A catchment's runoff response to precipitation largely depends on the antecedent soil moisture and on the characteristics of the precipitation event, but also on other hydro-meteorological conditions, such as evapotranspiration. Studies investigating the effects of hydro-meteorological variables on runoff characteristics in catchments with daily temporal resolution mostly used surrogate measures of soil moisture derived from hydrological models or remote sensing products. Here, we applied a time series-based pattern search to up to 12 years of daily in situ measured soil moisture in three depths (5, 20 and 50 cm) in three headwater catchments, two of which are located in Germany (forest and grassland) and one in Austria (agriculture), to identify key variables influencing runoff characteristics under analogous soil moisture patterns. After detecting groups of analogous soil moisture, we split the corresponding runoff into similar and different patterns based on goodness-of-fit criteria and analysed their influencing hydro-meteorological variables with descriptive statistics and Spearman rank correlation coefficients (ρ). Results showed that in the forest and in the grassland catchment, the antecedent soil moisture mainly influenced runoff characteristics for analogous soil moisture patterns. In the agricultural catchment in Austria, both the antecedent soil moisture and rainfall characteristics had an influence on runoff characteristics. The proposed method can be used to evaluate hydro-meteorological drivers of event runoff characteristics under analogous soil moisture. In this way, hydrological processes that dominate in either group of similar or different runoff patterns can be differentiated, providing insights into the potential predictability of the respective runoff pattern.
Hövel, A., Stumpp, C., Bogena, H., Lücke, A., Strauss, P., Bloeschl, G., et al. (2025). Hydro‐Meteorological Drivers of Event Runoff Characteristics Under Analogous Soil Moisture Patterns in Three Small‐Scale Headwater Catchments. HYDROLOGICAL PROCESSES, 39(6), 1-15 [10.1002/hyp.70173].
Hydro‐Meteorological Drivers of Event Runoff Characteristics Under Analogous Soil Moisture Patterns in Three Small‐Scale Headwater Catchments
Bloeschl, Guenter;
2025
Abstract
A catchment's runoff response to precipitation largely depends on the antecedent soil moisture and on the characteristics of the precipitation event, but also on other hydro-meteorological conditions, such as evapotranspiration. Studies investigating the effects of hydro-meteorological variables on runoff characteristics in catchments with daily temporal resolution mostly used surrogate measures of soil moisture derived from hydrological models or remote sensing products. Here, we applied a time series-based pattern search to up to 12 years of daily in situ measured soil moisture in three depths (5, 20 and 50 cm) in three headwater catchments, two of which are located in Germany (forest and grassland) and one in Austria (agriculture), to identify key variables influencing runoff characteristics under analogous soil moisture patterns. After detecting groups of analogous soil moisture, we split the corresponding runoff into similar and different patterns based on goodness-of-fit criteria and analysed their influencing hydro-meteorological variables with descriptive statistics and Spearman rank correlation coefficients (ρ). Results showed that in the forest and in the grassland catchment, the antecedent soil moisture mainly influenced runoff characteristics for analogous soil moisture patterns. In the agricultural catchment in Austria, both the antecedent soil moisture and rainfall characteristics had an influence on runoff characteristics. The proposed method can be used to evaluate hydro-meteorological drivers of event runoff characteristics under analogous soil moisture. In this way, hydrological processes that dominate in either group of similar or different runoff patterns can be differentiated, providing insights into the potential predictability of the respective runoff pattern.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


