Water Resources Management Strategies Research Articles

Evaluating the effects of heatwave events on hydrological processes in the contiguous United States (2003–2022)

Extreme heat and drought conditions are affecting water availability in many regions worldwide, leading to negative impacts on human societies, agriculture, and ecosystems. However, current research lacks comprehensive spatiotemporal analysis examining the interplay between multiple hydrological factors and heatwave events, especially in the context of climate change. This research broadly pertains to understanding the dynamics of hydrological factors and their potential responses to heatwave during warm seasons across the contiguous United States for the period from 2003 to 2022. Utilizing data from the Global Land Data Assimilation System (GLDAS), we analyzed surface runoff, evapotranspiration (ET), precipitation, Groundwater Storage (GWS), Root Zone Soil Moisture (RZSM), and Total Water Storage (TWS) to discern annual patterns and the impacts of heatwave. The spatial patterns of heatwave highlighted a higher occurrence in the western, central, and northeastern U.S., with longer average durations in the western and south-central regions. These events are predominantly dry, characterized by low Relative Humidity (RH), except in the southeastern U.S., where heatwave coincide with high RH levels. Post-heatwave analysis indicated a reduction in GWS, TWS, RZSM, and ET, alongside an increase in surface runoff, RH, and precipitation. An in-depth examination of rainfall and temperature dynamics during heatwave revealed weak correlations between rainfall and temperature, as well as between rainfall and heatwave duration, highlighting the complex nature of these interactions. The study also found an enhanced probability of rainfall following heatwave, particularly in the eastern regions, drawing attention to the potential for increased flood risks post-heatwave. Our findings contribute to the growing body of knowledge on the impacts of heatwave on hydrological factors, providing valuable insights for climate change adaptation and water resource management strategies.

Resident water conservation behaviors among different age groups in rural areas of the Weibei arid belt, China

Understanding water conservation behaviors across various age groups is crucial for developing effective water resource management strategies particularly in arid and semiarid zones. Based on a semi-structural questionnaire survey of 445 households in China's Weibei arid belt and extended Theory of Planned Behavior Model, a Structural Equation Model (SEM) was constructed to elucidate the age-related impact of water conservation knowledge, attitudes, subjective norms, and perceived control on water-saving behaviors. The results show that (1) youth group prioritizes personal hygiene and laundry activities whereas the elderly exhibit lower such requirements. (2) Water consumption varies significantly by age, with the elderly group consumes the least, averaging 62.26 L per capita per day (Lpcd), followed by the middle-aged group at 73.95 Lpcd, and the youth at the highest consumption rate of 84.60 Lpcd. (3) Influential factors on water conservation behavior differ substantially by age: Among the youth, water conservation behavior is strongly influenced by attitude in this domain (standardized path coefficient [SPC] = 0.32). The middle-aged group is influenced by subjective norms (SPC = 0.27) and attitudes toward water conservation (SPC = 0.27). Conversely, the elder group's behavior is dominated by knowledge (SPC = 0.35) and perceived control (SPC = 0.32). Given such distinct perceptions and behaviors of household water consumption, tailored water conservation strategies are essential of water conservation education through social media for youth, tiered pricing for the middle-aged, and water-saving subsidies to the elderly in the case areas.

Evaluating the impacts of climate change and land-use change on future droughts in northeast Thailand

The impacts of climate change (CC) on droughts are well documented, but the effects of land-use change (LUC) are poorly understood. This study compares the projected individual and combined impacts of these stressors on future droughts (2021–2050), with respect to baseline (1981–2010) in one of the major tributaries of the Mekong River. LUC impacts on hydrological droughts are minimal compared to CC, with the latter expected to shorten the recurrence interval of a 20-year return period event to every 14 years. Both CC and LUC have significant impacts on agricultural droughts with heightened sensitivity. ‘Once in a Decade’ agricultural droughts will be 40% (35%) longer and 88% (87%) more severe under the CC (LUC) scenario. Under both stressors, the events occurring every 20 years will be twice as frequent. Results highlight the intensification of future droughts and the urgency for actions to mitigate/adapt to climate change and manage land use. Future policy shall holistically address agricultural water management, sustainable land use management, and crop management to cope with future droughts. We recommend developing resilient agricultural practices, enhanced water resource management strategies, and incorporating drought risk into land-use planning to mitigate the compounded impacts of CC and LUC.

