Management Of Available Water Resources Research Articles

Study of the Hydrochemical Characterization of Drinking Water from the Aquifer of the Town of Guitté at Hadjer Lamis

A hydrogeological study was carried out in and around Guitté. This study aims to contribute to the understanding of the hydrochemical parameters of the waters of the Guitté aquifer. with a view to the sound and sustainable management of available water resources. A field mission to measure and sample borehole water was carried out from March 26 to 28. 2023 in and around Guitté. Physicochemical analyses were carried out on 28 water samples from human-driven pumps). The study showed that the groundwater exploited in this area has an average temperature of 29°C. Overall. the pH values measured in the sampled waters are not very heterogeneous and are around neutral. Electrical conductivity values are highly heterogeneous. Two types of chemical facies have been identified in Guitté groundwater: sodium or potassium bicarbonate facies. and calcium and magnesium bicarbonate facies. The overall quality of the groundwater obtained for consumption is 60.71% rated as good. 39.28% as poor. The origin of the mineralization could be linked. on the one hand. to water/rock contact. due to the dissolution of natron. limestone. gypsum and thenardite and on the other hand. to the phenomenon of intense evaporation.

Rainfall prediction using multiple inclusive models and large climate indices.

Rainfall prediction is vital for the management of available water resources. Accordingly, this study used large lagged climate indices to predict rainfall in Iran's Sefidrood basin. A radial basis function neural network (RBFNN) and a multilayer perceptron (MLP) network were used to predict monthly rainfall. The models were trained using the naked mole rat (NMR) algorithm, firefly algorithm (FFA), genetic algorithm (GA), and particle swarm optimization (PSO) algorithm. Large lagged climate indices, as well as three hybrid models, i.e., inclusive multiple model (IMM)-MLP, IMM-RBFNN, and the simple average method (SAM), were then employed to predict rainfall. This paper aims to predict rainfall using large climate indices, ensemble models, and optimized artificial neural network models. Also, the paper considers the uncertainty resources in the modeling process. The inputs were selected using a new input selection method, namely a hybrid gamma test (GT). The GT was integrated with the NMR algorithm to create a new test for determining the best input scenario. Therefore, the main innovations of this study were the introduction of the new ensemble and the new hybrid GT, as well as the new MLP and RBFNN models. The introduced ensemble models of the current study are not only useful for rainfall prediction but also can be used to predict other metrological parameters. The uncertainty of the model parameters and input data were also analysed. It was found that the IMM-MLP model reduced the root mean square error (RMSE) of the IMM-RBFNN, SAM, MLP-NMR, RBFNN-NMR, MLP-FFA, RBFNN-FFA, MLP-PSO, RBFNN-PSO, MLP-GA, and RBFNN-GA, MLP, and RBFNN models by 12%, 25%, 31%, 55%, 60%, 62%, 66%, 69%, 70%, 71%, 72%, and 72%, respectively. The IMMs, such as the IMM-MLP, IMM-RBFNN, and SAM, outperformed standalone models. The uncertainty bound of the multiple inclusive models was narrower than that of the standalone MLP and RBFNN models. The MLP-NMR model decreased the RMSE of the RBFNN-NMR, RBFNN-FFA, RBFNN-PSO, and RBFNN models by 15%, 26%, 37%, 42%, and 45%, respectively. The proposed ensemble models were robust tools for combining standalone models to predict hydrological variables.

Comparative evaluation of deep learning and machine learning in modelling pan evaporation using limited inputs

ABSTRACT Estimation of pan evaporation (Epan) is an important issue for planning and management of available water resources. In the present study, the accuracy of a new deep learning method, long short-term memory (LSTM) with grey wolf optimization (GWO), in modelling Epan using limited climatic variables as input is investigated. The outcomes of the LSTM-GWO are compared with the single LSTM and advanced machine learning (ML) methods. Minimum and maximum temperatures and extra-terrestrial radiation are used as inputs to the models. Three data splitting scenarios are considered and the outcomes of the abovementioned methods are also compared with the Stephen-Stewart (SS) and calibrated Hargreaves-Samani (CHS) empirical methods. The results reveal that the LSTM-GWO method has a better ability in estimating Epan using limited inputs compared to other ML and empirical methods. They also indicate that an increase in the amount of training data used improves the accuracy of the models.

