Satellite-based Flood Modeling Using TRMM-based Rainfall Products

Harris, A.; Rahman, S. H.; Hossain, Faisal; Yarborough, Lance; Bagtzoglou, Amvrossios C.; Easson, Greg

doi:10.3390/s7123416

Cited by 86 publications

(62 citation statements)

References 26 publications

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“…For the GSMaP products, which are available in near real time (about 4 hours after observation) via the Internet (Kachi et al 2011), analysis data such as the JMA global analysis or forecasting data should be used instead of the reanalysis data used here. Despite these remaining issues, this study shows a remarkable advance in high-resolution satellite rainfall products and in the possibility of their application to flood and landslide analysis/prediction because signals of heavy rainfall are vital for these applications (Harris et al 2007;Hong et al 2007). The revised GSMaP algorithm succeeds in detecting heavy orographic rainfall continuously in the sense of time and space.…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, Chen et al (2013) showed that the TMPA 3B42, which is adjusted by gauged measurements, presented less heavy rainfall than the TMPA 3B42RT, probably because of the process of rescaling the TMPA 3B42RT to the monthly rain gauge data. As signals of heavy rainfall are indispensable for flood and landslide analysis/prediction applications (Harris et al 2007;Hong et al 2007), it is a remarkable advance for these applications that the revised GSMaP algorithm succeeds in detecting heavy orographic rainfall continuously in the sense of time and space, while the present algorithms fail. The results indicate that the revised GSMaP algorithm is quite effective for the Taiwan case if the horizontal length scale for averaging the elevation data is appropriate for calculating w oro and if the thresholds in Eq.…”

Section: Fig 5 Correlation Coefficients Between Pr 2a25 Near-surfacmentioning

confidence: 99%

See 1 more Smart Citation

Improvement of High-Resolution Satellite Rainfall Product for Typhoon Morakot (2009) over Taiwan

Taniguchi

Shige

Yamamoto

et al. 2013

Journal of Hydrometeorology

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The authors improve the high-resolution Global Satellite Mapping of Precipitation (GSMaP) product for Typhoon Morakot (2009) over Taiwan by using an orographic/nonorographic rainfall classification scheme. For the estimation of the orographically forced upward motion used in the orographic/nonorographic rainfall classification scheme, the optimal horizontal length scale for averaging the elevation data is examined and found to be about 50 km. It is inferred that as the air ascends en masse on the horizontal scale, it becomes unstable and convection develops. The orographic/nonorographic rainfall classification scheme is extended to the GSMaP algorithm for all passive microwave radiometers in orbit, including not just microwave imagers but also microwave sounders. The retrieved rainfall rates, together with infrared images, are used for the highresolution rainfall products, which leads to much better agreement with rain gauge observations.

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Section: Discussionmentioning

confidence: 99%

Section: Fig 5 Correlation Coefficients Between Pr 2a25 Near-surfacmentioning

confidence: 99%

Improvement of High-Resolution Satellite Rainfall Product for Typhoon Morakot (2009) over Taiwan

Taniguchi

Shige

Yamamoto

et al. 2013

Journal of Hydrometeorology

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show abstract

“…For the detailed methodology of the ModClark, readers can see references [55][56][57]. Also, many previous studies have used the ModClark for various hydrologic applications [58][59][60][61][62][63][64]. In most of the studies cited above, the CN method was used with the ModClark approach.…”

Section: Application Instancementioning

confidence: 99%

Derivation of Soil Moisture Recovery Relation Using Soil Conservation Service (SCS) Curve Number Method

Kim

Johnson

Cifelli

et al. 2018

Water

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Soil moisture retention (SMR) capacity plays a key role in estimating the direct runoff when a multi-pulse storm event occurs. It is very important to know how much SMR will be recovered during the intervals of no rain of a multi-pulse storm. This study developed a new approach for derivation of the SMR recovery curve (R-curve) at sub-daily time-scales using the Curve Number (CN) method. The methodology was applied using complex storm events in the Napa River basin, California. The R-curve is classified into three sections depending on the recovery rate of SMR during the inter-storm interval of no rain (INR), and this study defines the characteristics. The first section of the R-curve (INR 0-21 h with 0.97 mm/h) is described as gradually recovering SMR, since water is being infiltrated and the upper soil layer is not fully saturated. The second section (INR 21-36 h with 2.11 mm/h) is defined as steeply recovering S due to downward drainage (sub-surface/inter flows) and evaporation without infiltration. The third section (INR 36-68 h with 0.34 mm/h) is described as gradually decreasing recovery dependent on evaporation since percolation and drainage have almost stopped.

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“…One such satellite rainfall product, the National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) has been used extensively and provides quasi global (50 o S-50 o N) precipitation analyses at 3-hourly, 0.25 o latitudelongitude resolution, with all satellite estimates calibrated or adjusted to the information from the TRMM satellite itself, which carries both a radar and passive microwave sensor [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…It was reported that 69 villages in 13 sub-districts in Rokan Hulu regency was inundated by the flood, 18 people were killed, 17,816 houses were damaged, and 53,725 people were evacuated [13]. (1) to (5). In the process of river routing, the Kinematic Wave Model is employed.…”

Section: Introductionmentioning

confidence: 99%

Hydrologic modelling using TRMM-based rainfall products for flood analysis

et al. 2017

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Abstract. The low resolution and the limitation of data are the main problems for flood analysis, so that the flood prediction often becomes inaccurate. This led to the decision policy for flood disaster mitigation often becomes ineffective. Currently the available of satellite-estimated rainfall data is gradually becoming a cost-effective source of input for flood prediction under a variety of circumstances. This study developed a hydrologic modelling using Tropical Rainfall Measuring Mission (TRMM) satellites data and IFAS (Integrated Flood Analysis System) tool for flood analysis. Upper Rokan watershed with the AWLR (Automatic Water Level Recorder) station of Lubuk Bendahara and Pasir Pangaraian in Riau Province were picked up as study area of this research. The study areas are located in Rokan Hulu regency which is the most vulnerable regency against flood disaster in Riau Province. The results show that the hydrologic modelling using satellite data can be used as an alternative for flood analysis in the area with limited ground data. The flood discharge prediction shows an acceptable error with the ground measurement data. The wave shape error, the volume error, and the peak discharge error for Lubuk Bendahara station are 9.58%, 17.28%, and 10.81%, and for Pasir Pangaraian station are 33.62%, 8.60% and 5.88% respectively.

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Satellite-based Flood Modeling Using TRMM-based Rainfall Products

Cited by 86 publications

References 26 publications

Improvement of High-Resolution Satellite Rainfall Product for Typhoon Morakot (2009) over Taiwan

Improvement of High-Resolution Satellite Rainfall Product for Typhoon Morakot (2009) over Taiwan

Derivation of Soil Moisture Recovery Relation Using Soil Conservation Service (SCS) Curve Number Method

Hydrologic modelling using TRMM-based rainfall products for flood analysis

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