A D-vine copula-based quantile regression towards merging satellite precipitation products over rugged topography: a case study in the upper Tekeze-Atbara Basin
文献类型：期刊论文
| 作者 | Abdallah, Mohammed1,2,6; Zhang, Ke1,2,3,4,5; Chao, Lijun1,2,4; Omer, Abubaker7; Hassaballah, Khalid8; Reda, Kidane Welde9,10; Liu, Linxin1,2; Tola, Tolossa Lemma1,2; Nour, Omar M.1,2,6 |
| 刊名 | HYDROLOGY AND EARTH SYSTEM SCIENCES
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| 出版日期 | 2024-03-07 |
| 卷号 | 28期号:5页码:1147-1172 |
| ISSN号 | 1027-5606 |
| DOI | 10.5194/hess-28-1147-2024 |
| 通讯作者 | Zhang, Ke(kzhang@hhu.edu.cn) |
| 英文摘要 | Precipitation is a vital key element in various studies of hydrology, flood prediction, drought monitoring, and water resource management. The main challenge in conducting studies over remote regions with rugged topography is that weather stations are usually scarce and unevenly distributed. However, open-source satellite-based precipitation products (SPPs) with a suitable resolution provide alternative options in these data-scarce regions, which are typically associated with high uncertainty. To reduce the uncertainty of individual satellite products, we have proposed a D-vine copula-based quantile regression (DVQR) model to merge multiple SPPs with rain gauges (RGs). The DVQR model was employed during the 2001-2017 summer monsoon seasons and compared with two other quantile regression methods based on the multivariate linear (MLQR) and the Bayesian model averaging (BMAQ) techniques, respectively, and with two traditional merging methods - the simple modeling average (SMA) and the one-outlier-removed average (OORA) - using descriptive and categorical statistics. Four SPPs have been considered in this study, namely, Tropical Applications of Meteorology using SATellite (TAMSAT v3.1), the Climate Prediction Center MORPHing Product Climate Data Record (CMORPH-CDR), Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG v06), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN-CDR). The bilinear (BIL) interpolation technique was applied to downscale SPPs from a coarse to a fine spatial resolution (1 km). The rugged-topography region of the upper Tekeze-Atbara Basin (UTAB) in Ethiopia was selected as the study area. The results indicate that the precipitation data estimates with the DVQR, MLQR, and BMAQ models and with traditional merging methods outperform the downscaled SPPs. Monthly evaluations reveal that all products perform better in July and September than in June and August due to precipitation variability. The DVQR, MLQR, and BMAQ models exhibit higher accuracy than the traditional merging methods over the UTAB. The DVQR model substantially improved all of the statistical metrics (CC = 0.80, NSE = 0.615, KGE = 0.785, MAE = 1.97 mm d - 1 , RMSE = 2.86 mm d - 1 , and PBIAS = 0.96 %) considered compared with the BMAQ and MLQR models. However, the DVQR model did not outperform the BMAQ and MLQR models with respect to the probability of detection (POD) and false-alarm ratio (FAR), although it had the best frequency bias index (FBI) and critical success index (CSI) among all of the employed models. Overall, the newly proposed merging approach improves the quality of SPPs and demonstrates the value of the proposed DVQR model in merging multiple SPPs over regions with rugged topography such as the UTAB. |
| WOS关键词 | LAKE TANA BASIN ; UNCERTAINTY ANALYSIS ; RAINFALL PRODUCTS ; HYDROLOGIC APPLICATIONS ; GRIDDED PRECIPITATION ; RIVER-BASIN ; ENSEMBLE ; VALIDATION ; PREDICTION ; ALGORITHM |
| 资助项目 | National Key Research and Development Program of China |
| WOS研究方向 | Geology ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:001190509800001 |
| 出版者 | COPERNICUS GESELLSCHAFT MBH |
| 资助机构 | National Key Research and Development Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/203743]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhang, Ke |
| 作者单位 | 1.Hohai Univ, Natl Key Lab Water Disaster Prevent, Nanjing 210024, Jiangsu, Peoples R China 2.Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210024, Jiangsu, Peoples R China 3.Hohai Univ, Yangtze Inst Conservat & Dev, Nanjing 210024, Jiangsu, Peoples R China 4.Hohai Univ, China Meteorol Adm Hydrometeorol Key Lab, Nanjing 210024, Jiangsu, Peoples R China 5.Hohai Univ, Key Lab Water Big Data Technol Minist Water Resour, Minist Water Resources, Nanjing 210024, Jiangsu, Peoples R China 6.Hydraul Res Stn, POB 318, Wad Madani, Sudan 7.Korea Adv Inst Sci & Technol KAIST, Moon Soul Grad Sch Future Strat, Daejeon, South Korea 8.IGAD Climate Predict & Applicat Ctr ICPAC, Nairobi, Kenya 9.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 10.Tigray Agr Res Inst, Mekele, Ethiopia |
| 推荐引用方式 GB/T 7714 | Abdallah, Mohammed,Zhang, Ke,Chao, Lijun,et al. A D-vine copula-based quantile regression towards merging satellite precipitation products over rugged topography: a case study in the upper Tekeze-Atbara Basin[J]. HYDROLOGY AND EARTH SYSTEM SCIENCES,2024,28(5):1147-1172. |
| APA | Abdallah, Mohammed.,Zhang, Ke.,Chao, Lijun.,Omer, Abubaker.,Hassaballah, Khalid.,...&Nour, Omar M..(2024).A D-vine copula-based quantile regression towards merging satellite precipitation products over rugged topography: a case study in the upper Tekeze-Atbara Basin.HYDROLOGY AND EARTH SYSTEM SCIENCES,28(5),1147-1172. |
| MLA | Abdallah, Mohammed,et al."A D-vine copula-based quantile regression towards merging satellite precipitation products over rugged topography: a case study in the upper Tekeze-Atbara Basin".HYDROLOGY AND EARTH SYSTEM SCIENCES 28.5(2024):1147-1172. |
入库方式： OAI收割
来源：地理科学与资源研究所
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