On the selection of precipitation products for the regionalisation of hydrological model parameters

Abstract

Abstract. Over the past decades, novel parameter regionalisation techniques have been developed to predict streamflow in data-scarce regions. In this paper, we examined how the choice of gridded daily precipitation (P) products affects the relative performance of three well-known parameter regionalisation techniques (spatial proximity, feature similarity, and parameter regression) over 100 near-natural catchments with diverse hydrological regimes across Chile. We set up and calibrated a conceptual semi-distributed HBV-like hydrological model (TUWmodel) for each catchment, using four P products (CR2MET, RF-MEP, ERA5, and MSWEPv2.8). We assessed the ability of these regionalisation techniques to transfer the parameters of a rainfall-runoff model, implementing a leave-one-out cross-validation procedure for each P product. Despite differences in the spatio-temporal distribution of P, all products provided good performance during calibration (median Kling–Gupta efficiencies (KGE′s) > 0.77), two independent verification periods (median KGE′s >0.70 and 0.61, for near-normal and dry conditions, respectively), and regionalisation (median KGE′s for the best method ranging from 0.56 to 0.63). We show how model calibration is able to compensate, to some extent, differences between P forcings by adjusting model parameters and thus the water balance components. Overall, feature similarity provided the best results, followed by spatial proximity, while parameter regression resulted in the worst performance, reinforcing the importance of transferring complete model parameter sets to ungauged catchments. Our results suggest that (i) merging P products and ground-based measurements does not necessarily translate into an improved hydrologic model performance; (ii) the spatial resolution of P products does not substantially affect the regionalisation performance; (iii) a P product that provides the best individual model performance during calibration and verification does not necessarily yield the best performance in terms of parameter regionalisation; and (iv) the model parameters and the performance of regionalisation methods are affected by the hydrological regime, with the best results for spatial proximity and feature similarity obtained for rain-dominated catchments with a minor snowmelt component.

Unlocking the potential of stochastic simulation through Bluecat: Enhancing runoff predictions in arid and high‐altitude regions

“…To ensure near‐natural hydrological regimes, 99 of 516 catchments were selected for further analyses following Baez‐Villanueva et al (2021) criteria, which are briefly described as follows (see the Supplementary Material for a complete list of selected catchments): Less than 25% of missing values in the daily discharge time series for the selected period (1990–2018, it may be non‐consecutive); Absence of large dams (big_dam = 0); Less than 10% of discharge allocated to consumptive uses (interv_degree < 0.1); Not dominated by glaciers (lc_glacier < 5%); Less than 5% of the area is defined as urban (imp_frac < 5%); Absence of substantial irrigation abstractions (crop_frac < 20%); Less than 20% of the area is covered by forest plantations (fp_frac < 20%); No signs of artificial regulation in the hydrograph (10 catchments excluded in total). …”

“…To ensure near-natural hydrological regimes, 99 of 516 catchments were selected for further analyses following Baez-Villanueva et al (2021) criteria, which are briefly described as follows (see the Supplementary Material for a complete list of selected catchments): i. Less than 25% of missing values in the daily discharge time series for the selected period (1990-2018, it may be nonconsecutive);…”

Prediction at Ungauged Catchments through Parameter Optimization and Uncertainty Estimation to Quantify the Regional Water Balance of the Ethiopian Rift Valley Lake Basin

“…The global MSWEP data have been evaluated and showed better performance for data-scarce regions including Ethiopia [41]. The data product has been widely applied for the evaluation of gridded satellite products and regionalization studies in data-scarce regions [42]. For the discharge data due to monitoring and organization issues, high-quality streamflow data are only available from 1995 to 2007.…”

Impacts of Subgrid Temperature Distribution Along Elevation Bands in Snowpack Modeling: Insights From a Suite of Andean Catchments

“…The latter hydrological regimes can be further stratified into (a) pluvio-nival, where rainfall is the main control for runoff production (Claro), (b) fully mixed, with comparable rainfall and snowmelt-driven peak monthly runoff (Ñuble), or (c) nivo-pluvial, with snowmelt dominating catchment-scale hydrology (Arrayán, Mapocho, Colorado, Palos, and Melado). The reader is referred to Baez-Villanueva et al (2021) for further details on the classification criteria used here for hydrological regimes. Interestingly, there are catchments where the seasonal cycles of soil moisture and runoff are similar, regardless of their hydrological regimes (Las Leñas, Colorado, Palos, and Melado), and basins where these cycles are different (Arrayán, Mapocho, Claro, and Ñuble).…”

“…The reader is referred to Baez‐Villanueva et al. (2021) for further details on the classification criteria used here for hydrological regimes. Interestingly, there are catchments where the seasonal cycles of soil moisture and runoff are similar, regardless of their hydrological regimes (Las Leñas, Colorado, Palos, and Melado), and basins where these cycles are different (Arrayán, Mapocho, Claro, and Ñuble).…”