Hydrometeorology doi: 10.3390/hydrometeorology1020010

Authors: George Faidon D. Papakonstantinou

Urban areas face cumulative environmental pressures from climate variability, rapid urbanization, and growing concentrations of built assets, requiring geospatial methods that capture gradual, overlapping susceptibility patterns rather than rigid thresholds. This study presents the Urban Geoenvironmental Impact Index (UGII), a GIS-based fuzzy hydro-climatic and Earth Observation (EO) framework evaluating cumulative urban environmental susceptibility and built-asset exposure, supporting hazard-informed planning and climate adaptation. Nine indicators are integrated: precipitation intensity (annualized 99th-percentile daily contribution, R99p) from ERA5-Land reanalysis (1995–2024); NDVI, NDBI, and Land Surface Temperature from Landsat 9; DEM-derived Topographic Wetness Index, flow accumulation, slope, and plan curvature; and road density. Fuzzy membership functions and AHP weighting (Consistency Ratio = 0.0537) aggregate the standardized indicators into continuous susceptibility surfaces. Applied to the southern Athens Metropolitan Area, Greece, the framework compares a conventional AHP model (UGII 0.18–0.65) with a fuzzy-AHP model (UGII 0.10–0.75; pixel-wise differences −0.09 to 0.14). The fuzzy formulation widens the dynamic range and enhances spatial differentiation while preserving the principal susceptibility patterns of the conventional model. Elevated-susceptibility zones intersect high built-asset concentrations, identifying exposure hotspots relevant to hazard-informed planning, climate adaptation, and disaster-resilience decision support, with direct application to real-estate exposure assessment.

Hydrometeorology doi: 10.3390/hydrometeorology1020009

Authors: Gabriel J. Williams

This study investigates how cloud-radiative forcing interacts with continental thermodynamic environments to influence the evolution of the tropical cyclone boundary layer (TCBL) during landfall using high-resolution, full-physics numerical simulations. Three idealized landfall experiments representative of Atlantic continental environments are analyzed to examine how cloud-radiative processes respond to progressively stronger environmental thermodynamic forcing. The simulations show that cloud-radiative forcing influences the TCBL through a coupled thermodynamic pathway in which cloud condensate modifies radiative heating and cooling, altering boundary-layer stability and equivalent potential temperature. These thermodynamic changes, in turn, reorganize the secondary circulation, leading to changes in hurricane boundary-layer depth (HPBL), turbulent mixing, and radial inflow. The strength of this feedback depends strongly on the surrounding continental environment. Under warm-moist conditions, an extensive cloud shield at landfall generates longwave radiative forcing that broadens the inflow layer and deepens the HPBL. In warm-dry environments, dry-air intrusion fragments the onshore cloud shield, confining the radiative forcing and its boundary-layer response to localized regions. Under cool-moist conditions, environmental thermodynamic forcing increasingly competes with cloud-radiative forcing, shifting the secondary circulation rearward as cool continental air is advected cyclonically into the vortex. Taken together, these experiments identify three distinct regimes of TCBL evolution during landfall and show that the dominant control shifts from cloud-radiative forcing to environmental thermodynamic forcing as the strength of the continental thermodynamic forcing increases. These results provide a conceptual framework for understanding the transition from cloud-radiation-dominated to environmentally dominated TCBL evolution during tropical cyclone landfall, with implications for inland intensity forecasts and the evolution of the hurricane boundary layer.

Hydrometeorology doi: 10.3390/hydrometeorology1020008

Authors: Raúl Arasa-Agudo Matilde García-Valdecasas Ojeda José Luis Gil

During August 2022, several significant hail events were recorded in Catalonia (Spain), including 12 cm hail on the 30th, the largest size ever documented in Spain. This study evaluates the performance of the HAILCAST model coupled with WRF for these hail episodes. The model output has been compared with information from the Catalan Meteorological Agency (SMC) and with reports from the European Severe Weather Database (ESWD) including their observed sizes and locations. Daily HAILCAST maximum hail diameter fields were analyzed, together with accumulated hail simulated by WRF. Moreover, the events of 17, 21 and 30 August were selected for a further analysis, comparing the HAILCAST maximum hail size, accumulated hail from WRF working without HAILCAST, and WRF-simulated accumulated precipitation with precipitation from ERA5-Land, GPM IMERG product and observations from local stations. The results show that HAILCAST can substantially overestimate both the size and spatial extent of hail, with predicted diameters reaching up to 25 cm at specific points in the domain. The model’s ability to generate convection can be observed, which is closely related to the HAILCAST output. Overall, HAILCAST proves to be promising for hail forecasting, but its performance is tightly constrained by the convective activity produced by WRF.

