Extreme meteorological and climate events, such as floods and prolonged droughts, cause socio-environmental disasters in several regions of the world, including the Amazon. The Amazon Delta-Estuary, which is shaped by coastal and river environments, has constantly changing land use patterns, making it vulnerable to such events. This study aimed to evaluate rainfall regimes and flood scenarios in the tributaries of the Amazon Delta-Estuary, known as the Ottocoded River sub-basins, which are located in the municipalities of Abaetetuba and Barcarena in the Brazilian state of Pará. The Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset was used to analyze rainfall dynamics. The Height Above the Nearest Drainage (HAND) model was employed for flood modeling. The geomorphological, altimetric, bathymetric, and hydrodynamic components of the water bodies were also analyzed. Flood susceptibility was zoned as follows: Very High, High, Medium, Low and Very Low. Of the surveyed buildings, 28.8% were classified as ‘Very High’, 29.1% as ‘High’, 20.2% as ‘Medium’, 13.4% as ‘Low’, and 8.5% as ‘Very Low’. Many of these buildings are located in flood-prone areas, posing a significant risk of socio-environmental disasters. This research could inform public policies aimed at managing the risks associated with environmental disasters and extreme events.
Floods are among the most harmful natural disasters for humans, and rising global temperatures tend to make them more frequent. This paper aims to model flood susceptibility in Rio de Janeiro, Brazil, based on the 2019 and 2020 floods. The methodology used in the paper is based on the Analytical Hierarchy Process. The contribution of variables to extreme flood events was calculated to assess the influence of oceanic tides in conjunction with the extreme rainfall. The methodological procedures were mainly based on acquiring data referring to rainfall records, ocean tide oscillations, and other natural-anthropogenic variables. The results showed that ocean tidal oscillation in that region has played a secondary but essential role in flood events. Furthermore, observing ocean tide dynamics and extreme rainfall events is the key combination for explaining, preventing, and forecasting extreme flood events. For future research, it is recommended that the improvement of quality data (geodetic and meteorological) is essential to model flood susceptibility in coastal areas.
Victor Matheus C. de Carvalho, G. Guimarães, L. C. M. Xavier et al.· Anais da Academia Brasileira...· 0 citations
The Kelani River basin (KRB) is the highest flooding conditions appeared river basin in Sri Lanka. Based on this, the study investigates the impact of climate resilience on rainfall patterns, temperature, wind speed, and streamflow dynamics of the Kelani River basin in Sri Lanka to enhance flood risk prediction and floodplain restoration planning. Rainfall, temperature, and wind speed data for the 2013 to 2024 time period were obtained from five stations: Angoda, Colombo, Hanwella, Maliboda, and Rathnapura. Long-term trends were detected using statistical approaches such as the Mann-Kendall test. Actual versus predicted streamflow data were used to determine the effectiveness of the hydrological model, along with error distribution analysis. There was some variation in the rainfall; Rathnapura peaked at 6000 mm in 2019, and Maliboda was almost constant throughout. Statistical tests indicated an increase of 3.12 mm per year in rainfall. Within the temperature trends, there was no long-term variation at the Colombo and Rathnapura stations, while in wind speed, a moderate decline without statistical significance was recorded. The hydrological model showed shortcomings in the streamflow forecast, mainly due to underestimating the high flows and overestimating the low flows. The residual analysis indicated a deficiency in the model's representation of extreme events, and the Q-Q plot indicated poor performance in predicting runoff extremes. These limitations highlight the need for model refinement using nonlinear-learning-based approaches to improve flood risk assessment and inform adaptive restoration strategies under changing climate conditions.
Ravindya Samaranayake, A. Liyanage, R. T. K. Ariyawansha· Journal of Climate Change· 0 citations
Climate change necessitates basin scale assessments in vulnerable countries such as Türkiye due to its impacts on water resources and drought patterns. In this study, precipitation and runoff data up to the year 2100 were analyzed in the Harşit River Basin, one of the subbasins of the Eastern Black Sea Basin, to identify potential drought events. The SSP585 scenario of the HadGEM3-GC31-MM model was used for temperature and precipitation projections; model outputs were fed into the TUW hydrological model to obtain future flow values for the basin. The data were evaluated using the Standardized Precipitation Index and the Standardized Runoff Index at 1, 3, 6, 9, and 12 month time scales; comparing the 2009–2021 observation period, the 2040–2070 short term period, and the 2071–2100 long term period. The findings indicate that there will be significant increases in the intensity and frequency of dry and wet periods, particularly during the 2071–2100 period, thereby raising the risks of extreme drought and flash floods in the basin. The results are expected to contribute to drought risk management and sustainable water resources planning in the region.