Cryogenic Pits and Quaternary Glacial Evidence in Central Iran

Quaternary glaciation studies in Central Iran reveal that it is not implausible to anticipate glaciation traces in this region. It is feasible to provide conclusive evidence about the behavior of ice sheets by referring to geomorphological factors and climatic statistical analyses. Factors such as flatness and accidental geographical features contribute to the existence of ice sheets in the Namdan Fars region. The digital reconstruction of past climatic conditions، using the Wright method، along with the absence of lake terraces around Kaftar Lake، signifies the presence of ice instead of water in the lake. The multi-axial morphology of the Namdan Plain، the shape and form of main valleys and passes، and the existence of numerous glacial cirque traces in the surrounding heights are also indicators of this phenomenon. The lack of evidence of ancient settlements in the plain، despite the availability of water and fertile soil، can be attributed to the region's historical thermal conditions. Investigating ancient glaciers helps us understand the natural history of the land. This knowledge can aid planners in devising macro strategies for regional development and water resource management، as glacial performance has always been associated with optimal water levels. Although glacial activities can create aquifers، the movement of ice sheets or ice surfaces does not support the accumulation of sediments required for creating aquifers with sufficient water storage. Instead، their performance leads to the creation of suitable agricultural soil layers. In summary، regional glaciers play a positive role in transforming and creating favorable agricultural soils and can be beneficial in adapting to climatic changes and extending statistical periods.

Investigation and classification of water resources management strategies: possible threats and solutions

Investigation and classification of water resources management strategies: possible threats and solutions

Effects of climate variability and/or land use dynamics on the hydrological balance of the Cavally river catchment at Toulepleu, West Africa

Abstract The study focuses on assessing the individual and combined impacts of climate variability and land use change on hydrological responses. The results indicate that the basin, urban area, cropland, degraded forest, and open forest shows an increasing trend, while gallery forest show a decreasing trend over the period 1992–2015. Climatic variability is marked by two climatic periods (a wet one from 1980 to 1996 and a dry one from 1997 to 2016) with a 35% decrease in rainfall. Regardless of the state of the landcover used, the simulated mean annual runoff decreases by 67.92% between the wet and dry climate periods. Changes in land use between 1992 and 2015 reduce mean annual runoff by 4.71%. Analysis of the joint effect of climatic and LU variation shows a 68.96% reduction in runoff. In this catchment, the joint impact has a clearly greater effect on runoff than the climatic impact, which is greater than that of human activities. There is a need for policymakers to prioritise sustainable land use practices and integrated water resource management strategies in the area to mitigate the combined effects of climate variability and anthropogenic activities, ensuring the long-term resilience of the ecosystem and water availability for local communities.

Projected water availability in the Tawa River Basin India in changing climate

The Tawa River is one among the major southern tributary of the Narmada River in India, exhibiting substantial variation in rainfall, altering the water availability. The variation in water availability effect the hydrological characteristics such groundwater recharge, soil moisture level, water balance. Studying rainfall-runoff conversion is necessary for proper and sustainable surface and ground water resources planning and management. In the changing climate, it becomes imperative to understand the hydrological response and project water availability for sustainable water management. In this work, the MIKE 11 NAM model is calibrated and validated to evaluate the climate change impact on availability of water. Using the outputs of downscaled, bias-corrected data of CMIP6, the future projection of runoff is done for the near century, mid-century and end century under the scenario SSP245 and SSP 585. MPI-ESM1-2-HRand EC-EARTH 3-VEG climate models were selected. Temporal analysis was performed to evaluate the impact on the availability of water at the 50%, 75% and 90% percentage dependability flow. The annual analysis revealed that scenario SSP5-8.5 has a higher increase in the runoff than SSP2- 4.5, mainly for the end century, as depicted by both the models. Monthly analysis revealed strong intra-seasonal variations and highlighted that August is projected as the most active month of the year, and wet seasons displayed a larger change than dry seasons. The findings indicate that climate change shall significantly influence hydrological processes in the Tawa watershed and potentially impact the availability of water in the Tawa River basin. Our study underscores the imperative need to adapt water resource planning and management strategies to mitigate the potential impacts of climate change on the availability of water in the Tawa River basin.

