Chloride mass balance for estimation of groundwater recharge in a semi-arid catchment of northern Ethiopia

Gebru, Teklebirhan Arefaine; Tesfahunegn, Gebreyesus Brhane

doi:10.1007/s10040-018-1845-8

Cited by 21 publications

(31 citation statements)

References 32 publications

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“…The average recharge value is 16 mm yr −1 , which is consistent with previous estimates at the site and with those obtained for other sandstone aquifers in semiarid areas in the US (4 % - Heilweil et al, 2006) and other studies in semiarid regions around the world (0.2-35 mm yr −1 equal to 0 %-5 % of the average precipitation, Scanlon et al, 2006). Recharge varies greatly across the catchment as a function of topography, surface geology and land use.…”

Section: Discussion and Conceptual Model For Rechargesupporting

confidence: 91%

“…In favorable circumstances, geochemically based methods have proven to be especially useful for estimating recharge rates. In areas where the geologic and anthropogenic sources of chloride in the subsurface are negligible, the distribution of chloride in the vadose zone and groundwater has been used to calculate long-term, site-wide (Wood and Sanford, 1995;Gebru and Tesfahunegn, 2018;Jebreen et al, 2018) and location-specific recharge values (Heilweil et al, 2006;Huang et al, 2018) to determine mechanisms of flow in the vadose zone (Sukhija et al, 2003;Li et al, 2017) and to evaluate the effects of environmental changes on recharge (Scanlon et al, 2007;Cartwright et al, 2007). Elevated tritium in precipitation derived from atmospheric releases during nuclear tests in the 1960s and transported into the subsurface has also been an invaluable tracer to determine modern recharge and mechanisms of flow in both vadose and groundwater zones (Cook and Böhlke, 2000;De Vries and Simmers, 2002).…”

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confidence: 99%

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Spatial and temporal variability of groundwater recharge in a sandstone aquifer in a semiarid region

Manna

Murray²,

Abbey³

et al. 2019

Hydrol. Earth Syst. Sci.

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Abstract. With the aim to understand the spatial and temporal variability of groundwater recharge, a high-resolution, spatially distributed numerical model (MIKE SHE) representing surface water and groundwater was used to simulate responses to precipitation in a 2.16 km2 upland catchment on fractured sandstone near Los Angeles, California. Exceptionally high temporal and spatial resolution was used for this catchment modeling: hourly climate data, a 20 m×20 m grid in the horizontal plane, and 240 numerical layers distributed vertically within the thick vadose zone and in the upper part of the groundwater zone. The finest practical spatial and temporal resolutions were selected to accommodate the large degree of surface and subsurface variability of catchment features. Physical property values for the different lithologies were assigned based on previous on-site investigations, whereas the parameters controlling streamflow and evapotranspiration were derived from calibration to continuous streamflow at the outfall and to average hydraulic heads from 17 wells. Confidence in the calibrated model was enhanced by validation through (i) comparison of simulated average recharge to estimates based on the applications of the chloride mass-balance method to data from the groundwater and vadose zones within and beyond the catchment, (ii) comparison of the water isotope signature (18O and 2H) in shallow groundwater to the variability of isotope signatures for precipitation events over an annual cycle, and (iii) comparison of simulated recharge time series and observed fluctuation of water levels. The average simulated recharge across the catchment for the period 1995–2014 is 16 mm yr−1 (4 % of the average annual precipitation), which is consistent with previous estimates obtained by using the chloride mass balance method (4.2 % of the average precipitation). However, one of the most unexpected results was that local recharge was simulated to vary from 0 to >1000 mm yr−1 due to episodic precipitation and overland runoff effects. This recharge occurs episodically with the major flux events at the bottom of the evapotranspiration zone, as simulated by MIKE SHE and confirmed by the isotope signatures, occurring only at the end of the rainy season. This is the first study that combines MIKE SHE simulations with the analysis of water isotopes in groundwater and rainfall to determine the timing of recharge in a sedimentary bedrock aquifer in a semiarid region. The study advances the understanding of recharge and unsaturated flow processes and enhances our ability to predict the effects of surface and subsurface features on recharge rates. This is crucial in highly heterogeneous contaminated sites because different contaminant source areas have widely varying recharge and, hence, groundwater fluxes impacting their mobility.

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Section: Discussion and Conceptual Model For Rechargesupporting

confidence: 91%

mentioning

confidence: 99%

Spatial and temporal variability of groundwater recharge in a sandstone aquifer in a semiarid region

Manna

Murray²,

Abbey³

et al. 2019

Hydrol. Earth Syst. Sci.

