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首页> 外文期刊>Hydrology and Earth System Sciences >Regionalised spatiotemporal rainfall and temperature models for flood studies in the Basque Country, Spain
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Regionalised spatiotemporal rainfall and temperature models for flood studies in the Basque Country, Spain

机译:西班牙巴斯克地区洪水研究的区域时空降雨和温度模型

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摘要

A spatiotemporal point process model of rainfall is fitted to data takenfrom three homogeneous regions in the Basque Country, Spain. The model is thesuperposition of two spatiotemporal Neyman–Scott processes, in which raincells are modelled as discs with radii that follow exponential distributions.In addition, the model includes a parameter for the radius of storm discs, sothat rain only occurs when both a cell and a storm disc overlap a point. Themodel is fitted to data for each month, taken from each of the threehomogeneous regions, using a modified method of moments procedure thatensures a smooth seasonal variation in the parameter estimates.Daily temperature data from 23 sites are used to fit a stochastictemperature model. A principal component analysis of the maximum dailytemperatures across the sites indicates that 92% of the variance isexplained by the first component, implying that this component can be used toaccount for spatial variation. A harmonic equation with autoregressive errorterms is fitted to the first principal component. The temperature model isobtained by regressing the maximum daily temperature on the first principalcomponent, an indicator variable for the region, and altitude. This, togetherwith scaling and a regression model of temperature range, enables hourlytemperatures to be predicted. Rainfall is included as an explanatory variablebut has only a marginal influence when predicting temperatures.A distributed model (TETIS; Francés et al., 2007) is calibrated for aselected catchment. Five hundred years of data are simulated using therainfall and temperature models and used as input to the calibrated TETISmodel to obtain simulated discharges to compare with observed discharges.Kolmogorov–Smirnov tests indicate that there is no significant difference inthe distributions of observed and simulated maximum flows at the same sites,thus supporting the use of the spatiotemporal models for the intendedapplication.
机译:降雨的时空点过程模型适合于来自西班牙巴斯克地区三个均质地区的数据。该模型是两个时空Neyman-Scott过程的叠加,其中雨单元被建模为半径遵循指数分布的圆盘。此外,该模型还包括一个风暴圆盘半径的参数,因此,降雨仅在一个单元和两个风暴盘与一点重叠。使用改进的矩量法确保从参数估计的平滑季节性变化,该模型适合每个月从三个同质区域获取的数据。 使用23个站点的每日温度数据进行拟合随机温度模型。对站点最高每日温度的主成分分析表明,第一个成分解释了92%的方差,这意味着该成分可用于解释空间变化。将具有自回归误差项的调和方程拟合到第一个主分量。通过对第一主成分上的最高每日温度,该区域的指示变量和海拔高度进行回归,可以获得温度模型。结合比例和温度范围的回归模型,可以预测每小时的温度。降雨作为解释变量被包括在内,但在预测温度时仅具有边际影响。 针对选定的流域校准了分布式模型(TETIS;Françes等,2007)。使用降雨和温度模型对五百年的数据进行了模拟,并将其用作已校准的TETIS模型的输入,以获取模拟排放量与观测排放量进行比较。相同的站点,从而支持将时空模型用于预期的应用程序。

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