The investigation of river levees holds significant implications for mitigating flood damage. Sand boiling, backward erosion piping, and phenomena manifesting along the riverside of levees directly imperil the integrity of these structures. It is imperative to address these phenomena comprehensively to safeguard both lives and property amidst flood events. The principal aim of this research is to delineate the variances in geotechnical conditions between sand boils observed at slope toes on the landside and those occurring at a distance from this region along the levee. Therefore, this study conducted extensive boring investigations at sites where sand boils occurred. The soil samples sampled from the boring investigations were analysed for grain size. The results of a series of geotechnical investigations showed that in the cases where sand boils occurred near the toe of the slope, a series of sandy soils with grain size characteristics similar to those of the sand boils were deposited in the foundation of the levee. On the other hand, in the case where the sand boil occurred far from the toe of the slope, sandy soil with grain size characteristics similar to that of the sand boil was deposited only on the landside.

An increase in extreme rainfall frequency across the midwestern United States has been accompanied by an increase in damaging floods. The US has over 90,000 dams, more than 75% of which are small and rarely used for flood mitigation. Recent research focused on operating these ponds for flood reduction using gated outlets, a technique known as activated distributed storage, has confirmed its potential for reducing flood impacts. Here, the authors build upon this work by developing a hydrologic model to simulate the active management of a distributed network of 130 ponds that employs up to 18 h of forecasted rainfall for operational decision making, a process known as forecast-informed reservoir operation (FIRO). Using five observed rainfall events and a single dam operations scheme, the effects of using FIRO for real-time gate operations on both downstream peak flows and basin wide storage utilization are evaluated. Simulation results that use the high-resolution rapid refresh (HRRR) product, were compared to those that (1) use no rainfall forecasts for decision making; and (2) use 18 h of observed rainfall mimicking an ideal forecast. Regardless of forecast accuracy or rainfall accumulation, shorter forecast lead times result in operational decisions that release water early in an event, vacating storage, while longer lead times result in increased storage throughout an event, thus reducing downstream flows. These results indicate that rainfall forecasts may not be solely capable of addressing the complexities governing a distributed storage network's ability to release water. This suggests that a more nuanced approach, utilizing optimal control of the storage network is required to unlock the technique's full potential.

In recent years, frequent flood disasters have posed significant threats to human life and property. From 28 July to 1 August 2023, a basin-wide extreme flood occurred in the Haihe River Basin (23.7 flood). The Gravity Recovery and Climate Experiment satellite can effectively detect the spatiotemporal characteristics of terrestrial water storage anomalies (TWSA) and has been widely used in flood disaster monitoring. However, flood events usually occur on a submonthly scale. This study first utilizes near-real-time precipitation data to illustrate the evolution of the 23.7 extreme flood. We then reconstruct daily TWSA to improve the issues of coarse temporal resolution and data latency and further calculate wetness index (WI) to explore its flood warning. In addition, we analyze soil moisture storage anomalies to provide a comprehensive understanding of flood mechanisms. The study also compares the 2023 floods to a severe flood event in 2021. Results indicate that reconstructed daily TWSA increases by 143.43 mm in 6 days during the 23.7 flood, highlighting the high sensitivity of our approach to extreme events. Moreover, compared to daily runoff data, the WI consistently exceeds warning thresholds 2-3 days in advance, demonstrating the flood warning capability. The flood event 2021 is characterized by long duration and large precipitation extremes, whereas the 2023 flood affects a wider area. This study provides a reference for using daily TWSA to monitor short-term flood events and evaluate the flood warning potential of WI, aiming to enhance near-real-time flood monitoring and support flood prevention and damage mitigation efforts.

The 2021 Cyclone Seroja was a category 3 storm that made landfall on Lembata Island, causing extensive damage. This study aims to identify key interpretations of sediment transport related to tropical cyclones (TC) Seroja and past floods using a geopedological approach, estimate the return period through frequency analysis, and determine the rainfall threshold for flooding using HEC-RAS software. Extreme rainfall data from global precipitation model (GPM) (2000-2023) in Wei Laing watershed were analysed alongside LiDAR terrain data, physical and chemical properties of soil, and land cover data. Based on geopedological analysis, the result shows that the erosional-transfer zone of Wei Laing Watershed has thin, loamy, and slightly sandy soils due to erosion and limited pedogenesis. The depositional zone contains flood deposits with abrupt vertical texture changes, reflecting transported coarse grains and finer in-situ sediments. The modern flood deposit (TC Seroja flood deposit) was identified by texture, CaCO3 content, organic matter, and coarse organic material. The fine-grained flood deposits (<_ 4 cm) are classified as slackwater deposits, consist of silty clay loam and silt loam textures, reflecting deposition under slow-flowing conditions. TC Seroja corresponds to a 50-year return period. Hydrological modelling indicates a 60 mm/day rainfall threshold for flooding, with 77 flood events recorded between 2000-2023. The model is confirmed by thick past flood deposits enriched with coarse organic materials. These findings provide insight into flood dynamics and sedimentary responses, supporting future flood risk mitigation efforts.

