Improving hydrological process understanding and model prediction using soil moisture data

Soil moisture is a critical control of process-based hydrologic models. This variable has so far been little used, mainly due to the difficulty to extract information from in-situ soil moisture observations that can be directly compared to simulated model variables. The concept of hydrological signature is now being increasingly used for the evaluation of hydrological models. However, hydrological signatures based on soil moisture are still rarely used.

We propose nine soil moisture signatures, encompassing three levels of hydrological time response (storm event response : rising time, normalized amplitude, response type, rising limb density, seasonal response : dates and durations of seasonal transitions, average characteristic values : distribution type, field capacity and wilting point). These signatures were applied to datasets from six in-situ observatories around the world with contrasted climates and land uses. The obtained values were analysed to assess whether the signatures could discriminate between land uses and could be interpreted in terms of hydrological processes.

Results showed that differences could be found between land uses for most signatures, and that these differences could be attributed to flow pathways or soil wetness, hence indicating that the signatures are good indicators of key hydrological processes and potentially useful for model evaluation.