基于哨兵和 MODIS 数据的马拉维姆祖祖市城市山洪模型

IF 3.3 Q2 ENVIRONMENTAL SCIENCES Frontiers in Climate Pub Date : 2024-05-21 DOI:10.3389/fclim.2024.1284437
W. Gumindoga, Chikumbutso Liwonde, D. Rwasoka, P. Kowe, Auther Maviza, James Magidi, Lloyd Chikwiramakomo, Moises Mavaringana, Eric Tshitende
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引用次数: 0

摘要

洪水是马拉维姆祖祖市的主要灾害。本研究应用地理空间和水文建模技术绘制了该市的洪水发生率和危害图。多传感器[哨兵 1 号、哨兵 2 号和中分辨率成像分光仪 (MODIS)归一化植被指数 (NDVI) 数据集用于确定洪水淹没的时空变化。利用参与式地理信息系统制图方法收集的地面控制点被用来验证已确定的洪水灾害区域。使用二元逻辑回归(BLR)模型来确定和预测洪水危害的空间变化与选定环境因素的函数关系。水文工程中心的水文建模系统 (HEC-HMS) 被用来量化城市洪水所需的峰值流量和径流量。在将 HEC-HMS 模型中的径流和峰值流量输入水文工程中心河流分析系统(RAS)(HEC-RAS)之前,使用 Gumbel 分布法对其进行了极值频率分析。然后,将 HEC-RAS 模型应用于绘制洪水淹没区地图,利用雨量计和气候预测中心 MORPHed 降水量(CMORPH)卫星降雨量输入,绘制出 100 年、50 年、20 年和 10 年重现期的洪水范围图。结果表明,选定的 MODIS 和哨兵数据集能够有效划分洪水事件的空间分布。与河网的距离和城市排水是影响洪水的最重要因素(p < 0.05)。因此,研究区东南部和最西部地区的洪水灾害概率和/或易发性相对较高。HEC-HMS 模型校准(验证)的性能指标为 0.7(0.6),令人满意;同样,HEC-RAS 模型的性能指标也令人满意(p < 0.05)。我们的结论是,经过偏差校正的卫星降雨量估计值和水文建模工具可用于洪水淹没模拟,尤其是在姆祖祖市等雨量计缺乏或设计不完善的地区以及受气候变化影响的地区。这些发现对提供信息和/或更新洪水预警系统的设计以及姆祖祖等发展中城市的影响缓解计划和战略具有重要意义。
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Urban flash floods modeling in Mzuzu City, Malawi based on Sentinel and MODIS data
Floods are major hazard in Mzuzu City, Malawi. This study applied geospatial and hydrological modeling techniques to map flood incidences and hazard in the city. Multi-sensor [Sentinel 1, Sentinel 2, and Moderate Resolution Imaging Spectroradiometer (MODIS)] Normalized Difference Vegetation Index (NDVI) datasets were used to determine the spatio-temporal variation of flood inundation. Ground control points collected using a participatory GIS mapping approach were used to validate the identified flood hazard areas. A Binary Logistic Regression (BLR) model was used to determine and predict the spatial variation of flood hazard as a function of selected environmental factors. The Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) was used to quantify the peak flow and runoff contribution needed for flood in the city. The runoff and peak flow from the HEC-HMS model were subjected to extreme value frequency analysis using the Gumbel Distribution approach before input into the Hydrologic Engineering Center River Analysis System (RAS) (HEC-RAS). The HEC-RAS model was then applied to map flood inundated areas producing flood extents maps for 100, 50, 20, and 10-year return periods, with rain-gauge and Climate Prediction Center MORPHed precipitation (CMORPH) satellite-based rainfall inputs. Results revealed that selected MODIS and Sentinel datasets were effective in delineating the spatial distribution of flood events. Distance from the river network and urban drainage are the most significant factors (p < 0.05) influencing flooding. Consequently, a relatively higher flood hazard probability and/susceptibility was noted in the south-eastern and western-most regions of the study area. The HEC-HMS model calibration (validation) showed satisfactory performance metrics of 0.7 (0.6) and similarly, the HEC-RAS model significantly performed satisfactorily as well (p < 0.05). We conclude that bias corrected satellite rainfall estimates and hydrological modeling tools can be used for flood inundation simulation especially in areas with scarce or poorly designed rain gauges such as Mzuzu City as well as those affected by climate change. These findings have important implications in informing and/updating designs of flood early warning systems and impacts mitigation plans and strategies in developing cities such as Mzuzu.
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来源期刊
Frontiers in Climate
Frontiers in Climate Environmental Science-Environmental Science (miscellaneous)
CiteScore
4.50
自引率
0.00%
发文量
233
审稿时长
15 weeks
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