ABSTRACT
High-resolution soil moisture data is crucial in the development of hydrological applications as it provides detailed insights into the spatiotemporal variability of soil moisture. The emergence of advanced remote sensing technologies, alongside the widespread adoption of machine learning, has facilitated the creation of continental and global soil moisture products both at fine spatial (1 km) and temporal (daily) scales. Some of these products rely on several data sources as input (satellite, in situ, modelling), and therefore an evaluation of their actual spatial and temporal resolution is required. Nevertheless, the absence of appropriate ground monitoring networks poses a significant challenge for this assessment. In this study, five high-resolution (1 km) soil moisture products (S1-RT1, S1-COP, SMAP-Planet, SMAP-NSIDC, and ESACCI-Zheng) were analysed and evaluated throughout the Italian territory, together with a coarse resolution (12.5 km) dataset for comparison (ASCAT-HSAF). The main objective is to investigate their actual spatial and temporal resolution, and accuracy. Firstly, a cross-comparison of the products in space and time is carried out, including the use of triple collocation analysis. Secondly, an application-based assessment is implemented, considering irrigation, fire, drought, and precipitation case studies. The results clearly indicate the limitations and the potential of each product. Sentinel-1 based products (S1-COP and S1-RT1) are found able to reproduce high-resolution spatial patterns by detecting localised events for irrigation, fire, and precipitation. Their lower temporal resolution leads to accuracies lower than that of the SMAP-Planet product, and comparable with SMAP-NSIDC and ESACCI-Zheng products. However, SMAP-Planet is found to have an actual spatial resolution coarser than 1 km. The study highlights the need for further research to improve the high-resolution soil moisture products, and particularly to determine accurately the spatial resolution represented in soil moisture products. At the same time, the analysed products are found able to address high-resolution applications for the first time, opening promising activities for their operational use in hydrology and water resources management.
ABSTRACT
Understanding the role of soil moisture and other controls in runoff generation is important for predicting runoff across scales. This paper aims to identify the degree of non-linearity of the relationship between event peak runoff and potential controls for different runoff generation mechanisms in a small agricultural catchment. The study is set in the 66 ha Hydrological Open Air Laboratory, Austria, where discharge was measured at the catchment outlet and for 11 sub-catchments or hillslopes with different runoff generation mechanisms. Peak runoff of 73 events was related to three potential controls: event precipitation, soil moisture and groundwater levels. The results suggest that the hillslopes dominated by ephemeral overland flow exhibit the most non-linear runoff generation behaviour for its controls; runoff is only generated above a threshold of 95% of the maximum soil moisture. Runoff generation through tile drains and in wetlands is more linear. The largest winter and spring events at the catchment outlet are caused by runoff from hillslopes with shallow flow paths (ephemeral overland flow and tile drainage mechanisms), while the largest summer events are caused by other hillslopes, those with deeper flow paths or with saturation areas throughout the year. Therefore, the response of the entire catchment is a mix of the various mechanisms, and the groundwater contribution makes the response more linear. The implications for hydrological modelling are discussed.
