根据我国安徽省5个试验流域的实测资料,分析了各流域场次洪水的特性,并利用TOPMODEL模型对各流域进行次洪模拟,进一步探讨该模型在我国东部季风区洪水预报方面的适用性。结果表明:安徽省各试验流域场次洪水的降雨量-径流深散点均呈现较好的正相关性,降雨量随着海拔的升高而增大,山区的径流系数大于平原丘陵区;面积最小的瓦屋刘流域对暴雨的响应最为敏感,孙村流域场次洪水的洪峰模数差异最小、起涨时间最长,黄山流域场次洪水的历时最久;随着海拔的升高,流域地形指数的平均值逐渐增大,同时各流域面积占比最大所对应的地形指数逐渐减小;地形指数标准差越大的流域,土地利用类型也越丰富;TOPMODEL模型总体上可以较好地模拟安徽省各试验流域场次洪水过程,且对大流量的捕捉效果优于小流量,对天然流域的模拟效果优于人类活动扰动的流域。
Abstract
Study on flood characteristics and hydrological simulations are of great significance to flood control and disaster mitigation. According to the measured data of five experimental watersheds in Anhui Province, we analyze the characteristics of the floods in each watershed, and then simulate the floods in each watershed by using TOPMODEL to examine its applicability in flood forecasting in the monsoon region of east China. Our results reveal that the rainfall-runoff scatter points of floods in each experimental watershed all present a good positive correlation. The rainfall amount increases with the rising of elevation, and the runoff coefficients in mountainous area are greater than those in the plain and hilly area. The Wawuliu watershed which has the smallest area is the most sensitive to storms; the Suncun watershed features the smallest difference in the modulus of flood peak and the longest flood rising time; while the Huangshan watershed has the longest flood duration. The average value of watershed's topographic index gradually increases with the rising of altitude, while the value corresponding to the largest proportion drops. And the larger the standard deviation of the topographic index is, the more diversified land use types the watershed has. The TOPMODEL can generally reproduce the flood processes of each experimental watershed, and the captured results of large flows are better than those of small ones. The simulation of natural watersheds is better than that of human-disturbed watersheds.
关键词
洪水特性 /
地形指数 /
试验流域 /
TOPMODEL模型 /
次洪模拟
Key words
flood characteristics /
topographic index /
experimental watersheds /
TOPMODEL /
flood simulations
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基金
国家自然科学基金项目(41830863, 51879162)
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