Displaying publications 21 - 40 of 43 in total

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  1. Ali H. Ahmed Suliman, Webster Gumindoga, Ayob Katimon, Intan Zaurah Mat Darus
    Sains Malaysiana, 2014;43:1379-1388.
    This paper presents the application of TOPMODEL in the Pinang catchment of Malaysia for stream flow simulation. An attempt has been made to use remote-sensing data (ASTER DEM of 30 m resolution) as a primary input for TOPMODEL in order to simulate the stream flow pattern of this tropical catchment. A calibration period was executed based on 2007-2008 hydro-meteorological dataset which gave a satisfactory Nash-Sutcliffe model (NS) model efficiency of 0.749 and a relative volume error (RVE) of -19.2. The recession curve parameter (m) and soil transmissivity at saturation zone (To), were established as the most sensitive parameters through a sensitivity analysis processes. Hydro-meteorological datasets for the period between 2009 and 2010 were used to validate the model which resulted in satisfactory efficiencies of 0.774 (NS) and -19.84 (RVE), respectively. This study demonstrated the ability ASTER DEM acquired from remote sensing to generate the required TOPMODEL parameters for stream flow simulation which gives insights into better management of available water resources.
    Matched MeSH terms: Water Resources
  2. Shafika Sultan Abdullah, M.A. Malek, Namiq Sultan Abdullah, A. Mustapha
    Sains Malaysiana, 2015;44:1053-1059.
    Water scarcity is a global concern, as the demand for water is increasing tremendously and poor management of water resources will accelerates dramatically the depletion of available water. The precise prediction of evapotranspiration (ET), that consumes almost 100% of the supplied irrigation water, is one of the goals that should be adopted in order to avoid more squandering of water especially in arid and semiarid regions. The capabilities of feedforward backpropagation neural networks (FFBP) in predicting reference evapotranspiration (ET0) are evaluated in this paper in comparison with the empirical FAO Penman-Monteith (P-M) equation, later a model of FFBP+Genetic Algorithm (GA) is implemented for the same evaluation purpose. The study location is the main station in Iraq, namely Baghdad Station. Records of weather variables from the related meteorological station, including monthly mean records of maximum air temperature (Tmax), minimum air temperature (Tmin), sunshine hours (Rn), relative humidity (Rh) and wind speed (U2), from the related meteorological station are used in the prediction of ET0 values. The performance of both simulation models were evaluated using statistical coefficients such as the root of mean squared error (RMSE), mean absolute error (MAE) and coefficient of determination (R2). The results of both models are promising, however the hybrid model shows higher efficiency in predicting ET0 and could be recommended for modeling of ET0 in arid and semiarid regions.
    Matched MeSH terms: Water Resources
  3. Seyed Reza Saghravani, Ismail Yusoff, Sa’ari Mustapha, Seyed Fazlollah Saghravani
    Sains Malaysiana, 2013;42:553-560.
    Estimation and forecast of groundwater recharge and capacity of aquifer are essential issues in water resources investigation. In the current research, groundwater recharge, recharge coefficient and effective rainfall were determined through a case study using empirical methods applicable to the tropical zones. The related climatological data between January 2000 and December 2010 were collected in Selangor, Malaysia. The results showed that groundwater recharge was326.39 mm per year, effective precipitation was 1807.97 mm per year and recharge coefficient was 18% for the study area. In summary, the precipitation converted to recharge, surface runoff and evapotranspiration are 12, 32 and 56% of rainfall, respectively. Correlation between climatic parameters and groundwater recharge showed positive and negative relationships. The highest correlation was found between precipitation and recharge. Linear multiple regressions between
    recharge and measured climatologic data proved significant relationship between recharge and rainfall and wind speed. It was also proven that the proposed model provided an accurate estimation for similar projects.
    Matched MeSH terms: Water Resources
  4. Karimi-Googhari, Shahram, Huang, Yuk Feng, Abdul Halim B. Ghazali, Lee, Teang Shui
    MyJurnal
    Proper integrated management of a dam reservoir requires that all components of the water resource system be known. One of these components is the daily reservoir inflow which is the subject matter of this study, i.e. to establish predictions of what is coming in the next rainfall-runoff process over a catchment. The transformation of rainfall into runoff is an extremely complex, dynamic, and more of a non-linear process. The available six-year average daily rainfall data across the Sembrong dam catchment were computed using the well-known Theissen’s polygon method. Daily reservoir inflow data were extracted by applying the water balance model to the Sembrong dam reservoir. Modelling of relationship between rainfall and reservoir inflow data was done using feed-forward back-propagation neural networks. The final selected model has one hidden layer with 11 neurons in the hidden layer. The selected model was applied for an independent data series testing. Results in relation to specific climatic and hydrologic properties of a small tropical catchment suggested that the model is suitable to be used in forecasting the next day’s reservoir inflow. The efficiencies of the model Abtained indicated the validity of using the neural network for modelling reservoir inflow series.
