions: closed (30 September 2019).

Special Issue Editors

Prof. Dr. Nadhir Al-Ansari
Website
Guest Editor
Department of Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, Lulea 97187, Lulea, Sweden
Interests: water resources; environment; geology; civil engineering
Prof. Rafid Alkhadar
Website
Guest Editor
Liverpool John Moores University, U.K.
Interests: water and wastewater treatment; water resources and conservation
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Fresh water in rivers is only 0.01% of the water available on the earth and provides 80% of the water for human beings on earth. The 80 countries in the developing world that support 40% of the world’s population suffer, however, from water shortage problems that have become a daily fact of life. Consequently, 1.2 billion people are suffering physically from water shortages and, 1.8 billion lack adequate sanitation. Future predictions suggest that there will be 37 countries in 2025 with a shortage of water for all needs. More shortages are expected, and half of the world’s population is expected to live in water stressed areas by 2025. This is mainly due to climate change, population growth rates and development. This Special Issue will address these problems and highlight possible solutions.

Prof. Dr. Nadhir Al-Ansari
Prof. Dr. Rafid Alkhadar
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climate change and water resources
  • water quality and population growth
  • non-conventional water resources
  • river basin planning
  • basin water allocation planning
  • flood risk management
  • drought risk management
  • river restoration
  • coordinated and integrated management of international river basins
  • water demand, population growth rates and development

Published Papers (10 papers)

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Research

Open AccessArticle
Assessment of Water Resources Management Strategy Under Different Evolutionary Optimization Techniques
Water 2019, 11(10), 2021; https://doi.org/10.3390/w11102021 - 28 Sep 2019
Cited by 2
Abstract
Competitive optimization techniques have been developed to address the complexity of integrated water resources management (IWRM) modelling; however, model adaptation due to changing environments is still a challenge. In this paper we employ multi-variable techniques to increase confidence in model-driven decision-making scenarios. Here, [...] Read more.
Competitive optimization techniques have been developed to address the complexity of integrated water resources management (IWRM) modelling; however, model adaptation due to changing environments is still a challenge. In this paper we employ multi-variable techniques to increase confidence in model-driven decision-making scenarios. Here, water reservoir management was assessed using two evolutionary algorithm (EA) techniques, the epsilon-dominance-driven self-adaptive evolutionary algorithm (ε-DSEA) and the Borg multi-objective evolutionary algorithm (MOEA). Many objective scenarios were evaluated to manage flood risk, hydropower generation, water supply, and release sequences over three decades. Computationally, the ε-DSEA’s results are generally reliable, robust, effective and efficient when compared directly with the Borg MOEA but both provide decision support model outputs of value. Full article
(This article belongs to the Special Issue Water Resources Management Strategy Under Global Change)
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Open AccessArticle
Site Selection of Aquifer Thermal Energy Storage Systems in Shallow Groundwater Conditions
Water 2019, 11(7), 1393; https://doi.org/10.3390/w11071393 - 06 Jul 2019
Cited by 2
Abstract
Underground thermal energy storage (UTES) systems are well known applications around the world, due to their relation to heating ventilation and air conditioning (HVAC) applications. There are six kinds of UTES systems, they are tank, pit, aquifer, cavern, tubes, and borehole. Apart from [...] Read more.
