Modeling of rainfall-runoff process using HEC-HMS model for an urban ungauged watershed in Tunisia
Modeling of rainfall-runoff process using HEC-HMS model for an urban ungauged watershed in Tunisia
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DOI：
10.1007/s40808-021-01177-6
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发表时间：
2021-05-18
影响因子：
3
通讯作者：
Mosbahi, Manel
中科院分区：
文献类型：
--
作者：
Ben Khelifa, Walid;Mosbahi, Manel
洪水是城市小流域最具破坏性的自然灾害之一，造成生命损失、巨大财产损失，并对经济造成严重威胁。适当的建模可以是预防和减少这种洪水风险的有用工具。然而，由于缺乏径流观测，山洪预测仍然是无资料流域水文模拟的挑战之一。本研究的主要目的是开发一个完整的径流模型，使用HEC-HMS软件来估计洪峰流量和重现相关的主要事件发生在一个小的城市无资料流域位于突尼斯东北部的水文过程。一个地理信息系统环境被用来生成研究区域的地理空间信息和计算水文参数。在众多现有的方法中，美国农业部开发的土壤保持服务被选择用于通过水文模型进行径流估计，由于其准确的结果和有限的数据要求。在突尼斯，城市流域监测不存在，因此，该模型不能与实地测量校准。因此，采用有理公式对不同重现期的洪峰流量进行近似估算。结果表明，2003年的降雨过程产生了100年一遇的洪峰流量，而2019年的模拟洪峰流量对应20年一遇。鉴于观测数据的稀缺性，这些研究结果是有用的，以认识到极端降雨事件的规模，并在城市地区设计适当的雨水结构。
Floods are among the most devastating natural disasters in small urban watersheds, resulting in loss of lifes, enormous damages to properties, and causing a serious threat to the economy. Appropriate modeling can be a useful tool to prevent and reduce such flood risks. Nevertheless, due to the lack of runoff observations, flash flood prediction remains one of the challenges of hydrological modeling in ungauged basins. The main objective of this study is to develop a rainfall-runoff modeling using HEC-HMS software to estimate the flood peak discharges and reproduce hydrographs related to the main events that occurred in a small urban ungauged watershed located in North-East of Tunisia. A GIS environment was used to generate geospatial information of the study area and compute hydrologic parameters. Among many existing methods, the Soil Conservation Service, developed by the United States Department of Agriculture, is selected for runoff estimation through hydrological modeling due to its accurate results and its limited data requirements. In Tunisia, urban watershed monitoring does not exist, thus, the model can't be calibrated with field measurements. Thus, the Rational Formula was adopted for approximate estimation of flood peak discharge for different return periods. Results showed that the rainfall event of 2003 generated a peak flow with a 100 years return period, while in 2019, the simulated peak flow corresponded to 20-years return period. Given the scarcity of observed data, these findings are useful to recognize the magnitude of the extreme rainfall events and to design the appropriate stormwater structures in urban areas.