Monthly Rainfall in Moroccan Arid Oasis Regions (1940-2017): Homogenization and Trends

The rapid urbanization and population growth in India have led to increased pressure on water resources in urban centers. As one of the fastest-growing cities in the country, Jaipur is facing significant challenges in meeting the water demands of its expanding population. Therefore, it is crucial to estimate the future population and water demand of Jaipur city to develop effective strategies for sustainable water management. This case study aims to estimate the future population and water demand of Jaipur city using a comprehensive analysis of demographic and water consumption trends. The study utilizes a combination of statistical methods, demographic projections, and water demand modeling techniques to provide a holistic understanding of the city's future water requirements. The results of this case study provide valuable insights into the future population growth and water demand trends of Jaipur city. The findings can assist urban planners, policymakers, and water resource managers in formulating effective strategies for sustainable water management and infrastructure development. The study emphasizes the importance of incorporating future population growth projections and water demand estimations into long-term urban planning processes. This case study contributes to the understanding of the challenges posed by population growth and urbanization on water resources in India, using Jaipur city as a specific example. The estimation of future population and water demand serves as a foundation for developing proactive measures to ensure adequate water supply and sustainable urban development in the face of increasing demand and limited resources

The study explored the trend of rainfall and rainfall erosivity (R-factor) over 120 years (1901-2020) using monthly precipitation data from 16 stations in Chhattisgarh state, India. Various statistical methods were employed to discern the trend and slope values, including homogeneity tests, non-parametric trend tests, and Sen's slope estimator. The results, at a 5% significance level, underscored a significant increasing trend in rainfall for the Bastar plateau, while the Chhattisgarh plains, Northern hills, and Chhattisgarh state exhibited a declining trend in annual rainfall. However, no specific trend was observed in pre- and post-monsoon seasons. During the winter, the Bastar plateau, Northern Hills, and Chhattisgarh state experienced declining rainfall, whereas the Chhattisgarh plains showed no discernible trend. Notably, the Northern hills exhibited the highest mean annual R-factor (12519.4 MJ mm ha-1 h-1 yr-1), followed by the Chhattisgarh plains (11587.7 MJ mm ha-1 h-1 yr-1) and the Bastar plateau (9633.5 MJ mm ha-1 h-1 yr-1). On the broader scale, the annual R-factor for Chhattisgarh state indicated a declining trend, estimated at a rate of 7.4 MJ mm ha-1 h-1 yr-1. This decline was attributed to a reduction in overall rainfall. However, it is important to note that this decrease in the R-factor does not necessarily signify a decline in soil erosion or soil health deterioration. In order to adapt to changing rainfall patterns, it is important to implement region-specific measures. These measures include dhodhi (well-like structures in natural drains), ponds, gabion structures, loose boulder check dams, gunny bag check dams, vegetative barriers, peripheral stone bunds, and borrow pits. Deep ploughing can also be used to address both increasing and decreasing trends in rainfall effectively. This targeted approach is crucial for sustainable soil erosion management and preserving soil health in the study area.

Identification of trends in rainfall, rainy days and 24 h maximum rainfall over subtropical Assam in Northeast India

