本数据集为2011年-2020年黄土丘陵沟壑区第三副区罗玉沟流域13个雨量站(赵家湾、廖家陷、姚家沟、石山下、吊沟门、下茹、马周、师家湾、刘家河、马家山、唐家河、滴水崖、罗玉沟口)的降水观测数据。采用SM1型普通雨量器和SL-1型自记雨量计进行观测,本数据集包括逐日降水量表、降水量摘录表、时段最大降水量表(1)、逐次洪水降水量观测成果表。
采集时间 | 2011/01/01 - 2020/12/31 |
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采集地点 | 甘肃省天水市秦州区罗玉沟流域 |
海拔 | 1189.0m - 1895.3m |
数据量 | 1.6 MiB |
数据格式 | Excel表格 |
数据时间分辨率 | 分、日、次 |
坐标系 |
仪器连续观测;人工定时观测;人工摘录整编数据。
SM1型普通雨量器全年观测,汛期(5~10月)4段制摘录,非汛期2段制摘录;SL-1型自记雨量计汛期观测,24段制摘录。 自记式雨量计汛前进行仪器校准,观测过程中出现异常值使用普通雨量计观测值插补。
降水量观测数据严格按照“降水量观测规范”(SL21)的规定进行观测、整理、整编。 观测资料按照“四随”要求,随测、随算、随整理、随分析,发现观测的差错和不合理记录,及时进行处理、改正,并备注说明。观测数据整编录入过程中经过四级人工校核(制表、初校、复校、审核),确保数据质量。
# | 标题 | 文件大小 |
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1 | 罗玉沟小流域降水观测概况说明.docx | 29.4 KiB |
2 | 罗玉沟时段最大降水量表(1).xlsx | 31.4 KiB |
3 | 罗玉沟逐日降水量表.zip | 487.8 KiB |
4 | 罗玉沟逐次洪水降水量观测成果.xlsx | 51.2 KiB |
5 | 罗玉沟降水量摘录表.zip | 1002.1 KiB |
# | 时间 | 姓名 | 用途 |
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1 | 2022/07/21 19:54 | 张* |
项目需要进行小流域侵蚀产沙的模拟研究,需要对模型进行率定验证,需要拓展时间尺度,特申请此数据。
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2 | 2022/02/08 00:59 | 江* |
论文题目:An Effective Multi-Satellite Precipitation Fusion Procedure Conditioned by Gauge Background Fields over Chinese Mainland
论文摘要:The accurate estimation of precipitation has a basis for atmospheric and hydrological applications. However, large uncertainties exist in the estimation of regional precipitation derived solely from remote sensing data. Herein, we develop an effective method for fusing multiple satellite-based precipitation products to capitalize on their strengths and maximize their applicability at 0.25° scales. Specifically, we describe an approach based on bias correction in individual satellite-based products and their merging with up-scaled (1.0°) gauge-based interpolated data to produce finer -resolution (0.25°) data outputs. By focusing on seven regions to generate the estimates of merged precipitation across the Chinese mainland (MPCM), we perform a full evaluation based on a range of error metrics. The results show that the bias correction procedure can effectively reduce the discrepancies in the individual satellite-based precipitation products. In addition, the mean absolute error values are also considerably reduced (20%−45%) with respect to the original data over the Chinese mainland. Error statistical metrics demonstrates that, overall the MPCM generated much better accurate estimates on a daily scale, and performed better than the satellite-based precipitation products across different precipitation thresholds. Moreover, the intercomparison results clearly states the superiority of the MPCM against the Multi-Source Weighted-Ensemble Precipitation version 2 global product. Overall, this study provides important advances in merging satellite based remote-sensing methods, which can potentially generate a valuable benchmark precipitation dataset for various applications over Chinese mainland and beyond.
论文类型:期刊论文
导师姓名:李巍岳
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