Behind the scenes of streamflow model performance

Abstract

Abstract. Streamflow is often the only variable used to evaluate hydrological models. In a previous international comparison study, eight research groups followed an identical protocol to calibrate 12 hydrological models using observed streamflow of catchments within the Meuse basin. In the current study, we quantify the differences in five states and fluxes of these 12 process-based models with similar streamflow performance, in a systematic and comprehensive way. Next, we assess model behavior plausibility by ranking the models for a set of criteria using streamflow and remote-sensing data of evaporation, snow cover, soil moisture and total storage anomalies. We found substantial dissimilarities between models for annual interception and seasonal evaporation rates, the annual number of days with water stored as snow, the mean annual maximum snow storage and the size of the root-zone storage capacity. These differences in internal process representation imply that these models cannot all simultaneously be close to reality. Modeled annual evaporation rates are consistent with Global Land Evaporation Amsterdam Model (GLEAM) estimates. However, there is a large uncertainty in modeled and remote-sensing annual interception. Substantial differences are also found between Moderate Resolution Imaging Spectroradiometer (MODIS) and modeled number of days with snow storage. Models with relatively small root-zone storage capacities and without root water uptake reduction under dry conditions tend to have an empty root-zone storage for several days each summer, while this is not suggested by remote-sensing data of evaporation, soil moisture and vegetation indices. On the other hand, models with relatively large root-zone storage capacities tend to overestimate very dry total storage anomalies of the Gravity Recovery and Climate Experiment (GRACE). None of the models is systematically consistent with the information available from all different (remote-sensing) data sources. Yet we did not reject models given the uncertainties in these data sources and their changing relevance for the system under investigation.

Understanding each other's models: an introduction and a standard representation of 16 global water models to support intercomparison, improvement, and communication

“…A widely accepted list of definitions would avoid confusion and facilitate successful interaction and collaboration. Furthermore, we need to clarify hydrological terms for peers from other disciplines, stakeholders, and a general audience (Brunner et al, 2018) to facilitate easier communication, understanding, and analysis.…”

Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment

“…Isotope analysis was carried out using laser-based cavity ring-down spectrometers (L2120-i/L2130-i, Picarro Inc.). Internal standards calibrated against VSMOW, Greenland Ice Sheet Precipitation (GISP) and Standard Light Antarctic Precipitation (SLAP2) were used for calibration and to ensure long-term stability of analyses (Brand et al, 2014). The longterm precision of the analytical system was ≤ 0.1 % for δ 18 O.…”

Future changes in annual, seasonal and monthly runoff signatures in contrasting Alpine catchments in Austria

“…Similarly, snow processes are simplified by using a degree day method and, in the absence of more detailed data, not considering snow redistribution and sublimation, although it can have a significant effect in high-elevation areas (MacDonald et al, 2010). In general, different models with different structures are often not consistent in the results (e.g., Knoben et al, 2020) or their internal dynamics (Bouaziz et al, 2021). This uncertainty in model structure was not assessed here, and it would be worthwhile to repeat a similar study using another hydrological model.…”

“…As reiterated by the latest IPCC report (IPCC, 2019), special attention needs to be given to high-elevation areas as their hydrological regimes are strongly influenced by snow dynamics and changes in glaciated areas. Furthermore, the S. Hanus et al: Future changes in annual, seasonal and monthly runoff signatures average temperature increase in the Alps over the last century was by a factor of 1.6 higher than the average worldwide temperature increase over land (IPCC, 2007;Brunetti et al, 2009). In alpine regions, monthly runoff and the associated occurrence of flow extremes are characterized by a strong seasonality, with maximum runoff typically occurring in spring and summer during the snowmelt season and minimum runoff in winter.…”