Engineering Center-Hydrologic Modeling System Research Articles

Flood Modeling using Hydrologic Engineering Center's - Hydrologic Modeling System (HEC-HMS) and River Analysis System (HEC-RAS) for a Micro Watershed in Castilla, Sorsogon

Flood Modeling using Hydrologic Engineering Center's - Hydrologic Modeling System (HEC-HMS) and River Analysis System (HEC-RAS) for a Micro Watershed in Castilla, Sorsogon

Three-phase data augmentation for the prediction of sediment flux in mountain basins during typhoon events

Abstract Discrepancies between estimated sediment and actual yields are large. The sedimentation often causes severe damage due to a lack of on-site measurement data in the current disaster prevention system. This paper presents a robust early-warning system in which the statistical analysis used to predict sedimentation is conducted within the context of the underlying physical mechanisms. This three-phase early-warning system employs data collection, data generation, and AI (Artificial Intelligence) prediction. Data collection involves the use of HEC-HMS (Hydrologic Engineering Center – Hydrologic Modeling System) to transform measured precipitation data into flow discharge from various sub-catchments. Empirical formulas related to landslide volume and soil erosion are then used to establish suitable boundary conditions for data generation. Finally, a 2D model, SRH-2D (Sediment and River Hydraulic-Two Dimension model), is used to simulate data pertaining to temporal variations in sediment flux under various storm event scenarios. The simulated data are then used as input for the training and testing three artificial neural networks. The primary strength of this study is to improve the prediction ability in large-scale sedimentation issues in mountain rivers. These models returned good prediction results with 1–6 h lead times by interdisciplinary integration with the hydraulic and statistical fields.

Ensemble physically based semi-distributed models for the rainfall-runoff process modeling in the data-scarce Katar catchment, Ethiopia

Abstract This study evaluates the performance of the soil and water assessment tool (SWAT), the hydrologiska byråns vattenbalansavdelning (HBV) and the hydrologic engineering center-hydrologic modeling system (HEC-HMS) for modeling rainfall-runoff in the data-scarce Katar catchment, Ethiopia. First, the rainfall-runoff process was simulated using the SWAT, HBV and HEC-HMS models individually. Second, simple average ensemble (SAE), weighted average ensemble (WAE) and neural network ensemble (NNE) techniques were developed by combining the results of individual models to improve overall accuracy. Statistical performance measures and flow duration curves (FDCs) were used to compare and evaluate the performance of the models. The results showed that the SWAT model outperformed the HBV and HEC-HMS models with the coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) of 0.857 and 0.83 for calibration and 0.85 and 0.799 for validation, respectively. The ensemble result showed that NNE outperformed the SAE and WAE techniques, with NSE and R2 values of 0.924 and 0.925 for calibration and 0.896 and 0.904 for validation, respectively. The NNE technique improved the performance of SWAT, HBV and HEC-HMS by 12.14, 22.7 and 26.8%, respectively, in the validation phase. Overall, the results showed that ensemble modeling is a promising option for accurate modeling of the rainfall-runoff process.

Prediction of Continuous Rainfall-Runoff Scenarios for Snow-Fed Watershed of Himachal Pradesh, India using Geographical Information System GIS based on Hydrological Modelling

