Dataset underlying the publication: Revealing spatial patterns of lateral hydraulic conductivity through sensitivity analysis

This dataset contains the results from a sensitivity analysis conducted for many catchments in England, Scotland, and Wales; We used wflow_sbm (Imhoff et al., 2020; van Verseveld et al., 2024) to run the wflow_sbm models. Wflow_sbm models were built using HydroMT (Eilander et al., 2022) for each CAMELS-GB catchment. The models were forced with CEH-GEAR rainfall, ERA5 derived PET and downscaled ERA5 temperature (using environmental lapse rate). The models were run for the period 01/01/1970-31/12/2015 . To investigate the sensitivity of the wflow_sbm model results to ksathorfrac values, this parameter was varied over a wide range (1,2,3,4,5,6,7,8,9,10,15,20,25,30,40,50,60,80,100,200,400,800,1000,2000,4000,6000,8000,10000). CAMELS-GB data was used as source for discharge observations. The first two years (01/9/1970-30/09/1972) were disregarded when calculating the metrics. We used the non parametric KGE (using python package hydromt) to assess the performance of each simulation and we selected the ksathorfrac from run with the highest performance . Along side the non parametric KGE , we also calculated KGE (using python package spotpy). The Ksathorfrac was multiplied with the mean vertical hydraulic conductivity to derived the mean horizontal lateral hydraulic conductivity which was used for plotting and calculating the Spearman rank correlation with base flow recession K estimates from McMillan et al (2022);