Hydrochemical characterisation of a landslide prone area, South Western Ghats, India

ABSTRACT This study focuses on the Manimala River Basin (MMRB) situated in the Western Ghats region of Kerala, which has been significantly affected by landslides. The water quality in the MMRB is likely to be impacted by heavy rainfall and the resulting debris flows. A comprehensive analysis was conducted for 157 water samples collected from the MMRB, with an objective to evaluate the hydrogeological conditions and estimation of 23 physico-chemical parameters to determine the water quality. Pearson’s correlation matrix for geochemical data was performed to investigate the relationships among physical and chemical parameters, and various ions in the MMRB. The present study also aimed to identify the dominant geochemical facies present in the water samples and determine the geochemical processes responsible for modifying the hydrochemistry. The results revealed that elevated concentrations of Ca2+ and SO4 2- ions, which exert influence on the hydrochemistry of the region. Moreover, we utilized a fuzzy logic tool to categorize the water samples based on a water quality index, which indicated that approximately 92% of the MMRB samples are suitable for human consumption. This study offers valuable insights into the interplay of geochemical factors and water quality assessment, contributing to effective strategies for water resource management and conservation.

Advancing understanding of lake–watershed hydrology: a fully coupled numerical model illustrated by Qinghai Lake

Abstract. Understanding the intricate hydrological interactions between lakes and their surrounding watersheds is pivotal for advancing hydrological research, optimizing water resource management, and informing climate change mitigation strategies. Yet, these complex dynamics are often insufficiently captured in existing hydrological models, such as the bi-direction surface and subsurface flow. To bridge this gap, we introduce a novel lake–watershed coupled model, an enhancement of the Simulator of Hydrological Unstructured Domains. This high-resolution, distributed model employs unstructured triangles as its fundamental hydrological computing units (HCUs), offering a physical approach to hydrological modeling. We validated our model using data from Qinghai Lake in China, spanning from 1979 to 2018. Remarkably, the model not only successfully simulated the streamflow of the Buha River, a key river within the Qinghai Lake basin, achieving a Nash–Sutcliffe efficiency (NSE) of 0.62 and 0.76 for daily and monthly streamflow, respectively, but also accurately reproduced the decrease–increase U-shaped curve of lake level change over the past 40 years, with an NSE of 0.71. Our model uniquely distinguishes the contributions of various components to the lake's long-term water balance, including river runoff, surface direct runoff, lateral groundwater contribution, direct evaporation, and precipitation. This work underscores the potential of our coupled model as a powerful tool for understanding and predicting hydrological processes in lake basins, thereby contributing to more effective water resource management and climate change mitigation strategies.

Simulation of national-scale groundwater dynamics in geologically complex aquifer systems: an example from Great Britain

ABSTRACT The national-scale British Groundwater Model (BGWM) is implemented to simulate groundwater dynamics and budgets in Great Britain. Notwithstanding the challenges of integrating a very large amount of data, finding a trade-off between computational efficiency and realism, performing automatic calibration, and addressing multiple sources of structural and parameter uncertainty, a quantitative–qualitive evaluation approach showed that the BGWM provides a reasonably accurate digital representation of groundwater systems and processes at a national scale. In this work, the model was applied to understand the variability of budget components across multiple spatial and temporal scales. Comparisons showed regional differences linked to lithological and climatic factors, which in turn can be associated with more or less groundwater resilience to extreme climatic events. There is confidence that the current and future versions of the BGWM can become valuable tools for effective water resources management and adaptation strategies under future climatic and population changes.

Utilizing waveform synthesis in harmonic oscillator seasonal trend model for short- and long-term streamflow drought modeling and forecasting

ABSTRACT This study introduces an improved version of the harmonic oscillator seasonal trend (HOST) model framework to accurately simulate medium- and long-term changes in extreme events, focusing on streamflow droughts in the Mobile River catchment. The updated model incorporates new mathematical formulas and waveform synthesis, resulting in improved performance. The updated framework successfully captures long-term and seasonal patterns with a Kling -Gupta efficiency exceeding 0.5 for seasonal fluctuations and over 0.9 for trends. The best-fit model explains around 98% of long-term and approximately 55% of seasonal variance. Test sets show slightly lower accuracies, with about 20% of nodes underperforming due to the absence of drought during the test phase resulting in false-positive model forecasts. The newly developed weighted occurrence classification outperforms the binary classification occurrence model. In addition, application of an automatic period multiplier for decomposition using the seasonal trend decomposition using LOESS (locally estimated scatterplot smoothing) method improves test dataset performance and reduces false-positive forecasts. The improved framework provides valuable insights for extreme flow distribution, offering potential for improved water management planning, and the combination of the HOST model with physical models can address short-term drivers of extreme events, enhancing drought occurrence forecasting and water resource management strategies.

