Estimation of groundwater recharge and drought severity with varying model complexity

Freyberg, Jana von; Moeck, Christian; Schirmer, Mario

doi:10.1016/j.jhydrol.2015.05.025

Cited by 38 publications

(33 citation statements)

References 67 publications

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“…Several studies were based on lysimeters measurements for recharge estimation and understanding of flow drainage in the unsaturated zone (Chapman and Malone 2002;Freyberg et al 2015;Duncan et al 2016). The drawbacks of lysimeters are that they are expensive to install and need careful calibration.…”

Section: Introductionmentioning

confidence: 99%

Using Monte Carlo simulation to estimate natural groundwater recharge in Qatar

Baalousha

2016

Model. Earth Syst. Environ.

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Rainfall is the only source of groundwater recharge in arid countries, where no surface water exists. Quantification of the total volume of rainfall recharge is essential for water resources management, development and protection, but it is challenging. Numerous recharge estimation methods can be found in the literature, but the selection of the most appropriate one depends on the hydrogeological setting of the area of study and on the available data. Qatar is an arid country as rainfall is very little and surface water is non-existent. Aquifer is the only conventional source of water, which has been over-exploited in the last few decades. One of the main country's grand challenges is to implement an aquifer storage and recovery scheme, which requires understanding of the flow regime and quantification of the natural rainfall recharge. This study uses a water balance model coupled with Monte Carlo Simulation to quantify rainfall recharge. Using a historical groundwater piezometric map, the flow to the sea was calculated by applying Monte Carlo Simulation to the Darcy's Law. The natural recharge was calculated considering all water budget components. Results reveal the groundwater rainfall recharge amounts to 58.7 million m 3 , which is close to literature values obtained by other means.

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Section: Introductionmentioning

confidence: 99%

Using Monte Carlo simulation to estimate natural groundwater recharge in Qatar

Baalousha

2016

Model. Earth Syst. Environ.

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“…Recharge occurs when the soil moisture content exceeds the field capacity (von Freyberg et al 2015). Interception and root water uptake was included.…”

Section: And Lumped Parameter Bucket Model (Lumprem)mentioning

confidence: 99%

The influence of model structure on groundwater recharge rates in climate-change impact studies

2016

Self Cite

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Numerous modeling approaches are available to provide insight into the relationship between climate change and groundwater recharge. However, several aspects of how hydrological model choice and structure affect recharge predictions have not been fully explored, unlike the wellestablished variability of climate model chains-combination of global climate models (GCM) and regional climate models (RCM). Furthermore, the influence on predictions related to subsoil parameterization and the variability of observation data employed during calibration remain unclear. This paper compares and quantifies these different sources of uncertainty in a systematic way. The described numerical experiment is based on a heterogeneous two-dimensional reference model. Four simpler models were calibrated against the output of the reference model, and recharge predictions of both reference and simpler models were compared to evaluate the effect of model structure on climate-change impact studies. The results highlight that model simplification leads to different recharge rates under climate change, especially under extreme conditions, although the different models performed similarly under historical climate conditions. Extreme weather conditions lead to model bias in the predictions and therefore must be considered. Consequently, the chosen calibration strategy is important and, if possible, the calibration data set should include climatic extremes in order to minimise model bias introduced by the calibration. The results strongly suggest that ensembles of climate projections should be coupled with ensembles of hydrogeological models to produce credible predictions of future recharge and with the associated uncertainties.

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“…Several methods can be used to quantify groundwater recharge using different types of data (geological, hydrological and geochemical indicators) [11] and models [12]. For broad-scale assessments, river flow records are convenient because they integrate information over areas as large as the catchments of the gauged rivers, and they are a good alternative to other approaches whose data requirement is not compatible with the overall data scarcity characterizing the Mekong Basin.…”

Section: Introductionmentioning

confidence: 99%

Regional Assessment of Groundwater Recharge in the Lower Mekong Basin

Lacombe¹,

Douangsavanh

Vongphachanh

et al. 2017

Hydrology

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Abstract:Groundwater recharge remains almost totally unknown across the Mekong River Basin, hindering the evaluation of groundwater potential for irrigation. A regional regression model was developed to map groundwater recharge across the Lower Mekong Basin where agricultural water demand is increasing, especially during the dry season. The model was calibrated with baseflow computed with the local-minimum flow separation method applied to streamflow recorded in 65 unregulated sub-catchments since 1951. Our results, in agreement with previous local studies, indicate that spatial variations in groundwater recharge are predominantly controlled by the climate (rainfall and evapotranspiration) while aquifer characteristics seem to play a secondary role at this regional scale. While this analysis suggests large scope for expanding agricultural groundwater use, the map derived from this study provides a simple way to assess the limits of groundwater-fed irrigation development. Further data measurements to capture local variations in hydrogeology will be required to refine the evaluation of recharge rates to support practical implementations.

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Estimation of groundwater recharge and drought severity with varying model complexity

Cited by 38 publications

References 67 publications

Using Monte Carlo simulation to estimate natural groundwater recharge in Qatar

Using Monte Carlo simulation to estimate natural groundwater recharge in Qatar

The influence of model structure on groundwater recharge rates in climate-change impact studies

Regional Assessment of Groundwater Recharge in the Lower Mekong Basin

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