逻辑斯蒂模型在河谷型城市洪水事件研究中的验证

发布时间：2018-02-01 02:11

本文关键词： 洪水事件逻辑斯蒂模型城市地貌河谷型城市　出处：《西北师范大学学报(自然科学版)》2017年01期 　论文类型：期刊论文

【摘要】：以黄河河谷型城市兰州市为研究区,基于原生自然地理及地形要素,使用文献、气象、自然地理资料和数字高程模型,同时应用GIS空间分析方法并结合逻辑斯蒂回归模型,对兰州盆地洪水事件进行了危险性评价.结果表明,近百年来兰州市河道洪水灾害集中在黄河河漫滩上;洪道洪水灾害发生时间比较频繁,与河道洪水灾害相比,灾害的发生范围较小,具有区域性.利用逻辑斯蒂回归建立河道洪水事件预测模型,得出发生河道洪水事件的概率与高程、距黄河距离呈负相关关系,与传统经验符合,并经过模型检验,预测正确率达94.4%,Nagelkerke R~2值为0.870,接近1,拟合优度较好.利用逻辑斯蒂回归建立洪道洪水事件预测模型,得出发生洪道洪水事件的概率与高程、距黄河距离也呈负相关关系,与传统经验符合,经过模型检验,预测正确率达74.8%,预测效果较好.
[Abstract]:Based on the primary natural geography and topographic elements, the paper uses literature, meteorology, natural geographical data and digital elevation model in Lanzhou, a city of the Yellow River valley. At the same time, the GIS spatial analysis method and the logistic regression model are used to evaluate the risk of flood events in Lanzhou Basin. In the last hundred years, the flood disaster of the river course in Lanzhou City is concentrated on the Yellow River floodplain. Compared with the river flood disaster, the flood disaster occurs in a smaller range and has a regional area. The prediction model of river flood event is established by using logistic regression. It is concluded that the probability of river flood event is negatively related to elevation and distance from the Yellow River, which is consistent with the traditional experience, and the correct prediction rate is 94.4% after model test. The value of Nagelkerke Rn2 is 0.870, which is close to 1, and the degree of good fit is good. A flood event prediction model is established by using logistic regression. It is concluded that the probability of flood events in flood track is negatively related to elevation and distance from the Yellow River, which is consistent with the traditional experience. After model test, the correct rate of prediction is 74.8, and the prediction effect is good.
【作者单位】：兰州大学西部环境教育部重点实验室;兰州大学资源环境学院;兰州大学干旱区水循环与水资源研究中心;
【基金】：国家自然科学基金资助项目(41571178;41371009)
【分类号】：P333.2;X43
【正文快照】： 洪水灾害是一种非常严重的自然灾害,无论是发生的时空强度,还是对人类生存发展的影响,在所有自然灾害中,洪水灾害都是最严重的[1-4].21世纪以来,随着全球气候变暖以及人类活动的影响,洪水发生的频率不断上升,造成的经济损失不断增大[5].因此,对洪水灾害的发生进行研究具有重要

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