Underground thermal energy storage (UTES) systems are well known applications around the world, due to their relation to heating ventilation and air conditioning (HVAC) applications. There are six kinds of UTES systems, they are tank, pit, aquifer, cavern, tubes, and borehole. Apart from the tank, all other kinds are site condition dependent (hydro-geologically and geologically). The aquifer thermal energy storage (ATES) system is a widespread and desirable system, due to its thermal features and feasibility. In spite of all the advantages which it possesses, it has not been adopted in very shallow groundwater (less than 2 m depth) regions, till now, due to the susceptibility of the storage efficiency of these systems to the in-site parameters. This paper aims to find a reliable method that can be used to find the best location to install ATES systems. The concept of the suggested method is based on integrating three methods. They are, the analytical hierarchy process (AHP), the DRASTIC index method, and ArcMap/GIS software. The results from this method include a criterion that summarizes the best location to install an ATES system. This criterion is depicted by ArcMap/GIS software, producing raster maps that specify the best location for the storage system. The suggested method can be used to find the best location to install the thermal storage, especially in susceptible aquifers. Full article
(This article belongs to the Special Issue Water Resources Management Strategy Under Global Change)
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Open AccessArticle
The Impacts of Water Demand and Its Implications for Future Surface Water Resource Management: The Case of Tanzania’s Wami Ruvu Basin (WRB)
Water 2019, 11(6), 1280; https://doi.org/10.3390/w11061280 - 19 Jun 2019
Cited by 4
Abstract
River basins around the world face similar issues of water scarcity, deficient infrastructure, and great disparities in water availability between sub-regions, both within and between countries. In this study, different strategies under the Water Evaluation and Planning system (WEAP) were assessed to mitigate [...] Read more.
River basins around the world face similar issues of water scarcity, deficient infrastructure, and great disparities in water availability between sub-regions, both within and between countries. In this study, different strategies under the Water Evaluation and Planning system (WEAP) were assessed to mitigate water overuse practices under the Current Trend (CT), Economic Growth (EG), and Demand Side Management (DSM) scenarios in relation to current and future statuses of Tanzania’s Wami Ruvu Basin (WRB). The results show that neither domestic nor irrigation water demand will be met based on the current trend. Under the CT scenario, the total water demand is projected to rise from 1050.0 million cubic meters in the year 2015, to 2122.9 million cubic meters by the year 2035, while under the DSM scenario the demand dropped to 990.0 million cubic meters in the year 2015 and to 1715.8 million cubic meters by the year 2035. This study reveals that there is a positive correlation between the highest surface runoff events and the highest unmet demand events in the basin. Terrestrial water demand alters the hydrological cycle of a catchment by modifying parameters such as surface runoff, particularly in small catchments. The results of this study prove that DSM strategies are more amenable to mitigate the impacts and implications of water demand, as they increase water sustainability and ensure ecosystem security by reducing the annual water demands and surface runoff by 15% and 2%, respectively. Full article
(This article belongs to the Special Issue Water Resources Management Strategy Under Global Change)
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Open AccessEditor’s ChoiceArticle
Analysis and Projection of Flood Hazards over China
Water 2019, 11(5), 1022; https://doi.org/10.3390/w11051022 - 16 May 2019
Cited by 8
Abstract
Floods have been experienced with greater frequency and more severity under global climate change. To understand the flood hazard and its variation in the future, the current and future flood hazards in the 21st century in China are discussed. Floods and their trends [...] Read more.
Floods have been experienced with greater frequency and more severity under global climate change. To understand the flood hazard and its variation in the future, the current and future flood hazards in the 21st century in China are discussed. Floods and their trends are assessed using the accumulation precipitation during heavy rainfall process (AP_HRP), which are calculated based on historical meteorological observations and the outputs of a global climate model (GCM) under three Representative Concentration Pathway (RCP) scenarios. The flood-causing HRPs counted by the flood-causing critical precipitation (the 60% fractile of AP_HRP) capture more than 70% of historical flood events. The projection results indicate that the flood hazards could increase under RCP4.5 and RCP8.5 and increase slightly under RCP2.6 during the 21st century (2011–2099). The spatial characteristics of flood hazards and their increasing trends under the three RCPs are similar in most areas of China. More floods could occur in southern China, including Guangdong, Hainan, Guangxi and Fujian provinces, which could become more serious in southeastern China and the northern Yunnan province. Construction of water conservancy projects, reservoir dredging, improvement of drainage and irrigation equipment and enhancement of flood control and storage capacity can mitigate the impacts of floods and waterlogging on agriculture. Full article
(This article belongs to the Special Issue Water Resources Management Strategy Under Global Change)
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Open AccessArticle
Dew Point Temperature Estimation: Application of Artificial Intelligence Model Integrated with Nature-Inspired Optimization Algorithms
Water 2019, 11(4), 742; https://doi.org/10.3390/w11040742 - 10 Apr 2019
Cited by 27
Abstract
Dew point temperature (DPT) is known to fluctuate in space and time regardless of the climatic zone considered. The accurate estimation of the DPT is highly significant for various applications of hydro and agro–climatological researches. The current research investigated the hybridization of a [...] Read more.
