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.

Flash floods induced by high-intensity and short-duration monsoon rainfall can cause severe damage in arid regions. To properly size in-stream infrastructures, such as levees, bridges, and culverts, it is crucial to accurately calculate the peak runoff and sediment load from these flash floods. This case study utilized the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model to simulate flash floods and sediment transport in the Lucky Hills watershed located in the Walnut Gulch Experimental Watershed in southern Arizona. The Lucky Hills watershed has two rain gauges and three flumes to measure runoff and sediment load. The HEC-HMS model was used to simulate the three largest precipitation events observed in 2007, 2009, and 2010 with precipitation volumes of 41.66, 46.36, and 37.85 mm, and durations of 126, 99, and 101 min, respectively. The study discussed various methods for simulating rainfall loss, surface and channel flow routing, and soil erosion. Watershed delineations were adopted to evaluate the accuracy of the simulated runoff and sediment concentration. Results showed that the HEC-HMS model can accurately predict surface runoff and sediment concentration, but the threshold value for subbasin size is critical for the model to converge to accurate results.

Due to underlying surface changes (USCs), the changes in the Taojiang River Basin's flood generation conditions could impact the flooding process in the basin. However, most studies have typically focused on either land-use changes (LUCs) or soil and water conservation measures (SWCMs) to assess the impact of the USCs on floods, which may not provide a more comprehensive understanding of the response of floods to the USCs. To investigate how the USCs have altered the floods in the Taojiang River Basin, located upstream of Poyang Lake, China, the HEC-HMS model, which incorporates the influence of the USCs into the parameter calibration, is established in this study to investigate the flood processes on an hourly scale. The flood peak and the maximum 72 h flood volume are selected as two indexes and are applied to analyze the changes in floods caused by the USCs. The 1981-2020 period is divided into three sub-periods (i.e., 1981-1992, 1993-2007, and 2008-2020) based on the conditions of the USCs. It is found that the two indexes have exhibited decreasing trends, mainly due to the USCs during 1981-2020. Benchmarked against the baseline period of 1981-1992, the two indexes decreased by 3.06% (the flood peak) and 4.00% (the maximum 72 h flood volume) during 1993-2007 and by 5.92% and 7.58% during 2008-2020. Moreover, the impacts of the LUCs and SWCMs are separated through parameter adjustments in the model, revealing that the SWCMs played a dominant role in the USCs in the Taojiang River Basin. The quantification and assessment of the impact of the USCs on floods of different magnitudes revealed that the influence decreases with increasing flood magnitude. The results of this study improve our understanding of how USCs affect the flooding process and therefore provide support for flood control management under changing environments.

The objective of the study was to configure the Hydrological Modeling System (HEC-HMS) in such a way that it could simulate all-important hydrological components (e.g., streamflow, soil moisture, snowmelt water, terrestrial water storage, baseflow, surface flow, and evapotranspiration) in the Three-River Headwater Region. However, the problem we faced was unsatisfactory simulations of these hydrological components, except streamflow. The main reason we found was the auto-calibration method of HEC-HMS because it generated irrational parameters, especially with the inclusion of Temperature Index Method and Soil Moisture Accounting (an advanced and complex loss method). Similar problems have been reported by different previous studies. To overcome these problems, we designed a comprehensive approach to estimate initial parameters and to calibrate the model manually in such a way that the model could simulate all the important hydrological components satisfactorily.

The impact of climate change on water resources through increased evaporation (due to global warming) combined with regional changes in precipitation characteristics (such as total amount, variability, frequency of extremes) has the potential to affect mean runoff, the frequency and intensity of floods and droughts, soil moisture and water supply for irrigation and hydroelectric power generation. Indian water resources, being heavily dependent on mountain glaciers, river water being shared by neighbouring countries and the annual monsoon being confined to four months only, are seriously susceptible to the climate change. The distribution and availability of water is not uniform across the country throughout the year. The Ganga-Brahmaputra-Meghna (GBM) system is the largest in India with a catchment area of about 110 Mha, which is more than 43% of the cumulative catchment area of all the major rivers in the country. The River Damodar is an important sub catchment of the GBM basin and its three tributaries, the Bokaro, the Konar and the Barakar, form an important tributary of the Bhagirathi-Hughli (a distributory of Ganga) in its lower reaches. The present study is an attempt to assess the impacts of climate change on the water resources of the Damodar basin, which has immense importance in industrial and agricultural scenarios through its river valley project in eastern India. This basin has already witnessed the most severe flood of the last century in 1978. A distributed hydrological model (HEC-HMS) has been used on the Damodar River basin for a controlled flow system, owing to the presence of four reservoirs and one barrage, using HadRM2 daily weather data for the period 2041-2060. The initial analysis has revealed that, under the climate change scenario, the conditions may deteriorate in terms of severity of droughts and intensity of flash floods. Furthermore, seasonal shifts of streamflow pattern, reduction of peak flow and conditions of water stress in meeting the various demands have been observed in the Damodar basin.