Evaluating applicability of multi-source precipitation datasets for runoff simulation of small watersheds: a case study in the United States
Small watersheds are ideal objects for studying the evolution of hydrological and water resources at small scales. Whether precipitation products can meet the runoff simulation of small watersheds is the main purpose of this study. With NOAA-CPC-US precipitation as a reference, in nine small watersh...
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Format: | Article |
Language: | English |
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Taylor & Francis Group
2020-09-01
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Series: | European Journal of Remote Sensing |
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Online Access: | http://dx.doi.org/10.1080/22797254.2020.1819169 |
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author | Kepeng Feng Yang Hong Juncang Tian Xiangyu Luo Guoqiang Tang Guangyuan Kan |
author_facet | Kepeng Feng Yang Hong Juncang Tian Xiangyu Luo Guoqiang Tang Guangyuan Kan |
author_sort | Kepeng Feng |
collection | DOAJ |
description | Small watersheds are ideal objects for studying the evolution of hydrological and water resources at small scales. Whether precipitation products can meet the runoff simulation of small watersheds is the main purpose of this study. With NOAA-CPC-US precipitation as a reference, in nine small watersheds of the United States, accuracy of the precipitation products such as PERSIANN, PERSIANN-CDR, TRMM-3B42V7, GPM-IMERG, StageIV, and ERA5 is analyzed. By driving the CREST hydrological model using these datasets, the runoff simulation effects were evaluated. Result shows the precipitation products match the NOAA-CPC-US from high to low in the order of StageIV, PERSIANN-CDR, GPM-IMERG, PERSIANN, ERA5, and finally TRMM-3B42 V7. These datasets have relatively low accuracy in the northern high latitude area and the western mountains, while accuracy is better in the central, southern, and eastern parts of the United States. In the runoff simulation effectiveness evaluation, the daily runoff of watersheds is simulated during the same verification period. The results show that: NOAA-CPC-US and StageIV have good simulation effect in small watersheds. In the northern and western United States, the PERSIANN, PERSIANN-CDR, GPM-IMERG, and ERA5 for runoff simulation should be used with caution. TRMM-3B42V7 is not suitable for runoff simulation in small watershed. |
first_indexed | 2024-12-13T00:42:25Z |
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id | doaj.art-5a43a54ec8034609bd8955fc349b2cb7 |
institution | Directory Open Access Journal |
issn | 2279-7254 |
language | English |
last_indexed | 2024-12-13T00:42:25Z |
publishDate | 2020-09-01 |
publisher | Taylor & Francis Group |
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series | European Journal of Remote Sensing |
spelling | doaj.art-5a43a54ec8034609bd8955fc349b2cb72022-12-22T00:05:05ZengTaylor & Francis GroupEuropean Journal of Remote Sensing2279-72542020-09-010011110.1080/22797254.2020.18191691819169Evaluating applicability of multi-source precipitation datasets for runoff simulation of small watersheds: a case study in the United StatesKepeng Feng0Yang Hong1Juncang Tian2Xiangyu Luo3Guoqiang Tang4Guangyuan Kan5Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in NorthwestUniversity of OklahomaBreeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in NorthwestUniversity of OklahomaTsinghua UniversityTsinghua UniversitySmall watersheds are ideal objects for studying the evolution of hydrological and water resources at small scales. Whether precipitation products can meet the runoff simulation of small watersheds is the main purpose of this study. With NOAA-CPC-US precipitation as a reference, in nine small watersheds of the United States, accuracy of the precipitation products such as PERSIANN, PERSIANN-CDR, TRMM-3B42V7, GPM-IMERG, StageIV, and ERA5 is analyzed. By driving the CREST hydrological model using these datasets, the runoff simulation effects were evaluated. Result shows the precipitation products match the NOAA-CPC-US from high to low in the order of StageIV, PERSIANN-CDR, GPM-IMERG, PERSIANN, ERA5, and finally TRMM-3B42 V7. These datasets have relatively low accuracy in the northern high latitude area and the western mountains, while accuracy is better in the central, southern, and eastern parts of the United States. In the runoff simulation effectiveness evaluation, the daily runoff of watersheds is simulated during the same verification period. The results show that: NOAA-CPC-US and StageIV have good simulation effect in small watersheds. In the northern and western United States, the PERSIANN, PERSIANN-CDR, GPM-IMERG, and ERA5 for runoff simulation should be used with caution. TRMM-3B42V7 is not suitable for runoff simulation in small watershed.http://dx.doi.org/10.1080/22797254.2020.1819169runoff simulationsmall watershedsatellite precipitation datasethydrological model |
spellingShingle | Kepeng Feng Yang Hong Juncang Tian Xiangyu Luo Guoqiang Tang Guangyuan Kan Evaluating applicability of multi-source precipitation datasets for runoff simulation of small watersheds: a case study in the United States European Journal of Remote Sensing runoff simulation small watershed satellite precipitation dataset hydrological model |
title | Evaluating applicability of multi-source precipitation datasets for runoff simulation of small watersheds: a case study in the United States |
title_full | Evaluating applicability of multi-source precipitation datasets for runoff simulation of small watersheds: a case study in the United States |
title_fullStr | Evaluating applicability of multi-source precipitation datasets for runoff simulation of small watersheds: a case study in the United States |
title_full_unstemmed | Evaluating applicability of multi-source precipitation datasets for runoff simulation of small watersheds: a case study in the United States |
title_short | Evaluating applicability of multi-source precipitation datasets for runoff simulation of small watersheds: a case study in the United States |
title_sort | evaluating applicability of multi source precipitation datasets for runoff simulation of small watersheds a case study in the united states |
topic | runoff simulation small watershed satellite precipitation dataset hydrological model |
url | http://dx.doi.org/10.1080/22797254.2020.1819169 |
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