Risk Evaluation of Rainstorm and Flood in the Upper Reaches of Hunhe River (Qingyuan Section) Based on the FloodArea Model

By using data of hourly rainfall with all of the meteorological stations in the upper reaches of Hunhe River (Qingyuan Section), the digital elevation model, the land use and the disasters data etc., the storm flood process which happened on 16 August 2013 is reproduced simulated based on the rainstorm flooding of FloodArea model, also the flooding simulation and its effectiveness have been carried out. Conclusions are drawn as follows: there is a sharp rise of the flood depth falling behind the change of rainfall three or four hours. As the accumulation of the precipitation, the water level has increased, and when the precipitation process stops, the flood pooled into midstream and downstream gradually. According to the disaster investigation, in both the aspects of flooding scope and flooding depth of warning spots, the simulation result of FloodArea model agrees with the fact. It indicates that the FloodArea model generates good simulation effect in the upper reaches of Hunhe River (Qingyuan Section). Combined with population and GDP information, in the whole river, about eighty-three thousand people were affected by flooding, also one billion and five hundred seventy five million RMB of gross domestic product was lost. When the flood depth deepens and the flooding scope increases, correspondingly the loss rate of population and GDP rises and the flood risk increases.

Risk Assessment and Simulation on Storm Flood of the 100-Year Return Period in Hunhe River Basin

Based on the meteorological and geographic information data, with statistical method and the FloodArea model, the extreme daily rainfall of the 100-year return period in Hunhe River basin was established, through the simulation of rainstorm and flood disaster, characteristics of flood depth in warning spot Cangshi village in the upstream of the river were analysed, and possible effect on community economy was also evaluated. Results showed that, the precipitation of 100-year return period occurred, the flood depth has been below 1.0 meter in the most areas of Hunhe River basin, the depth was between 1.0 meter and 2.5 meters in the part areas of Hunhe River basin, and the flood depth has been exceed 2.5 meters in a small part of Hunhe River basin. After the beginning of precipitation, the flood was concentrated in the upper reaches of the river. With the accumulation of precipitation and the passage of time, the flood pools into midstream and downstream. Precipitation lasted for 24 hours, the warning spot was flooded in the beginning of precipitation. With the accumulation of precipitation, water level of the river increases gradually. The depth of warning spot has passed 1.0 meter at the 07 time of the whole process, and the maximum value of flood depth at warning spot was 1.083 meters that occurred at the 19 time. The flood depth of warning spot decreased gradually after the precipitation stopping, and the depth has been below 0.2 meters, the flood of upstream ended. Up to the end of the upstream flood process, in the whole river, about one million five hundred and sixty thousand people were affected by flooding, and thirty-eight billion and two hundred million RMB of gross domestic product were lost, in addition, dry land and paddy field were affected greatly, but woodland and grassland were less affected.

Identification of Suitable Hydrologic Response Unit Thresholds for Soil and Water Assessment Tool Streamflow Modelling

Use of a non-zero hydrologic response unit(HRU) threshold is an effective way of reducing unmanageable HRU numbers and simplifying computational cost in the Soil and Water Assessment Tool(SWAT) hydrologic modelling. However, being less representative of watershed heterogeneity and increasing the level of model output uncertainty are inevitable when minor HRU combinations are disproportionately eliminated. This study examined 20 scenarios by running the model with various HRU threshold settings to understand the mechanism of HRU threshold effects on watershed representation as well as streamflow predictions and identify the appropriate HRU thresholds. Findings show that HRU numbers decrease sharply with increasing HRU thresholds. Among different HRU threshold scenarios, the composition of land-use, soil, and slope all contribute to notable variations which are directly related to the model input parameters and consequently affect the streamflow predictions. Results indicate that saturated hydraulic conductivity, average slope of the HRU, and curve number are the three key factors affecting stream discharge when changing the HRU thresholds. It is also found that HRU thresholds have little effect on monthly model performance, while evaluation statistics for daily discharges are more sensitive than monthly results. For daily streamflow predictions, thresholds of 5%/5%/5%(land-use/soil/slope) are the optimum HRU threshold level for the watershed to allow full consideration of model accuracy and efficiency in the present work. Besides, the results provide strategies for selecting appropriate HRU thresholds based on the modelling goal.