Drivers of Model Uncertainty for Urban Runoff in a Tropical Climate: The Effect of Rainfall Variability and Subcatchment Parameterization

IF 1.2 Q4 WATER RESOURCES
K. Irvine, L. Chua, M. Ashrafi, H. Loc, Song Ha Le
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引用次数: 1

Abstract

Urbanization continues to increase in countries with tropical climates and this trend, combined with the likely increasing frequency of extreme rainfall events due to a changing climate, places such development at risk and in need of resiliency assessment. Conceptual models to assess runoff dynamics can be an important component of resiliency assessment, but there are comparatively less data to calibrate these models than are available in the global north. As such, there also is less information with respect to the drivers of model uncertainty and sensitivity. To address this gap in knowledge, we summarize the calibration results of PCSWMM for subcatchment areas in a tropical climate study catchment for which there are substantial rainfall and runoff data. Subsequently, we used the calibrated model to evaluate the impact that rain gauge density may have on runoff estimates. We also investigated the sensitivity of PCSWMM peak flow and total volume estimates to physical subcatchment parameters other than rainfall. With between 38 and 87 events captured for each monitoring station, the NSE, r2, and ISE ratings varied, but generally were in the respective ranges 0.7–0.8, 0.79–0.85, and good–excellent. It can be concluded that PCSWMM performed well in representing the tropical storm events. The rainfall pattern in the study catchment exhibited considerable spatial variability, both annually and seasonally, with annual rainfall increasing from 2063 mm near the coast to 3100 mm less than 17 km further inland. While the model was sensitive to %imperviousness, subcatchment width, impervious Manning’s n, and, to a lesser extent, various surface storage and infiltration parameters, the spatial variability of rainfall had the greatest impact on model uncertainty.
热带气候下城市径流模式不确定性的驱动因素:降雨变率和小集水区参数化的影响
热带气候国家的城市化进程继续加快,这一趋势加上气候变化可能导致极端降雨事件的频率增加,使这种发展面临风险,需要对其进行复原力评估。评估径流动态的概念模型可以成为恢复力评估的重要组成部分,但与全球北方相比,校准这些模型的数据相对较少。因此,关于模型不确定性和敏感性的驱动因素的信息也较少。为了解决这一知识上的差距,我们总结了PCSWMM在热带气候研究集水区的子集水区的校准结果,其中有大量的降雨和径流数据。随后,我们使用校准模型来评估雨量计密度可能对径流估算的影响。我们还研究了PCSWMM峰值流量和总体积估计对除降雨以外的物理集水区参数的敏感性。每个监测站捕获的事件在38到87之间,NSE, r2和ISE评级各不相同,但通常分别在0.7-0.8,0.79-0.85和良好-优秀的范围内。由此可见,PCSWMM对热带风暴事件具有较好的表征效果。研究流域的降雨模式在年和季节上都表现出相当大的空间变异性,年降雨量从海岸附近的2063毫米增加到内陆不到17公里的3100毫米。模型对不透水率、集水区宽度、不透水曼宁系数敏感,对各种地表蓄水量和入渗参数的影响较小,但降雨的空间变异性对模型不确定性的影响最大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.30
自引率
0.00%
发文量
8
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