Seasonal dynamics of water and sediment in the permafrost basin of the Qinghai‐Tibet plateau and its driving factors

AbstractClimate change has regulated cryosphere‐fed rivers and altered interannual and seasonal sediment dynamics, with significant implications for terrestrial material cycles and downstream aquatic ecosystems. However, there has been a notable scarcity of research focusing on the patterns of water–sediment transport within these permafrost zones. Integrating 6 years (2017–2022) of in‐situ observational data from FengHuoShan basin with the partial least squares‐structural equation modelling (PLS‐SEM) method, we analyse the driving factors, characteristics and seasonal patterns of the water–sediment transport process. We observed a gradual increase in both suspended sediment flux (SSF, Mt/yr) and runoff (Q, km3/yr) within the basin, with annual growth rates of 1.34%/yr and 0.75%/yr, respectively. It is worth noting that these growth rates exhibit seasonal variations, with the highest values observed in spring (SSF: 1.76%/yr, Q: 1.71%/yr). This indicates that the response to climate change is more pronounced in spring compared with summer and autumn. Through mathematical statistics and the PLS‐SEM model, we found that temperature plays a predominant role in the dynamics of water–sediment in both spring and autumn, whereas rainfall exerts a more significant impact during the summer. Most suspended sediment concentration (SSC, kg/m3) peak events throughout the year are primarily driven by rainfall. Affected by the freeze–thaw cycle of permafrost, SSC and discharge (Q, m3/s) exhibit distinct seasonality. SSC and Q demonstrate a clockwise trend; both Q and SSC begin to increase from May and peak in August before declining. The insights gleaned from this study hold significant implications for water resource management and soil conservation strategies in the region, particularly in the face of ongoing climatic changes characterized by warming and increased humidity.

Assessing Nitrate Leaching and Runoff Coefficients in the Dynamic Interplay of Seasonal Crop Biomass: A Study of Surface and Groundwater Nitrate Contamination in the Bilate Cropland Watershed

Effective water resource management and sustainable agricultural practices are contingent upon a thorough understanding of nitrate dynamics. This study investigates the utilization of seasonal average cropland runoff observations to improve the prediction accuracy of nitrate runoff loads to surface water originating from cropping zones. By integrating data from various sources, including seasonal rainfall/runoff observations and cropland parameters, the study explores the complex relationship between crop biomass growth, nitrogen fertilizer application, and seasonal rainfall over cropland. Monthly average observations of cropping zone rainfall/runoff in the cropping zone are analyzed to understand the response of seasonal crop biomass to nitrogen fertilizer application and seasonally calibrated rainfall/runoff in the cropland watershed. The study demonstrates the prototypical runoff observation from cultivated areas and statistically estimates seasonal runoff at downstream stream outlets. This shows a strong correlation with an R² of 0.9742 with a p-value less than 0.001 for seasonal rainfall climate parameters. Seasonal cropland runoff observations from EWX lite are presented for model calibration at downstream outlets, based on regional crop calendars, facilitating the estimation of nitrate loading to surface water and nitrate contamination from cropping zones. The findings reveal distinct cropping zones, particularly zones 5, 6, 11, and 13, which significantly contribute, each exceeding 50 mg/l of leaching load to groundwater. Moreover, more than ten zones surpass the threshold of 50mg/l in nitrate loading to surface water. These quantitative insights provide valuable spatial information regarding nitrate runoff relationships within the watershed, enabling the identification of specific zones with heightened nitrate contributions and offering actionable solutions for promoting sustainable agriculture and refining water resource management strategies.

