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Abstract

Jordan is facing significant challenges related to water scarcity, including overexploitation of groundwater, increasing demand, and wasteful practices. Despite efforts to manage water resources, inadequate planning has resulted in ongoing water security concerns and deteriorating water quantity and quality. To address water stress, Jordan has implemented measures such as desalination, dam construction, and water conservation initiatives. However, water stress remains high, necessitating a comprehensive strategy that includes short-term demand-side interventions and long-term supply-side reforms. Financial and governance challenges hinder the implementation of these measures, requiring private investment and coordination among stakeholders. This paper provides a comprehensive review of Jordan’s water resources, analyzing current trends, challenges, and opportunities. The aim is to offer insight into the current situation and propose sustainable management approaches. The findings will be valuable for policymakers, researchers, and stakeholders working towards addressing Jordan’s complex water challenges and securing a sustainable water future for its citizens.
Keywords: water resources; management; challenges; opportunities; wastewater; desalination; conventional; nonconventional; harvesting; water sustainability

Abstract

Study region

The upstream part of the Essaouira basin, a data-scare region in Morocco, Northwestern Africa.

Study focus

The scarcity of hydro-climate data is a significant challenge found in several regions worldwide, where qualitative and quantitative water resource information remains limited. Estimating and predicting groundwater levels (GWL) in such areas is a significant challenge in producing knowledge for effective water resource management. To address this issue, the present study aimed to use the Soil and Water Assessment Tool (SWAT) model in conjunction with downscaled total water storage (TWS) data (9 km) obtained from Gravity Recovery And Climate Experiment (GRACE) and machine learning techniques, specifically random forest (RF) and support vector machine (SVM), to estimate and predict the variation in GWL.

New hydrological insights for the region

This study constitutes a first of its kind in the study area; the SWAT model was set up for 10 years, with a warm-up period from 2000 to 2001, calibration from 2002 to 2007, and validation from 2008 to 2010. The statistical indices (Coefficient of Determination (R²) ≥ 0.73, R² ≥ 0.78, Nash–Sutcliffe model efficiency coefficient (NSE) ≥ 0.67, NSE ≥ 0.80 respectively for calibration and validation) highlight a significant correlation, implying the model's capability to faithfully reproduce the streamflow. The downscaled TWS demonstrates an impressive ability to identify and monitor fluctuations in GWL. Using machine learning algorithms (RF and SVR), the prediction of GWL yielded satisfactory results, NSE = 0.78 and root mean square error (RMSE) = 0.33, NSE = 0.51 and RMSE = 0.49 for the RF and SVR, respectively. Despite some limitations, our approach provided promising results in GWL prediction, with the possibility of expanding to other data-scarce regions.

Abstract

Under arid and semi-arid climatic conditions, groundwater is a basic resource to meet the requirements of socioeconomic development. Better conservation of this resource requires understanding the functioning of aquifer systems by informing about the degree of its vulnerability, the hydrochemical processes that control it, as well as the mode and origin of groundwater recharge. The location of vulnerable recharge areas is of crucial importance for the protection and rational management of groundwater, particularly in arid and semi-arid areas where a systematic monitoring and the master of pollution sources are lacking. In this context, this study aims to develop a 3D conceptual model of the Chiadma-South aquifer system (Essaouira basin, Morocco) based on hydrochemical, isotopic data and the DRASTIC model. The vulnerability and NO3 contents maps show that the upstream part and the downstream part of the study area are the most threatened by intrinsic pollution. The chemical characterization of the investigated aquifer shows that the mineralisation is governed by the dissolution of the surrounding formations, and evaporation phenomena and no seawater intrusion has been detected. The isotopic characterization of the input signal displayed that precipitation replenishing groundwater within the catchment have an Atlantic fingerprint, with the evaporation focused on the midstream part in the North and the upstream part in the South. However, visualisation of all highlighted processes under a 3D conceptual model could be a support for decision-makers to implement a rational management strategy for the vital resource of the study area.

AGREEMED is part of the PRIMA programme supported
by the European Union.

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