The amounts of annual rainfall in the southwestern part of Bangladesh are almost equal having very little spatial variation. Significant decreasing trend (Mann-Kendal) of annual rainfall over the region is found (-4.5 mm/year at Mongla, -9.14 mm/year at Jessore, -15.71 mm/year at Madaripur) except Khulna, Satkhira and Khepupara, where the trend is positive over the long period (1948-2014) but it exhibits a decreasing trend during the recent period i.e., after 1980s. It clearly indicates a gradual decrease of the amount of rainfall over southwestern part, which has become most prominent in the recent climatic period of 1981-2014. The trend is more intense at the upper southwestern part, i.e., places like Jessore and Madaripur. Annual rainfall deviates within the range -42.6% to +48.6% over the region. Most wide annual deviation is observed in Khulna from 48.6% to -35.5%. Like annual rainfall, seasonal rainfall also has anomalous behaviour over the region. Monsoon rainfall at maximum locations are syncline with annual trend, but at Khulna, Satkhira and Mongla though the annual trend is negative but the monsoon trend is positive, it clearly indicates, intensification of rainfall in monsoon period over the fore southwestern part. In pre-monsoon season, overall rainfall trend is significantly negative at maximum places (-8.49 mm/year at Jessore, -2.02 mm/year at Barisal, -7.80 mm/year at Madaripur) over the region except Khulna, satkhira and Khepupara. But in Khulna and Satkhira it is also significantly negative over recent climatic period. Rainfall deviation is higher in seasonal scale than the annual scale. Among the seasons wider deviation is observed in winter (from -100.0% to +586%) and narrower in monsoon (from -43.0% to +62.1%). The coastal region of southwest Bangladesh has been facing various natural extremes like salinity intensification, drainage congestion, inundation, water logging etc. Anomalous behavior of rainfall in combination with these problems, affecting agricultural crop production in the upazilas under study. The problem is serious in Rabi season, where groundwater irrigation facility is limited for salinity problem. In these areas agriculture is totally dependent on surface water (irrigation canal), which becomes scarce during the month of January, February, March and rainfall is also becoming low in this time (supports by public opinion and rainfall trend analysis) imposing water shortage in crop field and as a result farmers have to incur yield reduction. In monsoon season problem is different. Drainage congestion is a major problem in this time. A little heavy rainfall causes inundation and water logged condition. Besides this problem, increasing trend of rainfall in monsoon is very likely to intensify the risk of inundation. And the farmers of the study area have already faced total damage of Aus crop due to flooding in some years with comparatively high rainfall or fallow due to water logged condition. Moreover, overall decreasing trend of rainfall is more likely to intensify the risks of salinization due to decreasing upstream flow as well as sedimentation on river bed and consequent poor drainage and water logging. This intensified environmental problem is further likely to intensify the detrimental effects on crop production. So, changing pattern of rainfall in combination with the local environmental stress is being imposed on risk of agricultural crop production over the study area. It is also occasionally responsible for crop failure over the study area. It is also likely to further intensify the risk for future time.

Rainfall is the primary source of surface and groundwater recharge. The state receives 91% of its annual rainfall due to the southwest monsoon, which is its principal rainy season. The contribution of winter, Pre-Monsoon, and Post-Monsoon season’s rainfall amount to about 2%, 3%, and 4%, respectively, of the annual total rainfall. Therefore, the temporal and spatial distribution of rainfall plays a vital role not only in the agricultural community but also in water resources management. This study investigates the rainfall variability over Jharkhand by using past 116 years data from 1901 to 2016. The extreme annual one-day rainfall depths investigated by using normal frequency distribution. The period examined for extreme rainfall events is 1986–2016. The data showed that the annual daily maximum rainfall received at any time ranged between 34.2 mm (minimum) to 341.0 mm (maximum) over Jamshedpur, indicating a very large range of fluctuation during the period of study. The magnitude of one-day annual maximum rainfall corresponds to return period were investigated. The depth of maximum daily rainfall is found highest over Jamshedpur. The highest rainfall observed in a day is: 224.3 mm at Ranchi, 341.0 mm at Jamshedpur and 240.4 mm at Dalton-ganj during the study period. The return period of extremely heavy rainfall (greater than or equal to 204.5 mm) in a day is 6 years, and the probability of exceedance is found 18% at Jamshedpur. Heavy rainfall events with more 402than 64.5 mm rain in a day was examined by using past 31 years daily rainfall data of Ranchi, Jamshedpur, and Daltonganj stations. To study the presence of a trend in rainfall, a widely used nonparametric Mann-Kendall test is applied. The linear trend line suggests that there is a decreasing trend in seasonal rainfall. The value of Kendall Score is found –2.82, which reveals that the decreasing trend in seasonal rainfall over Jharkhand is significant. An increasing trend is found in annual heavy rainy days over Jamshedpur, and the value of Kendall test statistics Zs for Jamshedpur is +2.43, which reveals that the increasing trend in an annual number of heavy rainy days is significant at 5% significance level. However, no significant trend is found over Ranchi and Daltonganj.

Agriculture is vital for human survival and irrigation water quality plays an important role in agricultural growing and harvest. Although Taiwan has abundant rainfall, the uneven distribution of rainfall in time and space makes the irrigation water management difficult. In the past two decades, climate change has led to frequent occurrence of extreme weather events and global disasters, and the increase in the frequency and intensity of extreme events enhances the potential disaster risk in Taiwan, impacting the water resource management severely. Meanwhile, industrial wastewater is a significant pollution source, and the surface water quality would be further deteriorated if the industrial wastewater was not treated properly before its release. In Taiwan, the needs of water resources for domestic and industrial uses have the higher allocation priority than that for agricultural use, considering the political concerns and economical contribution. Oftentimes, a supplementary water resource to meet irrigation need is required due to the scarce of available water resources. The situation may become even worse under the influence of climate change.Given the information above, this study explored the irrigation water quality variation under the influence of climate change on agricultural water resource management. The Taoyuan City (including Taoyuan irrigation Shimen irrigation areas) were selected as the study area. The potential impact of climate change on irrigation water quality, considering factors of pollution discharges and economic development, was assessed. Adaptive strategies including stabilizing irrigation water demand, strengthening irrigation water supply and building an agricultural technology auxiliary system were discussed. The result showed that the increasing frequency of heavy rainfall events in Bade, Xinwu, and Guanyin Districts. The surface pollutant would be washed out easily during heavy rainfall events, impacting neighboring water bodies. On the other hand, drought events appear in Daxi and Fuhsing Districts in extreme climate events. Therefore, a new strategy for sustainable water management is needed.

