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Evaluation of ground-based, daily, gridded precipitation products for Upper Benue River basin, Nigeria

机译:尼日利亚上Bonue River盆地地面,日沉淀产品的评价

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In-situ rain gauge stations are not adequately covering the total area of Upper Benue basin in Nigeria. An accurate gridded precipitation dataset is therefore required for climate study, hydrological modelling and water resource management. For this purpose, three candidates of global, gauge-based, daily, gridded precipitation products were evaluated and compared with the monitoring data from eight stations spanning 25 years period from 1982 to 2006. The three products are Climate Research Unit (CRU), the Climate Prediction Centre (CPC), and the Global Precipitation Climatology Centre (GPCC). The evaluations covered spatial analyses and statistical validations for daily, monthly, seasonal, and extreme rainfall data. Results show that all the three datasets captured well the spatial rainfall characteristics and were able to replicate the rainfall gradient and orographic conditions of the study area, though the GPCC dataset outperformed the others. Line plots and scatter plots were used to compare the gridded datasets with the observation data for monthly data. The GPCC and CRU datasets are both better than that of the CPC. We also used the mean absolute error, the mean bias error, the correlation coefficient, and the modified index of agreement to compare daily data, and found that the GPCC set is the most agreeable with the observation and the CPC set is the least. The daily gridded data products were also compared using probability distribution similarity, with the in-situ data by KS and AD tests. We found the distributions of GPCC and CRU datasets to follow the same distribution as that of the rain gauge data but that of the CPC does not. The results of the extreme events namely annual maximum numbers of consecutive dry-, wet-day, and total rainfall depth show that the dataset of GPCC is the most compatible with the observation and the CPC set is again the least. The most suitable daily ground-based gridded precipitation dataset for hydrological study and modelling in the Upper Benue basin is therefore the GPCC.
机译:原位雨量站没有充分地覆盖尼日利亚上部Bonue盆地的总面积。因此,需要一种准确的网格降水数据集来实现气候研究,水文建模和水资源管理。为此目的,评估了三种全球,仪表,每日网格降水产品的候选物,并与来自1982年至2006年的25年期间的8站的监测数据进行了比较。这三个产品是气候研究单位(CRU),气候预测中心(CPC)和全球降水气候中心(GPCC)。评估涵盖日常,月,季节性和极端降雨数据的空间分析和统计验证。结果表明,所有三个数据集都捕获了空间降雨特性,并且能够复制研究区域的降雨梯度和地形条件,尽管GPCC数据集优于其他GPC数据集。线图和散点图用于将网格化数据集与每月数据的观察数据进行比较。 GPCC和CRU数据集既优于CPC。我们还使用了平均绝对误差,平均偏差误差,相关系数和修改的协议索引来比较日常数据,发现GPCC集是最令人讨厌的观察,CPC集是最少的。还使用概率分布相似性的日常网格数据产品,通过KS和AD测试的原位数据进行比较。我们发现GPCC和CRU数据集的发行版跟随与雨量仪数据相同的分布,但CPC的数据集没有。极端事件的结果即连续的干燥,湿日和总降雨量的年度最大数量显示,GPCC的数据集与观察最兼容,CPC集合是最少的。因此,上Bonue盆地的水文研究和模型中最合适的日常基于地基沉淀数据集是GPCC。

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