HGS RESEARCH HIGHLIGHT – Using High-Resolution Data to Test Parameter Sensitivity of the Distributed Hydrological Model HydroGeoSphere
Cornelissen, T., Diekkrüger, B., & Bogena, H. (2016). Using High-Resolution Data to Test Parameter Sensitivity of the Distributed Hydrological Model HydroGeoSphere. In Water (Vol. 8, Issue 5, p. 202). MDPI AG. https://doi.org/10.3390/w8050202
“In this study we use the distributed hydrological 3D-model HydroGeoSphere in a nested simulation approach to conduct a sensitivity analysis across scales.”
Graphical Abstract showing simulated vs observed evapotranspiration (ET) rates (top) and sensitivity of the simulated ET rates to changes in land use, potential ET rates and precipitation (bottom)
Fig. 1. Location of the Erkensruhr catchment and climate stations (A); land use (B) and soil type distribution in the Erkensruhr catchment (C). The bottom map also illustrates the border between the slope of the hill and the riparian area (refer to Chapter 2.3).
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In a recent study conducted by researchers Thomas Cornelissen, Bernd Diekkrüger, and Heye R. Bogena, the sensitivity of HydroGeoSphere (HGS) simulation results to high-resolution data is thoroughly examined to assess its sensitivity to high-resolution data.
The study focuses on parameterizing a mesoscale catchment for the HydroGeoSphere model by transferring evapotranspiration parameters from a well-equipped headwater catchment and incorporating literature data. By utilizing these parameters, the researchers aim to enhance the model's performance in simulating daily discharge dynamics and monthly evapotranspiration across different land use types within the mesoscale catchment.
The study successfully reproduces discharge dynamics and evapotranspiration patterns in Erkensruhr catchment is located in western Germany (~42 sqkm) using transferred parameters. Precipitation emerges as the most sensitive input data, significantly influencing total runoff and peak flow rates. Additionally, the study highlights the importance of spatially distributed land use parameterization in accurately simulating evapotranspiration components and patterns.
The study reveals that coarse soil data can lead to changes in runoff generation processes, affecting groundwater level rise and transpiration rates. These insights underscore the significance of utilizing high-resolution data and parameter transfer techniques to improve the accuracy of distributed hydrological models, particularly in mesoscale catchments where data scarcity poses a significant challenge.
By integrating HydroGeoSphere in this study, the researchers demonstrate its versatility in accommodating high-resolution data and conducting sensitivity analyses across different spatial scales. This research contributes to advancing our understanding of hydrological processes and improving the accuracy of distributed hydrological models in simulating complex catchment behaviors.
Abstract:
Parameterization of physically based and distributed hydrological models for mesoscale catchments remains challenging because the commonly available data base is insufficient for calibration. In this paper, we parameterize a mesoscale catchment for the distributed model HydroGeoSphere by transferring evapotranspiration parameters calibrated at a highly-equipped headwater catchment in addition to literature data. Based on this parameterization, the sensitivity of the mesoscale catchment to spatial variability in land use, potential evapotranspiration and precipitation and of the headwater catchment to mesoscale soil and land use data was conducted. Simulations of the mesoscale catchment with transferred parameters reproduced daily discharge dynamics and monthly evapotranspiration of grassland, deciduous and coniferous vegetation in a satisfactory manner. Precipitation was the most sensitive input data with respect to total runoff and peak flow rates, while simulated evapotranspiration components and patterns were most sensitive to spatially distributed land use parameterization. At the headwater catchment, coarse soil data resulted in a change in runoff generating processes based on the interplay between higher wetness prior to a rainfall event, enhanced groundwater level rise and accordingly, lower transpiration rates. Our results indicate that the direct transfer of parameters is a promising method to benefit highly equipped simulations of the headwater catchments.