Estimating groundwater recharge for a freshwater lens in an arid region: Formative and stability assessment

Alrashidi, Mosaed S.; Bailey, Ryan T.

doi:10.1002/hyp.13649

Cited by 7 publications

(4 citation statements)

References 68 publications

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“…We simulated an island with an enhanced‐recharge area at the domain center, which can be caused by a lake or an artificial recharge trench (Bouchez et al., 2016; Bouwer, 2002, Tu et al., 2011). Table 1 lists the typical hydrogeologic and geometric parameters (Alrashidi & Bailey, 2019; Chui & Terry, 2015; Ketabchi et al., 2014). This domain is 600 × 150 m, and the size of each cell is 1 × 1 m. Two top corners are set as fixed head ( h = 0).…”

Section: Numerical Validationmentioning

confidence: 99%

Analytical Solutions for Fresh Groundwater Lenses in Small Strip Islands With Spatially Variable Recharge

Tang

Yan

Wang

et al. 2021

Water Resources Research

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Groundwater lens may provide the primary freshwater supply for the inhabitants of small islands. The lens profile and volume are sensitive to spatially variable recharge caused by topography, soil type, land cover, evapotranspiration and human activities. We derive analytical solutions based on the sharp‐interface approximation to describe transient and steady‐state lens profiles for spatially variable recharge rates in small strip islands. The derived solutions are validated by a steady‐state solution for simple spatial recharge patterns and numerical simulations. Numerical investigations show that the spatial recharge pattern has a significant impact on the lens profile. For a given constant total recharge, smaller recharge areas or a more concentrated recharge rate can result in a larger lens volume. The volume increase can be over 20% compared with the lens volume of a uniform recharge. For the steady‐state lens profile corresponding to a point recharge, the squared lens thickness peaks at the recharge location and linearly decreases to the boundary, resulting in a triangle shape for the profile of squared lens thickness. Moreover, compared with recharges in other locations, recharge in a small area at the domain center has the greatest impact. Uncertainty analysis can be conveniently implemented based on the derived analytical solution to investigate the lens behavior under spatially variable recharge with uncertainties. Results show that the lens volume tends to have a larger variance for a recharge rate with a higher variance and longer correlation length.

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Section: Numerical Validationmentioning

confidence: 99%

Analytical Solutions for Fresh Groundwater Lenses in Small Strip Islands With Spatially Variable Recharge

Tang

Yan

Wang

et al. 2021

Water Resources Research

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“…The longer time scales (12 and 24 months) used in this study are more suitable for characterizing drought impacts on groundwater resources. Groundwater aquifers respond slowly to rainfall shortages [48]; therefore, shorter drought analysis scales (e.g., 1-6 months) would certainly fail to present the true drought status given Kuwait's long annual zero-rainfall period, making their usage for drought analysis meaningless.…”

Section: Drought Forecasting In Hyper-arid Climatesmentioning

confidence: 99%

Hydrometeorological Drought Forecasting in Hyper-Arid Climates Using Nonlinear Autoregressive Neural Networks

Alsumaiei

Alrashidi

2020

Water

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Drought forecasting is an essential component of efficient water resource management that helps water planners mitigate the severe consequences of water shortages. This is especially important in hyper-arid climates, where drought consequences are more drastic due to the limited water resources and harsh environments. This paper presents a data-driven approach based on an artificial neural network algorithm for predicting droughts. Initially, the observed drought events in the State of Kuwait were tested for autocorrelation using the correlogram test. Due to the cyclic nature of the observed drought time series, nonlinear autoregressive neural networks (NARs) were used to predict the occurrence of drought events using the Levenberg–Marquardt algorithm to train the NAR models. This approach was tested for the forecasting of 12- and 24-month droughts using the recently developed precipitation index (PI). Four statistical measures were used to assess the model’s performance during training and validation. The performance metrics indicated that the drought prediction was reliable, with Nash–Sutcliffe values of 0.761–0.878 during the validation period. Additionally, the computed R2 values for model forecasts ranged between 0.784–0.883, which indicated the quality of the model predictions. These findings contribute to the development of more efficient drought forecasting tools for use by water managers in hyper-arid regions.

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“…In addition, anthropogenic stresses to the groundwater reserves through abstraction in the study area are minimal. Previous studies estimated that the annual recharge volumes to Al-Rawdatain basin are in the order of millions of cubic meters while current withdrawals rates do not exceed 100,000 m 3 /year [22,[37][38][39][40]. On the other hand, at Umm-Al-Aish basin, there are no current withdrawals due to the lower quality of groundwater.…”

Section: Case Study Of Groundwater Aquifers In the State Of Kuwaitmentioning

confidence: 99%

Monitoring Hydrometeorological Droughts Using a Simplified Precipitation Index

Alsumaiei

2020

Climate

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Efficient water management plans should rely on quantitative metrics for assessing water resource shortage scenarios. This study develops a simplified precipitation index (PI) requiring precipitation data only in order to assess hydrometeorological droughts affecting various hydrological systems. The PI index is inspired by the famous Standardized Precipitation Index (SPI), and it aims to provide the same indication for drought severity and duration while overcoming the disadvantage of needing hydrological data normalization. Avoiding hydrological data normalization overcomes the non-satisfactory results of this procedure that were reported in previous studies. Analysis of groundwater drought drivers in the arid region of Kuwait is presented to test the index applicability at timescales 12 and 24 months using available historical precipitation data from 1958 to 2017. A bivariate joint probability analysis was conducted by Clayton copula to assess the occurrence of certain drought severities and durations. The results showed that PI is comparable to the original SPI and provides drought severity linearly propagating with respect to time. This index constitutes a simple means to help water managers assess and describe the impact of droughts in precipitation-controlled systems and establish appropriate water management plans.

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Estimating groundwater recharge for a freshwater lens in an arid region: Formative and stability assessment

Cited by 7 publications

References 68 publications

Analytical Solutions for Fresh Groundwater Lenses in Small Strip Islands With Spatially Variable Recharge

Analytical Solutions for Fresh Groundwater Lenses in Small Strip Islands With Spatially Variable Recharge

Hydrometeorological Drought Forecasting in Hyper-Arid Climates Using Nonlinear Autoregressive Neural Networks

Monitoring Hydrometeorological Droughts Using a Simplified Precipitation Index

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