Dew point temperature (DPT) is known to fluctuate in space and time regardless of the climatic zone considered. The accurate estimation of the DPT is highly significant for various applications of hydro and agro–climatological researches. The current research investigated the hybridization of a multilayer perceptron (MLP) neural network with nature-inspired optimization algorithms (i.e., gravitational search (GSA) and firefly (FFA)) to model the DPT of two climatically contrasted (humid and semi-arid) regions in India. Daily time scale measured weather information, such as wet bulb temperature (WBT), vapor pressure (VP), relative humidity (RH), and dew point temperature, was used to build the proposed predictive models. The efficiencies of the proposed hybrid MLP networks (MLP–FFA and MLP–GSA) were authenticated against standard MLP tuned by a Levenberg–Marquardt back-propagation algorithm, extreme learning machine (ELM), and support vector machine (SVM) models. Statistical evaluation metrics such as Nash Sutcliffe efficiency (NSE), root mean square error (RMSE), and mean absolute error (MAE) were used to validate the model efficiency. The proposed hybrid MLP models exhibited excellent estimation accuracy. The hybridization of MLP with nature-inspired optimization algorithms boosted the estimation accuracy that is clearly owing to the tuning robustness. In general, the applied methodology showed very convincing results for both inspected climate zones. Full article
(This article belongs to the Special Issue Water Resources Management Strategy Under Global Change)
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Open AccessArticle
Novel Hybrid Data-Intelligence Model for Forecasting Monthly Rainfall with Uncertainty Analysis
Water 2019, 11(3), 502; https://doi.org/10.3390/w11030502 - 10 Mar 2019
Cited by 36
Abstract
In this research, three different evolutionary algorithms (EAs), namely, particle swarm optimization (PSO), genetic algorithm (GA) and differential evolution (DE), are integrated with the adaptive neuro-fuzzy inference system (ANFIS) model. The developed hybrid models are proposed to forecast rainfall time series. The capability [...] Read more.
In this research, three different evolutionary algorithms (EAs), namely, particle swarm optimization (PSO), genetic algorithm (GA) and differential evolution (DE), are integrated with the adaptive neuro-fuzzy inference system (ANFIS) model. The developed hybrid models are proposed to forecast rainfall time series. The capability of the proposed evolutionary hybrid ANFIS was compared with the conventional ANFIS in forecasting monthly rainfall for the Pahang watershed, Malaysia. To select the optimal model, sixteen different combinations of six different lag attributes taking into account the effect of monthly, seasonal, and annual history were considered. The performances of the forecasting models were assessed using various forecasting skill indicators. Moreover, an uncertainty analysis of the developed forecasting models was performed to evaluate the ability of the hybrid ANFIS models. The bound width of 95% confidence interval (d-factor) and the percentage of observed samples which was enveloped by 95% forecasted uncertainties (95PPU) were used for this purpose. The results indicated that all the hybrid ANFIS models performed better than the conventional ANFIS and for all input combinations. The obtained results showed that the models with best input combinations had the (95PPU and d-factor) values of (91.67 and 1.41), (91.03 and 1.41), (89.74 and 1.42), and (88.46 and 1.43) for ANFIS-PSO, ANFIS-GA, ANFIS-DE, and the conventional ANFIS, respectively. Based on the 95PPU and d-factor, it is concluded that all hybrid ANFIS models have an acceptable degree of uncertainty in forecasting monthly rainfall. The results of this study proved that the hybrid ANFIS with an evolutionary algorithm is a reliable modeling technique for forecasting monthly rainfall. Full article
(This article belongs to the Special Issue Water Resources Management Strategy Under Global Change)
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Open AccessArticle
Open Channel Sluice Gate Scouring Parameters Prediction: Different Scenarios of Dimensional and Non-Dimensional Input Parameters
Water 2019, 11(2), 353; https://doi.org/10.3390/w11020353 - 19 Feb 2019
Cited by 13
Abstract
The determination of scour characteristics in the downstream of sluice gate is highly important for designing and protection of hydraulic structure. The applicability of modern data-intelligence technique known as extreme learning machine (ELM) to simulate scour characteristics has been examined in this study. [...] Read more.
