Catchments characteristics, such as geomorphology, geology, soil, land use, and climatic variables, play an important role in total stream flow responses, a critical resource for people and the environment. Most of the previous literatures were applied a conventional statistical regression model to assess the relationship between landscape-climate descriptors, and streamflow and PET. However, a conventional statistical regression model didn’t consider dependence of explanatory variables that were collected or extracted across both space and time. This paper investigated the impacts of landscape attributes and climate variables on catchment scale temporal variation of total streamflow and spatio-temporal variation of potential evapotranspiration (PET) in the Mille catchment using multiple linear regression techniques, and the importance of this study was to test spatial autocorrelation in the spatial regression model which is required to properly assess and quantify the relationship between hydrological regime response components and Landscape-climate descriptors in a catchment with topographically complex, and high spatio-temporal climatic variation like in our case study area, the Mille catchment. Statistical regression analysis revealed significant relationships between streamflow and climate variables, especially with rainfall. Mean maximum temperature is the most dominant factor controlling temporal variation of potential evapotranspiration at a monthly scale, whereas NDVI is the most significant factor that controls the spatial variability of PET. The multiple regression model shows that 91.1% of temporal variation in streamflow was accounted for rainfall, whereas, 96.6% and 78.4% of temporal and spatial variation in potential evapotranspiration was accounted for in maximum temperature and NDVI, respectively. Methods also can be applied to catchments with similar landscape attributes and climate variables.

中文翻译：

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景观属性和气候变量对流域水文的影响

流域特征，如地貌、地质、土壤、土地利用和气候变量，在总流量响应中起着重要作用，是人类和环境的关键资源。大多数以前的文献都应用了传统的统计回归模型来评估景观-气候描述符与径流量和 PET 之间的关系。然而，传统的统计回归模型没有考虑跨空间和时间收集或提取的解释变量的依赖性。本文使用多元线性回归技术研究了景观属性和气候变量对 Mille 流域总流量的流域尺度时间变化和潜在蒸散量 (PET) 的时空变化的影响，这项研究的重要性在于测试空间回归模型中的空间自相关性，这是正确评估和量化地形复杂、时空气候变化大的流域中水文状况响应成分与景观气候描述符之间关系所必需的就像在我们的案例研究区 Mille 流域。统计回归分析揭示了流量与气候变量之间的显着关系，尤其是与降雨量之间的关系。平均最高温度是控制月尺度潜在蒸散时间变化的最主要因素，而 NDVI 是控制 PET 空间变化的最重要因素。多元回归模型显示 91. 径流时间变化的 1% 与降雨有关，而潜在蒸散量的时间和空间变化的 96.6% 和 78.4% 分别与最高温度和 NDVI 有关。方法也可以应用于具有相似景观属性和气候变量的集水区。