Spatiotemporal variations of extreme weather events and climate drivers in the Three Gorges Reservoir Area and its surrounding regions from 1960 to 2020

The Three Gorges Reservoir Area and its Surrounding Region (TGRASR) play a crucial role in the Yangtze River Basin. Over the past years, there has been growing concern about the effects of extreme weather events in this area, mainly attributed to climate change. To effectively address the implications of climate change, a thorough understanding of the temporal and spatial variability of these events is necessary. However, some of the previous studies have been limited to analyzing trend changes in events and have not sufficiently considered the connection with atmospheric circulation indices. In this study, we analyzed the spatio-temporal variations of extreme weather events using the Mann-Kendall and Sen's slope trend methods. Then, the correlation between extreme weather events and climate factors is explored using the Mantel test, Geo-Detector method (GDM), and Partial wavelet coherency (PWC) in terms of linear, hierarchical heterogeneity, and nonlinear, respectively. Finally, we investigated the potential climate factors that affect the temporal and spatial variability of extreme weather occurrences. The results showed that(1) among the 12 extreme indices analyzed in the TGRASR region from 1960 to 2020, there was a decreasing trend observed in Consecutive dry days (CDD), Consecutive wet days (CWD), and Annual count of days when precipitation is ≥10 mm (R10), while the remaining indices exhibited an increasing trend. Subsequent analysis employing the M-K mutation revealed that the mutation point for CWD occurred around 1975, resulting in a significant decrease in its trend. Additionally, the Simple daily intensity index (SDII), Annual count of days when the daily maximum temperature (TX) is >25 °C (SU25), and R10 displayed a decreasing trend. Mutations in the trends SU25, Annual count of days when the daily minimum temperature (TN) is >20 °C (TR20), and Annual count of days with at least 6 consecutive days when TX > 90th percentile (WSDI) were observed in 1997, 1999, 2003, and 2005, respectively. Following these mutations, all four indices displayed a substantial increase. (2) CDD, CWD, and R10 exhibit a decreasing trend across most stations, whereas the remaining indices demonstrate an increasing trend. Regarding spatial distribution, indices characterizing precipitation frequency and intensity exhibit higher mean values in the southeastern part of the TGRASR. (3) Mantel test: North Pacific pattern (NP), North Tropical Atlantic (NTA), and Global Mean Land/Ocean Temperature (GMLOT) have significant linear correlations with extreme precipitation and extreme temperature events; GDM: GMLOT and NTA are the main contributors to extreme precipitation and extreme temperature; PWC: 12 extreme indices have some nonlinear associations with all five climate factors. The study's findings can assist decision-makers in formulating sustainable water resource management strategies and measures for mitigating drought and flood risks. Additionally, the study contributes to uncovering climatic factors that influence changes in extreme weather events.

Global Events and Surge in Residential Water Demand: Exploring Possible Hydraulic Scenarios

For humankind to survive, access to sufficient and safe drinking water is fundamental. This study explores the connection between rising domestic water consumption and planetary phenomena, such as rapid population growth, climate change, and pandemics. To achieve the study’s objectives, it provides a thorough forecast of water use, considering probable global scenarios for the years 2030 and 2050. The modeling approach is adapted from a consistent case study taken from the body of scientific literature on water supply hydraulics. The study’s results highlight the necessity for proactive and flexible management strategies for water resources. Notably, it observes significant alterations in water supply management to adjust water allocation due to the unanticipated and ongoing increase in consumer demand. The forecasted scenarios indicate potential difficulties that may arise in meeting rising domestic water demand amid planetary phenomena. The presented results offer valuable insights to policymakers and water supply authorities, enabling them to effectively address the rising domestic water demand while considering potential adverse conditions, ensuring a sustainable water supply for future generations.

Sustainable Adaptation Plan in Response to Climate Change and Population Growth in the Iraqi Part of Tigris River Basin

Climate change and population growth play crucial roles in the planning of future water resources management strategies. In this paper, a balancing between projected water resources and water demands in the Iraqi Part of the Tigris River Basin (TRB) was evaluated till the year 2080 based on RCPs 2.6, 4.5 and 8.5 and population growth. This paper examined a sustainable adaptation plan of water resources in the TRB considering three scenarios; (S1) as no change in the current strategy, (S2) as improved irrigation efficiency and (S3) as improved irrigation and municipal water use efficiency. The results showed a decline in streamflow will occur in the range from 5 to 18.4% under RCP 2.6 and RCP 8.5, respectively. The minimum increase in water demand is expected for RCP 2.6 (maximum increase for RCP 8.5) by 51.8 (208.2), 9.9 (42) and 1.2 (7)% for the municipal–industrial, irrigation and environmental water demands, respectively, compared with the RP. The main finding indicated that S1 is the worst scenario, with water stress in four provinces, especially on the warmest RCP. Whereas, under S2 and S3 conditions, water stress can be eliminated. Increasing ambition towards adaptation becomes obligatory for developing sustainable water sources, supporting water food securities and increasing resilience towards climate change.

