Hydrologic Modeling System 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.

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.

Impacts of Vegetation Removal on Urban Mediterranean Stream Hydrology and Hydraulics

Given the widespread presence of non-native vegetation in urban and Mediterranean watersheds, it is important to evaluate how these sensitive ecosystems will respond to activities to manage and restore native vegetation conditions. This research focuses on Del Cerro, a tributary of the San Diego River in California, where non-native vegetation dominates the riparian zone, creating flooding and fire hazards. Field data were collected in 2018 to 2021 and consisted of water depth, streamflow, and stream temperature. Our data set also captured baseline conditions in the floodplain before and after the removal of burned non-native vegetation in November 2020. Observed changes in hydrologic and geomorphic conditions were used to parameterize and calibrate a two-dimensional hydraulic model to simulate urban floodplain hydraulics after vegetation removal. We utilized the U.S. Army Corps of Engineers’ Hydrologic Engineering Center River Assessment System (HEC-RAS) model to simulate the influence of canopy loss and vegetation disturbance and to assess the impacts of vegetation removal on stream restoration. We simulated streamflow, water depth, and flood extent for two scenarios: (1) 2019; pre-restoration where non-native vegetation dominated the riparian area, and (2) 2021; post-restoration following the removal of non-native vegetation and canopy. Flooding after restoration in 2021 was more frequent compared to 2019. We also observed similar flood extents and peak streamflow for storm events that accumulated half the amount of precipitation as pre-restoration conditions. Our results provide insight into the responses of small urban stream reaches to the removal of invasive vegetation and canopy cover.

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.

A regional hydrological model for arid and semi-arid river basins with consideration of irrigation

We develop a regional hydrological model that applies to arid and semi-arid regions, by explicitly considering the effect of irrigation on the hydrological processes. A new irrigation module is here integrated into the recently introduced Atmospheric and Hydrological Modelling System (AHMS) for the quantitative assessment of basin-scale hydrological response to climate change and the impact of anthropogenic activities on water resources. The land surface, channel routing and groundwater modules of the AHMS are extended here to incorporate the new module. We then apply the model to simulating the hydrological processes in the Yellow River Basin, an arid and semi-arid region where irrigation constitutes the most important source of water use. The model is calibrated and validated using in-situ and remote sensing observations. This study demonstrates the capability of the AHMS for regional hydrological modelling in arid and semi-arid basins where irrigation profoundly influences the water balance.

Hydrological Modeling of the Cambamba Watershed in Angola Using the HEC-HMS Model

When evaluating the impact of climate change on water resources in river basins it is crucial to accurately estimate the availability of water and such can be attained through hydrological modeling of the basin. The studies of the Hydrological Modeling System (HEC-HMS) for the Cambamba River Basin in Angola has been calibrated and validated for the prediction of its hydrologic response. Due to the complexity of Hydrologic models, a good calibration of the model should be established, therefore, improving its skills and effectiveness. A combination of both the energy budget and a physically-based rainfall-runoff model, which are used for the estimation of lake evaporation, were applied in the lake water balance model. Soil storage, as well as groundwater storage coefficient, are essential parameters for estimating the simulated streamflow. For an adequate performance evaluation of the model which entails the simulation of the streamflow on Cambamba watershed and quantification of water availability, The Nash-Sutcliffe model efficiency criterion; root mean square error; percentage error in volume PEV; and percentage error in peak PEP, were implemented. Model performance is improved by using semiannual parameter sets that consider the change in hydrological conditions, as evaluated in this study. Key words: HEC-HMS, watershed, rainfall-runoff, flood hazards

A Comprehensive Approach to Develop a Hydrological Model for the Simulation of All the Important Hydrological Components: The Case of the Three-River Headwater Region, China

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.

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.

