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Parameterization based on NOAA-AVHRR NDVI to improve conceptual rainfall- runoff modelling in a large West African catchment

机译:基于NOAA-AVHRR NDVI的参数化可改善大型西非流域的概念性降雨径流模型

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A conceptual hydrological model (GR2M) is applied to a large, poorly gauged catchment in West Africa. The purpose is to simulate the rainfall-runoff relationship at a monthly time step over the period 1982-2000 during which marked hydro-climatic changes took place. The model is based on two parameters: XI for the production function and X2 for the routing function. The size of the production reservoir is usually fixed over time by using data from the FAO soil map. Hydroclimatic data consist of observed series of rainfall, PET and discharge data. The advantage of calibrating the size of the production reservoir by using spatiotemporal satellite NDVI data from NOAA-AVHRR images is investigated. Indeed, in a context of substantial climatic variability, or even of non-stationarity of the observed series, it may be difficult for conceptual models to reproduce runoff precisely over long periods of time. Introducing a spatiotemporal vegetation signal using NDVI data enables partial capture of the effect of the climatic and environmental variability on the functioning of the catchment. Calibrating the model using these additional forcing data significantly enhances the simulation results at the basin outlet, whatever the spatial complexity considered within the watershed through lumped or semi-distributed applications of the model. This study is a first step towards the design of a production function accounting for the spatiotemporal variability of a vegetation index.
机译:概念性水文模型(GR2M)被应用于西非的一个大型,计量欠佳的流域。目的是模拟1982-2000年期间每月一次的降雨-径流关系,在此期间发生了明显的水文气候变化。该模型基于两个参数:用于生产功能的XI和用于工艺路线功能的X2。通常使用粮农组织土壤图的数据来确定生产储集层的大小。水文气候数据包括观测到的一系列降雨,PET和排放数据。研究了使用来自NOAA-AVHRR图像的时空卫星NDVI数据校准生产储层大小的优势。确实,在气候变化很大,甚至观测序列不平稳的情况下,概念模型可能很难长时间精确地再现径流。使用NDVI数据引入时空植被信号可以部分捕获气候和环境变化对流域功能的影响。使用这些额外的强迫数据对模型进行校准可以显着提高流域出口处的仿真结果,无论通过集总或半分布式模型应用在流域内考虑的空间复杂性如何。这项研究是朝着解释植被指数时空变化的生产函数迈出的第一步。

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