    Matched MeSH terms: Water Resources
  5. Leila Khodapanah, Wan Nor Azmin Sulaiman
    MyJurnal
    Eshtehard aquifer located in southwest of Tehran province, Iran, provides a large amount of water requirement for inhabitants of Eshtehard district. Monitoring and analyzing of groundwater quality are important for protecting groundwater as sustainable water resource. One of the most advanced techniques for groundwater quality interpolation and mapping is geostatistics methods. The purposes of this study are (1) to investigate major ions concentration and their relative abundance to provide an overview of present groundwater chemistry and (2) to map the groundwater quality in the study area using geostatistics techniques. In this investigation, ArcGIS 9.2 was used for predicting spatial distribution of some groundwater characteristics such as: Chloride, Sulfate, pH, and Conductivity. These methods are applied for data from 44 wells within the study area. The final maps show that the south parts of the Eshtehard aquifer have suitable groundwater quality for human consumption and in general, the groundwater quality degrades south to north and west to east of the Eshtehard plain along the groundwater flow path.
    Matched MeSH terms: Water Resources
  6. Al-Hassoun, Saleh A., Mohammad, Thamer Ahmed
    MyJurnal
    Groundwater is the main source of water in the Kingdom of Saudi Arabia (KSA). A larger part of groundwater is founded in alluvial (unconfined) aquifers. Prediction of water table elevations in
    unconfined aquifers is very useful in water resources planning and management. During the last two
    decades, many aquifers in different regions of the KSA experienced significant groundwater decline.
    The declines in these aquifers raised concerns over the quantity and quality of groundwater, as well
    as concerns over the planning and management policies used in KSA. The main objective of this study was to predict water table fluctuations and to estimate the annual change in water table at an alluvial aquifer at wadi Hada Al Sham near Makkah, KSA. The methodology was achieved using numerical groundwater model (MODFLOW). The model was calibrated and then used to predict water table elevations due to pumping for a period of 5 years. The output of the model was found to be in agreement with the previous records. Moreover, the simulation results also show reasonable declination of water table elevations in the study area during the study period.
    Matched MeSH terms: Water Resources
  7. Oloruntade, A.J., Mohammad, T.A., Aimrun, W.
    MyJurnal
    Understanding rainfall trend can be a first step in the planning and management of water resources
    especially at the basin scale. In this study, standard tests are used to examine rainfall trends based on monthly, seasonal and mean annual series at the Niger-South Basin, Nigeria, between 1948 and 2008. Rainfall variability index showed that the decade 2000s was the driest (-2.1), while 1950s was the wettest (+0.8), with the decade 1980s being the driest in the second half of the last century, whereas the year 1983 was the driest throughout the series. Over the entire basin, rainfall variability was generally low, but higher intra-monthly than inter-annually. Annual rainfall was dominated by August, contributing about 15%, while December contributed the least (0.7%). On a seasonal scale, July-August-September (JJA) contributed over 40% of the annual rainfall, while rainfall was lowest during December-January-February (DJF) (4.5%). The entire basin displayed negative trends but only 15% indicated significant changes (α ‹ 0.1), while the magnitudes of change varied between -3.75 and -0.25 mm/yr. Similarly, only JJA exhibited insignificant upward trend, while the rest showed negative trends. About eight months of the year showed reducing trends, but only January trend was significant. Annual downward trend was generally observed in the series. The trend during 1948–1977 was negative, but it was positive for the 1978–2008 period. Hence, water resources management planning may require construction of water storage facilities to reduce summer flooding and prevent possible future water scarcity in the basin.
    Matched MeSH terms: Water Resources
  8. Guan Q, Kong W, Zhu D, Zhu W, Dufresne C, Tian J, et al.
    J Proteomics, 2021 01 16;231:104019.