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“…However, uncertainty of chloride input and its transient variability in particular is expressed in rather wide and partly bimodal distribution of the scaling factor (sc_Conc) included in the calibration (Figures S1-S6 in supplement material). On one hand, measured chloride concentration in precipitation are in agreement with other studies in central Africa (Goni et al 2001, Gebru andTesfahunegn, 2019) and its transient behavior within the rainy season is considered in the applied model. On the other hand, impact of dry deposition is unknown, because of data scarcity and potential lateral flow of periodical flooding.…”

Section: Discussionsupporting

confidence: 87%

“…Dry deposition of chloride is estimated between 10 -30% of wet deposition (Bouchez et al 2019). The measured values are in the range of published data (Goni et al 2001, Gebru andTesfahunegn, 2019). However, not all rain samples could be analyzed for chloride concentration, due to limited sample amount.…”

Section: Climate Datamentioning

confidence: 52%

Modelling groundwater recharge, actual evaporation and transpiration in semi-arid sites of the Lake Chad Basin: The role of soil and vegetation on groundwater recharge

Neukum

Santos

Ronelngar

et al. 2021

Preprint

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Abstract. The Lake Chad Basin, located in the center of North Africa, is characterized by strong climate seasonality with a pronounced short annual precipitation period and high potential evapotranspiration. Groundwater is an essential source for drinking water supply as well as for agriculture and groundwater related ecosystems. Thus, assessment of groundwater recharge is very important although difficult, because of the strong effects of evaporation and transpiration as well as limited available data. A simple, generalized approach, which requires only a small number of field data, freely available remote sensing data, and well-established concepts and models, is tested for assessing groundwater recharge in the southern part of the basin. This work uses the FAO-dual Kc concept to estimate E and T coefficients at six locations that differ in soil texture, climate, and vegetation conditions. Measured values of soil water content and chloride concentrations along vertical soil profiles at these locations together with different scenarios for E and T partitioning and a Bayesian calibration approach are used to numerically simulate water flow and chloride transport. Average potential groundwater recharges and the associated model uncertainty at the six locations are assessed for the time-period 2003–2016. Model results show that interannual variability of groundwater recharge is generally higher than the uncertainty of the modelled groundwater recharge. Furthermore, the soil moisture dynamics at all locations are limited by water availability for evaporation in the uppermost part of the soil and by water uptake in the root zone rather than by the reference evapotranspiration.

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“…Previous studies on groundwater recharge have outlined numerous methods for estimating recharge, including chemical tracers [7][8][9][10][11], physical methods [12][13][14][15][16][17] and mathematical approaches [18,19]. The most widely used chemical tracer method is the chloride mass-balance method (CMB) [7][8][9][10], because it is conceptually simple and inexpensive to implement. However, the CMB method cannot estimate the negative component (groundwater evapotranspiration) of net recharge [1], therefore cannot be applied to groundwater discharge regions.…”

Section: Introductionmentioning

confidence: 99%

Groundwater Recharge Prediction Using Linear Regression, Multi-Layer Perception Network, and Deep Learning

Huang

Gao

Crosbie

et al. 2019

Water

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As the largest freshwater storage in the world, groundwater plays an important role in maintaining ecosystems and helping humans adapt to climate change. However, groundwater dynamics, such as groundwater recharge, cannot be measured directly and is influenced by spatially and temporally complex processes, models are therefore required to capture the dynamics and provide scientific advice for decision-making. This paper developed, estimated and compared the performance of linear regression, multi-layer perception (MLP) and Long Short-Term Memory (LSTM) models in predicting groundwater recharge. The experimental dataset consists of time series of annual recharge from the year 1970 to 2012, based on water table fluctuation estimates from 465 bores in the states of South Australia and Victoria, Australia. We identified the factors that influenced groundwater recharge and found that the correlation between rainfall and groundwater recharge was strongest. The linear regression model had the poorest fitting performance, with the root mean squared error (RMSE) being greater than 0.19 when various proportions of training data were considered. The MLP model outperformed the linear regression in the prediction capability, achieving RMSE = 0.11 when 80% of training data was considered. The LSTM model was found to have the best performance, whose root mean squared errors were less than 0.12 when various proportions of training data were applied. The relative importance of influential predictors was evaluated using the above three models.

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Chloride mass balance for estimation of groundwater recharge in a semi-arid catchment of northern Ethiopia

Cited by 21 publications

References 32 publications

Spatial and temporal variability of groundwater recharge in a sandstone aquifer in a semiarid region

Spatial and temporal variability of groundwater recharge in a sandstone aquifer in a semiarid region

Modelling groundwater recharge, actual evaporation and transpiration in semi-arid sites of the Lake Chad Basin: The role of soil and vegetation on groundwater recharge

Groundwater Recharge Prediction Using Linear Regression, Multi-Layer Perception Network, and Deep Learning

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