Updating flood annual maxima in Southern Italy
In recent years, numerous studies have shown a growing concern about the effects of climate change on the hydrological cycle and hydrological extremes. In particular, statistical analyses on either long hydrological series or modelled data show conflicting trends in different areas of Europe. In addition, the absence of continuous observations ...
Ensemble of optimised machine learning algorithms for predicting surface soil moisture content at global scale
Abstract. Accurate information on surface soil moisture (SSM) content at a global scale under different climatic conditions is important for hydrological and climatological applications. Machine learning (ML) based systematic integration of in-situ hydrological measurements, complex environmental and climate data and satellite observation facilitate to generate the best data products to monitor ...
The Theoretical Probability Distribution of Peak Outflows of Small Detention Dams
The functional relationship between detention dam inflows and outflows was derived in a closed form in a recent work, which led to a theoretically derived probability distribution (TDD) of the peak outflows from in-line detention dams. This TDD is tested using the generalized extreme value (GEV) as a reference distribution ...
Operations Manual for the Use of UAS in Environmental Studies (based on SORA 2.0)
This set of three documents represents a blueprint of an Operations Manual for UAS operations (OM) targeting environmental studies, accompanied by an Emergency Response Plan (ERP) and an example of UAS operation description and risk assessment according to JARUS SORA 2.0 (also known as ConOps). The OM focuses on normal ...
Detection of Surface Water and Floods with Multispectral Satellites
The use of multispectral satellite imagery for water monitoring is a fast and cost-effective method that can benefit from the growing availability of medium–high-resolution and free remote sensing data. Since the 1970s, multispectral satellite imagery has been exploited by adopting different techniques and spectral indices. The high number of available ...
Satellite flood detection integrating hydrogeomorphic and spectral indices
Satellite remote sensing is a highly valuable data source useful in the monitoring of surface water dynamics and an essential tool in flood risk management although several factors can interfere with the detection of water features. This study explores an approach that integrates satellite optical images and DEM-based hydrogeomorphic features ...
Monitoring Water Turbidity Using Remote Sensing Techniques
In the present work, the use of optical cameras for turbidity measurements is tested on the Bode River in Germany, which is one of the best-instrumented catchments in Central Germany with a long-term time series on water quantity and quality. Four trap cameras have been installed on monitored cross-sections with ...
Flood Susceptibility Mapping Using a Deep Neural Network Model: The Case Study of Southern Italy
This study suggests a rapid methodology to delineate areas prone to flood using machine learning techniques. Based on available historically flooded areas, the model employs and combines globally collectible and reproducible conditioning factors to analyze flood susceptibility. The flood inventory map includes historically flooded areas from 1920 that occurred over ...