The determination of scour characteristics in the downstream of sluice gate is highly important for designing and protection of hydraulic structure. The applicability of modern data-intelligence technique known as extreme learning machine (ELM) to simulate scour characteristics has been examined in this study. Three major characteristics of scour hole in the downstream of a sluice gate, namely the length of scour hole (Ls), the maximum scour depth (Ds), and the position of maximum scour depth (Lsm), are modeled using different properties of the flow and bed material. The obtained results using ELM were compared with multivariate adaptive regression spline (MARS). The dimensional analysis technique was used to reduce the number of input variable to a smaller number of dimensionless groups and both the dimensional and non-dimensional variables were used to model the scour characteristics. The prediction performances of the developed models were examined using several statistical metrics. The results revealed that ELM can predict scour properties with much higher accuracy compared to MARS. The errors in prediction can be reduced in the range of 79%–81% using ELM models compared to MARS models. Better performance of the models was observed when dimensional variables were used as input. The result indicates that the use of ELM with non-dimensional data can provide high accuracy in modeling complex hydrological problems. Full article
(This article belongs to the Special Issue Water Resources Management Strategy Under Global Change)
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Open AccessArticle
Planning Considerations of Managed Aquifer Recharge (MAR) Projects in Jordan
Water 2019, 11(2), 182; https://doi.org/10.3390/w11020182 - 22 Jan 2019
Cited by 6
Abstract
This work discussed the conditions for the successful implementation of managed aquifer recharge, with various case studies in Jordan. The motivation behind this study was that many managed aquifer projects have been implemented in Jordan without adequate studies and they have since failed. [...] Read more.
This work discussed the conditions for the successful implementation of managed aquifer recharge, with various case studies in Jordan. The motivation behind this study was that many managed aquifer projects have been implemented in Jordan without adequate studies and they have since failed. Examples from Jordan were provided to serve as an illustration of Middle Eastern and North African countries, with their semi-arid to arid climates and increasing demand for water. The methodology included the evaluation of the implemented managed aquifer projects in Jordan and whether they achieved success or failure in fulfilling the purposes of aquifer recharging, as well as to clarify the reasons for the failure or success. The results showed that a minimum level of study must be carried out before starting any artificial recharge projects, such as defining the aquifer parameters and the water quality evolution after recharge, in addition to understanding of the fate of the recharged water. Managed aquifer recharge can alleviate the impacts of climate change by making use of unused water, and in the case of Jordan, it can alleviate the implications of dropping groundwater levels. Full article
(This article belongs to the Special Issue Water Resources Management Strategy Under Global Change)
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Open AccessArticle
Comparison of Optimal Hedging Policies for Hydropower Reservoir System Operation
Water 2019, 11(1), 121; https://doi.org/10.3390/w11010121 - 10 Jan 2019
Cited by 4
Abstract
Reservoir operation rules play an important role in regions economic development. Meanwhile, hedging policies are mostly applied for municipal, industrial, and irrigation water supplies from reservoirs and it is less used for reservoir operation for hydropower generation. The concept of hedging and rationing [...] Read more.
