Modelling hydrological impact of remotely sensed vegetation change

Hongxing Zheng, D. Robertson, F. Chiew
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Abstract

: Vegetation cover over a catchment could be altered by a changing climate, bushfire or human interventions. This will result in changes of catchment hydrological response that may affect catchment water resources management. For developing adaptative water resources management strategies under a changing climate, it is essential to take into account hydrological responses to the dynamics of vegetation. In this study, we adapt an existing hydrological model (GR4J) by incorporating remotely sensed vegetation cover (represented by leaf area index) into the model, in an attempt to better reflect the relationship between catchment evapotranspiration and vegetation cover. The model is designed to be parsimonious and plausible for quantifying hydrological impacts of vegetation change. The model has been tested in 122 catchments across the Murray Darling Basin (MDB), with remotely sensed leaf area index (LAI) from GIMMS3g and climate inputs from the SILO gridded dataset. Results show that the model performs reasonably well in most catchments (with NSE>0.5 for 95% of the catchments). The model performance is comparable to the original GR4J for most tested catchments but is notably better for 20% of the studied catchments (Figure 1a). The results indicate that remotely sensed LAI can help improve hydrological modelling, particularly by better reflecting the impact of vegetation dynamics on evapotranspiration. However, uncertainty exists in the remotely sensed LAI, which in some cases could affect model performance negatively.
遥感植被变化的水文影响模拟
集水区的植被覆盖可能会因气候变化、森林大火或人为干预而改变。这将导致流域水文反应的变化,从而可能影响流域水资源的管理。为了在气候变化下制定适应性水资源管理战略,必须考虑到植被动态的水文响应。本研究采用现有的GR4J水文模型,将遥感植被覆盖(以叶面积指数为代表)纳入模型,以更好地反映流域蒸散发与植被覆盖之间的关系。该模型被设计为简洁和合理的量化植被变化的水文影响。该模型已经在墨累达令盆地(MDB)的122个集水区进行了测试,使用了GIMMS3g的遥感叶面积指数(LAI)和SILO网格数据集的气候输入。结果表明,该模型在大多数集水区表现良好(95%的集水区NSE为0.5)。对于大多数测试的集水区,该模型的性能与原始GR4J相当,但对于20%的研究集水区,该模型的性能明显更好(图1a)。结果表明,遥感LAI有助于改善水文模型,特别是可以更好地反映植被动态对蒸散发的影响。然而,遥感LAI存在不确定性,在某些情况下会对模型性能产生负面影响。
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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