Rainfall runoff modeling is one of the most complex hydrological modeling due to the involvement of different watershed physical parameters. It is essential for the analysis of watershed hydrological response towards the received precipitation under the influence of watershed variables. As it is a replica of watershed hydrological response, Rainfall-Runoff modeling is essential to evaluate the general characteristics of total surface runoff at catchment’s outlet. The main objective of this study was prediction of rainfall runoff using Hydrologic Engineering Center-Hydrologic Modeling System [HEC-HMS] model for Rampur watershed which was covered in Kullu and Shimla districts situated at Upper Sutlej sub-basin of Himachal Pradesh, India. Geo-spatial data of Digital Elevation Model,LandUse-LandCover (LU-LC) map, Soil map and Hydro-meteorological data of rainfall were collected from different open source web portals to utilise as input parameters for modeling. Soil Conservation Service-Curve Number (SCS-CN) for precipitation loss modeling, Soil Conservation Service–Dimensionless Unit Hydrograph [SCS-UH] for transform modeling, Muskingum method for Runoff routing were used as input parameters of respective components of HEC-HMS model. This article proposes a methodology for generating hourly rainfall data from daily rainfall data using Intensity-Duration-Frequencycurves in Meteorological model of HMS. The simulation results of runoff with 5 different return period scenarios are follows the return period frequency tendency, such as 1000 year return period runoff peak delivers 4729.5 m3/s, 500 year return period delivers a peak runoff of 4263.9 m3/s, 100 year return period gives a peak runoff of 3196.5 m3/s, 50 year return period runoff deliver 2745.3 m3/s and 10 year return period deliver 953.7 m3/s runoff at the outlet of Rampur watershed.

GIS preprocessing for rainfall-runoff modeling using HEC-HMS in Nekkor watershed (Al-Hoceima, Northern Morocco)

All Discharge data are among the most critical factors that must be considered when evaluating the management of water resources in a watershed. Simulation of rainfall-runoff is therefore an important element in assessing the impacts of serious flooding. In the present study, rainfall-runoff in the Nekkor watershed in Al Hoceima province was simulated using GIS, remote sensing and the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model. The applicability, capacity and suitability of this model for rainfall runoff in the watershed were examined. The watershed parameters were generated using (HEC-GeoHMS) and ArcGIS. The model was calibrated using a daily data set that occurred in the watershed between 2003 and 2007, the validation period was from 2009 to 2012. Model performance was evaluated using a variety of different statistical indices to study the response and impact of rainfall-runoff. Model parameters were changed and calibration was performed using the Soil Conservation Service Curve Number loss method. Consistent and satisfactory performance in terms of peak discharge, total flood volume, timing of peak discharge and overall hydrograph adjustment effect was found. The determination coefficient (R2) for the validation period reached 0.73 versus 0.71 for the calibration period. The root mean square error (RMSE) is within the acceptable range. The relative bias (RE) demonstrates an overestimation in the calibration period and an underestimation in the validation period in the peak flows. These results will help decision makers to better manage water resources in this watershed and mitigate flood risks.

Development of a Water Quality Management Model for Dry Rivers in Arid Regions: Application on Wadi Rumah, Saudi Arabia

In dry rivers, urban wastewater discharge forms a pond in the dry period, and surface runoff shapes a longer pond in the wet period. A water quality management model developed for dry rivers is applied on Wadi Rumah in Saudi Arabia. The sub-basin was delineated from 30-m × 30-m spatial resolution digital elevation model. Hydrologic loss, runoff rates, and time of concentration were determined using the soil conservation service curve number, soil conservation service unit hydrograph methods, and Kirpich formula. Hydrologic Engineering Center Hydrologic Modeling System estimated the wet weather flows for 10 low-to-medium rainfall events. A steady-state hydrodynamic model including river flows, effluent discharge, and evaporation and infiltration losses estimated the hydraulic retention time for the explicit case of ponding conditions of dry rivers. Mass balance and first-order kinetics modeled the physical (total dissolved solid and total suspended solid), chemical (biochemical oxygen demand, dissolved oxygen, chemical oxygen demand, NH3, PO4, and Cl2), and microbiological (total coliform and fecal coliform) parameters. The hydrodynamic model and biokinetic rate coefficients were calibrated with satellite images, reported literature, and field measurements. A water quality index compared the aggregated water quality against the standards for 4 intended uses. The study yields “very good” water quality for restricted and unrestricted irrigation for the dry period, “fair” for livestock drinking, and “marginal” for fishery and recreation for the dry period, while water quality remained “marginal” for all the uses in the wet period. Water quality management implies regular water quality monitoring, continuous improvement of treatment facilities, and flood plain management initiatives for the long-term sustainability of dry rivers in arid regions.