Optimizing urban water sustainability: Integrating deep learning, genetic algorithm, and CMIP6 GCM for groundwater potential zone prediction within a social-ecological-technological framework

This study presents a novel approach to groundwater resource assessment and drought vulnerability, achieved through integrating cutting-edge deep-learning algorithms into a comprehensive framework. In regions susceptible to drought, ensuring groundwater availability is of paramount importance. Addressing this critical need, our research employs an ensemble of advanced algorithms, including long short-term memory, convolutional neural network, deep neural network, and recurrent neural network. These algorithms are further enhanced through optimization using a genetic algorithm to map groundwater potential zones (GWPZ). Leveraging model validation based on the area under the receiver operating characteristic curve (AUCROC), the long short-term memory-genetic algorithm model emerges as the superior algorithm, boasting the highest values of AUCROC: 0.995 for training and 0.996 for testing). Utilizing this optimized model, this study developed the GWPZ map, subsequently overlaying it with established drought maps developed by the Bangladesh Agricultural Research Council across distinct periods—Pre-Kharif, Kharif, and Rabi. The derived baseline GWPZ spatial distribution revealed five categories—very low (34.99%), low (27.67%), moderate (13.26%), high (11.71%), and very high (12.37%)—and their intersection with drought-prone regions, indicative of probabilities of drought occurrence ranging from very severe to low (15.14% to 24.69%). Moreover, employing the best-predicted model, this study projected future GWPZ for 2050 and 2100 using the coupled model intercomparison project 6 general circulation model data under the ambit of three distinct shared socioeconomic pathways (SSPs): SSP1-2.6, SSP2-4.5, and SSP5-8.5. Our findings suggested a contraction in the groundwater potential area by the end of the twenty-first century (2100). This pioneering integration sheds light on the intricate relationship between groundwater availability and drought susceptibility, furnishing invaluable insights for formulating targeted water resource management strategies. By amalgamating advanced computational techniques with geospatial analyses, this research contributes to a more comprehensive grasp of water resource dynamics within the context of escalating climate challenges. Consequently, it offers a foundation for informed decision-making and implementing sustainable water management practices in regions grappling with the dual challenges of groundwater scarcity and recurrent droughts.

How accurate are the machine learning models in improving monthly rainfall prediction in hyper arid environment?

Arid regions like the United Arab Emirates (UAE) face a dire challenge of scarce water resources and unpredictable climate patterns. This study investigates the efficacy of advanced Machine Learning (ML) techniques in enhancing rainfall prediction within hyper-arid environments. Leveraging an extensive 30-year dataset from 1991 to 2020, this study harnessed the power of XGBoost, LSTM, Random Forest (RF), Gradient Boost (GB), Support Vector Machine (SVM), Multilayer Perceptron (MLP), Linear Regression (LR), and ensemble methods to significantly enhance the prediction accuracy of monthly rainfall over UAE. In the initial univariate analysis, focused solely on rainfall as the predictor, the ML models displayed encouraging performance during the training phase, achieving an impressive correlation coefficient (CC) of 0.88 for both XGBoost and the ensemble models. However, their predictive efficacy witnessed a decline during the testing phase, where the maximum CC reached 0.45. In contrast, traditional models like Linear Regression and SVM, yielded subpar results in both training and testing, exhibiting correlation values lower than 0.3. To address these limitations, a multivariate analysis is conducted by incorporating additional meteorological parameters, including wind speed, temperature, humidity, and evapotranspiration. This augmentation proved highly beneficial as it substantially enhanced the models' predictive capacities during the testing period. The XGB achieves a CC of 0.76, LSTM improves from 0.21 to 0.71, and stacked models exhibit promising behavior jumping from an average of 0.44 to 0.82 during the testing periods. Additionally, we performed a sensitivity analysis utilizing LASSO regression, which revealed that wind speed and minimum temperature emerged as the most influential parameters for monthly rainfall prediction in the arid context. These two meteorological factors exerted a substantial impact on the accuracy of our predictive models, underscoring their significance in understanding and forecasting rainfall patterns in hyper-arid regions, such as the United Arab Emirates. The identification of these key drivers further strengthens the foundation for effective water resource management and climate adaptation strategies in such challenging environments. This study provides valuable insights for water resource planning, agriculture, and climate resilience strategies in hyper-arid regions. Further research can build upon these results to enhance rainfall prediction models and support sustainable development in arid regions.

