Refining flood estimation in urbanized catchments using landscape metrics
Refining flood estimation in urbanized catchments using landscape metrics
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DOI：
10.1016/j.landurbplan.2018.02.003
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发表时间：
2018-03
影响因子：
9.1
通讯作者：
James Miller;T. Brewer
中科院分区：
文献类型：
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作者：
James Miller;T. Brewer
无资料流域的洪水估算方法依赖于流量和集水特性之间的广义关系。一般来说，这种集水特性是基于低密度城市化流域的低分辨率国家数据集，不考虑位置，连通性和斑块大小。这些因素更经常地表示在生态学中采用的景观指标，并可能是特别有用的代表城市土地利用的多样性。在这里，水文相关的景观指标与完善的土地利用类和集水区描述符通常应用于英国洪水估计方法，估计中位数年洪水（QMED），以评估这些指标的潜在作用。结果表明，使用更高的分辨率的地理空间数据可以提高城市环境的代表性，具有特定的影响，对划定城市水域功能和集水区，但不是城市范围。细化景观指标的基础上的相关性，导致12个指标和5个集水区描述符进行测试，对观察到的QMED在18个站点使用加权最小二乘回归。修订后的方程表明，某些景观指标可以更好地代表水文复杂性的城市集水区在一个单一的分布式数值形式，导致改进估计QMED非分布式描述符，为选定的案例研究网站。景观指标表达连通性和相对大小和城市发展的位置的能力，承诺在城市洪水估计和流域尺度水文模型的应用潜力巨大。
Flood estimation methods in ungauged basins rely upon generalized relationships between flows and catchment properties. Generally such catchment properties are based on low-resolution national datasets from low density urbanized basins and do not consider location, connectivity and patch size. Such factors are more routinely represented in landscape metrics employed in ecology, and could be particularly useful for representing the diversity of urban land-use. Here, hydrologically relevant landscape metrics are brought together with refined land-use classes and catchment descriptors routinely applied in UK flood estimation methods to estimate the median annual flood (QMED) in order to evaluate the potential role of such metrics. The results show that using higher resolution geospatial data can improve the representation of the urban environment, having particular effects on the delineation of urban water features and catchment area, but not urban extent. Refinement of landscape metrics based on correlations resulted in 12 metrics and 5 catchment descriptors being tested against observed QMED at 18 sites using a weighted least squares regression. The revised equation showed that certain landscape metrics can better represent the hydrological complexity of an urban catchment in a single distributed numerical form, leading to improved estimates of QMED over non-distributed descriptors, for the selected case-study sites. The ability of landscape metrics to express connectivity and relative size and location of urban development promises significant potential for application in urban flood estimation and catchment-scale hydrological modelling.