Biospheric Theory and Modelling Group, Max Planck Institute for Biogeochemistry, Jena, Germany.
Department of Innovation, Constructora Conconcreto, Medellín, Colombia.
Ann N Y Acad Sci. 2021 Nov;1504(1):76-94. doi: 10.1111/nyas.14515. Epub 2020 Nov 5.
We employ the approach of Roderick and Farquhar (2011) to assess the sensitivity of runoff (R) given changes in precipitation (P), potential evapotranspiration (E ), and other properties that change the partitioning of P (n) by estimating coefficients that predict the weight of each variable in the relative change of R. We use this framework using different data sources and products for P, actual evapotranspiration (E), and E within the Amazon River basin to quantify the uncertainty of the hydrologic response at the subcatchment scale. We show that when estimating results from the different combinations of datasets for the entire river basin (at Óbidos), a 10% increase in P would increase R on average 16%, while a 10% increase in E would decrease R about 6%. In addition, a 10% change in the parameter n would affect the hydrological response of the entire basin around 5%. However, results change from catchment to catchment and are dependent on the combination of datasets. Finally, results suggest that enhanced estimates of E and E are needed to improve our understanding of the future scenarios of hydrological sensitivity with implications for the quantification of climate change impacts at the regional (subcatchment and subbasin) scale in Amazonia.
我们采用罗德里克和法夸尔（2011）的方法，通过估计预测 R 相对变化中每个变量权重的系数，评估降水（P）、潜在蒸散（E）和其他改变 P 分配的特性（n）变化对径流量（R）的敏感性。我们使用来自不同数据源和产品的 P、实际蒸散（E）和亚马逊河流域内 E 的数据，在子流域尺度上量化水文响应的不确定性。我们表明，当估计整个流域（在奥比杜斯）不同数据集组合的结果时，P 增加 10%将使 R 平均增加 16%，而 E 增加 10%将使 R 减少约 6%。此外，n 参数的 10%变化将影响整个流域的水文响应约 5%。然而，结果因集水区而异，并且取决于数据集的组合。最后，结果表明，需要增强对 E 和 E 的估计，以提高我们对未来水文敏感性情景的理解，这对亚马孙地区区域（子流域和子流域）尺度上量化气候变化影响具有重要意义。