A Geo Spatial Approaches for Integrated Watershed Management (IWM) Case Study of Boni Mukundaraju Cheruvu, Andhra Pradesh, India

Sustainable management of available water resources and judicious allocation to user needs within the ecosystem threshold can be achieved through Remote Sensing. To estimate the surface features with the help of change analysis which improves better resource management and decision-making in watershed hydrology assessment, interactions and relationships between human activities and natural phenomena are important. The present study on Geo-spatial approaches for Watershed management of Boni Mukundaraju cheruvu in Visakhapatnam district, Andhra Pradesh, India. From the study, we fixed it that the LULC of study area was classified into 5 major classes and 13 sub classes. During the study period from 2010-11 to 2020-21, it was observed that the wastelands in the catchment area were converted into water bodies seasonal and agricultural lands. It is also observed that the forest area was increased and majorly built up area was decreased from 2010-11 to 2020-21. The present study brings out the potential of geospatial techniques in LULC changes from 2010-11 to 2020-21, drainage patterns, Hydrological soil types (4types) and rainfall-runoffs from 1991-2021 (30 years) were described in detail.

Monitoring and Assessment of Water Quality using Multivariate Statistics of Physico-chemical Parameters to establish Baseline Level around proposed Jaitapur Nuclear Power Plant (JNPP), India

This study illustrates the usefulness of multivariate statistical techniques to provide straightforward data interpretation as well as valuable insights of datasets to get better information about the water quality and helps to design monitoring networks for effective management of available water resources. In this study, Multivariate statistical analysis, Cluster analysis, Principal Component Analysis, Factor Analysis, Water Quality Index and Piper diagram are used to analyze the water data and to prepare the baseline of water parameters around the proposed JNPP. Piper diagram indicates that the primary salinity ("non-carbonate alkali") exceeds 50 % which means that the chemical properties of water are dominated by alkalies and strong acids. Water quality indices indicate that water is non-polluted and fully fit for drinking purposes. Principal component analysis and factor analysis applied for water parameters point towards the common source of minerals and high level of dissolved organic matter. Trace metal analysis shows significant but little participation of zinc, copper, nickel, iron and barium in water quality. The baseline developed and the data obtained will be useful for the water quality analysis after post-plant operation in this region.

Spatial and Temporal Effects of Irrigation Canals Rehabilitation on the Land and Crop Yields, a Case Study: The Nile Delta, Egypt

Shortage of surface water is considered an international problem that has even extended to countries that have rivers, in particular countries sharing the same river basins and downstream countries, such as Egypt. This issue requires intensive management of available water resources. Irrigation Canals Rehabilitation (ICR) has become essential to protect surface water in irrigation canals from losses due to seepage. Egypt is one of the countries that has started using this technique. This paper aims to evaluate the impact of ICR using concrete on the land and on crop yields. The SEEP/W model is used in the current study to estimate changes in the groundwater table and moisture in the root zone. Three cases studies have been simulated and compared including unlined, lined, and lined canals with a drainage pipe. The methodology is applied to three canals in the Nile Delta: Sero, Dafan, and New-Aslogy. The results demonstrate that ICR has decreased the losses from canals which resulted in lowering the groundwater, where the case of lining gave a higher reduction than the case of lining with a drainage pipe. In addition, the water table underneath the embankment was lowered. Decreasing the groundwater table could help to protect the land from logging and increase crop yields, but it may reduce the recharging of groundwater aquifers. Such a study is highly recommended in arid regions to decrease water losses where many countries are suffering from water shortage.

АНАЛИЗ ЗАРУБЕЖНОГО ОПЫТА УТИЛИЗАЦИИ СБРОСНЫХ И ДРЕНАЖНЫХ ВОД В ОРОСИТЕЛЬНЫХ МЕЛИОРАЦИЯХ

Purpose: to review the practice of using drainage and waste water for irrigating agricul-tural crops as a priority for their utilization. Discussions. One of the priority strategies for sustainable management of available water resources is the reuse of drainage and waste water for irrigation reclamation, taking into account the hydrogeological and reclamation conditions of the area. The reducing of the degradation rate of water supply sources subject to the impact of drainage and waste water, is possible only with the creation of a system for regulating water distribution in irrigation systems of various levels, which would allow taking into account the resource of drainage and waste water for irrigation. Most often, drainage and waste water is used for irrigating salt-tolerant crops. The use of drai-nage and waste water with salinity from 1.5 to 10.0 g/dm³ for irrigating grain and fodder crops did not cause a reduction in yield. Conclusions. As the analysis of drainage and waste water utilization shows, their wide-spread use in irrigation reclamation is explained by the increased mineralization and technogenic impurities (pesticides, herbicides, trace elements, oil products, etc.). The measures taken to dilute such waters with fresh water from canals only partially solved the problem of their accumulation and reduction of discharges into water bodies. Also, there was still an increase in the irrigation water consumption for irrigating crops. In this regard, it is relevant to conduct exploratory research in the field of technologies preparation and purification of drainage and waste water for irrigation purposes.