Effects of Increasing Rainfall Depths and Impervious Areas on the Hydrologic Responses

Hydrologic modeling is a popular tool for estimating the hydrological response of a watershed. However, modeling processes are becoming more complex due to land-use changes such as urbanization, industrialization, and the expansion of agricultural activities. The primary goal of the research was to use the HEC-HMS model to evaluate the impact of impervious soil layers and the increase in rainfall-runoff processes on hydrologic processes. For these purposes, the Watershed Modelling System (WMS) and Hydrologic Engineering Center’s-Hydrologic Modeling System (HEC-HMS) models were used in this study to simulate the rainfall-runoff process. To compute runoff rate, runoff volume, base flow, and flow routing methods SCS curve number, SCS unit hydrograph, recession, and loss routing methods were selected for the research, respectively. To reduce the processing time and computational complexity, a small section of the Pipestem Creek Watershed was selected to understand the methods and concepts associated with the hydrologic simulation model building. A DEM along with other required data such as land use land cover data, soil type data, and meteorological data was utilized to delineate the watershed in WMS. The output of WMS was utilized to run the HEC-HMS model for five different scenario analyses. All the relevant data were plugged in to the model to get the desired map. Subsequently, outlets at appropriate locations were selected for the sub-basin delineation for further analysis. Finally, the model was parametrized to get successful simulation results. Overall, peak discharges and runoff volumes were increased with increasing storm depths and impervious areas. Peak discharges were increased to 36% and 51% when rainfall depths were increased by 10% and 20% from the initial rainfall depth, respectively. Runoff volumes were also increased to 35% and 49% for the same scenarios, respectively. Peak discharges were increased to 12% and 78% with a 10% and 20%, respectively, increase in impervious areas. The runoff volumes were increased by 12% and 76% when impervious areas were increased by 10% and 20%, respectively. The simulation models responded well, and the peak discharges and runoff volumes increased with increasing storm depths and impervious areas.

RAINFALL-RUNOFF SIMULATION OF A SUB-CATCHMENT USING HEC-HMS

Hydrological data in the form of stream flow is very scarce in most developing countries. This affects the planning and management of urban watersheds. Therefore, it is necessary to estimate peak discharge from rainfall using hydrologic models based on some measurable watershed characteristics. This study aims to model the rainfall-runoff process from a typical urban watershed using Hydrologic Engineering Center Hydrological Modeling System (HEC-HMS) software. The catchment basin has a total area of 21.91 km2, and a dendritic stream system. Soil Conservative Services (SCS) Curve number was used for getting excess rainfall from total rainfall, SCS dimensionless unit hydrograph for converting the excess rainfall to direct runoff and Muskingum for the channel routing. The rainfall-runoff simulation was conducted using six (6) rainfall events. Model calibration and validation were done using optimized parameters and the result shows a reasonable fit between the observed and simulated hydrograph. The model result has an RMS error of 1.5 m3/s, and a Nash-Sutcliff of 0.585. It is concluded that the model can be used to predict runoff from rainfall with reasonable accuracy. The result can be used for watershed planning and management.Keywords: HEC HMS, rainfall, runoff

Application of Hydrologic Engineering Centers Hydrologic Modeling System (HEC-HMS) Model for Modelling Flood in Sub Basin of Meenachil River, Kerala, India

Meenachil river basin, located in southern part of Kerala, is frequently liable to flood. It is an area predominant with agricultural land and falls under tropical humid zone. Hence, water resources planning and management and understanding of rainfall-runoff relationship along with its land characteristics, is necessary for irrigation scheduling, flood control and design of various engineering structures. HEC-HMS(Hydrologic Engineering Centers Hydrologic Modeling System) which is a widely used rainfall-runoff model was chosen for the simulation of watershed responses and generation of flood hydrographs. This research was done to establish the peak discharge rate of the river as well as calibrate and validate the HEC-HMS model for the Meenachil subbasin and obtain long-term flow data. The performance parameters NSE (Nash–Sutcliffe model efficiency) coefficient and R² (coefficient of determination) values were obtained above 0.7. The Error in Peak Flow and Volume were calculated below 20%. All these values indicated satisfactory performance of the model simulation both in the calibration (2013-2016) and validation (2017-2018) period. Curve number (61.46-79.93 mm), Initial abstraction(10.29-31.87 mm) and Lag time(208.27 min and 4456.2 min) were found to be the most sensitive parameters of the model. Simulated and observed stream flow values (viz. lowest peak flow of river was found during the year 2013 and it was predicted as 168.9 m³/s and observed as 158.5 m³/s) indicated that the model was able to predict and present credible results for the sub basin.

