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.
Branching channel flow refers to any side water withdrawals from rivers or main channels.
Branching channels have wide application in many practical projects, such as irrigation and drainage
network systems, water and waste water treatment plants, and many water resources projects. In the
last decades, extensive theoretical and experimental investigations of the branching open channels
have been carried out to understand the characteristics of this branching flow, varying from case
studies to theoretical and experimental investigations. The objectives of this paper are to review and
summarise the relevant literatures regarding branching channel flow. These literatures were reviewed
based on flow characteristics, physical characteristics, and modeling of the branching flow.
Investigations of the flow into branching channel show that the branching discharge depends on many
interlinked parameters. It increases with the decreasing of the main channel flow velocity and Froude
number at the upstream of the branch channel junction. Also it increases with the increasing of the
branch channel bed slope. In subcritical flow, water depth in the branch channel is always lower than
the main channel water depth. The flow diversion to the branch channel leads to an increase of water
depth at the downstream of the main channel. From the review, it is important to highlight that most
of the study concentrated on flow characteristics in a right angle branch channel with a rigid boundary.
Investigations on different branching angles with movable bed have still to be explored.
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.
The aim of the current study was to produce groundwater spring potential maps using novel ensemble weights-of-evidence (WoE) with logistic regression (LR) and functional tree (FT) models. First, a total of 66 springs were identified by field surveys, out of which 70% of the spring locations were used for training the models and 30% of the spring locations were employed for the validation process. Second, a total of 14 affecting factors including aspect, altitude, slope, plan curvature, profile curvature, stream power index (SPI), topographic wetness index (TWI), sediment transport index (STI), lithology, normalized difference vegetation index (NDVI), land use, soil, distance to roads, and distance to streams was used to analyze the spatial relationship between these affecting factors and spring occurrences. Multicollinearity analysis and feature selection of the correlation attribute evaluation (CAE) method were employed to optimize the affecting factors. Subsequently, the novel ensembles of the WoE, LR, and FT models were constructed using the training dataset. Finally, the receiver operating characteristic (ROC) curves, standard error, confidence interval (CI) at 95%, and significance level P were employed to validate and compare the performance of three models. Overall, all three models performed well for groundwater spring potential evaluation. The prediction capability of the FT model, with the highest AUC values, the smallest standard errors, the narrowest CIs, and the smallest P values for the training and validation datasets, is better compared to those of other models. The groundwater spring potential maps can be adopted for the management of water resources and land use by planners and engineers.
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.
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.
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.
In low concentration, fluoride is considered a necessary compound for human health. Exposure to high concentrations of fluoride is the reason for a serious disease called fluorosis. Fluorosis is categorized as Skeletal and Dental fluorosis. Several Asian countries, such as India, face contamination of water resources with fluoride. In this study, a comprehensive overview on fluoride contamination in Asian water resources has been presented. Since water contamination with fluoride in India is higher than other Asian countries, a separate section was dedicated to review published articles on fluoride contamination in this country. The status of health effects in Asian countries was another topic that was reviewed in this study. The effects of fluoride on human organs/systems such as urinary, renal, endocrine, gastrointestinal, cardiovascular, brain, and reproductive systems were another topic that was reviewed in this study. Different methods to remove fluoride from water such as reverse osmosis, electrocoagulation, nanofiltration, adsorption, ion-exchange and precipitation/coagulation were introduced in this study. Although several studies have been carried out on contamination of water resources with fluoride, the situation of water contamination with fluoride and newly developed technology to remove fluoride from water in Asian countries has not been reviewed. Therefore, this review is focused on these issues: 1) The status of fluoride contamination in Asian countries, 2) health effects of fluoride contamination in drinking water in Asia, and 3) the existing current technologies for defluoridation in Asia.
Conventional hydrogeologic framework models used to compute ocean island sustainable yields and aquifer storage neglect the complexity of the nearshore and offshore submarine environment. However, the onshore aquifer at the island of Hawai'i exhibits a notable volumetric discrepancy between high-elevation freshwater recharge and coastal discharge. In this study, we present a novel transport mechanism of freshwater moving from onshore to offshore through a multilayer formation of water-saturated layered basalts with interbedded low-permeability layers of ash/soil. Marine electromagnetic imaging reveals ∼35 km of laterally continuous resistive layers that extend to at least 4 km from west of Hawai'i's coastline, containing about 3.5 km3 of freshened water. We propose that this newly found transport mechanism of fresh groundwater may be the governing mechanism in other volcanic islands. In such a scenario, volcanic islands worldwide can use these renewable offshore reservoirs, considered more resilient to climate change-driven droughts, as new water resources.
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.
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.
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*
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).
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.