Geospatial Analysis of Hydrometeorological Dynamics for Managing Socio-economic and COVID-19 Threats in the Ossiomo Watershed, Nigeria

The geographical occurrence and spread of the current novel COVID-19 pandemic are partly a function of the awareness, socio-economics, mobility, and health management practices in place. Ossiomo watershed in Edo State, Nigeria, is mainly a rural region with limited healthcare access and abundant water from River Ossiomo. One of the recommendations for preventing COVID-19 is washing hands with soap using running water. Thus, the novel COVID-19, a highly transmittable and pathogenic viral disease, requires effective management of available water resources for sustainable health development. The first confirmed case relating to the COVID-19 pandemic in Nigeria was announced on February 27, 2020, when an Italian citizen in Lagos tested positive for the virus. In most rural Africa, including Ossiomo, no pipe-borne water except rain harvesting for survival. Using GIS Inverse Distance Weighted (IDW) interpolation technique, the rainfall map produced (derived from a 31-year collated geo-located hydro-meteorological data - rainfall and discharge, covering the Ossiomo watershed) shows that rainfall decreases northward with minimum monthly precipitation of 18.8mm in January and to the south with a mean maximum rainfall of 339.0mm in July. NCDC records on Covid-19 were used to create Choropleth maps that revealed very low confirmed cases and relatively high deaths, though considered relatively low compared with global statistics. The Pearson Product Moment Correlation Coefficient (PPMCC) further indicates a strong correlation between rainfall and catchment discharge with r=0.717. With adequate socio-economic activities and water provisions, coupled with effective COVID-19 management practices, the pandemic may not linger in the study area.

Future Climate Change Impact on the Nyabugogo Catchment Water Balance in Rwanda

Droughts and floods are common in tropical regions, including Rwanda, and are likely to be aggravated by climate change. Consequently, assessing the effects of climate change on hydrological systems has become critical. The goal of this study is to analyze the impact of climate change on the water balance in the Nyabugogo catchment by downscaling 10 global climate models (GCMs) from CMIP6 using the inverse distance weighting (IDW) method. To apply climate change signals under the Shared Socioeconomic Pathways (SSPs) (low and high emission) scenarios, the Soil and Water Assessment Tool (SWAT) model was used. For the baseline scenario, the period 1950–2014 was employed, whereas the periods 2020–2050 and 2050–2100 were used for future scenario analysis. The streamflow was projected to decrease by 7.2 and 3.49% under SSP126 in the 2020–2050 and 2050–2100 periods, respectively; under SSP585, it showed a 3.26% increase in 2020–2050 and a 4.53% decrease in 2050–2100. The average annual surface runoff was projected to decrease by 11.66 (4.40)% under SSP126 in the 2020–2050 (2050–2100) period, while an increase of 3.25% in 2020–2050 and a decline of 5.42% in 2050–2100 were expected under SSP585. Climate change is expected to have an impact on the components of the hydrological cycle (such as streamflow and surface runoff). This situation may, therefore, lead to an increase in water stress, calling for the integrated management of available water resources in order to match the increasing water demand in the study area. This study’s findings could be useful for the establishment of adaptation plans to climate change, managing water resources, and water engineering.

Aquappolis: Mobile application for rainwater harvesting in Mexico City

Rainwater harvesting has become a necessary action around the world to satisfy the big cities needs where the water access is restrained (Shivakumar, 2017), which is the case of Mexico City where the water demand exceeds the supply sources, and many other problems are related to water (Arto-Olaizola et al., 2016). Aquappolis is a mobile application intended to compute the amount of rainwater that can be harvested from specific zones in Mexico City. The app information is provided from extensive rain gauge network data collected from Hydrological Observatory stations across Mexico City. This paper provides an example of how the technological innovation and instant information available for decision maker authorities and general population are indispensable to achieve a responsible, careful, and sustainable management of available water resources in Mexico´s Valley.

Machine Learning with Metaheuristic Algorithms for Sustainable Water Resources Management

Management of available water resources needs good planning and to do this, prognostication of hydrological parameters (parameters of the hydrological cycle such as rainfall, runoff, solar radiation, groundwater, evaporation/evapotranspiration) [...]

