Evaluation of the TRMM multisatellite precipitation analysis and its applicability in supporting reservoir operation and water resources management in Hanjiang basin, China

Yang, Na; Zhang, Ke; Hong, Yang; Zhao, Qiang; Huang, Qin; Xu, Yan; Xue, Xianwu; Chen, Sheng

doi:10.1016/j.jhydrol.2017.04.006

Cited by 62 publications

(26 citation statements)

References 28 publications

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“…Additional deficiencies were reported by Yang et al. () in China and Liu () and Qiao et al. (), who compared both V6 and V7 versions globally and for U.S. Southern Plains, respectively.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Satellite‐Derived Rainfall Data for Multiple Physio‐Climatic Regions in the Santiago River Basin, Mexico

Ávila-Carrasco

Júnez-Ferreira

Gowda

et al. 2018

J American Water Resour Assoc

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Assessment of water resources requires reliable rainfall data, and rain gauge networks may not provide adequate spatial representation due to limited point measurements. The Tropical Rainfall Measuring Mission (TRMM) provides rainfall data at global scale, and has been used with good results. However, TRMM data are an indirect measurement of rainfall, and therefore must be validated for its proper use. In this work, a validation scheme was designed and implemented to compare the TRMM Version 7 (V7) monthly rainfall product at different time frames with data measured in two hydrologic subregions of the Santiago River Basin (SRB) in Mexico: Río Alto Santiago and Río Bajo Santiago (RBS). Additionally, three physio‐climatic regions provide an assessment of the interplay of topography, distance from coastal regions, and seasonal weather patterns on the correspondence between both datasets. The TRMM V7 rainfall product exhibited good agreement with the rain gauge data particularly for the RBS and for the whole SRB during wettest summer and autumn seasons. However, strong regional dependence was observed due to differences in climate and topography. Overall, in spite of some noted underestimations, the monthly TRMM V7 rainfall product was found to provide useful information that can be used to complement limited monitoring as is the case of RBS. An improved combined rainfall product could be generated and thus gaining the most benefits from both data sources.

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“…Additional deficiencies were reported by Yang et al. () in China and Liu () and Qiao et al. (), who compared both V6 and V7 versions globally and for U.S. Southern Plains, respectively.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Satellite‐Derived Rainfall Data for Multiple Physio‐Climatic Regions in the Santiago River Basin, Mexico

Ávila-Carrasco

Júnez-Ferreira

Gowda

et al. 2018

J American Water Resour Assoc

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“…However, its density of the meteorological stations is far greater than that of the Hexi region (226.46 km 2 /rain gauge vs. 15,858.71 km 2 /rain gauge) [19]. In the context of such high Compared with other evaluation studies in China, the accuracy of 3B42V7 rainfall product in the Hexi region is significantly lower than that in the southeastern region of China [18,23,52], but slightly better than that of the Tibetan Plateau [17,21]. The main reason for this difference is the different geographical location, underlying surface and climate conditions in different research areas, which will significantly affect the detection capability of remote sensing satellites [53][54][55].…”

Section: Overall Assessmentmentioning

confidence: 87%

“…In this study, six widely used statistical approaches were adopted to evaluate the TRMM 3B42V7 rainfall product against the rain gauge data. Correlation Coefficient (CC) measures the goodness of fit and linear association between satellite products and rain gauge data [23]. Root Mean Square Error (RMSE) is used to measure the average error magnitude, and is very sensitive to the outliers.…”

Section: Meteorological Stations Based Precipitation Datamentioning

confidence: 99%

“…Li et al demonstrated that TRMM satellite was inclined to underestimate the monthly rainfall in Xinjiang catchment, Poyang lake basin [22]. Yang et al evaluated the TRMM 3B42V7 rainfall product using gauge precipitation observations and then investigated its application in supporting reservoir operation and water resources management, considered that the 3B42V7 can capture well the spatial and temporal characteristics of precipitation and perform well in water allocation decision-making over the Hanjiang basin in China [23]. Different studies show that the applicability and accuracy of the satellite rainfall products in different regions are significantly differ for diverse inversion algorithm and underlying surface [19,[24][25][26].…”