Urbanization and Its Potential Impact on the Peak Discharge from the Watershed of the Upper Merced River in California

Urbanization is an unavoidable process that influences many components of a watershed, and thus hydrologic processes are severely affected by changes in land use due to this urbanization. During this study, the objective was to assess the impact of urbanization on the peak discharge of a watershed in accordance with the outcome of this research. For this purpose, Watershed Modeling System (WMS) software and Hydrologic Engineering Center- Hydrologic Modeling System (HEC-HMS) model were used for simulating various land-use scenarios of Merced County, in the central part of California, USA. Simulation results were analyzed to assess the impact of land-use changes on the peak discharge of the watershed. The results showed that approximately 18% peak discharge was increased at the sub-basin level and approximately 2% peak discharge was increased at the final outlet. In the future, the study could help researchers, policymakers, and structural designers to foresee and prevent the unpleasant effects of urbanization so that they can take specific measures to prevent calamities beforehand. Keywords: Watershed-modeling, urbanization, land use, peak discharge, WMS, HEC-HMS. DOI: 10.7176/CER/14-7-02 Publication date: November 30 th 2022

Evaluating the performance of HBV, HEC-HMS and ANN models in simulating streamflow for a data scarce high-humid tropical catchment in Tanzania

ABSTRACT This study evaluates the performance of the Hydrologic Engineering Center-Hydrologic Modelling System (HEC-HMS), the Hydrologiska Byråns Vattenbalansavdelning (HBV) model, and an artificial neural network (ANN) model in a data-scarce high-humidity tropical catchment. Statistical indices, simulated and observed hydrographs, and flow duration curves were employed for evaluating and comparing their performances. The results indicate that the HEC-HMS model is superior, with Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R2) values of 0.80 and 0.82 for calibration and 0.84 and 0.79 for validation, respectively. The HBV model is also suitable for simulating catchment hydrology, with NSE and R2 values of 0.73 and 0.74 for calibration and 0.64 and 0.64 for validation, respectively. The ANN model performed satisfactorily, with NSE and R2 values of 0.66 and 0.67 for calibration, and 0.55 and 0.52 for validation, respectively. These findings provide insight into the effectiveness of hydrological models, which is important for effective water resources management in light of climate change impacts in the region.

Potential of Satellite Rainfall Estimates as Inputs for Flood Forecasting: Case Study Gash River, Sudan

This study is an attempt to test the potential of using real time Satellite Rainfall Estimates (SRE) data for hydrological modeling. Tropical Rainfall Measurement Mission (TRMM-3B42RT V7) SRE was evaluated against observed rain gauge data in Gash river catchment. The TRMM was evaluated against intensity as well as elevation dependency. The Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) software of the Army Corps of Engineering of the USA was used to simulate the rainfall - runoff process. The performance of TRMM was found to underestimate the rainfall for most of the events, the underestimation increases with the increase in elevation. TRMM data set was biased corrected and used as input to derive the hydrological model. Observed hydrographs at the catchment outlet were compared to the simulated flow hydrographs using events and continuous modeling. The results of hydrological modeling showed that events based modeling performed better, the coefficient of determination (R2) vary between 0.87 to 0.96 while Nash-Sutcliffe Efficiency (NSE), vary from 0.84 to 0.96 and Root Mean Square Error (RMSE) vary from 45 to 118.3 m3/s. While the same statistics for continuous modeling showed, (NSE = 0.65) and (RMSE 44.5 m3/s). These results reflect the high potential of TRMM data set as inputs for hydrological modeling and flood forecasting in the Gash river and other basins with similar characteristics.