Monitoring Land Use/Cover Changes by Using Multi-Temporal Remote Sensing for Urban Hydrological Assessment: A Case Study in Beijing, China

Understanding the change in hydrological response due to urban dynamics is important for better flood preparedness and future sustainable urban planning. This study investigated the influence of urban land cover change on spatiotemporal changes in flood peak discharge and flood volume within a rapidly urbanizing catchment located in Beijing, China. We used Landsat satellite data ranging from 1986 to 2017 to monitor and quantify urban growth. Moreover, the Hydrological Modeling System (HEC-HMS) coupled with meteorological data was utilized to examine the impact of urban growth on hydrological responses. The results revealed that major changes in land use/cover (LULC) were detected in the urban landscape, which increased from 25.22% to 65.48% of the total catchment area, while agricultural land decreased from 64.85% to 25.28% during 1986–2017. The flood peak discharge and flood volume average of the three rainstorms events reached 7.02% and 11.93%, respectively. Furthermore, the changes in flood peak discharge and flood volume were more obvious at the sub-catchment scale. These findings indicate that urban growth enhanced the possible flooding risk in the study catchment. This study improves the understanding of the isolated impacts of urbanization on flooding and provides essential information for sustainable urban planning.

Applied methodology based on HEC-HMS for reservoir filling estimation due to soil erosion

Abstract Authors propose a beneficial methodology for hydrological planning in their study. Prospective evaluations of the basins’ net capacity can be done using the technique presented. The HEC-HMS (Hydrologic Modelling System) software can be used to estimate in a basin, the sediment emitted. For a certain precipitation, this methodology allows estimating, within a certain range, the gradual blockage of a reservoir, and even a projected date for total blockage. This has some applications to adopt corrective measures that prevent or delay the planned blockage deadlines. The model is of the semi-distributed type, estimating the generation and emission of sediments by sub-basins. The integration of different return periods in HEC-HMS with a semi-distributed model by sub-basins and the application of a mathematical model are the differentiating element of this research. The novelty of this work is to allow prognosing the reservoir sedimentation rate of basins in a local and regional scale with a medium and large temporary framework. The developed methodology allows public institutions to take decisions concerning hydrological planning. It has been applied to the case of “Charco Redondo” reservoir, in Cádiz, Andalusia, in southern Spain. Applying the methodology to this case, an average soil degradation of the reservoir basin has been estimated. Therefore, it is verified that in 50 years the reservoir is expected to lose 8.4% of its capacity.

An algorithm for deriving the topology of belowground urban stormwater networks

Abstract. Belowground urban stormwater networks (BUSNs) are critical for removing excess rainfall from impervious urban areas and preventing or mitigating urban flooding. However, available BUSN data are sparse, preventing the modeling and analysis of urban hydrologic processes at regional and larger scales. We propose a novel algorithm for estimating BUSNs by drawing on concepts from graph theory and existing, extensively available land surface data, such as street network, topography, and land use/land cover. First, we derive the causal relationships between the topology of BUSNs and urban surface features based on graph theory concepts. We then apply the causal relationships and estimate BUSNs using web-service data retrieval, spatial analysis, and high-performance computing techniques. Finally, we validate the derived BUSNs in the metropolitan areas of Los Angeles, Seattle, Houston, and Baltimore in the US, where real BUSN data are partly available to the public. Results show that our algorithm can effectively capture 59 %–76 % of the topology of real BUSN data, depending on the supporting data quality. This algorithm has promising potential to support large-scale urban hydrologic modeling and future urban drainage system planning.

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.

Performance evaluation of satellite-based rainfall estimates for hydrological modeling over Bilate river basin, Ethiopia

