Combining APHRODITE Rain Gauges-Based Precipitation with Downscaled-TRMM Data to Translate High-Resolution Precipitation Estimates in the Indus Basin
文献类型：期刊论文
| 作者 | Noor, Rabeea; Arshad, Arfan15,16; Shafeeque, Muhammad4; Liu, Jinping5,6,7; Baig, Azhar8; Ali, Shoaib9; Maqsood, Aarish; Pham, Quoc Bao10; Dilawar, Adil11,12; Khan, Shahbaz Nasir13 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023 |
| 卷号 | 15期号:2页码:318 |
| 关键词 | RF MGWR TRMM spatial downscaling calibration rain gauges |
| DOI | 10.3390/rs15020318 |
| 文献子类 | Article |
| 英文摘要 | Understanding the pixel-scale hydrology and the spatiotemporal distribution of regional precipitation requires high precision and high-resolution precipitation data. Satellite-based precipitation products have coarse spatial resolutions (similar to 10 km-75 km), rendering them incapable of translating high-resolution precipitation variability induced by dynamic interactions between climatic forcing, ground cover, and altitude variations. This study investigates the performance of a downscaled-calibration procedure to generate fine-scale (1 km x 1 km) gridded precipitation estimates from the coarser resolution of TRMM data (similar to 25 km) in the Indus Basin. The mixed geographically weighted regression (MGWR) and random forest (RF) models were utilized to spatially downscale the TRMM precipitation data using high-resolution (1 km x 1 km) explanatory variables. Downscaled precipitation estimates were combined with APHRODITE rain gauge-based data using the calibration procedure (geographical ratio analysis (GRA)). Results indicated that the MGWR model performed better on fit and accuracy than the RF model to predict the precipitation. Annual TRMM estimates after downscaling and calibration not only translate the spatial heterogeneity of precipitation but also improved the agreement with rain gauge observations with a reduction in RMSE and bias of similar to 88 mm/year and 27%, respectively. Significant improvement was also observed in monthly (and daily) precipitation estimates with a higher reduction in RMSE and bias of similar to 30 mm mm/month (0.92 mm/day) and 10.57% (3.93%), respectively, after downscaling and calibration procedures. In general, the higher reduction in bias values after downscaling and calibration procedures was noted across the downstream low elevation zones (e.g., zone 1 correspond to elevation changes from 0 to 500 m). The low performance of precipitation products across the elevation zone 3 (>1000 m) might be associated with the fact that satellite observations at high-altitude regions with glacier coverage are most likely subjected to higher uncertainties. The high-resolution grided precipitation data generated by the MGWR-based proposed framework can facilitate the characterization of distributed hydrology in the Indus Basin. The method may have strong adoptability in the other catchments of the world, with varying climates and topography conditions. |
| WOS关键词 | GEOGRAPHICALLY WEIGHTED REGRESSION ; RIVER-BASIN ; ANALYSIS TMPA ; SATELLITE ; CLIMATE ; 3B43 ; NONSTATIONARY ; NDVI |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS记录号 | WOS:000926961200001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/200783]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Van Lang Univ, Fac Environm, Ho Chi Minh City 700000, Vietnam 2.Mansoura Univ, Fac Agr, Agr Engn Dept, Mansoura 35516, Egypt 3.Van Lang Univ, Inst Computat Sci & Artificial Intelligence, Lab Environm Sci & Climate Change, Ho Chi Minh City 700000, Vietnam 4.Univ Agr Faisalabad, Fac Agr Engn & Technol, Dept Irrigat & Drainage, Faisalabad 38000, Pakistan 5.Univ Bremen, Inst Geog, Climate Lab, D-28359 Bremen, Germany 6.North China Univ Water Resources & Elect Power, Coll Surveying & Geoinformat, Zhengzhou 450046, Peoples R China 7.Hohai Univ, Key Lab Hydrol Water Resources & Hydraul Engn, Nanjing 210098, Peoples R China 8.Katholieke Univ Leuven, Hydraul & Geotech Sect, Kasteelpk Arenberg 40, BE-3001 Leuven, Belgium 9.McGill Univ, Dept Bioresource Engn, 21111 Lakeshore, Ste Anne De Bellevue, PQ H9X 3V9, Canada 10.Northeast Agr Univ, Sch Water Conservancy & Civil Engn, Harbin 150030, Peoples R China |
| 推荐引用方式 GB/T 7714 | Noor, Rabeea,Arshad, Arfan,Shafeeque, Muhammad,et al. Combining APHRODITE Rain Gauges-Based Precipitation with Downscaled-TRMM Data to Translate High-Resolution Precipitation Estimates in the Indus Basin[J]. REMOTE SENSING,2023,15(2):318. |
| APA | Noor, Rabeea.,Arshad, Arfan.,Shafeeque, Muhammad.,Liu, Jinping.,Baig, Azhar.,...&Elbeltagi, Ahmed.(2023).Combining APHRODITE Rain Gauges-Based Precipitation with Downscaled-TRMM Data to Translate High-Resolution Precipitation Estimates in the Indus Basin.REMOTE SENSING,15(2),318. |
| MLA | Noor, Rabeea,et al."Combining APHRODITE Rain Gauges-Based Precipitation with Downscaled-TRMM Data to Translate High-Resolution Precipitation Estimates in the Indus Basin".REMOTE SENSING 15.2(2023):318. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。