Evaluating the Spatio-Temporal Distribution of Irrigation Water Components for Water Resources Management Using Geo-Informatics Approach

Spatio-temporal distribution of irrigation water components was evaluated at the canal command area in Indus Basin Irrigation System (IBIS) by using a remote sensing-based geo-informatics approach. Satellite-derived MODIS product-based Surface Energy Balance Algorithm for Land (SEBAL) was used for the estimation of the actual evapotranspiration (ETa). The ground data-based advection aridity method (AA) was used to calibrate and validate the model. Statistical analysis of the SEBAL based ETa and AA shows the mean values of 87.1 mm and 47.9 mm during Kharif season (May–November) and 100 mm and 77 mm during the Rabi Season (December–April). Mean NSEs of 0.72 and 0.85 and RMSEs 34.9 and 5.76 during the Kharif and the Rabi seasons were observed for ETa and AA, respectively. Rainfall data were calibrated with the point observatory data of the metrological stations. The average annual ETa was found 899 mm for defined four cropping years (2011–2012 to 2014–2015) with the minimum average value of 63.3 mm in January and the maximum average value of 110.6 mm in August. Average of the sum of net canal water use (NCWU) and rainfall during the study period of four years was 548 mm (36% of ETa). Seasonal analysis revealed 39% and 61% of groundwater extraction proportion during Rabi and Kharif seasons, dependent upon the occurrence of rainfall and crop phenology. Overall, the results provide insight into the interrelationships between key water resources management components and the variation of these through time, offering information to improve the strategic planning and management of available water resources in this region.

Groundwater vulnerability assessment using water quality index (WQI) under geographic information system (GIS) framework in parts of Uttar Pradesh, India

Groundwater resources are affected in principle by three major activities. First is excessive use of fertilizers and pesticides in agricultural areas. The second is untreated/partially treated wastewater to the soil/water and the third one is excessive pumping and improper management of aquifers. Due to large-scale urban growth which has triggered domestic effluents and on the other hand industrial development activities has resulted in the generation of a copious volume of industrial effluents directly and indirectly contaminate the groundwater. In a drinking water quality assessment, the decision-making based on water quality data is a crucial issue because several parameters compromise its quality. There has been considerable advancement in the field of water quality assessment particularly based on the principle of the water quality index (WQI) using modified concepts. The study area which includes part of Varanasi and Sant Ravidas Nagar districts are centers for urban growth along with industrial setup in Uttar Pradesh, India. Water quality index (WQI) is an index reflecting the composite influence of different water quality parameters which is considered for calculation. 50 numbers of groundwater samples were collected from various locations in the study area as per the standard protocol prescribed by the American Public Health Association (APHA). Twenty-two water quality parameters have been considered for the calculation of water quality index viz. pH, electrical conductivity (EC), total hardness (TH), total dissolved solids (TDS), alkalinity, sodium (Na+), potassium (K+), calcium (Ca2+), magnesium (Mg2+), nitrates (NO3−), bicarbonate (HCO3−), chlorides (Cl−), sulphates (SO4−), fluorides (F−), chromium (Cr), zinc (Zn), copper (Cu), manganese (Mn), iron (Fe), nickel (Ni), lead (Pb) and cadmium (Cd). The Bureau of Indian Standard has been considered to assess the suitability of groundwater for drinking purposes and the calculation of the water quality index (WQI). Correlation study among various physicochemical properties also reflects certain significant negative relationships. The current study shows that 50% of the collected water samples are non-suitable for the drinking water category and the rest is falling under the good, moderate, poor, very poor as per the Water Quality Index (WQI) classification. The present study is quite helpful for the proper planning and management of available water resources for drinking purposes.

Monitoring Terrestrial Water Storage Changes with the Tongji-Grace2018 Model in the Nine Major River Basins of the Chinese Mainland

