How is Baseflow Index (BFI) impacted by water resource management practices?
نویسندگان
چکیده
Abstract. Water resource management (WRM) practices, such as groundwater and surface water abstractions effluent discharges, may impact baseflow. Here the CAMELS-GB large-sample hydrology dataset is used to assess impacts of practices on Baseflow Index (BFI) using statistical models 429 catchments from Great Britain. Two complementary modelling schemes, multiple linear regression (LR) machine learning (random forests, RF), are investigate relationship between BFI two sets covariates (natural only a combined set natural WRM covariates). The LR RF show good agreement explanatory covariates. In all models, extent fractured aquifers, clay soils, non-aquifers, crop cover in catchments, catchment topography, aridity significant or important explaining BFI. When terms included, abstraction most covariate both discharge rivers also identified influential, although still provide main power models. Surface model but minor importance model. Reservoir storage not unimportant for this analysis. Inclusion improves performance some specific catchments. high with relatively levels greatest improvements, there evidence improvement moderate discharges. However, no that inclusion they improve These observations discussed within conceptual framework baseflow generation incorporates practices. A wide range schemes measures manage resources UK. include conjunctive-use low-flow alleviation hands-off flow measures. Systematic information currently unavailable CAMELS-GB, their effects cannot be constrained by current study. Given significance it recommended WRM, particularly abstraction, should included where possible future hydrological datasets analysis prediction other
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ژورنال
عنوان ژورنال: Hydrology and Earth System Sciences
سال: 2021
ISSN: ['1607-7938', '1027-5606']
DOI: https://doi.org/10.5194/hess-25-5355-2021