Web-based prototype system for flood simulation and forecasting based on the HEC-HMS model

This study addresses Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model simulation issues in web environments and identifies key model parameters to facilitate practical flood forecasting. Jython scripts serving as an intermedium layer between the web-based forecast system and HEC-HMS model were created to enable HEC-DSS database writing and reading and HEC-HMS model execution as a background process. Empirical relationships between model parameters and time series characteristics were established to mitigate the difficulty in determining event-dependent model parameters. An open-source web-based prototype system for flood simulation and forecasting (WSFF) based on the HEC-HMS was built by incorporating these methods and parameter knowledge into the model and knowledge subsystem. The WSFF performance was evaluated via a case study involving 12 historical flood events in the Chuanchang watershed, southeastern China. Among these 12 events, nine events served as calibration events to establish WSFF parameter knowledge, and three events were used to verify the WSFF performance. A consistent and satisfactory performance in terms of peak flow, total flood volume, peak flow timing and overall hydrograph fitting effect was found. The average Nash–Sutcliffe efficiency (NSE) for the validation events reached 0.81 versus 0.82 for the calibration events. The relative error in peak flow (REP) and relative error in flood volume (REV) indicated a reasonable flood forecasting accuracy, with an REP within 15% and RET within 1 h. Developed as open-source software, the WSFF could serve as a useful basis for the hydrological community regarding HEC-HMS adoption in flood forecasting.

Rainfall-runoff modeling using HEC-HMS model for Meki river watershed, rift valley basin, Ethiopia

Detail understanding of rainfall-runoff processes is tremendously important for a watershed with variable streamflow generation. The streamflow of the Meki River fluctuates seasonally causing flooding on surrounding agricultural land. This study adopted Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) to model the streamflow and predict flood in the Meki watershed, Rift valley basin. The model was calibrated with observed streamflow data from (1987–2004) whereas the consecutive year's data (2005–2010) was used for model validation. The evaluation criteria namely: Nash Sutcliff Efficiency and coefficient of determination were preferred to evaluate the model performance. The finding relieved that, the model can perform very well (NSE = 0.83, R2 = 0.91) during Calibration, and (NSE = 0.804, R2 = 0.89) at validation period. Moreover, the predicted floods at 2, 10, 25, 50, and 100 years were 133.2, 178.1, 239.7, 313.2, and 346.19 m3/s, respectively in the watershed. The novelty of this study lies in evaluating the model results using both statistical parameters (NSE and R2) and the Generalized Extreme Value method). The finding of this study is vital to developing flood mapping and designing flood mitigation measures in the study area. Further, the developed models can be applied to other hydrology with similar hydrological conditions.

Integrated Surface Water and Groundwater Modeling in Arid Environment, Al-Lusub Watershed, Saudi Arabia

Coupling surface and groundwater for a better understanding of the hydrologic response in arid basins is essential for managing water resources. The study aims to integrate surface water (SW) and groundwater (GW) modeling in an arid environment and to identify groundwater sources at Hadat Ash-Sham farm station in the Al-Lusub watershed, located in the western part of Saudi Arabia. The curve number (CN) method for SW modeling is primarily used to estimate GW potential recharge based on a developed correlation equation between event-based rainfall and potential recharge, which is processed in the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) software. Monthly potential recharge is utilized to compute GW modeling in MODFLOW. Van Mullem’s equation is used to calculate hydraulic conductivity (K) from CN. The calibration of steady-state GW modeling reveals that the K (from Van Mullem’s equation) is within the range of measured K in the field. The transient groundwater modeling phase concludes that the groundwater system in the Al-Lusub watershed can be interpreted based on two different scenarios. The first is that an extra recharge from a nearby watershed flows through the geological structure into a downstream area. The second scenario involves potential recharge from surface water flowing on the Al-Lusub watershed’s mainstream bed. Validation reveals a strong relationship between predicted and observed water tables. The root mean square error (RMSE) for Scenarios 1 and 2 are 0.6 m and 0.7 m, respectively. Further investigation is needed to determine the region’s most common scenario.

