Hydrologic Engineering Center-Hydrologic Modeling System Model Research Articles

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.

Study on the early warning and forecasting of flash floods in small watersheds based on the rainfall pattern of risk probability combination

Flash floods cause great harm to people’s lives and property safety. Rainfall is one of the main causes of flash floods in small watersheds. The uncertainty of rainfall events results in inconsistency between the traditional single rainfall pattern and the actual rainfall process, which poses a great challenge for the early warning and forecasting of flash floods. To carry out the effective flash flood early warning and forecasting, this paper proposes a novel rainfall pattern by coupling total rainfall and peak rainfall intensity based on copula functions, i.e., the rainfall pattern of risk probability combination (RPRPC). On this basis, the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) hydrological model is used to simulate the rainfall-runoff process, the trial algorithm is used to calculate the critical rainfall (CR), and the optimistic-general-pessimistic (O–G-P) early warning mode considering the decision maker's risk preference is proposed. The small watershed of Xinxian in Henan province, China, is taken as a case study for calculation. The results show that the RPRPC is feasible and closer to the actual rainfall process than the traditional rainfall pattern, Frank copula function is the best for determining the joint distribution function of total rainfall and peak rainfall intensity, and the HEC-HMS model can be applied to small watersheds in hilly areas. Additionally, both RPRPC and antecedent soil moisture condition (ASMC) have influence on CR, and the variation of RPRPC will change the influence of ASMC on CR. Finally, the effectiveness of O–G-P early warning mode is verified.

Estimation of Initial Abstraction for Hydrological Modeling Based on Global Land Data Assimilation System–Simulated Datasets

AbstractInitial abstraction (Ia) is a sensitive parameter in hydrological models, and its value directly determines the amount of runoff. Ia, which is influenced by many factors related to antecedent watershed condition (AWC), is difficult to estimate due to lack of observed data. In the Soil Conservation Service curve number (SCS-CN) method, it is often assumed that Ia is 0.2 times the potential maximum retention S. Yet this assumption has frequently been questioned. In this paper, Ia/S and factors potentially influencing Ia were collected from rainfall–runoff events. Soil moisture and evaporation data were extracted from GLDAS-Noah datasets to represent AWC. Based on the driving factors of Ia, identified using the Pearson correlation coefficient and maximal information coefficient, artificial neural network (ANN)-estimated Ia was applied to simulate the selected flood events in the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model. The results indicated that Ia/S varies over different events and different watersheds. Over 75% of the Ia/S values are less than 0.2 in the two study areas. The driving factors affecting Ia vary over different watersheds, and the antecedent precipitation index appears to be the most influential factor. Flood simulation by the HEC-HMS model using statistical Ia gives the best fitness, whereas applying ANN-estimated Ia outperforms the simulation with median Ia/S. For over 60% of the flood events, ANN-estimated Ia provided better fitness in flood peak and depth, with an average Nash–Sutcliffe efficiency coefficient of 0.76 compared to 0.71 for median Ia/S. The proposed ANN-estimated Ia is physically based and can be applied without calibration, saving time in constructing hydrological models.

Different Flooding Behaviors Due to Varied Urbanization Levels within River Basin: A Case Study from the Xiang River Basin, China

Booming urbanization due to a fast-growing population results in more impervious areas, less infiltration, and hence greater flood peak and runoff. Clear understanding of flood responses in regions with different levels and expansions of urbanization is of great importance for regional urban planning. In this study, comparison of flooding responses to urbanization processes in terms of flood peak and runoff volume in the upper, middle, and lower Xiang River Basin (XRB), China, was carried out using the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model. From 2005 to 2015, urbanization level and intensity were higher in the lower XRB compared to the upper and middle XRB, and the overall expansion rate of urban areas was 112.8%. Modeling results by the HEC-HMS model indicate elevated flood peak discharges and volumes due to fast urbanization in the XRB from the 1980s to 2015. This rapid increase is particularly the case in the lower XRB. The study also revealed different hydrological responses of flood regimes—urbanization tends to have larger impacts on peak flood flow rather than on flood volume in the lower XRB, which further corroborated urbanization-induced intensifying flood processes in terms of peak flood flow. Urbanization has increasing impacts on flood volume from the upper to the lower XRB, which can be attributed to accumulated runoff down the river system. This study provides a reference for basin-wide land use and urban planning as well as flood hazard mitigation.