Rainfall and temperature are the most important environmental factors influencing crop growth, development, and yield. The northwestern (NW) part of India is one of the main regions of food grain production of the country. It comprises of six meteorological subdivisions (Haryana, Punjab, West Rajasthan, East Rajasthan, Gujarat and Saurashtra, Kutch and Diu). In this study, attempts were made to study variability and trends in rainfall and temperature during 30-year climate normal periods (CN) and 10-year decadal excess or deficit rainfall frequency during the historical period from 1871 to 2016. The Mann-Kendall and Spearman’s rank correlation (Spearman’s rho) tests were used to determine significance of trends. Least square linear fitting method was adopted to find out the slopes of the trend lines. The long-term mean annual rainfall over North West India is 587.7 mm (standard deviation of 153.0 mm and coefficient of variation 26.0). There was increasing trend in minimum and maximum temperatures during post monsoon season in entire study period and current climate normal period (1991–2016) due to which the sowing of rabi season crops may be delayed and there may be germination problem too. There was a non-significant decreasing trend in rainfall during monsoon season and an increasing trend in rainfall during post monsoon over North West India during entire study period. During current CN5 (1991–2016), all the subdivision (except the Saurashtra region) showed a decreasing trend in rainfall during monsoon season which is a matter of concern for kharif crops and those rabi crops which are grown as rainfed on conserved soil moisture. The decadal annual and seasonal frequencies of excess and deficit years results revealed that the annual total deficit rainfall years (24) exceeded total excess rainfall years (22) in North West India during the entire study period. While during the current decadal period (2011 to 2016), single year was the excess year and 2 years were deficit rainfall years in all subdivisions (except East Rajasthan) on annual basis.

This study investigates the spatial variability of surface water balance within the Semen Omo Zone in Ethiopia, leveraging data from the Global Land Data Assimilation System (GLDAS) and Empirical Bayesian Kriging (EBK) techniques. The primary parameters analyzed include total precipitation rate (TPR), evapotranspiration (ET), storm surface runoff (SRO), and baseflow groundwater runoff (BF). The study focuses on two scenarios: Scenario I, which considers only surface water components (TPR-ET-SRO), and Scenario II, which incorporates partial groundwater (TPR-ET-SRO-BF). In Scenario I, significant variations in water balance were identified across different watersheds. Watersheds such as WS16, WS15, and WS14 exhibited surplus water, while WS3 showed a notable deficit, indicating insufficient precipitation compared to evapotranspiration and runoff. Scenario II provided a more comprehensive analysis, revealing that watersheds WS17, WS14, and WS6 experienced substantial water deficits when both surface and groundwater components were considered. Conversely, watersheds like WS21 and WS19 were identified as water-efficient areas. The geological context significantly influenced the water balance outcomes. Regions underlain by old crystalline granite schist diorite and marine sediments demonstrated higher water budgets in Scenario I. Scenario II indicated the crucial role these formations play in groundwater recharge and storage. The findings underscore the necessity of integrated water management practices that consider both surface and groundwater resources alongside geological variability. This comprehensive analysis offers valuable insights for policymakers and water resource managers in developing targeted strategies for sustainable water management, ensuring long-term water resource sustainability in the Semen Omo Zone and potentially other similar regions.