Section: Introductionmentioning

confidence: 99%

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Validation of TRMM 3B42V7 Rainfall Product under Complex Topographic and Climatic Conditions over Hexi Region in the Northwest Arid Region of China

Wang

Ding

Zhao

et al. 2018

Water

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Continuous and accurate spatiotemporal precipitation data plays an important role in regional climate and hydrology research, particularly in the arid inland regions where rain gauges are sparse and unevenly distributed. The main objective of this study is to evaluate and bias-correct the Tropical Rainfall Measuring Mission (TRMM) 3B42V7 rainfall product under complex topographic and climatic conditions over the Hexi region in the northwest arid region of China with the reference of rain gauge observation data during 2009-2015. A series of statistical indicators were adopted to quantitatively evaluate the error of 3B42V7 and its ability in detecting precipitation events. Overall, the 3B42V7 overestimates the precipitation with Bias of 11.16%, and its performance generally becomes better with the increasing of time scale. The agreements between the rain gauge data and 3B42V7 are very low in cold season, and moderate in warm season. The 3B42V7 shows better correlation with rain gauges located in the southern mountainous and central oasis areas than in the northern extreme arid regions, and is more likely to underestimate the precipitation in high-altitude mountainous areas and overestimate the precipitation in low-elevation regions. The distribution of the error on the daily scale is more related to the elevation and rainfall than in monthly and annual scale. The 3B42V7 significantly overestimates the precipitation events, and the overestimation mainly focuses on tiny amounts of rainfall (0-1 mm/d), which is also the range of false alarm concentration. Bias correction for 3B42V7 was carried out based on the deviation of the average monthly precipitation data during 2009-2015. The bias-corrected 3B42V7 was significantly improved compared with the original product. Results suggest that regional assessment and bias correction of 3B42V7 rainfall product are of vital importance and will provide substantive reference for regional hydrological studies.

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“…From this description can be said that rainfall data is climatological data that is quite important. Accurate and timely observations and estimates of regional and global precipitation are crucial for various researches and applications [6].…”

Section: Introductionmentioning

confidence: 99%

Hydrological Analysis of TRMM (Tropical Rainfall Measuring Mission) Data in Lesti Sub Watershed

Suryaningtyas¹,

Suhartanto²,

Rispiningtati³

2020

Civense

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Alternative solution for availability of inadequate rain data as input to hydrological data is with the assist of Tropical Rainfall Measurement Mission (TRMM) satellite rainfall data which using remote sensing technology (satellite). The purpose of this study is to look for correlations and data corrections and validate TRMM satellite data with rainfall data at the rain station and discharge observation data. Lesti sub-watershed is used as a case study with consideration of the data availability that is considered sufficient. The validation results of corrected TRMM rain data produce Nash-Sutcliffe Efficiency (NSE), Root Mean Squared Error (RMSE), Correlation Coefficient (R), and Relative Error (KR). Then, conducted an analysis of the flow discharge estimation using TRMM rainfall data and validated with Tawangrejeni Automatic Water Level Record (AWLR) data. The results of flow discharge validation using the FJ Mock Method produce an NSE value of 0.507, RMSE 19.383, Correlation Coefficient (R) 0.713, and Relative Error of 0.001. Overall analysis shows TRMM data can be used as an alternative of the rain data that is used to estimate flow discharge, but the result of flow discharge analysis is still better using rainfall data from the rain station post.

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Evaluation of the TRMM multisatellite precipitation analysis and its applicability in supporting reservoir operation and water resources management in Hanjiang basin, China

Cited by 62 publications

References 28 publications

Evaluation of Satellite‐Derived Rainfall Data for Multiple Physio‐Climatic Regions in the Santiago River Basin, Mexico

Evaluation of Satellite‐Derived Rainfall Data for Multiple Physio‐Climatic Regions in the Santiago River Basin, Mexico

Validation of TRMM 3B42V7 Rainfall Product under Complex Topographic and Climatic Conditions over Hexi Region in the Northwest Arid Region of China

Hydrological Analysis of TRMM (Tropical Rainfall Measuring Mission) Data in Lesti Sub Watershed

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