Reservoir operation rules play an important role in regions economic development. Meanwhile, hedging policies are mostly applied for municipal, industrial, and irrigation water supplies from reservoirs and it is less used for reservoir operation for hydropower generation. The concept of hedging and rationing factors can be used to maintain the water in a reservoir for the sake of increasing water storage and water head for future use. However, water storage and head are the key factors in operation of reservoir systems for hydropower generation. This study investigates the applicability of seven competing hedging policies including four customary forms of hedging (1PHP, 2PHP, 3PHP, DHP) and three new forms of hedging rules (SOPHP, BSOPHP, SHPHP) for reservoir operation for hydropower generation. The models were constructed in MATLAB R2011b based on the characteristics of the Batang Padang hydropower reservoir system, Malaysia. In order to maximize the output of power generation in operational periods (2003–2009), three optimization algorithms namely particle swarm optimization (PSO), genetic algorithm (GA), and hybrid PSO-GA were linked to one of the constructed model (1PHP as a test) to find the most effective algorithm. Since the results demonstrated the superiority of the hybrid PSO-GA algorithm compared to either PSO or GA, the hybrid PSO-GA were linked to each constructed model in order to find the optimal decision variables of each model. The proposed methodology was validated using monthly data from 2010–2012. The results showed that there are no significant difference between the output of monthly mean power generation during 2003–2009 and 2010–2012.The results declared that by applying the proposed policies, the output of power generation could increase by 13% with respect to the historical management. Moreover, the discrepancies between mean power generations from highest to lowest months were reduced from 49 MW to 26 MW, which is almost half. This means that hedging policies could efficiently distribute the water-supply and power-supply in the operational period and increase the stability of the system. Among the studied hedging policies, SHPHP is the most convenient policy for hydropower reservoir operation and gave the best result. Full article
(This article belongs to the Special Issue Water Resources Management Strategy Under Global Change)
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Open AccessArticle
Recent Trends and Long-Range Forecasts of Water Resources of Northeast Iraq and Climate Change Adaptation Measures
Water 2018, 10(11), 1562; https://doi.org/10.3390/w10111562 - 02 Nov 2018
Cited by 8
Abstract
Iraq has been experiencing water resources scarcity, and is vulnerable to climate change. Analysis of historical data revealed that the region is experiencing climate change to a degree higher than generally reported elsewhere. The relationship between climate change and its effect on water [...] Read more.
Iraq has been experiencing water resources scarcity, and is vulnerable to climate change. Analysis of historical data revealed that the region is experiencing climate change to a degree higher than generally reported elsewhere. The relationship between climate change and its effect on water resources of a region has been sparsely addressed in published literature. To fill that gap this research work first investigates if there has been a significant change in climate in the region, which has been found to be true. In the next stage, the research projects future climatic scenarios of the region based on six oft-used General Circulation Model (GCM) ensembles, namely CCSM4, CSIRO-Mk3.6.0, GFDL-ESM2M, MEROC5, HadGEM2-ES, and IPSL-CM5A-LR. The relationship between climate change and its impact on water resources is explored through the application of the popular, widely used SWAT model. The model depicts the availability of water resources, classified separately as blue and green waters, for near and distant futures for the region. Some of the findings are foreboding and warrants urgent attention of planners and decision makers. According to model outputs, the region may experience precipitation reduction of about 12.6% and 21% in near (2049–2069) and distant (2080–2099) futures, respectively under RCP8.5. Those figures under RCP4.5 are 15% and 23.4%, respectively and under RCP2.6 are 12.2% and 18.4%, respectively. As a consequence, the blue water may experience decreases of about 22.6% and 40% under RCP8.5, 25.8% and 46% under RCP4.5, and 34.4% and 31% under RCP2.6 during the periods 2049–2069 and 2080–2099, respectively. Green water, by contrast, may reduce by about 10.6% and 19.6% under RCP8.5, by about 14.8% and 19.4% under RCP4.5, and by about 15.8% and 14.2% under RCP2.6 during the periods 2049–2069 and 2080–2099, respectively. The research further investigates how the population are adapting to already changed climates and how they are expected to cope in the future when the shift in climate is expected to be much greater. Full article
(This article belongs to the Special Issue Water Resources Management Strategy Under Global Change)
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