Regional analysis of parameter sensitivity for simulation of streamflow and hydrological fingerprints

Abstract

Abstract. Diagnostics of hydrological models are pivotal for a better understanding of catchment functioning, and the analysis of dominating model parameters plays a key role for region-specific calibration or parameter transfer. A major challenge in the analysis of parameter sensitivity is the assessment of both temporal and spatial differences of parameter influences on simulated streamflow response. We present a methodological approach for global sensitivity analysis of hydrological models. The multilevel approach is geared towards complementary forms of streamflow response targets, and combines sensitivity analysis directed to hydrological fingerprints, i.e. temporally independent and temporally aggregated characteristics of streamflow (INDPAS), with the conventional analysis of the temporal dynamics of parameter sensitivity (TEDPAS).The approach was tested in 14 mesoscale headwater catchments of the Ruhr River in western Germany using simulations with the spatially distributed hydrological model mHM. The multilevel analysis with diverse response characteristics allowed us to pinpoint parameter sensitivity patterns much more clearly as compared to using TEDPAS alone. It was not only possible to identify two dominating parameters, for soil moisture dynamics and evapotranspiration, but we could also disentangle the role of these and other parameters with reference to different streamflow characteristics. The combination of TEDPAS and INDPAS further allowed us to detect regional differences in parameter sensitivity and in simulated hydrological functioning, despite the rather small differences in the hydroclimatic and topographic setting of the Ruhr headwaters.

Time Variant Sensitivity Analysis of Hydrological Model Parameters in a Cold Region Using Flow Signatures

“…Finally, we have used the Slope of the Flow duration Curve (SFDC) to evaluate the response of the rising and falling limb of the hydrograph (indicated by the central part of the flow duration curve) to major hydrological events, compared to the real watershed system. SFDC is obtained as in Equation (6) [27] for the region bounded by the 30% and 70% probabilities of exceedance, as represented by the two center dotted lines in Figure 2. It is calculated for both the measured and simulated streamflow and their difference is used as an evaluation metric:…”

“…Sensitivity analysis (SA) can assist the modeler in identifying the relative influence each model parameter has on the variation in model output. This information is typically used by the modeler to limit the number of parameters in calibration, thereby increasing the efficiency and computation speed of the calibration process [5,6]. In practice, SA is useful for determining the most informative parameters prior to model calibration.…”

Spatial Pattern Oriented Multi-Criteria Sensitivity Analysis of a Distributed Hydrologic Model

“…Recently it has been reported that the VIC model showed difficulty in simulating spatial variability and hydrologic connectivity [20]. Höllering et al [26] used hydrologic fingerprint-based sensitivity analysis using temporally independent and temporal dynamics of only streamflow data. They could identify two major driving parameters for evapotranspiration and soil moisture dynamics in different mesoscale catchments in Germany and reveal their relation to different streamflow characteristics.…”

New high-resolution gridded dataset of daily mean, minimum, and maximum temperature and relative humidity for Central Europe (HYRAS)

“…These grids consist of station measurements interpolated at a desired resolution using one of the various interpolation methods available. They are used as inputs for various models (Heininger and Cullmann (2015), Gusyev et al (2016), Stahl et al (2017), Höllering et al (2018)), and they can also be used for the bias correction of climate models (Imbery et al (2013), Willkofer et al (2018), Meyer et al (2019), Krähenmann et al (2020)). High-resolution observation grids furthermore allow for spatial analyses based on continuous surfaces rather than on irregularly spaced point measurements, and long-term daily grids allow for analyses on different spatial scales and for the analysis of trends.…”