Climate change is now considered as a newly added threat for natural resource management, which has significant impact on agriculture and allied sectors. Climate change studies play a pivotal role in developing sustainable natural resource management strategies. The present study assesses the effect of climate change on hydro-climatic fluxes in Kantamal catchment of the Mahanadi River basin, India. Utilizing the modified Mann-Kendall test, analysis of long-term climatic variables revealed a decreasing trend in rainfall and increasing trend in temperature. Employing a bias-corrected, multi-model ensemble of three regional climate models (RegCM4-4, RCA4, REMO2009) under the Representative Concentration Pathways (RCPs) of RCP4.5 and RCP8.5 scenarios, a rise in the average maximum temperature of 0.86°C under RCP4.5 and 1.16°C under RCP8.5, as well as an increase in the average minimum temperature of 2.35°C under RCP4.5 and 2.89°C under RCP8.5, by 2099 were projected. Rainfall is projected to decrease by 29.53% (RCP4.5) and 24.34% (RCP8.5), with surface runoff decreasing by 13.91% (RCP4.5) and 9.94% (RCP8.5), actual evapotranspiration declining by 7.81% (RCP4.5) and 7.77% (RCP8.5), soil moisture reducing by 11.17% (RCP4.5) and 9.69% (RCP8.5), and water yield is projected to decline by 39.45% (RCP4.5) and 33.05% (RCP8.5) as compared to the baseline period. Water stress situation is anticipated in the catchment emphasizing the need for planning and management of water resources, and sustainable agriculture.

Water resource management is crucial for sustainable agricultural and ecological development, particularly in regions with complex land-use patterns and sensitive eco-systems. The Bashang region of Zhangjiakou city, located in the agro-pastoral ecotone of northern China, is an ecologically fragile area that is currently undergoing significant land use and climate changes. Despite the importance of understanding the interplay between land use, climate change, and water conservation, few studies have comprehensively evaluated their combined effects on regional water resources. This study addresses this gap by investigating the spatiotemporal changes in the water yield (WY) and water conservation capacity (WCC) of the Bashang region under different land use and climate scenarios for the year 2035. This research employs the FLUS model to predict the future land use and the InVEST model to estimate the WY and WCC under a natural development scenario (NDS), an agricultural production scenario (APS), an ecological protection scenario (EPS), and a land planning scenario (LPS). The results reveal that the WCC is primarily influenced by precipitation, land use, and the topography. This study finds that scenarios which focus on ecological protection and land use optimization, such as the EPS and LPS, significantly enhance the water conservation capacity of the study region Notably, the LPS scenario, which limits urban expansion and increases the amount of ecological land, provides the best balance between the water yield and conservation. The findings highlight the need for integrated approaches to land use and water resource management, particularly in agro-pastoral transitional zones. The unique contribution of this research lies in its comprehensive modeling approach, which combines land use, climate data, and water resource analysis, and which provides valuable insights for sustainable land and water management strategies.

Human life is non-existent without water. In a state like Haryana, where agriculture plays a vital role in the economy, groundwater serves as a vital lifeline. The state faces increasingly serious challenges such as water scarcity, excessive water extraction, water quality degradation, and inequitable distribution. Recognizing the need to address these issues, we were inspired to write "Water Resource Management in Haryana: Challenges and Prospects." This book attempts to present a comprehensive and analytical overview of Haryana's current water situation, emerging challenges, and potential strategies for sustainable water management. This book will provide readers with a holistic view of groundwater and surface water dynamics in the region. We hope this book will inspire further research on sustainable water governance in Haryana.

This study aims to determine trends in annual and seasonal rainfall and rainy days over different river basins across India. The data used consists of daily gridded rainfall at 1° × 1° resolution for the period 1951–2004. Sen's non-parametric estimator of slope was used to estimate the magnitude of trend whose statistical significance was assessed by the Mann–Kendall test. Among 22 basins studied, 15 showed a decreasing trend in annual rainfall; only one basin showed a significant decreasing trend at 95% confidence level. Of the 6 basins showing an increasing trend, 1 basin showed a significant positive trend. The monsoon rainfall increased over 6 basins, decreased over 16 basins and a decreasing trend for 2 basins was found statistical significant. With the exception of Ganga, Brahmaputra and EFR4, all river basins experienced the same direction of trend in monsoon and annual rainfall. Four river basins experienced increasing (non-significant) trend in annual rainy days; three basins did not show any change in annual rainy days whereas 15 basins have shown a decreasing trend in annual rainy days. The decreasing trend in three basins was statistically significant. Most of the basins have shown the same direction of trend in rainfall and rainy days at the annual and seasonal scale.

