Advancing isotope‐enabled hydrological modelling for ungauged calibration of data‐scarce humid tropical catchments

Abstract

AbstractRealistic projections of the future climate and how this translates to water availability is crucial for sustainable water resource management. However, data availability constrains the capacity to simulate streamflow and corresponding hydrological processes. Developing more robust hydrological models and methods that can circumvent the need for large amounts of hydro‐climatic data is crucial to support water‐related decisions, particularly in developing countries. In this study, we use natural isotope tracers in addition to hydro‐climate data within a newly developed version of the spatially‐distributed J2000iso as an isotope‐enabled rainfall‐runoff model simulating both water and stable isotope (δ2H) fluxes. We pilot the model for the humid tropical San Carlos catchment (2500 km2) in northeastern Costa Rica, which has limited time series, but spatially distributed data. The added benefit of simulating stable isotopes was assessed by comparing different amounts of observation data using three model calibration strategies (i) three streamflow gauges, (ii) three gauges with stream isotopes and (iii) isotopes only. The J2000iso achieved a streamflow Kling–Gupta efficiency (KGE) of 0.55–0.70 across all the models and gauges, but differences in hydrological process simulations emerged when including stable water isotopes in the rainfall‐runoff calibration. Hydrological process simulation varied between the standard J2000 rainfall‐runoff model with a high simulated surface runoff proportion of 37% as opposed to the isotope version with 84%–89% simulated baseflow or interflow. The model solutions that used only isotope data for calibration exhibited differences in simulated interflow, baseflow and model performance but captured bulk water balances with a reasonable match between the simulated and observed hydrographs. We conclude that J2000iso has shown the potential to support water balance modelling for ungauged catchments using stable isotope, satellite and global reanalysis data sets.