Evaluation of soil hydrological simulations is essential to assess the model's reliability. Usually the evaluation is based on the comparison between simulations and observations. However, observing the soil-vegetation-atmosphere continuum is accompanied by large efforts. Due to the required efforts, availability of observations is spatio-temporal limited. If observations are not available simulations might be compared to benchmark values. These benchmark values can be generated by another model that is much simpler than the model under evaluation.

The aim of this MSc thesis is to generate benchmark values and compare the benchmark-based evaluation approach to observation-based evaluation approaches.

Benchmarking is already used in hydrological modelling to evaluate streamflow simulations (e.g. Knoben et al., 2019; Seibert et al., 2018; Seibert 2001). In soil hydrological modelling, benchmarking has not been employed, yet. In order to generate suitable benchmark values for soil hydrological modelling, the simple transfer function hydrograph separation model (TRANSEP; Weiler et al., 2003) will be used. The benchmarking experiment will be conducted with process-based soil hydrological model (RoGeR) and a physically-based hydrological model (HYDRUS-1D).

Robin Schwemmle, Markus Weiler

Soil hydrological observations and simulations are readily available for a weighing grassland lysimeter site (Seneviratne et al., 2012; Schwemmle & Weiler, 2023).

The TRANSEP model is available in Python (https://transep.readthedocs.io/en/latest/). The code is still very basic. The source code can be further modfied by the Msc-candidate.

Robin Schwemmle robin.schwemmle@hydrology.uni-freiburg.de

advanced programming skills, knowledge in the programming language Python

English (or German)

Knoben, W. J. M., Freer, J. E., and Woods, R. A.: Technical note: Inherent benchmark or not? Comparing Nash-Sutcliffe and Kling-Gupta efficiency scores, Hydrol. Earth Syst. Sci., 23, 4323–4331, [https://doi.org/10.5194/hess-23-4323-2019,](https://doi.org/10.5194/hess-23-4323-2019,) 2019.

Schwemmle, R., and Weiler, M.: Consistent modelling of transport processes and travel times - coupling soil hydrologic processes with StorAge Selection functions (in review), submitted to Water Resources Research, [https://doi.org/10.22541/essoar.167751575.55537069/v1,](https://doi.org/10.22541/essoar.167751575.55537069/v1,) 2023.

Seibert, J.: On the need for benchmarks in hydrological modelling, Hydrological Processes, 15, 1063-1064, [https://www.doi.org/10.1002/hyp.446,](https://www.doi.org/10.1002/hyp.446,) 2001.

Seibert, J., Vis, M. J. P., Lewis, E., and van Meerveld, H. J.: Upper and lower benchmarks in hydrological modelling, Hydrological Processes, 32, 1120-1125, [https://www.doi.org/10.1002/hyp.11476,](https://www.doi.org/10.1002/hyp.11476,) 2018.

Seneviratne, S. I., Lehner, I., Gurtz, J., Teuling, A. J., Lang, H., Moser, U., Grebner, D., Menzel, L., Schroff, K., Vitvar, T., and Zappa, M.: Swiss prealpine Rietholzbach research catchment and lysimeter: 32 year time series and 2003 drought event, Water Resources Research, 48, [https://doi.org/10.1029/2011wr011749,](https://doi.org/10.1029/2011wr011749,) 2012.

Weiler, M., McGlynn, B. L., McGuire, K. J., and McDonnell, J. J.: How does rainfall become runoff? A combined tracer and runoff transfer function approach, Water Resources Research, 39, [https://doi.org/10.1029/2003wr002331,](https://doi.org/10.1029/2003wr002331,) 2003.