Catchment-scale hydrological models encountered dichotomies with the numerical hydrodynamic models when describing surface routing process. We propose a new modeling framework, the so-called “Runoff-On-Grid” approach, for embedding distributed process-based hydrological modeling into shallow water models, as an alternative to the traditional Fully Hydrodynamic Approach (also known as Rain-On-Grid). Antecedent Soil ...

Abstract. The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to tackle catchment-scale challenges on a global scale. The already existing monitoring infrastructures have provided an enormous amount of hydrometeorological data, which has helped gain detailed insights into the causality of ...

Floods are the most frequent type of natural disasters occurring worldwide. In 2021 alone, in fact, the majority of the recorded catastrophic events were floods, which also dominated in terms of the highest number of disaster-related fatalities according to the Centre for Research on the Epidemiology of Disasters (CRED, Delforge ...

Flood extent delineation techniques have benefited from the increasing availability of remote sensing imagery, classification techniques and the introduction of geomorphic descriptors derived from Digital Elevation Models (DEM). On the other hand, high-performing Machine Learning (ML) methods have allowed for the development of accurate flood maps by integrating several predictor ...

Enhanced and effective hydrological monitoring plays a crucial role in understanding water-related processes in a rapidly changing world. Within this context, image-based river monitoring has shown to significantly enhance data collection, improve analysis and accuracy, and support effective and timely decision-making. The integration of remote and proximal sensing technologies, with ...

The growing number of extreme hydrological events observed worldwide has raised the level of attention towards the impact of climate change on the rainfall process, which is difficult to quantify given its strong spatial and temporal heterogeneity. Therefore, the impact of the climate change should be determined ranging from individual ...

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-based systematic integration of in situ hydrological measurements, complex environmental and climate data, and satellite observation facilitate the generation of reliable data products to monitor and analyse ...

The study centered on the comprehensive assessment of satellite-based microwave soil moisture (SM) products across Europe, taking into account crucial variables including geographical diversity, climate dynamics, and land cover variations. We systematically compared SM products from esteemed entities such as NASA, ESA, ASCAT, SENTINEL-1, and ESA's Climate Change Initiative against ...