Quantitative assessment of the impact of precipitation and vegetation variation on flooding under discrete and continuous rainstorm conditions

Precipitation and vegetation are two critical factors affecting floods in watersheds. A quantitative evaluation of their contribution to flooding is of great scientific significance for vegetation construction and water resource management. Thus, this study took the Pengchongjian small watershed, located in Southeastern China, as the research object. Based on geographic and hydrometeorological data from 1983 to 2017, the characteristics of rainstorm and flood in the watershed were analyzed. Meanwhile, the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) model was used to quantitatively calculate precipitation and vegetation variation contribution rates to the total flood volume and peak flow under discrete and continuous rainstorm conditions. The results indicated that the rainstorm volume and total flood volume showed a non-significant upward trend in the two periods of 1983–2003 and 2004–2017, and the variation coefficient of total flood volume was higher than that of rainstorm volume. At the same time, the periodic variation characteristics of rainstorm volume and total flood volume in 1983–2017 were basically consistent. The HEC-HMS model offered good simulation of discrete and continuous rainstorm floods, and the simulation accuracy met our requirements. Under the condition of discrete rainstorm, the average contribution rates of precipitation and vegetation variation to the total flood volume were 58.9 % and 41.1 %, and to the peak flow were 54.2 % and 45.8 %, respectively. In the case of continuous rainstorm, when the contribution rate of vegetation variation was positive, the average contribution rates of precipitation and vegetation variation to the total flood volume were 72.2 % and 27.8 %, and to the peak flow were 84.9 % and 15.1 %, respectively. When the contribution rate of vegetation variation was negative, the average contribution rates of precipitation and vegetation variation to the total flood volume were 125.0 % and −25.0 %, and to the peak flow were 132.1 % and −32.1 %, respectively. These results could provide a basis for the comprehensive management of soil and water loss, water resource planning, vegetation construction, and hydrological benefit evaluation.

Simulation of flood peak discharges and volumes for flood risk management in the ungauged urban informal settlement of Kibera, Kenya

In spite of the increasing extremity and adverse consequences of urban floods under climate change, flood characteristics in most developing countries are still largely unknown due to lack of continuous monitoring. This portentous uncertainty stances high flood risk, especially to a majority low-income urban population inhabiting the flood-prone informal settlements. Physically-based hydrologic models, whose parameters are derivable from catchment features, are often used for hydrological analysis in the ungauged regions. In this study, the Hydrologic Engineering Centre's-Hydrologic Modelling System (HEC-HMS) was used for rainfall-runoff simulation in the upper Ngong River Basin of Kenya, draining into the Kibera informal settlement, for purposes of estimating flood peak discharges (FPDs) and direct runoff volumes (DRVs), often required for flood risk management. The Soil Conservation Service-Curve Number (SCS-CN), SCS-Unit Hydrograph (SCS-UH) and Muskingum models were used for hydrological simulation from four (4) observed and fifty-four (54) hypothetical extreme rainfalls. The results obtained indicated that a 50 mm rainfall event with a duration of 2.5 h has the potential of producing FPD and DRV of about 90m3s−1 and 1.17×106m3 respectively at the Ngong River confluence at Sokomoko in Kibera. On the other hand, the non-intermittent 100-year storm event of about 172 mm in depth, occurring over a period of about 4 h, potentially generated FPD of about 460m3s−1 and DRV of about 4.89×106m3, portending calamitous impacts in the basin. These results can offer preliminary information on potential flood characteristics, that can be used as a baseline to support local-level flood risk mitigation measures in the ungauged Ngong River Basin.