Data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission can be used to monitor changes in terrestrial water storage (TWS). In this study, we exploit the TWS observations from a new temporal gravity field model, Tongji-Grace2018, which was developed using an optimized short-arc approach at Tongji University. We analyzed the changes in the TWS and groundwater storage (GWS) in each of the nine major river basins of the Chinese mainland from April 2002 to August 2016, using Tongji-Grace2018, the Global Land Data Assimilation System (GLDAS) hydrological model, in situ observations, and additional auxiliary data (such as precipitation and temperature). Our results indicate that the TWS of the Songliao, Yangtze, Pearl, and Southeastern River Basins are all increasing, with the most drastic TWS growth occurring in the Southeastern River Basin. The TWS of the Yellow, Haihe, Huaihe, and Southwestern River Basins are all decreasing, with the most drastic TWS loss occurring in the Haihe River Basin. The Continental River Basin TWS has remained largely unchanged over time. With the exception of the Songliao and Pearl River Basins, the GWS results produced by the Tongji-Grace2018 model are consistent with the in situ observations of these basins. The correlation coefficients for the Tongji-Grace2018 model results and the in situ observations for the Yellow, Huaihe, Yangtze, Southwestern, and Continental River Basins are higher than 0.710. Overall, the GWS results for the Songliao, Yellow, Haihe, Huaihe, Southwestern, and Continental River Basins all exhibit a downward trend, with the most severe groundwater loss occurring in the Haihe and Huaihe River Basins. However, the Yangtze and Southeastern River Basins both have upward-trending modeled and measured GWS values. This study demonstrates the effectiveness of the Tongji-Grace2018 model for the reliable estimation of TWS and GWS changes on the Chinese mainland, and may contribute to the management of available water resources.

STUDY ON LIVELIHOOD DYNAMICS OF RURAL HOUSEHOLD OF MUNGELI DISTRICT OF CHHATTISGARH STATE INDIA

The study was carried out to study the livelihood dynamics of rural household of Mungeli district of Chhattisgarh state. Two blocks namely Lormi and Mungeli were taken into consideration for the study. A total sample size of 89 farmers was made from 07 villages. The study finds that the largest participation of rural household was in the livelihood activities like agriculture (crop production) with 95.50 per cent and non-farm (construction) with 26.96 per cent. Agriculture and non-farm were identified as the main two sources of income for rural households. The participation in both the livelihood activities estimated 84.96 per cent and 12.39 per cent respectively. Crop production and horticulture (vegetable production) were the main contributors to the farm income of rural households their contribution being 62.67 per cent and 24.29 per cent. PersonalSocial services and whole sale-retail trade-small stall were the main contributors to the non-farm income of rural households their contribution being 16.99 per cent and 3.62 per cent. The degree of diversification was found to be greater with 0.56 per cent among the landless and those belonging to lower farm-size groups. Shortage of irrigation water leads to certain problems including lower yields, decrease cultivated area. Therefore, the government should form efficient and strong policies for the better management of available water resources, ensuring equal availability to every farmer.

The Effects of Climate Change on the Reuse of Agricultural Drainage Water in Irrigation

Climate change is projected to have a major impact on agricultural water resources availability. Comprehending the effects of climate change on water supplies for agriculture is an essential aid for the effective management of available water resources. A forecasting model, a surface water quality model coupled with an optimization algorithm have been used in forecasting agricultural water quality and to maximize the reuse of wastewater in the Osan watershed, South Korea. In forecasting water quality and streamflow parameters for a 30 year period, AutoRegressive Integrated Moving Average (ARIMA) was used. Both ARIMA model fit and model performance were within accepted levels. Water quality and quantity were simulated using the QUAL2Kw model. Jaya algorithm was executed to optimize the process for determining optimal quantities for agricultural drainage water (ADW) reused at withdrawal points. Simulations of water quality show that organic matter levels are key attributes in the management of the Osan drain. QUAL2Kw model calibration and validation show that the model can be applicable with values of Nash—Sutcliffe model efficiency (NSE) > 0.5 respectively. Water quality results show that Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), Total Nitrogen (TN) and Total Suspended Solids (TSS) were within acceptable ranges. ADW is suitable for indirect irrigation in the Osan watershed as water quality standards meets Korea’s standards and Food and Agricultural Organization (FAO) Guidelines. Irrigation water demand will increase by 47.1 % for summer and by 16.5% for winter by 2050 due to an increase in temperature. The total agricultural ADW reuse amounts will increase by 47.4% for summer and 17.5% for winter by 2050 due to the creation of farmlands, as there will be an increase in food demand. Optimization results show that drainage water availability will increase by 31.6% and 21.3% respectively for summer and winter by 2050 due to climate change effects. Overall, the results show that the reuse of ADW demand and the available amounts is most likely affected by climate change.

Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test

Ensuring accurate estimation of evaporation is weighty for effective planning and judicious management of available water resources for agricultural practices. Thus, this work enhances the potential of support vector regression (SVR) optimized with a novel nature-inspired algorithm, namely, Slap Swarm Algorithm (SVR-SSA) against Whale Optimization Algorithm (SVR-WOA), Multi-Verse Optimizer (SVR-MVO), Spotted Hyena Optimizer (SVR-SHO), Particle Swarm Optimization (SVR-PSO), and Penman model (PM). Daily EP (pan-evaporation) was estimated in two different agro-climatic zones (ACZ) in northern India. The optimal combination of input parameters was extracted by applying the Gamma test (GT). The outcomes of the hybrid of SVR and PM models were equated with recorded daily EP observations based on goodness-of-fit measures along with graphical scrutiny. The results of the appraisal showed that the novel hybrid SVR-SSA-5 model performed superior (MAE = 0.697, 1.556, 0.858 mm/day; RMSE = 1.116, 2.114, 1.202 mm/day; IOS = 0.250, 0.350, 0.303; NSE = 0.0.861, 0.750, 0.834; PCC = 0.929, 0.868, 0.918; IOA = 0.960, 0.925, 0.956) than other models in testing phase at Hisar, Bathinda, and Ludhiana stations, respectively. In conclusion, the hybrid SVR-SSA model was identified as more suitable, robust, and reliable than the other models for daily EP estimation in two different ACZ.

Evolution of Dam Lakes in the Kayanga/Geba Basin: Contribution of Remote Sensing and GIS

The Confluent and Niandouba dams were built in 1984 and 1997 respectively to better control water resources, increase agricultural production and promote local development. This article studies their evolution on the Kayanga/Geba River, a transboundary river between Guinea, Senegal and Guinea-Bissau, from its impoundment to the present day. The topographic characteristics analysed through the DTMs (Digital Terrain Models) show a flat shape for the Confluent Dam Lake and long plateaus for the Niandouba Dam Lake. The cross-sections present a variety of morphologies ranging from wide U-shaped valleys with sinuous bottoms to deep V-shaped valleys. The homogenisation and reconstruction of missing values were carried out using the regional vector method. The application of Pettitt’s statistical test on annual rainfall (1932-2019) indicates breaks of stationarity in 1967 or 1969. The post-breakage deficits range from 11.4% to 19.4%. The segmentation method corroborates the results of the Pettitt test. The variations of the surface area of the Confluent and Niandouba water bodies are linked to rainfall, evaporation and withdrawals for different uses. Their monitoring would allow for better management of available water resources but also for good planning of off-season crops.

Water balance model as a tool for building participation and joint water use promotion at the river basin level*

AbstractTo promote collaboration on water management between farmers and government agencies, both parties must have a mutual understanding of the measurement and management of available water resources using existing infra‐ and non‐infrastructure management tools. They are required to provide collaborative water management through appropriate technology, with capacity building and knowledge management. In this study, the water balance model was used as a tool to induce participation and the promotion of a joint water use at the river basin level. The amount and proportion of water use from different types of water sources were calculated based on this water balance model. Moreover, farmers were encouraged to help with water flow measurements using technologies and principles that were simple but accurate in terms of engineering aspects. According to the analyses of water use proportions, a large amount of water from pumping stations was used during the dry season at high cost. When aware of the proportion of water used, farmers collaboratively established guidelines on an effective water management in the area, including large‐scale viewpoints applicable beyond the actual areas. Overall, these guidelines will eventually bring positive results to other downstream water users.

The local meteoric relationship for 18O and 2H in precipitations and isotopic compositions of water resources in northeast Amara area (South of Iraq)

This paper focuses on determining the Amara meteoric water line for the study area (AMWL) is defined or the first time, based on samples of precipitation collected Amara city - southeast of Iraq. For an adequate management of available water resources in semi-arid and arid regions, it is important to compare isotopic data of surface water and groundwater with the local meteoric relationship for d18O and dD in precipitations.Isotope values of precipitation indicate a local meteoric water line (Amara MWL δ2H = 7.51 δ18O + 10.82; R2=0.94) situated between the Mediterranean MWL and Global MWL. Both the slope and 2H intercept for AMWL are deviated from the global meteoric water line - GMWL (δ2H = 8.13 18O + 10) and Mediterranean MWL (δ 2H = 8.13 18O + 22). The slightly variation in isotopic compositions of the Missan rain (from -4 to +3.2‰ and from -20 to -14‰ for 18O and 2H, respectively) is because of slightly seasonal changes in precipitations in this area. The 18O and 2H isotopes of local water resources show that the rainwater is affected by the Arabian Gulf Arabian Sea potential moisture sources.