Dataset of Sentinel-1 surface soil moisture time series at 1 km resolution over Southern Italy.

This paper describes the specifications of the surface soil volumetric water content ( Θ ) [m3/m3] product derived from Sentinel-1 (S-1) data and assessed in the study "Sentinel-1 soil moisture at 1 km resolution: a validation study" [1]. The S-1 Θ product consists of Θ mean and standard deviation values at 1 km spatial resolution and is expected to support applications in agriculture and hydrology as well as the Numerical Weather Prediction at regional scale [2]. The retrieval algorithm is a time series based short term change detection that is implemented in the "Soil MOisture retrieval from multi-temporal SAR data" (SMOSAR) code (v2.0). The provided dataset represents an example of the developed S-1 Θ product and consists of a time series of 183 S-1 Θ images over Southern Italy from January 2015 to December 2018. The maps were produced for each ascending S-1 acquisition date on the Relative Orbit Number (RON) 146 and the temporal gap between consecutive maps is 6 days (when both S-1A and S-1B data are available) or 12 days.

Sediment mobility and connectivity in a catchment: A new mapping approach.

In fluvial basin analysis, sediment connectivity is an important element for defining channel dynamics. Nevertheless, although several approaches to quantify this concept have been trialed, there is considerable discussion about ways to measure and assess sediment connectivity. The present study investigates sediment connectivity through the definition of a new index, aiming to integrate functional aspects within a structural component. Our objective is to produce a sediment flow connectivity index (SCI) map, directly applicable to monitoring and management activities. Our SCI is defined as the result of the gradient-based flow accumulation of a sediment mobility index, which is in turn a simple function of rainfall, geotechnical properties of soil and land use. This method is here applied to the Vernazza basin (eastern Liguria, Italy), producing a sediment connectivity map that shows good performance in predicting the positions and accumulation paths of mobilized deposits detected on the ground after the October 25th, 2011, flood event. A further evaluation of the proposed index is performed through a comparison of the maps derived using the SCI and connectivity index (IC) developed by Cavalli et al. (2013), which highlights comparable quantitative overall performances, together with a slightly better qualitative identification of subtle sediment flow paths by the SCI. In spite of current limitations due to, e.g., the local nature of the final index, the availability of input information through open global datasets promises the potential application of this method to larger-scale assessments, paying attention to properly addressing upscaling and standardization issues.