PurposeThe purpose of this study is to address a highly heterogeneous rift margin environment and exhibit considerable spatiotemporal hydro-climatic variations. In spite of limited, random and inaccurate data retrieved from rainfall gauging stations, the recent advancement of satellite rainfall estimate (SRE) has provided promising alternatives over such remote areas. The aim of this research is to take advantage of the technologies through performance evaluation of the SREs against ground-based-gauge rainfall data sets by incorporating its applicability in calibrating hydrological models.Design/methodology/approachSelected multi satellite-based rainfall estimates were primarily compared statistically with rain gauge observations using a point-to-pixel approach at different time scales (daily and seasonal). The continuous and categorical indices are used to evaluate the performance of SRE. The simple scaling time-variant bias correction method was further applied to remove the systematic error in satellite rainfall estimates before being used as input for a semi-distributed hydrologic engineering center's hydraulic modeling system (HEC-HMS). Runoff calibration and validation were conducted for consecutive periods ranging from 1999–2010 to 2011–2015, respectively.FindingsThe spatial patterns retrieved from climate hazards group infrared precipitation with stations (CHIRPS), multi-source weighted-ensemble precipitation (MSWEP) and tropical rainfall measuring mission (TRMM) rainfall estimates are more or less comparably underestimate the ground-based gauge observation at daily and seasonal scales. In comparison to the others, MSWEP has the best probability of detection followed by TRMM at all observation stations whereas CHIRPS performs the least in the study area. Accordingly, the relative calibration performance of the hydrological model (HEC-HMS) using ground-based gauge observation (Nash and Sutcliffe efficiency criteria [NSE] = 0.71; R2 = 0.72) is better as compared to MSWEP (NSE = 0.69; R2 = 0.7), TRMM (NSE = 0.67, R2 = 0.68) and CHIRPS (NSE = 0.58 and R2 = 0.62).Practical implicationsCalibration of hydrological model using the satellite rainfall estimate products have promising results. The results also suggest that products can be a potential alternative source of data sparse complex rift margin having heterogeneous characteristics for various water resource related applications in the study area.Originality/valueThis research is an original work that focuses on all three satellite rainfall estimates forced simulations displaying substantially improved performance after bias correction and recalibration.

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.

Flood inundation mapping under climate change scenarios in the Boyo watershed of Southern Ethiopia

Abstract This research aims to map flood inundated areas under changing climate in the Boyo watershed of Southern Ethiopia. A semi-distributed physically based Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) and Hydrologic Engineering Center-River Analysis System (HEC-RAS) were used to simulate the flood events and maps, respectively, for climate scenarios. The bias-corrected data of four climate models were used for the baseline (1976–2005), mid-term (2041–2070) and long-term (2071–2100) cycles under RCP4.5 and RCP8.5 scenarios. The 50- and 100-year return period flood events were generated from the baseline and future period streamflow data. The HEC-RAS model was used to simulate the inundation areas and depths from the flood events. The result exhibited that the average annual rainfall and maximum and minimum temperatures of the catchment will increase in the future with an increase in annual runoff. The severity of annual floods would increase in the future under RCP4.5 and RCP8.5 scenarios. Approximately, 193 ha of the study may be flooded with flood events having a return period of 100 years under the RCP8.5 scenario in the long-term period, which is an extreme case. The result is a benchmark to reduce the flood risk and management of floodplains in this watershed.

Augmentation of WRF-Hydro to simulate overland-flow- and streamflow-generated debris flow susceptibility in burn scars

Abstract. In steep wildfire-burned terrains, intense rainfall can produce large runoff that can trigger highly destructive debris flows. However, the ability to accurately characterize and forecast debris flow susceptibility in burned terrains using physics-based tools remains limited. Here, we augment the Weather Research and Forecasting Hydrological modeling system (WRF-Hydro) to simulate both overland and channelized flows and assess postfire debris flow susceptibility over a regional domain. We perform hindcast simulations using high-resolution weather-radar-derived precipitation and reanalysis data to drive non-burned baseline and burn scar sensitivity experiments. Our simulations focus on January 2021 when an atmospheric river triggered numerous debris flows within a wildfire burn scar in Big Sur – one of which destroyed California's famous Highway 1. Compared to the baseline, our burn scar simulation yields dramatic increases in total and peak discharge and shorter lags between rainfall onset and peak discharge, consistent with streamflow observations at nearby US Geological Survey (USGS) streamflow gage sites. For the 404 catchments located in the simulated burn scar area, median catchment-area-normalized peak discharge increases by ∼ 450 % compared to the baseline. Catchments with anomalously high catchment-area-normalized peak discharge correspond well with post-event field-based and remotely sensed debris flow observations. We suggest that our regional postfire debris flow susceptibility analysis demonstrates WRF-Hydro as a compelling new physics-based tool whose utility could be further extended via coupling to sediment erosion and transport models and/or ensemble-based operational weather forecasts. Given the high-fidelity performance of our augmented version of WRF-Hydro, as well as its potential usage in probabilistic hazard forecasts, we argue for its continued development and application in postfire hydrologic and natural hazard assessments.