Assessing the potential impacts of climate change on streamflow in the data-scarce Upper Ruvu River watershed, Tanzania

Abstract This study assessed the impacts of climate change on streamflow in the data-scarce Upper Ruvu River watershed (URRW). The Long Ashton Research Station Weather Generator (LARS-WG) was employed for generating the future ensemble-mean climate scenario based on six global circulation models (GCMs), under two representative concentration pathways (RCPs: RCP4.5 and RCP8.5). The future projections were made in two periods (2041–2060 and 2081–2100), and the baseline period (1951–1978) was used as a reference. The watershed hydrology was represented by the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) model, which was calibrated and validated by using 5 and 4 years of streamflow data, respectively. Results indicate that the rainfall and minimum and maximum temperatures will increase in both periods, under both scenarios. This will potentially affect the streamflow that is projected to increase from March to August and decrease from September to February. The mean annual streamflow could potentially change from 48 m3/s in the baseline period to 45.6 and 56.5 m3/s during 2041–2060, and 52.4 and 67.4 m3/s during 2081–2100, under RCP4.5 and RCP8.5, respectively. The minimum and maximum streamflows are also predicted to change in both periods, under both scenarios. Considering these results, the climate change will have significant impacts on the streamflows of the URRW.

Flash Flood Assessment and Management for Sustainable Development Using Geospatial Technology and WMS Models in Abha City, Aseer Region, Saudi Arabia

Abha city is distinguished by urbanization, infrastructure, deepening watercourses, and changes in runoff flow which encourage flash floods in the urban zones of many villages in the region. AlMahalah village is prone to flash flooding due to its geographic location near the outlet of convergence streams of significant flow. The Geographic Information System (GIS), Remote Sensing (RS), Water Modeling System (WMS), and Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) were used to assess the effects of flash floods on AlMahala village. Precipitation data from 1978 to 2020 was statistically processed and analysed to provide more information about flash flood hazards. With a 3-h lag time in both watersheds, the higher peak discharge in Wadi Abha than in Wadi Al Akkas indicates that flooding was a primary concern in Wadi Abha. With an average yearly rainfall of 520 mm, the hydrograph simulation from 1 to 5 April 2020 would contribute to the junction (outlet) point of AlMahala village with a peak discharge rate of 474.14 m3/s. The vegetation cover increased by 243 km2 in 2020 compared to 2016. The HEC-RAS model was used to calculate the water depth, velocity, and elevation of the water surface with and without dam installation. The study provides the administration with practical and reasonable procedures for avoiding flash flood destruction in urban areas.

Comparison of Two Hydrological Models, HEC-HMS and SWAT in Runoff Estimation: Application to Huai Bang Sai Tropical Watershed, Thailand

In the present study, the streamflow simulation capacities between the Soil and Water Assessment Tool (SWAT) and the Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS) were compared for the Huai Bang Sai (HBS) watershed in northeastern Thailand. During calibration (2007–2010) and validation (2011–2014), the SWAT model demonstrated a Coefficient of Determination (R2) and a Nash Sutcliffe Efficiency (NSE) of 0.83 and 0.82, and 0.78 and 0.77, respectively. During the same periods, the HEC-HMS model demonstrated values of 0.80 and 0.79, and 0.84 and 0.82. The exceedance probabilities at 10%, 40%, and 90% were 144.5, 14.5, and 0.9 mm in the flow duration curves (FDCs) obtained for observed flow. From the HEC-HMS and SWAT models, these indices yielded 109.0, 15.0, and 0.02 mm, and 123.5, 16.95, and 0.02 mm. These results inferred those high flows were captured well by the SWAT model, while medium flows were captured well by the HEC-HMS model. It is noteworthy that the low flows were accurately simulated by both models. Furthermore, dry and wet seasonal flows were simulated reasonably well by the SWAT model with slight under-predictions of 2.12% and 13.52% compared to the observed values. The HEC-HMS model under-predicted the dry and wet seasonal flows by 10.76% and 18.54% compared to observed flows. The results of the present study will provide valuable recommendations for the stakeholders of the HBS watershed to improve water usage policies. In addition, the present study will be helpful to select the most appropriate hydrologic model for humid tropical watersheds in Thailand and elsewhere in the world.