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On the ability of large-scale hydrological models to simulate land use and land cover change impacts in Amazonian basins

机译:关于大型水文模型模拟亚马逊河流域土地利用和土地覆盖变化影响的能力

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The MHD-INPE model was applied in the Ji-Parana Basin, a 30000km(2) catchment located in the southwest of the Amazon Basin which has lost more than 50% of its forest since the 1980s, to simulate land use and land cover change impacts on runoff generation process and how they are related to basin topography. Simulation results agree with observational studies in the sense that fast response processes are significant in sub-basins with steep slopes while in basins with gentle topography, the impacts are most visible in slow-response hydrological processes. On the other hand, the model is not able to capture the dependence of LUCC impacts on spatial scales. These discrepancies are probably associated with limitations in the spatial representation of heterogeneities within the model, which become more relevant at larger scales. We also tested the hypothesis that secondary forest growth should be able to compensate the decrease in evapotranspiration due to forest-cropland or forest-grassland conversion at a regional scale. Results showed that despite the small fraction of secondary forest estimated on the basin, the higher evapotranspiration efficiency of this type of forest counterbalances a large fraction of the LUCC impacts on evapotranspiration. This result suggests that enhanced transpiration due to secondary forest could explain, at least in part, the lack of clear LUCC signals in discharge series at larger scales.
机译:MHD-INPE模型应用于吉帕拉纳盆地,该盆地位于亚马逊盆地西南30000km(2)流域,自1980年代以来森林流失了50%以上,用于模拟土地利用和土地覆盖变化对径流产生过程的影响及其与流域地形的关系。模拟结果在一定意义上与观测研究相吻合,即在具有陡坡的子盆地中快速响应过程很重要,而在地形缓和的盆地中,影响在响应缓慢的水文过程中最为明显。另一方面,该模型无法捕获LUCC影响对空间尺度的依赖性。这些差异可能与模型中异质性的空间表示形式的局限性有关,这些局限性在更大范围内变得越来越重要。我们还检验了以下假设:在区域范围内,次生森林的生长应该能够补偿因森林-农田或森林-草地的转化而引起的蒸散量的减少。结果表明,尽管该流域的次生林估计很小,但这类森林较高的蒸散效率抵消了大部分LUCC对蒸散的影响。该结果表明,次生林带来的蒸腾作用可以至少部分解释在较大规模的排放序列中缺乏清晰的LUCC信号。

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