Hydrometeorology doi: 10.3390/hydrometeorology1010007

Authors: Mahesh Lal Maskey Bibash Dhakal Anitha Madapakula Arjun Thapa Gafar (Lanre) Agunbiade

Evapotranspiration (ET) is a major component of the water and energy cycle, influencing hydrologic processes, agricultural management, groundwater recharge, and land surface–atmosphere interactions. Water balance methods for estimating ET are widely used because of their direct connection to the conservation of mass and their applicability across scales. This review examines the theoretical basis and recent developments in water balance approaches for estimating ET across different hydroclimatic regimes. It summarizes classic soil water balance methods, physically based hydrologic models, remote-sensing approaches, and integrated machine learning techniques. Major themes include uncertainty in precipitation, runoff, and storage estimates; groundwater flow; water balance closure; spatial heterogeneity; and the integration of Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat, and ground-based observations. More recently, hybrid physics-based and machine learning approaches have advanced ET estimation by combining process-based understanding with data-driven methods. Advances in computational hydrology, data assimilation, and Earth observation datasets are improving applications related to irrigation management, drought assessment, climate adaptation, and water-resource planning. Challenges remain in quantifying uncertainty, assessing model transferability, and representing groundwater and storage dynamics under changing hydroclimatic conditions. Overall, the review highlights the continued importance of water balance approaches for understanding ET dynamics and supporting sustainable water-resource management.

Hydrometeorology doi: 10.3390/hydrometeorology1010006

Authors: Hanoch Lavee

On Earth, atmospheric components (wind, temperature, humidity, precipitation) and hydrological components (surface runoff, groundwater, bodies of water, the cryosphere) interact constantly [...]

Hydrometeorology doi: 10.3390/hydrometeorology1010005

Authors: Armand Ketcha Malan Kablan Narcisse Zegbé Gahi Agossou Gadedjisso-Tossou Kouassi Dongo

Extreme precipitation has caused catastrophic flooding across West Africa, worsened by climate change. Understanding which rainfall type (deep, stratiform, or shallow convective) drives flooding along the West African coast can improve disaster response. This study combines seven years (2015–2021) of Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) monthly rain-type retrievals with forty-two years (1984–2025) of in situ daily rainfall observations from SODEXAM at Abidjan. GPM DPR data were aggregated into monthly climatological maps to characterize each rain type’s spatial distribution and seasonal cycle, while SODEXAM daily records were analyzed for rainy-day frequency and depth to identify the flood-critical period. All three types of rainfall contribute to the region’s high seasonal totals, but deep convective rainfall dominates and peaks in May and June, contributing on average 60% of total monthly rainfall versus 35% for stratiform and 5% for shallow convective rainfall. The 42-year ground record showed elevated rainy-day frequency and rainfall depth between 29 May and 18 June, defining a flood-critical period. This period coincides with the climatological peak in GPM-derived deep convective rainfall, indicating that deep convective systems are closely associated with the recurrent severe flooding observed in Abidjan from late May to mid-June.

Hydrometeorology doi: 10.3390/hydrometeorology1010004

Authors: Niels Thevs Martin Jäger Karapet Ohanyan Edgar Pirumyan Varazdat Sargsyan

Lake Sevan, 1242 km2 large, is the largest lake in the Caucasus and the largest lake in Armenia. This mountain lake serves as a natural water reservoir for the Hrazdan River, which is critical for the water supply to the capital, Yerevan, and the Ararat Valley, the most important agricultural region of Armenia. The annual outflow from the lake shall not exceed 170 million m3. Agriculture is an important economic sector within the lake’s basin, with summer and perennial crops partly depending on irrigation. This study used remote sensing to map the evapotranspiration of agriculture and other vegetation types to assess the extent to which agriculture poses pressure on the lake’s water balance. From 2023 to 2025, the evapotranspiration averaged across all the cropland in the study area ranged between 204 mm and 307 mm, which coincides with low yields of agriculture. During the growing season, evapotranspiration of summer and permanent crops exceeded precipitation by 4.2 to 4.5 million m3, which is small compared with the annual outflow of 170 million m3. Overall, the annual precipitation exceeded evapotranspiration of cropland, including irrigated cropland. The findings suggest that, under current land use and climatic conditions, agriculture around Lake Sevan exerted limited pressure on the lake’s water balance for the years 2023–2025 and is unlikely to substantially affect its capacity to sustain the required outflow into the Hrazdan River.