Daily gridded (0.5° × 0.5°) rainfall data between 1971 and 2005 were used to detect spatial patterns of trend in rainfall and rainy days during the Indian Summer Monsoon (June to September). A non-parametric (Mann–Kendall test) method was used to test for monotonic trend at each grid level. The magnitude of trend is estimated using Sen's method. Further, a field significance test was applied to assess significant trend at an aggregated level over each meteorological subdivision. A statistically significant (α = 0.1) increasing trend of both rainfall and rainy days during the monsoon season was found over the east coast and Deccan Plateau region of India. Meteorological subdivisions over the west coast, western arid region and northeastern humid region showed significantly decreasing trends in both rainfall and rainy days. The northern hilly parts of the Himalaya were found to have a significantly increasing trend of rainfall but decreasing trend of rainy days. The north and central plains of India showed a decreasing trend of rainy days and the eastern plain was found to have a decreasing trend of rainfall during the summer monsoon period. Copyright © 2013 Royal Meteorological Society

Purpose: Maintaining agricultural output, protecting water supplies, and lessening environmental effects all depend on effective water management. Through a comprehensive review of the literature and an in-depth analysis of various AI and ML techniques, this paper aims to put light on the cutting-edge approaches used in irrigation scheduling predictive modeling. The goal of the research is to determine the advantages, disadvantages, and future directions of AI and ML-based irrigation management systems by means of a methodical analysis of various algorithms, data sources, and applications. Additionally, the study seeks to demonstrate how data-driven methods can enhance irrigation systems' sustainability, accuracy, and precision. Stakeholders in agriculture, water resource management, and environmental conservation can make well-informed decisions to maximize irrigation scheduling techniques by having a thorough understanding of the theoretical underpinnings and practical applications of predictive models. The study also attempts to tackle issues like scalability, model interpretability, and lack of data when implementing AI and ML solutions for practical irrigation management. In final form, this review's conclusions advance our understanding of how to use AI and ML to improve agricultural systems' resilience and water use efficiency, supporting adaptive and sustainable water management strategies in the face of rising water scarcity concerns and climate change. Design/Methodology/Approach: In order to gather information for this review study, several research articles from reliable sources were analyzed and compared. Objective: To provide the current research gaps in prediction models for the best irrigation scheduling and water management, and suggest using AI and ML techniques to fill in these gaps. Results/ Findings: In response to the growing challenges of water scarcity and climate change, the paper's findings highlight the transformative potential of AI and ML techniques in optimizing irrigation scheduling, enhancing agricultural resilience, increasing water use efficiency, and supporting adaptive and sustainable water management strategies. Originality/Value: This paper's uniqueness and significance come from its thorough analysis of AI and ML approaches in predictive modeling for ideal water management and irrigation scheduling. It also provides insights into new methods and their possible effects on resource optimization and agricultural sustainability. Type of Paper: Literature Review.

Investigating the dynamics of rainfall has become very crucial in managing water resources efficiently for sustainable development. The present study aimed to analyze the rainfall distribution in Kurunegala district. Historical rainfall data collected from four gauging stations were subjected to both mathematical and statistical analysis. In addition, trends of rainfall, probability of exceedance and meteorological drought conditions were studied. Rainfall distribution in the district shows high variations. Bathalagoda records the highest mean annual rainfall of 1843 mm. The corresponding values for Wariyapola, Mediyawa and Siyambalagamuwa are 1629 mm, 1315 mm and 1222 mm, respectively. Rainfall is concentrated only in certain months in a year. Annual rainfall exceedance at 50% probability is 1825 mm at Bathalagoda. The corresponding figures for Wariyapola, Mediyawa and Siyambalagamuwa are 1662 mm, 1284 mm and 1226 mm, respectively. Mediyawa, Wariyapola, and Siyambalagamuwa show a decreasing trend in annual rainfall while Bathalagoda shows an increasing trend. Southwest monsoonal (SWM) and 2nd inter-monsoonal (IM2) rainfalls show a decreasing trend at all gauging stations. Mediyawa and Bathalagoda show a positive trend in both 1st inter-monsoonal (IM1) and Northeast monsoonal (NEM) rainfalls. A negative trend in Maha seasonal rainfall is observed in all regions except Bathalagoda. A positive trend of Yala seasonal rainfall is observed at Mediyawewa and Bathalogoda. Further, severe drought conditions were experienced in the recent years at Wariyapola, Mediyawa, and Siyambalagamuwa. Compared to other regions, rainfall at Mediyawa and Siyambalagamuwa highly deviates from the long-term mean. In the study area, rainfall distribution shows a cyclic pattern over time. However, the amount of rainfall received in the recent years is lower than the amount received in the immediate past decade at all stations except Bathalagoda. Hence, proper management decisions based on rainfall distribution patterns is vital for the efficient management of water resources while guaranteeing sustainable agricultural production in this district.