    PMID: 33075550 DOI: 10.1016/j.jprot.2020.104019
    Salinity can induce Mesembryanthemum crystallinum to shift its photosynthesis from C3 to crassulacean acid metabolism (CAM), leading to enhanced plant water use efficiency. Studying how M. crystallinum changes its carbon fixation pathways is important for potential translation into crops and enhancing crop resilience. In this study, we examined proteomic changes in guard cells and mesophyll cells in the course of the C3 to CAM transition. We collected enriched guard cells and mesophyll cells during a short period of transition. A total of 1153 proteins were identified and quantified in the two cell-types. During the transition, proteins in the guard cells and mesophyll cells exhibited differential changes. For example, we observed nocturnal carbon fixation in mesophyll cells and proteins involved in cell growth in the two cell-types. Proteins involved in osmotic adjustment, ion transport, energy metabolism and light response may play important roles in the C3 to CAM transition. Real-time PCR experiments were conducted to determine potential correlations between transcript and protein levels. These results have highlighted potential molecular mechanisms underlying the C3 to CAM transition of guard cells and mesophyll cells of the important facultative CAM plant. BIOLOGICAL SIGNIFICANCE: Fresh water resource for agricultural food production is a global challenge. Nature has evolved crassulacean acid metabolism (CAM) plants with enhanced water use efficiency. Using single cell-type proteomics, this study revealed molecular changes taking place in guard cells and mesophyll cells during the shift of ice plant photosynthesis from C3 to CAM. The results have provided important insights into the CAM transition and may facilitate effort toward enhancing crop resilience for global food security.
    Matched MeSH terms: Water Resources
  9. Zomorodian M, Lai SH, Homayounfar M, Ibrahim S, Fatemi SE, El-Shafie A
    J Environ Manage, 2018 Dec 01;227:294-304.
    PMID: 30199725 DOI: 10.1016/j.jenvman.2018.08.097
    In recent years, water resources management has become more complicated and controversial due to the impacts of various factors affecting hydrological systems. System Dynamics (SD) has in turn become increasingly popular due to its advantages as a tool for dealing with such complex systems. However, SD also has some limitations. This review contains a comprehensive survey of the existing literature on SD as a potential method to deal with the complexity of system integrated modeling, with a particular focus on the application of SD to the integrated modeling of water resources systems. It discusses the limitations of SD in these contexts, and highlights a number of studies which have applied a combination of SD and other methods to overcome these limitations. Finally, our study makes a number of recommendations for future modifications in the application of SD methods in order to enhance their performance.
    Matched MeSH terms: Water Resources*
  10. Mustafa S, Bahar A, Aziz ZA, Darwish M
    J Contam Hydrol, 2020 Aug;233:103662.
    PMID: 32569923 DOI: 10.1016/j.jconhyd.2020.103662
    This article provides an analytical solute transport model to investigate the potential of groundwater contamination by polluted surface water in a two dimensional domain. The clogging of streambed which makes the aquifer partially penetrated by the stream, is considered in the model. The impacts of pumping process, hydraulic conductivity and clogging layer on the quality of water produced from nearby drinking water wells are evaluated. It is found that results are consistent with numerical simulation conducted by MODFLOW software. Moreover, the model is applied using data of contamination occurrence in Malaysia, where high contaminants concentrations are found close to streams. Results show that the pumping activities (rate and time period) are crucial factors when evaluating the risk of groundwater contamination from surface water. Additionally, this study illustrates that the increase in either hydraulic conductivity or leakance coefficient parameters due to the clogging layer will enlarge the area of contamination. The model is able to determine the suitable pumping rate and location of the well so that the contamination plume never reaches the extraction well, which is useful in constructing riverbank filtration sites.
    Matched MeSH terms: Water Resources
  11. Zaini Hamzah, Wan Noorhayani Wan Rosdi, Abdul Khalik Wood
    MyJurnal
    Well water is a renewable natural resources and one of the drinking water sources. The well water may constituted of dissolved essential chemicals such as K+, Ca''+ and Na+ ; and natural radionuclides such as radioisotopes from uranium-thorium decay series. The geology and mineral composition of the soil will determined the kinds and levels of chemical contents in the groundwater resources. The water flows through the geological formation and dissolved the chemicals before reaching the aquifers. To evaluate how much chemicals and natural radioactive in the water resources, a study has been carried out. Well water samples in this study were taken from 3 districts in Kelantan, which is Bachok, Machang and Kuala Krai. Similarly, in situ water quality parameters were measured using YSI portable water quality parameter include pH, salinity, dissolve oxygen(DO), conductivity, turbidity and total dissolved solids(TDS). The concentrations of K', Ca" and Na' were determined using Energy Dispersive X-ray Fluorescence (EDXRF). Five ml of filtered sample was pipette into the sample cup and, irradiated and measured for 100 seconds counting times. The type of filter used for measuring If+ and Cat{ was Al-thin and default for Nat The ranged of concentration of Kt Ce and Na+ is 23.04-251.89, 3.12-.45.41, and 3.71-125.75 ppm, respectively.
