Spatial distribution of groundwater recharge and base flow: Assessment of controlling factors

Z Zomlot, Boud Verbeiren, Marijke Huysmans, Okke Batelaan

    Research output: Contribution to journalArticlepeer-review

    51 Citations (Scopus)

    Abstract

    Study focus: Groundwater is of strategic importance. The accurate estimation of groundwater recharge and assessing the fundamental controlling factors are therefore of utmost importance to protect groundwater systems. We used the spatially-distributed water-balance model WetSpass to estimate long-term average recharge in Flanders. We validated recharge rates with base flow estimates of 67 daily stream flow records using the hydrograph analyses. To this end we performed principal component analysis, multiple linear regression analysis and relative importance analysis to assess the controlling factors of the spatial variation of recharge and base flow with the influencing watershed characteristics. New hydrological insights for the region: The average resulting recharge is 235. mm/year and occurs mainly in winter. The overall moderate correlation between base flow estimates and modeled recharge rates indicates that base flow is a reasonable proxy of recharge. Groundwater recharge variation was explained in order of importance by precipitation, soil texture and vegetation cover; while base flow variation was strongly controlled by vegetation cover and groundwater depth. The results of this study highlight the important role of spatial variables in estimation of recharge and base flow. In addition, the prominent role of vegetation makes clear the potential importance of land-use changes on recharge and hence the need to include a proper strategy for land-use change in sustainable management of groundwater resources.

    Original languageEnglish
    Pages (from-to)349-368
    Number of pages20
    JournalJournal of Hydrology: Regional Studies
    Volume4
    Issue numberPart B
    DOIs
    Publication statusPublished - 1 Sep 2015

    Keywords

    • Base flow
    • Flanders
    • Multiple linear regression
    • Principal component analysis
    • Recharge
    • Relative importance analysis

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