Preprints
https://doi.org/10.5194/hess-2021-428
https://doi.org/10.5194/hess-2021-428

  17 Aug 2021

17 Aug 2021

Review status: this preprint is currently under review for the journal HESS.

Remote sensing-aided large-scale rainfall-runoff modelling in the humid tropics

Saúl Arciniega-Esparza1, Christian Birkel2,3, Andrés Chavarría-Palma2, Berit Arheimer4, and Agustín Breña-Naranjo5,6 Saúl Arciniega-Esparza et al.
  • 1Hydrogeology Group, Faculty of Engineering, Universidad Nacional Autónoma de México, Mexico City, 04510, Mexico
  • 2Department of Geography and Water and Global Change Observatory, University of Costa Rica, San José, Costa Rica
  • 3Northern Rivers Institute, University of Aberdeen, Aberdeen, Scotland
  • 4Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
  • 5Institute of Engineering, Universidad Nacional Autónoma de México, Mexico City, Mexico
  • 6Instituto Mexicano de Tecnología del Agua, Jiutepec, Morelos, Mexico

Abstract. Streamflow simulation across the tropics is limited by the lack of data to calibrate and validate large-scale hydrological models. Here, we applied the process-based, conceptual HYPE (Hydrological Predictions for the Environment) model to quantitively assess Costa Rica’s water resources at a national scale. Data scarcity was compensated using adjusted global topography and remotely-sensed climate products to force, calibrate, and independently evaluate the model. We used a global temperature product and bias-corrected precipitation from CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) as model forcings. Daily streamflow from 13 gauges for the period 1990–2003 and monthly MODIS (Moderate Resolution Imaging Spectroradiometer) potential evapotranspiration (PET) and actual evapotranspiration (AET) for the period 2000–2014 were used to calibrate and evaluate the model applying four different model configurations. The calibration consisted in step-wise parameter constraints preserving the best parameter sets from previous simulations in an attempt to balance the variable data availability and time periods. The model configurations were independently evaluated using hydrological signatures such as the baseflow index, runoff coefficient, and aridity index, among others. Results suggested that a two-step calibration using monthly and daily streamflow was a better option instead of calibrating only with daily streamflow. Additionally, including PET and AET in the calibration improved the simulated water balance and better matched hydrological signatures. Thus, the constrained parameter uncertainty increased the confidence in the simulation results. Such a large-scale hydrological model has the potential to be used operationally across the humid tropics informing decision making at relatively high spatial and temporal resolution.

Saúl Arciniega-Esparza et al.

Status: open (until 12 Oct 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-428', Anonymous Referee #1, 15 Sep 2021 reply
  • RC2: 'Comment on hess-2021-428', Anonymous Referee #2, 18 Sep 2021 reply

Saúl Arciniega-Esparza et al.

Data sets

Hydrological simulations for Costa Rica from 1985 to 2019 using HYPE CR 1.0 Saúl Arciniega-Esparza, Christian Birkel https://doi.org/10.5281/zenodo.4029572

Saúl Arciniega-Esparza et al.

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Short summary
In the humid tropics, a notoriously data-scarce region, we need to find alternatives to be able to reasonably apply hydrological models. Here, we tested remotely sensed rainfall data to drive a model for Costa Rica and evaluated the simulations against evapotranspiration satellite products. We found that our model was able to reasonably simulate the water balance and streamflow dynamics of over 600 catchments, where the satellite data helped to reduce the model uncertainties.