    Matched MeSH terms: Water Resources
  12. Hossain K, Quaik S, Ismail N, Rafatullah M, Avasan M, Shaik R
    Iran J Biotechnol, 2016 Sep;14(3):154-162.
    PMID: 28959331 DOI: 10.15171/ijb.1216
    BACKGROUND: Application of membrane technology to wastewater treatment has expanded over the last decades due to increasingly stringent legislation, greater opportunities for water reuse/recycling processes and continuing advancement in membrane technology.

    OBJECTIVES: In the present study, a bench-scale submerged microfiltration membrane bioreactor (MBR) was used to assess the treatment of textile wastewater.

    MATERIALS AND METHODS: The decolorization capacity of white-rot fungus coriolus versicolor was confirmed through agar plate and liquid batch studies. The temperature and pH of the reactor were controlled at 29±1°C and 4.5±2, respectively. The bioreactor was operated with an average flux of 0.05 m.d(-1) (HRT=15hrs) for a month.

    RESULTS: Extensive growth of fungi and their attachment to the membrane led to its fouling and associated increase of the transmembrane pressure requiring a periodic withdrawal of sludge and membrane cleaning. However, stable decoloration activity (approx. 98%), BOD (40-50%), COD (50-67%) and total organic carbon (TOC) removal (>95%) was achieved using the entire system (fungi + membrane), while the contribution of the fungi culture alone for TOC removal, as indicated by the quality of the reactor supernatant, was 35-50% and 70%, respectively.

    CONCLUSIONS: The treated wastewater quality satisfied the requirement of water quality for dyeing and finishing process excluding light coloration. Therefore, textile wastewater reclamation and reuse is a promising alternative, which can both conserve or supplement the available water resource and reduce or eliminate the environmental pollution.

    Matched MeSH terms: Water Resources
  13. Allawi MF, Jaafar O, Mohamad Hamzah F, Abdullah SMS, El-Shafie A
    Environ Sci Pollut Res Int, 2018 May;25(14):13446-13469.
    PMID: 29616480 DOI: 10.1007/s11356-018-1867-8
    Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research. During the last two decades, artificial intelligence (AI) techniques have been significantly utilized for attaining a robust modeling to handle different stochastic hydrological parameters. AI techniques have also shown considerable progress in finding optimal rules for reservoir operation. This review research explores the history of developing AI in reservoir inflow forecasting and prediction of evaporation from a reservoir as the major components of the reservoir simulation. In addition, critical assessment of the advantages and disadvantages of integrated AI simulation methods with optimization methods has been reported. Future research on the potential of utilizing new innovative methods based AI techniques for reservoir simulation and optimization models have also been discussed. Finally, proposal for the new mathematical procedure to accomplish the realistic evaluation of the whole optimization model performance (reliability, resilience, and vulnerability indices) has been recommended.
