Evaluation of 42 lumped rainfall-runoff models for the Wairau River catchment, New Zealand, using the MARRMoT toolbox

For decades, lumped rainfall-runoff models have been used for hydrological analysis and forecasting such as operational flood forecasting. However, the accuracy of model forecasts depends on the ability of the model to approximate the dominant hydrological processes of the catchment under consideration. These processes are site specific and, therefore, the choice of a particular model is challenging. 

A large number of hydrological models has been developed and applied in various regions of the world. Model choice has often been hampered in the past by technical problems such as different programming languages, different software platforms, and different input formats and requirements.

The Modular Assessment of Rainfall Runoff Model Toolbox (MARRMoT) unites 46 lumped models from around the world within the same Matlab® framework with standardized inputs. The model equations have been simplified and adapted for this purpose. As a result, it is possible to test a large number of different models with comparatively little effort. The models implemented in MARRMoT vary in their structural complexity and have between 1-24 parameters and between 1-8 storages.

Here MARRMoT was used in order to find a model or model ensemble suitable for the simulation of precipitation-runoff relationships in the Wairau River catchment, New Zealand. The catchment area is assumed to have predominantly homogeneous runoff-generating properties. Model input data (precipitation and potential evapotranspiration) was derived from the Virtual Climate Station Network by National Institute of Water and Atmospheric Research, NZ.

In a first scenario, 42 selected models from MARRMoT were calibrated for the Wairau River catchment using 45 years of Wairau River flow data, an in-built nonlinear unconstrained optimization algorithm and the model fitness criteria Kling-Gupta-Efficiency (KGE). In two further scenarios, calibrations using the KGE with inversely transformed flows (KGEi) as well as a mixed form of the two criteria (KGEm) were realized. 

Model performance was further evaluated based on different performance criteria such as NSE, RMSE and R². It was demonstrated that the model ranking depends on the choice of the performance.

Evaluating the model performance for the different calibration scenarios showed that a few models with very different structures performed well to reproduce the flow data. No decisive structural feature could be identified which all models have in common and which led to a good representation of the rainfall-runoff processes in the Wairau River catchment. However, the differentiated consideration of flow routing and a high degree of flexibility seem to benefit model performance. Deficits in the modeling can be seen in the discharge peaks, which are not correctly simulated by many models. The simulation of fast direct runoff with lumped models seems to be less accurate for the relatively large catchment area of ​​the Wairau River (3430 km²).

Eventually, three models (GR4J, FLEX-I and HBV-96) demonstrated a high performance in all three calibration scenarios and were identified as suitable for further use in the Wairau River catchment.