Predicting the occurrence of channelized debris flow by an integrated cascading model: A case study of a small debris flow-prone catchment in Zhejiang Province, China

Excessive water in a channel is an important factor that triggers channelized debris flows. Floods and debris flows often occur in a cascading manner, and thus, calculating the amount of runoff accurately is important for predicting the occurrence of debris flows. In order to explore the runoff-rainfall relationship, we placed two measuring facilities at the outlet of a small, debris flow-prone headwater catchment to explore the hydrological response of the catchment. The runoff responses generally consisted of a rapid increase in runoff followed by a slower decrease. The peak runoff often occurred after the rainfall ended. The runoff discharge data were simulated by two different modeling approaches, i.e., the NAM model and the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model. The results showed that the NAM model performed better than the HEC-HMS model. The NAM model provided acceptable simulations, while the HEC-HMS model did not. Then, we coupled the calculated results of the NAM model with an empirically based debris flow initiation model to obtain a new integrated cascading disaster modeling system to provide improved disaster preparedness and hazard management. In this case study, we found that the coupled model could correctly predict the occurrence of debris flows. Furthermore, we evaluated the effect of the range of input parameter values on the hydrographical shape of the runoff. We also used the grey relational analysis to conduct a sensitivity analysis of the parameters of the model. This study highlighted the important connections between rainfall, hydrological processes, and debris flow, and it provides a useful prototype model system for operational forecasting of debris flows.

Application of HEC-HMS for simulation of peak runoff rates from a small watershed

Hydrologic Engineering Center - Hydrologic Modeling System (HEC-HMS), a versatile hydrological model, was applied to a small watershed situated in Chotanagpur plateau region of India for simulation of peak runoff rates. Initial and constant loss method and Snyder unit hydrograph were chosen for computing the precipitation losses and transforming the estimated runoff into direct surface runoff, respectively. Seven sets of observed hyetographs and corresponding flood hydrographs were used for calibration of model parameters viz., initial loss, constant loss rate, Snyder peaking coefficient and standard time lag. The model output was validated with other set of flood hydrographs (five in number) of the same watershed. A simple linear relationship between predicted and observed peak flow rates was also developed. The HEC-HMS simulated depths of runoff and peak runoff rates matched reasonably well with the observed data. The average value of absolute relative error in estimated peak, a measure of goodness of fit between the peak runoff rates of predicted and observed hydrographs was found to be 6.94%. It was concluded from the study that the HEC-HMS model with the calibrated parameters can be safely used for the determination of the depth of runoff and peak runoff rates from ungauged watersheds with similar hydrological conditions

Evaluation of the effects of underlying surface change on catchment hydrological response using the HEC-HMS model

Abstract. Due to rapid population growth, China, and urbanization, the Dongwan catchment, with a drainage area of 2856 km2 and located in Henan Province, has been subjected to considerable land-use changes since the 1990s. Distributed or semi-distributed models have been widely used in catchment hydrological modeling, along with the rapid development of computer and GIS technologies. The objective of this study is to assess the impact of underlying surface change on catchment hydrological response using the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS), which is a distributed hydrological model. Specifically, 21 flood events were selected for calibrating and validating the model parameters. The satisfactory results show that the HEC-HMS model can be used to simulate the rainfall–runoff response in the Dongwan catchment. In light of the analyses of simulation results, it is shown that the flood peaks and runoff yields after 1990 moderately decrease in comparison with that before 1990 at the same precipitation level. It is also indicated that the underlying surface change leads to the increased flood storage capacity after 1990 in this region.

Optimization – Simulation Model for Detention Basin System Design

A model for the design of detention basin systems is presented that interfaces a simulated annealing (SA) optimization procedure with the U.S. Army Corps of Engineer’s Hydrologic Engineering Center - Hydrologic Modeling System (HEC-HMS). The optimization model is based upon the simulated annealing method to optimize the size and location of detention basin system including the outlet structures subject to design constraints. The program is implemented in Visual Basic for Applications (VBA) interfacing the simulated annealing model with the HEC-HMS model using an MS Excel environment. The respective result files are created by using a VBA executed Python script to extract the appropriate data from the HEC-HMS project DSS file after each simulation performed for the SA procedure. Example applications include a single detention basin system and multiple detention basin systems considering two scenarios. Though the implementation requires considerable computational effort with respect to the number of hydrologic simulations, simulated annealing proves to be an effective tool in the optimal design of detention basin systems as compared to traditional standards of practice.