    Matched MeSH terms: Water Resources/supply & distribution*
  14. Malik A, Tikhamarine Y, Sammen SS, Abba SI, Shahid S
    PMID: 33751346 DOI: 10.1007/s11356-021-13445-0
    Drought is considered one of the costliest natural disasters that result in water scarcity and crop damage almost every year. Drought monitoring and forecasting are essential for the efficient management of water resources and sustainability in agriculture. However, the design of a consistent drought prediction model based on the dynamic relationship of the drought index with its antecedent values remains a challenging task. In the present research, the SVR (support vector regression) model was hybridized with two different optimization algorithms namely; Particle Swarm Optimization (PSO) and Harris Hawks Optimization (HHO) for reliable prediction of effective drought index (EDI) 1 month ahead, at different locations of Uttarakhand State of India. The inputs of the models were selected through partial autocorrelation function (PACF) analysis. The output produced by the SVR-HHO and SVR-PSO models was compared with the EDI estimated from observed data using five statistical indicators, i.e., RMSE (Root Mean Square Error), MAE (Mean Absolute Error), COC (Coefficient of Correlation), NSE (Nash-Sutcliffe Efficiency), WI (Willmott Index), and graphical inspection of radar-chart, time-variation plot, box-whisker plot, and Taylor diagram. Appraisal of results indicates that the SVR-HHO model (RMSE = 0.535-0.965, MAE = 0.363-0.622, NSE = 0.558-0.860, COC = 0.760-0.930, and WI = 0.862-0.959) outperformed the SVR-PSO model (RMSE = 0.546-0.967, MAE = 0.372-0.625, NSE = 0.556-0.855, COC = 0.758-0.929, and WI = 0.861-0.956) in predicting EDI. Visual inspection of model performances also showed a better performance of SVR-HHO compared to SVR-PSO in replicating the median, inter-quartile range, spread, and pattern of the EDI estimated from observed rainfall. The results indicate that the hybrid SVR-HHO approach can be utilized for reliable EDI predictions in the study area.
    Matched MeSH terms: Water Resources
  15. Allawi MF, Aidan IA, El-Shafie A
    Environ Sci Pollut Res Int, 2021 Feb;28(7):8281-8295.
    PMID: 33052565 DOI: 10.1007/s11356-020-11062-x
    The accuracy level for reservoir evaporation prediction is an important issue for decision making in the water resources field. The traditional methods for evaporation prediction could encounter numerous obstacles owing to the effect of several parameters on the shape of the evaporation pattern. The current research presented modern model called the Coactive Neuro-Fuzzy Inference System (CANFIS). Modification for such model has been achieved for enhancing the evaporation prediction accuracy. Genetic algorithm was utilized to select the effective input combination. The efficiency of the proposed model has been compared with popular artificial intelligence models according to several statistical indicators. Two different case studies Aswan High Dam (AHD) and Timah Tasoh Dam (TTD) have been considered to explore the performance of the proposed models. It is concluded that the modified GA-CANFIS model is better than GA-ANFIS, GA-SVR, and GA-RBFNN for evaporation prediction for both case studies. GA-CANFIS attained minimum RMSE (15.22 mm month-1 for AHD, 8.78 mm month-1 for TTD), minimum MAE (12.48 mm month-1 for AHD, 5.11 mm month-1 for TTD), and maximum determination coefficient (0.98 for AHD, 0.95 for TTD).
    Matched MeSH terms: Water Resources
  16. Banadkooki FB, Ehteram M, Ahmed AN, Teo FY, Ebrahimi M, Fai CM, et al.
    Environ Sci Pollut Res Int, 2020 Oct;27(30):38094-38116.
    PMID: 32621196 DOI: 10.1007/s11356-020-09876-w
    Suspended sediment load (SSL) estimation is a required exercise in water resource management. This article proposes the use of hybrid artificial neural network (ANN) models, for the prediction of SSL, based on previous SSL values. Different input scenarios of daily SSL were used to evaluate the capacity of the ANN-ant lion optimization (ALO), ANN-bat algorithm (BA) and ANN-particle swarm optimization (PSO). The Goorganrood basin in Iran was selected for this study. First, the lagged SSL data were used as the inputs to the models. Next, the rainfall and temperature data were used. Optimization algorithms were used to fine-tune the parameters of the ANN model. Three statistical indexes were used to evaluate the accuracy of the models: the root-mean-square error (RMSE), mean absolute error (MAE) and Nash-Sutcliffe efficiency (NSE). An uncertainty analysis of the predicting models was performed to evaluate the capability of the hybrid ANN models. A comparison of models indicated that the ANN-ALO improved the RMSE accuracy of the ANN-BA and ANN-PSO models by 18% and 26%, respectively. Based on the uncertainty analysis, it can be surmised that the ANN-ALO has an acceptable degree of uncertainty in predicting daily SSL. Generally, the results indicate that the ANN-ALO is applicable for a variety of water resource management operations.
    Matched MeSH terms: Water Resources
  17. Meo MS, Sabir SA, Arain H, Nazar R
    Environ Sci Pollut Res Int, 2020 Jun;27(16):19678-19687.