Located in a humid tropical monsoon region, Gin River Basin is frequently exposed to adverse flood impacts. Flood exposure assessments extending beyond traditional hazard assessments are crucial to understand these impacts. We examined flood hazard and exposure dynamics during three flood events in the basin, simulating flood hazard using the rainfall-runoff inundation model. Model parameters, including Manning's roughness coefficients and soil depth were tuned through a trial-and-error approach using daily rainfall data. Two datasets with different spatial resolutions (similar to 300 m and 30 m) were used to identify exposed areas. Despite differences in hazard characteristics, the impact on human settlements remained similar, with household damages of 43.72% in 2017, 52.74% in 2016, and 76.65% in 2003. Coarser (similar to 300 m) land-use maps failed to capture smaller settlements in heavily damaged mid- and upstream areas, whereas high-resolution settlement maps identified them, predominantly located in agricultural and shrubland areas. These areas accounted for 69.3% of exposure midstream, 19.8% downstream, and 10.9% upstream, correlating with the heavy damage reported midstream. This highlights the importance of high-resolution settlement data for accurate flood exposure assessments, even in data-scarce basins. Socio-economic factors, disaster preparedness, and government support should be integrated into detailed flood risk assessments to develop effective mitigation measures.

The Himalayan foothills are highly prone to rainfall induced flash floods. This research focuses on the August 19-20, 2022 flash flood event in Song watershed of Doon valley, Uttarakhand caused significant damages to buildings and a road bridge. The study aims to assess the flood intensity through flood simulation in a semi-distributed hydrological model by utilizing rainfall data, land use and soil data. Further, the flood hydrographs generated through hydrological modelling were used to simulate hydrodynamic model to estimate flood depth. Pre and post-flood inundation assessments were conducted using PlanetScope and Sentinel-1 imagery. Furthermore, development activities on river courses were analyzed utilizing Google earth and Bing maps high resolution imagery. Cumulative rainfall observations revealed 344 mm rainfall in Rishikesh and 225 mm in Sahastradhara on 19-20 August for the 24 hrs, contributed in a peak flood discharge 2679 m(3)/s at the Rishikesh outlet. The simulated flood depth depicted 4.81 m flood depth at the damaged Thano-Bhogpur bridge. The PlanetScope satellite imagery showed 182 m expansion in the cross-sectional width of river at Maldevta after the flood. A 5.36 sq. km. flood area observed throughout the entire Song catchment in two days post event Sentinel-1 imagery. Analysis of high-resolution imageries revealed increasing development activities in floodplains of the catchment, which got affected by flood. The findings indicate urgent need of floodplain management by implementing comprehensive flood risk management plans including early warning systems, land-use regulations based on flood hazard zonation and flood resilient infrastructure to mitigate future flood exposure to society.

The city of Arequipa, the second most important city in Per & uacute;, faces numerous daunting challenges, including high-intensity but short-induration rainfalls that leads to floods and the swelling of the Chili River (mud and landslides). This situation aggravates the vulnerability of the population settled on the margins of the gorges and gullies, due to little or no territorial planning from public institutions. The local news evidence negligence every year, both in terms of human lives and infrastructure loss. The frequency of these events has increased with time and that is the reason for prompting the establishment of rainfall thresholds and the compilation of a 41-year record (1981-2021), with the aim of informing about the dangerousness of an adverse meteorological phenomenon, either predicted or in progress. For the hydrological model, the authors used the highest 24-hour precipitation data from the SENAMHI's stations (National Service of Meteorology and Hydrology of Peru) to generate the liquid hydrograph for different return periods with the Hydrologic model of HEC-HMS. Soil mechanics studies were also carried out to determine the rheological parameters of the non-Newtonian flow and then calibrate through historical events in a hydraulic model of HEC-RAS. Finally, cartographic maps in QGIS were prepared to evaluate the hazard zones flooding in the Del Pato, San L & aacute;zaro, Venezuela and Los Incas gullies.