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.
Climate change-induced spatial and temporal variability of stremflow has significant implications for hydrological processes and water supplies at basin scale. This study investigated the impacts of climate change on streamflow of the Kurau River Basin in Malaysia using a Climate-Smart Decision Support System (CSDSS) to predict future climate sequences. For this, we used 25 reliazations consisting from 10 Global Climate Models (GCMs) and three IPCC Representative Concentration Pathways (RCP4.5, RCP6.0 and RCP8.5). The generated climate sequences were used as input to Soil and Water Assessment Tool (SWAT) to simulate projected changes in hydrological processes in the basin over the period 2021-2080. The model performed fairly well for the Kurau River Basin, with coefficient of determination (R2), Nash-Sutcliffe Efficiency (NSE) and Percent Bias (PBIAS) of 0.65, 0.65 and -3.0, respectively for calibration period (1981-1998) and 0.60, 0.59 and -4.6, respectively for validation period (1996-2005). Future projections over 2021-2080 period show an increase in rainfall during August to January (relatively wet season, called the main irrigation season) but a decrease in rainfall during February to July (relatively dry season, called the off season). Temperature projections show increase in both the maximum and minimum temperatures under the three RCP scenarios, with a maximum increase of 2.5 °C by 2021-2080 relative to baseline period of 1976-2005 under RCP8.5 scenario. The model predicted reduced streamflow under all RCP scenarios compared to the baseline period. Compared to 2021-2050 period, the projected streamflow will be higher during 2051-2080 period by 1.5 m3/s except in February for RCP8.5. The highest streamflow is predicted during August to December for both future periods under RCP8.5. The seasonal changes in streamflow range between -2.8% and -4.3% during the off season, and between 0% (nil) and -3.8% during the main season. The assessment of the impacts of climatic variabilities on the available water resources is necessary to identify adaptation strategies. It is supposed that such assessment on the Kurau River Basin under changing climate would improve operation policy for the Bukit Merah reservoir located at downstream of the basin. Thus, the predicted streamflow of the basin would be of importance to quantify potential impacts of climate change on the Bukit Merah reservoir and to determine the best possible operational strategies for irrigation release.
The water chemistry of selected rivers in Kota Marudu, Sabah was studied based on the major ion chemistry and its suitability for drinking and irrigation purposes. Ten sampling stations were selected and water samples were collected from each station to assess its chemical properties. The physico-chemical variables including temperature, electrical conductivity (EC), total dissolved solids (TDS), salinity, dissolved oxygen (DO), pH, turbidity, ammoniacal-nitrogen (NH3-N), biological oxygen demand (BOD), chemical oxygen demand (COD) and total suspended solid (TSS) were measured. The cations (K, Mg, Ca, Na) were analyzed by ICP-MS. Most of the variables were within the drinking water quality standards stipulated by the World Health Organization (WHO) and the Ministry of Health (MOH), Malaysia except for turbidity. Sodium adsorption ratio (SAR) and salinity hazard were calculated to identify the suitability of the water as irrigation water. The Wilcox diagram classifies that only 10% of samples are not suitable for the purpose of irrigation. The overall results showed that most of the rivers in Kota Marudu are still in a clean condition and suitable for drinking and irrigation purposes except for Sumbilingan River, which is considered as slightly polluted. The results are supported by the hierarchical cluster analysis as the stations were grouped into two groups; low and high pollution intensities. This preliminary result can update the baseline data of selected water quality parameters in the Kota Marudu and could serve as tool for assisting relevant government bodies in regulating the water resources policies in the future.
Managers of water quality and water monitoring programs are often faced with constraints in terms of budget, time, and laboratory capacity for sample analysis. In such situation, the ideal solution is to reduce the number of sampling sites and/or monitored variables. In this case, selecting appropriate monitoring sites is a challenge. To overcome this problem, this study was conducted to statistically assess and identify the appropriate sampling stations of monitoring network under the monitored parameters. To achieve this goal, two sets of water quality data acquired from two different monitoring networks were used. The hierarchical agglomerative cluster analysis (HACA) were used to group stations with similar characteristics in the networks, the time series analysis was then performed to observe the temporal variation of water quality within the station clusters, and the geo-statistical analysis associated Kendall's coefficient of concordance were finally applied to identify the most appropriate and least appropriate sampling stations. Based on the overall result, five stations were identified in the networks that contribute the most to the knowledge of water quality status of the entire river. In addition, five stations deemed less important were identified and could therefore be considered as redundant in the network. This result demonstrated that geo-statistical technique coupled with Kendall's coefficient of concordance can be a reliable method for water resource managers to identify appropriate sampling sites in a river monitoring network.
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*
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.