A Comparative Evaluation of Using Rain Gauge and NEXRAD Radar-Estimated Rainfall Data for Simulating Streamflow

Ascertaining the spatiotemporal accuracy of precipitation is a challenge for hydrologists and planners for flood protection measures. The objective of this study was to compare streamflow simulations using rain gauge and radar data from a watershed in Southern Ontario, Canada, using the Hydrologic Engineering Center’s event-based distributed Hydrologic Modeling System (HEC-HMS). The model was run using the curve number (CN) and the Green and Ampt infiltration methods. The results show that the streamflow simulated with rain gauge data compared better with the observed streamflow than the streamflow simulated using radar data. However, when the Mean Field Bias (MFB) corrections were applied, the quality of the streamflow results obtained from radar rainfall data improved. The results showed no significant difference between the simulated streamflow using the SCS and the Green and Ampt infiltration approach. However, the SCS method is reasonably more appropriate for modeling the runoff at the sub-basin-scale than the Green and Ampt infiltration approach. With the SCS method, the simulated and observed runoff amount obtained using rain gauge rainfall showed an R2 value of 0.88 and 0.78 for MFB-corrected radar and 0.75 for radar only. For the Green and Ampt modeling option, the R2 value for the simulated and observed runoff amounts were 0.87 with rain gauge, 0.66 with radar only, and 0.68 with MFB-corrected radar rainfall inputs. The NSE values for rain gauge input ranged from 0.65 to 0.35. Overall, three values were less than 0.5 for streamflow for both the methods. For seven radar rainfall events, the NSE was greater than 0.5, with a range of very good to satisfactory. The analysis of RSR showed a very good comparison of stream flow using the SCS curve number method and Green and Ampt method using different rainfall inputs. Only one value, the 2 November 2003 event, was above 0.7 for rain gauge-based streamflow. The other RSR values were in the range of “very good”. Overall, the study showed better results for the simulated runoff with the MFB-corrected radar rainfall when compared with the simulations obtained using radar rainfall only. Therefore, MFB-corrected radar could be explored as a substitute rainfall source.

Flood forecasting methods for a semi‐arid and semi‐humid area in Northern China

AbstractThe Double‐Excess (DE) model is a flood forecasting model which was developed to reflect the characteristics of runoff generation in semi‐arid and semi‐humid areas. However, the empirical unit hydrograph used in the subbasin confluence module often has low precision because of the difficulty associated with parameter quantification. This study improves the subbasin confluence module of the DE model by coupling the geomorphologic instantaneous unit hydrograph (GIUH) to establish the improved DE model (DE‐GIUH) to calculate the subbasin confluence based on topographic physical characteristics. The improved model is applied to the Wangjiahui Hydrological Station Basin in Northern China. Compared with the conventional DE model and the widely used hydrologic modelling system (HEC‐HMS) model, the results show that DE‐GIUH improved flood forecasting, including the component peak discharge, flood peak appearance time and flood progress. The qualified rate (QR) of all three models reached grade A (QR ≥ 85.0%). However, the proportion of the deterministic coefficient (DC) reaching grade B or above (DC ≥ 0.70) improved from 50% (HEC‐HMS) and 30% (DE) to 90% (DE‐GIUH) in the calibration period, and from 62.5% and 25% to 75% in the validation period. In particular, for large and medium floods, the proportion of DC reaching grade B and above is 100% for DE‐GIUH, which is much higher than that of the other two models. The proposed improved model provides an alternative method for flood prediction in ungauged areas.