    PMID: 32219658 DOI: 10.1007/s11356-020-08361-8
    The current study explores the relationship between water resources and tourism in South Asia for the period of 1995-2017. The study employs the CIPS unit root test for stationarity of the variables and the CD test for cross-sectional dependence among cross-sectional units. As for the long-run parameters, a novel technique, known as dynamic common correlated effect (DCCE) model, is used which was recently developed by Chudik and Pesaran (J Econ 188:393-420, 2015b). The outcomes from the DCCE method suggest that water resources have a positive impact on tourism in South Asia. It is also proven that ignoring cross-sectional dependence among the cross-sectional units may bring about misleading outcomes. The findings of the study can be helpful for policymakers to understand the role of water resources in boosting tourism and contributing to the economic prosperity of South Asian countries.
    Matched MeSH terms: Water Resources*
  18. Rafindadi AA, Yusof Z, Zaman K, Kyophilavong P, Akhmat G
    Environ Sci Pollut Res Int, 2014 Oct;21(19):11395-400.
    PMID: 24898296 DOI: 10.1007/s11356-014-3095-1
    The objective of the study is to examine the relationship between air pollution, fossil fuel energy consumption, water resources, and natural resource rents in the panel of selected Asia-Pacific countries, over a period of 1975-2012. The study includes number of variables in the model for robust analysis. The results of cross-sectional analysis show that there is a significant relationship between air pollution, energy consumption, and water productivity in the individual countries of Asia-Pacific. However, the results of each country vary according to the time invariant shocks. For this purpose, the study employed the panel least square technique which includes the panel least square regression, panel fixed effect regression, and panel two-stage least square regression. In general, all the panel tests indicate that there is a significant and positive relationship between air pollution, energy consumption, and water resources in the region. The fossil fuel energy consumption has a major dominating impact on the changes in the air pollution in the region.
    Matched MeSH terms: Water Resources*
  19. Abbas Khan K, Zaman K, Shoukry AM, Sharkawy A, Gani S, Sasmoko, et al.
    Environ Sci Pollut Res Int, 2019 May;26(14):14287-14299.
    PMID: 30864039 DOI: 10.1007/s11356-019-04755-5
    The objective of the study is to examine the impact of natural disasters on external migration, price level, poverty incidence, health expenditures, energy and environmental resources, water demand, financial development, and economic growth in a panel of selected Asian countries for a period of 2005-2017. The results confirm that natural disasters in the form of storm and flood largely increase migration, price level, and poverty incidence, which negatively influenced country's economic resources, including enlarge healthcare expenditures, high energy demand, and low economic growth. The study further presented the following results: i) natural resource depletion increases external migration, ii) FDI inflows increase price level, iii) increase healthcare spending and energy demand decreases poverty headcount, iv) poverty incidence and mortality rate negatively influenced healthcare expenditures, v) industrialization increases energy demand, and vi) agriculture value added, fertilizer, and cereal yields required more water supply to produce greater yield. The study emphasized the need to magnify the intensity of natural disasters and create natural disaster mitigation unit to access the human and infrastructure cost and attempt quick recovery for global prosperity.
    Matched MeSH terms: Water Resources/supply & distribution*
  20. Fulazzaky MA, Syafiuddin A, Muda K, Martin AY, Yusop Z, Ghani NHA
    Environ Sci Pollut Res Int, 2023 Dec;30(58):121865-121880.
    PMID: 37962755 DOI: 10.1007/s11356-023-30967-x
    This paper reviewed the impacts of climate change on the management of the water sector in Malaysia discussing the current status of water resources, water service, and water-related disasters. The implementation of engineering practices was discussed to provide the detailed assessment of climate change impacts, risks, and adaptation for sustainable development. The narrative methods of reviewing the literatures were used to get an understanding on the engineering practices of water infrastructures, implication of the government policies, and several models as the main motivation behind the concept of integrated water resource management to contribute as part of the sustainable development goals to achieve a better and more sustainable future for all. The findings of this review highlighted the impacts of climate change on the rivers, sea, lakes, dams, and groundwater affecting the availability of water for domestic and industrial water supplies, irrigation, hydropower, and fisheries. The impacts of climate change on the water-related disasters have been indicated affecting drought-flood abrupt alternation and water pollution. Challenges of water management practices facing climate change should be aware of the updated intensity-duration-frequency curves, alternative sources of water, effective water demand management, efficiency of irrigation water, inter-basin water transfer, and nonrevenue water. The transferability of this review findings contribute to an engagement with the society and policy makers to mobilize for climate change adaptation in the water sector.
    Matched MeSH terms: Water Resources*
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