Reviewing some water resources management strategies (Globally, Arabic, local)

لقد اخذ موضوع المياه حيزا كبيرا في كتابات الباحثين وصناع القرار على المستوى العالمي والعربي والمحلي لاسيما في المناطق الجافة وشبه الجافة لاسباب كثيرة منها ما هو متعلق بندرة هذا المورد، والذي يقابله زيادة في الطلب مع تزايد اعداد السكان وارتفاع مستوى معيشتهم اذ تزداد الحاجة اكثر للمياه فضلا عن استخدامها في مجالات الزراعة والصناعة والاحتياجات المنزلية مما يجعلها عنصرا ضروريا وحيويا في حياة المجتمعات، كما وتعد الموارد المائية لاسيما التي تشترك فيها اكثر من دولة مصدرا من مصادر النزاع والتوتر بين الدول وستشكل حلبة الصراع المستقبلي تحت مسمى (حرب المياه) فهنالك العديد من الدراسات العالمية التي اهتمت بالادارة الاستراتيجية للموارد المائية واخذت كل دراسة جانبا معينا بحسب الاولوية التي يراها الباحثون في تشخيص المشكلة مما يؤكد ازمة المياه على المستوى العالمي. لقد تباينت آراء الباحثين في عرض استراتيجيات ادارة الموارد المائية فمنهم من اعطى الاولوية لاصحاب المصلحة في حل المشكلة والبعض الآخر ركز على التحليل البيئي وآخرون بينوا اهمية الادارة الداخلية الصارمة وغيرهم وجدوا ان المحور القانوني والسياسي هو الاهم في الاستراتيجيات لاسيما في الموارد المائية التي تشترك فيها اكثر من دولة وذهب البعض الى ان المحاسبة المائية وبصمة المياه كفيلة في السيطرة على ادارة الموارد المائية وعدوها محورا مهما في الادارة المتكاملة للموارد المائية. وفي العراق فان مشكلة المياه مركبة تتكون من مجمل المحاور السابقة وهذا يتطلب صياغة استراتيجية مبنية على تحليل دقيق لهذه العوامل للخروج بخيار استراتيجي يتناسب وحجم هذه التحديات لمعالجة هذه الازمة الخطيرة وبالتالي فان اختيارنا للدراسات العالمية والعربية والمحلية المشابهة لحالة العراق سيسهم في توضيح الاستراتيجية المقترحة اختصارا للجهد والوقت وذلك من خلال تحليل الاستراتيجيات مدار البحث للاستفادة منها في رسم ملامح الاستراتيجية العراقية.

Evaluating the future total water storage change and hydrological drought under climate change over lake basins, East Africa

Climate change led an increase in the frequency of severe droughts, the effects of which are exacerbated by a lack of water storage. Despite increasing research on global-scale total water storage (TWS) change and drought prediction, basin-scale long-term hydrological drought, TWS change, and El Nino–Southern Oscillation (ENSO) influence in East Africa (EA) remain unexplored. In this paper, we used multiple approaches, of ensemble machine learning (ML) and weighted averaging, to conduct a basin-scale exploratory analysis of future hydrological drought and TWS change for the period 2025–2099. Climate change will affect future hydrological conditions in the basins, with maximum severity values of −90.3, −726.6, and −2567.7 Gt in the Tana, Turkana, and Victoria basins, respectively, under RCP6.0. Similarly, we found maximum severities of −187.5 and −277.7 Gt in the Abaya-Chamo and Tanganyika basins, respectively, under RCP 2.6. The most severe El Nino drought and exceptional La Nina conditions in the basins were found under both RCP scenarios. To ensure future water security in EA, sustainable water resource management strategies that can mitigate the impacts of extreme climate events in the future are urgently needed.