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Prediction of regional‐scale groundwater recharge and nitrate storage in the vadose zone: a comparison between a global model and a regional model

Turkeltaub, Tuvia; Ascott, Matthew J.; Gooddy, Daren C.; Jia, Xiaoxu; Shao, Ming‐An; Binley, Andrew. 2020 Prediction of regional‐scale groundwater recharge and nitrate storage in the vadose zone: a comparison between a global model and a regional model. Hydrological Processes, 34 (15). 3347-3357. 10.1002/hyp.13834

Abstract
Extensive nitrogen loads at the soil surface exceed plant uptake and soil biochemical capacity, and therefore lead to nitrogen accumulation in the deep vadose zone. Studies have shown that stored nitrogen in the vadose zone can eventually reach the water table and affect the quality of groundwater resources. Recently, global scale models have been implemented to quantify nitrate storage and nitrate travel time in the vadose zone. These global models are simplistic and relatively easy to implement and therefore facilitate analysis of the considered transport processes at a regional scale with no further requirements. However, the suitability of applying these models at a regional scale has not been tested. Here, we evaluate, for the first time, the performance and utility of global scale models at the regional scale. Applied to the Loess Plateau of China, we compare estimates of groundwater recharge and nitrate storage derived from global scale models with results from a regional scale approach utilizing the Richards and advection‐dispersion equations. The estimated nitrate storage was compared to nitrate observations collected in the deep vadose zone (>50 m) at five sites across the Loess Plateau. Although both models predict similar spatial patterns of nitrate storage, the recharge fluxes were three times smaller and the nitrate storage was two times higher compared with the regional model. The results suggest that global scale models are a potentially useful screening tool, but require refinement for local scale applications.
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Programmes:
BGS Programmes 2020 > Environmental change, adaptation & resilience
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