Floods accompanied by thunderstorms in developed cities are hazardous, causing damage to infrastructure. To secure infrastructure, it is important to employ an integrated approach, combining remote sensing, GIS and precipitation data. The model was developed based on the estimation of event-based runoff and investigated the relationship between runoff and impervious surfaces. The novel approach of combining Hydrologic Engineering Center's River Analysis System (HEC-GeoRAS) along with satellite imagery was utilized, where spatial data was combined with real-time values to run the model. As a first step, the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model was fed with information about precipitation, slope, soil type, as well as land use and land cover. The results reveal that the subbasins of Deira, Nief and Jumeirah have the largest impervious area and, thus, a higher probability of flood occurrence. The model was calibrated and validated using previous runoff events and by comparing observed and simulated streak flow and peak discharge against those reported in previous studies. It was found that the model is efficient and can be used in similar regions.

Floods in India are recurring natural disasters resulting from extreme precipitation during the summer monsoon season (June-September). The recent flood in North India in July 2023 caused substantial damage to lives, agriculture, and infrastructure. However, what led to the 2023 North India flood and the role of atmospheric and land drivers still need to be examined. Using in situ observations, satellite data, and ERA5 reanalysis combined with hydrological and hydrodynamical modeling, we examine the role of land and atmospheric drivers in flood occurrence and its impacts. Extreme precipitation in a large region during 7-10 July 2023 created favorable conditions for the flood in the hilly terrains and plains of north India. More than 300 mm of precipitation fell in just 4 days, which was eight times higher than the long-term average (2001-2022). Anomalously high moisture transport over northern India was recorded on 7 July 2023, making atmospheric conditions favorable for intense landfall. Increased column water vapor and specific humidity at different pressure levels confirmed the continuous moisture presence before the extreme rainfall that caused floods in northern India from 7 to 12 July 2023. Atmospheric and land (high antecedent soil moisture) conditions contributed to a more than 200% rise in streamflow at several gauge stations. Satellite-based flood extent shows a considerable flood inundation that caused damage in the Sutlej and Yamuna River basins. Our findings highlight the crucial role of the favorable land and atmospheric conditions that caused floods and flash floods in north India in July 2023. In July 2023, North India experienced a severe flood that caused significant damage to lives, agriculture, and infrastructure. However, the exact causes of this flood have yet to be examined. Using in situ, satellite, and reanalysis data, we examined the drivers of the flood. Favorable atmospheric and land conditions created a unique situation that led to a significant flood in north India. For instance, extreme precipitation during 7-10 July enhanced antecedent soil moisture conditions in the hilly and plain regions. Anomalously high moisture transport caused intense rainfall, which, combined with high soil moisture, produced high runoff and streamflow conditions. Flood inundation caused damage to the Sutlaj and Yamuna river basins. Our findings show the need to monitor soil moisture and atmospheric processes for early warning of floods in hilly regions. The flood in North India in July 2023 caused substantial damage to lives, agriculture, and infrastructure Anomalously high moisture transport over northern India created atmospheric conditions favorable for intense landfall High antecedent soil moisture and extreme precipitation caused the north India flood in 2023

The storm Daniel and subsequent floods hit the Region of Thessaly (Greece) in early September 2023, causing extensive damage to the built environment (buildings, networks, and infrastructure), the natural environment (water bodies and soil), and the population (fatalities, injured, homeless, and displaced people). Additionally, the conditions and factors favorable for indirect public health impact (infectious diseases) emerged in the flood-affected communities. The factors had to do with infectious diseases from rodents and vectors, injuries, respiratory infections, water contamination, flood waste and their disposal sites as well as structural damage to buildings and the failures of infrastructure. The conditions that evolved necessitated the mobilization of the Civil Protection and Public Health agencies not only to cope with the storm and subsequent floods but also to avoid and manage indirect public health impact. The instructions provided to affected residents, health experts, and Civil Protection staff were consistent with the best practices and lessons learned from previous disasters. The emphasis should be on training actions for competent agencies, as well as education and increasing the awareness of the general population. Non-structural and structural measures should be implemented for increasing the climate resilience of infrastructures including the health care systems within a One Health approach.