Hydrometeorology doi: 10.3390/hydrometeorology1010003

Authors: Effie Kostopoulou

This study examines the relationship between large-scale atmospheric circulation and precipitation variability over Greece, with a focus on both mean and extreme conditions. Seasonal mean sea level pressure anomalies over the Mediterranean are analysed using Principal Component Analysis with varimax rotation, followed by k-means clustering to identify dominant circulation patterns. The analysis is performed separately for each season over the period 1980–2025 using ERA5 reanalysis data. The identified circulation types are linked to precipitation over Greece through spatial composites and quantitative metrics, including seasonal precipitation totals and the maximum daily precipitation. The results reveal distinct spatial precipitation patterns associated with each circulation type, with cyclonic conditions favouring enhanced and widespread precipitation, particularly over western Greece, and anticyclonic types leading to suppressed rainfall. Despite relatively small differences in mean extreme precipitation intensity, substantial variations are observed in the upper tail of the distribution, with specific circulation types associated with a higher potential for intense daily rainfall events. This highlights differences between widespread precipitation and locally intense extremes, reflecting the role of circulation in modulating both the spatial extent and intensity of rainfall. The findings show that large-scale atmospheric circulation plays an important role in precipitation variability and extremes over Greece, particularly during the wet seasons, while summer precipitation appears to be more strongly influenced by local and convective processes.

Hydrometeorology doi: 10.3390/hydrometeorology1010002

Authors: Flávia M. Oliveira da Silva Nuno S. A. Pereira

Satellite-based remote sensing has become an essential tool for territorial monitoring and environmental analysis, particularly in the context of extreme events. The European Union’s Copernicus Programme provides open-access satellite data that support near-real-time environmental assessment. Among its missions, the Sentinel-2 satellites, equipped with the Multispectral Instrument (MSI), offer high spatial and spectral resolution through 13 spectral bands, enabling the detection and monitoring of water quality parameters in inland and coastal water bodies. In early May 2024, intense rainfall events in Rio Grande do Sul, southern Brazil, triggered one of the most severe flooding episodes recorded in the region over the past 40 years. The objective of this study is to assess the environmental impacts of this event by mapping the flooded areas and analysing changes in water quality using Sentinel-2 imagery. Sentinel-2 Level-1C (Top-of-Atmosphere) products were processed using the Copernicus Browser to evaluate variations in coloured dissolved organic matter (CDOM) and dissolved organic carbon (DOC). Temporal analysis based on true-colour composite images allowed the observation of a significant increase in water extent over a seven-day period. Temporal comparison of Sentinel-2 images acquired before, during, and after the flood consistently showed a progressive expansion of inundated areas, accompanied by spatially coherent increases in satellite-derived CDOM and DOC indicators during the flood peak, followed by a partial decrease after flood recession. Although no simultaneous field measurements were available for quantitative validation, the observed spatial–temporal patterns consistently indicate flood-induced deterioration of water quality. Elevated CDOM and DOC levels are commonly associated with increased organic matter inputs and may have implications for water availability and suitability for human and animal consumption. Given the expected increase in the frequency and intensity of extreme weather events driven by climate change, this study highlights the importance of satellite-based remote sensing for rapid environmental monitoring. The Sentinel satellite constellation demonstrates strong potential for near-real-time assessment, offering timely information and broad spatial coverage to support environmental management and decision-making.

Hydrometeorology doi: 10.3390/hydrometeorology1010001

Authors: Tomeu Rigo

Catalonia has a Mediterranean climate with intense, long drought or rainy periods, which are difficult to manage. The variable topography and sea conditions also help modulate the extreme atmospheric regime. The aim of this research is to model the regional precipitation regime using different radar and lightning fields. To conduct the analysis, several points at different heights have been selected to evaluate monthly values and establish common yearly patterns. It has been observed that there are two principal behaviours from the maxima: single and double modes. The single peak usually occurs during warm months (mainly July and August), meanwhile the bimodal maxima are concentrated in spring (March) and autumn (October or November).