Rainfall-runoff models are commonly evaluated against statistical evaluation metrics. However, these metrics do not provide much insight into what is hydrologically wrong if a model fails to simulate observed streamflow well and they are also not applicable for ungauged catchments. Here, we propose a signature-based hydrologic efficiency (SHE) metric consisting of hydrologic signatures that can be regionalized for model evaluation in ungauged catchments. We test our new efficiency metric across 633 catchments from Great Britain. Strong correlations with Spearman rank and Pearson correlation values around 0.8 are found between our proposed metric and commonly used statistical evaluation metrics (NSE, KGE, NP…) demonstrating that the proposed SHE metric is related to existing metrics as much as these metrics are related to each other. For ungauged catchments, we regionalise the three signatures included in SHE and find that 78% of catchments have an absolute difference of SHE values between gauged and ungauged cases of less than 0.2. This difference increases where the regionalized bias and variance signature values are different to the observed ones. It means that SHE metric is applicable for model evaluation in ungauged catchments if its signatures can be regionalized well.

The analysis of large samples of hydrologic catchments is regularly used to gain understanding of hydrologic variability and controlling processes. Several studies have pointed towards the problem that available catchment descriptors (such as mean topographic slope or average subsurface properties) are insufficient to capture hydrologically relevant properties. Here, we test the assumption that catchment location, i.e. the relative properties of catchments in relation to their surrounding neighbours, can provide additional information to reduce this problem. We test this idea in the context of Great Britain for a widely discussed problem, that of catchment water balance errors due to subsurface losses. We test three hypotheses while considering different locational aspects (1) location to coast, (2) location next a relevant neighbour and (3) location within the drainage basin, utilizing only basic and widely available geological and topographical information. We find that subsurface losses from catchments with a highly permeable geology connection to the coast are in order of 20% water balance error. We define a simple topographic-geologic index that is able to partially explain water balance issues between neighbours of highly permeable catchments. The results imply that location, geology and topography combine to define the differences of water balances of UK catchments compared to what we would expect from their climatic setting alone. The simple index defined here can easily be derived globally and tested regarding its wider applicability.