Gökhan Demiral, Muhammet Bahadır, H. Zeybek et al.· Adıyaman Üniversitesi Mühend...· 0 citations
Statistics for the Magadan Region show that catastrophic floods occur in the region every year, and the damage from them is estimated at hundreds of millions of rubles. There is no system for short-term forecasting hazardous hydrological phenomena in the region. The study aims to analyze the main factors in the formation of catastrophic rain floods in the Ust-Omchug village, as well as to assess the possibility of using the Hydrograf distributed hydrological model to develop a system for short-term forecasting of river flow in the Magadan Region using the example of the Detrin River basin. The impact of climate change on runoff formation is examined based on the hydrometeorological observation data from the Roshydromet network. Since 1967, precipitation in the region has increased by 16 %, with the largest increase observed in August and September. The forecast of changes in precipitation for 2041–2060 compared to the period 1981–2010, based on climate models, has shown that an increase in annual precipitation of 10–15 % or more is expected, as well as an increase in annual river runoff of 30 % or more. To assess the applicability of the Hydrograf hydrological model as the basis for a short-term flood forecasting system for Ust-Omchug, we carried out parameterization and verification of the model on the basis of historical data. The results of modeling based on a daily simulated time interval for the period 1966–2024 were accepted as satisfactory. The WRF numerical weather prediction model with a spatial resolution of 3 km and a lead time of 3–6 hours to 1 day was used to reproduce the catastrophic floods of 2013 and 2019. The WRF model significantly overestimates the amount of solid precipitation, while in the warm period it underestimates the amount of liquid precipitation despite the satisfactory reproduction of its timing. Uneven precipitation in mountainous conditions and a sparse network of meteorological stations reduce the timing and accuracy of forecasting hazardous hydrological phenomena. In order to improve the reliability of the forecasting system and to take into account the diversity of weather conditions, it is necessary to apply an ensemble approach based on the use of input data from a variety of hydrometeorological models. The scientific novelty of the study lies in complex application of hydrological modeling and a numerical weather prediction model for flood assessment in poorly studied river basins of the mountain cryolithozone.
E. K. Kudyakov, N. V. Nesterova, A. Zemlianskova et al.· Географический вестник = Geo...· 0 citations
This study examines the temporal patterns of flooding in the midstream and downstream catchments of the River Kaduna Basin, with a view to improving flood risk assessment and management. A mixed-methods approach combined GIS-based multi-criteria analysis (MCA) with a household survey of 384 respondents within a 1 km river buffer. Physical factors (rainfall, slope, soil permeability, wetness, NDBI, NDVI, drainage) were weighted using the Analytic Hierarchy Process to generate flood occurrence frequencies and predictions via Monte Carlo simulation. Flooding was strongly clustered (Moran’s I = 0.67, p<0.001). Chikun, Tudun Wada North, and Nassarawa wards constitute a persistent high-risk belt covering 32% of the study area. Time-series decomposition of flood vulnerability over an 18-year period revealed an upward trend, from 0.424115 in 2016 to 0.428838 in 2034. Vulnerability distribution is: Very High 11%, High 20%, Moderate 24%, Low 16%, Very Low 29%. Areas experiencing annual flooding grew from 28% (2016) to 37% (2024), and average flood duration increased from 3.2 to 4.8 days. The most pronounced increase occurred in the Very High vulnerability category, which expanded by 54.9 km2 (10.9%) over the study period. The study recommends risk-sensitive land-use planning, ecosystem-based measures, institutional coordination, and community resilience building.
Auwal Fagge, R. O. Yusuf, Ganiyu Onoruoiza Salawu et al.· Kaduna Journal of Geography· 0 citations
This study evaluates the influence of topographic and hydrological factors on flood susceptibility
in the South–South region of Nigeria using Geographic Information Systems (GIS), Remote
Sensing, and the Analytical Hierarchy Process (AHP). Digital Elevation Model (DEM), slope,
aspect, drainage density, stream density, flow direction, and distance from river variables were
analysed to determine their contribution to flooding. The results show that elevation ranges from
approximately 13 m in low-lying coastal areas (Delta, Rivers, Bayelsa, and Akwa Ibom States) to
about 256 m in elevated inland areas (Cross River and parts of Edo State). Slope analysis indicates
that coastal areas are dominated by very gentle slopes (0°–3.37°), which promote water
accumulation and increase flood susceptibility. Aspect results further reveal that much of the
coastal region is predominantly flat (−1), limiting directional flow and enhancing water
stagnation. Hydrological analysis shows that drainage density is mainly very low to moderate (0
89.89 km/km²), indicating high infiltration but increased water retention, while localized high
values (89.9–134.8 km/km²) enhance runoff. Stream density is highest (228.1–811 km/km²) in
Delta, Bayelsa, and Rivers States, whereas lower values occur in Edo and Cross River. Flow
direction exhibits a dominant east–west pattern, with accumulation values ranging from 1–16,
indicating runoff convergence. Distance-to-river analysis shows that large areas lie within 0
1,000 m of river channels. Flood susceptibility is highest in coastal zones and lowest in inland
elevated areas. The study demonstrates that terrain morphology and hydrological network
characteristics are key determinants of flooding in the region and highlights the effectiveness of
geospatial techniques in flood susceptibility assessment and management in the South–South
region of Nigeria
Anthony Chikaike Nwinye-Harrison· IIARD International Journal...· 0 citations
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