Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia)

Dandridge, Chelsea; Lakshmi, V.; Bolten, J. D.; Srinivasan, Raghavan

doi:10.3390/rs11222709

Cited by 31 publications

(16 citation statements)

References 38 publications

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“…The reasonably good results of CHIRPS are probably due to its higher spatial resolutions (in account to other data having a spatial resolution of 0.25°) and integrates more in-situ data with high-resolution climatology and multi-satellite products. It was observed higher resolution is generally directly proportional to accuracy but also relied on the method employed for the generation of products (Dandridge et al, 2019). Thus, this study confirms that CHIRPS products can be used for long-term drought events variability assessment with higher confidence.…”

Section: Discussionsupporting

confidence: 75%

Multi-satellite precipitation products for meteorological drought assessment and forecasting in Central India

Pandey

Srivastava

Mall

et al. 2020

Geocarto International

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Sparse ground observation networks with minimal maintenance limit spatio-temporal coverage of precipitation data in the Bundelkhand region of Uttar Pradesh state of India, which constraint the real-time drought assessment and monitoring. In this study, comparative analysis of three satellite precipitation products including Tropical Rainfall Measuring Mission (TRMM-3B43), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and Climate Hazards Group InfraRed Precipitation with Station (CHIRPS version-2) with ground-measured Indian Meteorological Department (IMD) precipitation data were performed to evaluate meteorological drought in Central India. Statistical comparison was performed for nineteen years (1998-2016) at the grid level (39 grids) to assess the performance and estimate the regional differences in the spatial distribution of satellite precipitation products as compared to IMD data. The high-resolution CHIRPS showed the closest 2 agreement with IMD precipitation and again it well captured the drought characteristics through the Standardized Precipitation Index (SPI). There are seven major droughts events were observed in the study area between the periods of 1981 to 2016. After proper calibration and validation of the datasets, the forecasting of drought using the Auto-Regressive Integrated Moving Average (ARIMA) model in the R programming environment was also established. The best model was selected based on the ARIMA and statistical analysis such as minimum Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Forecasting result showed a reasonably good agreement with the observed datasets. The outcomes of this study have policy level implications for drought monitoring and prior preparedness in response to projected drought conditions using satellite data in this region.

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Section: Discussionsupporting

confidence: 75%

Multi-satellite precipitation products for meteorological drought assessment and forecasting in Central India

Pandey

Srivastava

Mall

et al. 2020

Geocarto International

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“…Several studies have assessed the quality of the rainfall products of GPM missions when estimating global precipitation and the performance of precipitation nowcasting. At present, point measurements using a rain gauge and disdrometer [21,22], ground-based weather radar [23] and satellite-based sensors [24] are the most widely used techniques to measure and estimate precipitation. In most regions, tipping bucket rain gauges are frequently utilized to measure precipitation.…”

Section: Latest Developmentsmentioning

confidence: 99%

GPM Annual and Daily Precipitation Data for Real-Time Short-Term Nowcasting: A Pilot Study for a Way Forward in Data Assimilation

Wang

Kong

Yang

et al. 2021

Water

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This study explores the quality of data produced by Global Precipitation Measurement (GPM) and the potential of GPM for real-time short-term nowcasting using MATLAB and the Short-Term Ensemble Prediction System (STEPS). Precipitation data obtained by rain gauges during the period 2015 to 2017 were used in this comparative analysis. The results show that the quality of GPM precipitation has different degrees efficacies at the national scale, which were revealed at the performance analysis stage of the study. After data quality checking, five representative precipitation events were selected for nowcasting evaluation. The GPM estimated precipitation compared to a 30 min forecast using STEPS precipitation nowcast results, showing that the GPM precipitation data performed well in nowcasting between 0 to 120 min. However, the accuracy and quality of nowcasting precipitation significantly reduced with increased lead time. A major finding from the study is that the quality of precipitation data can be improved through blending processes such as kriging with external drift and the double-kernel smoothing method, which enhances the quality of nowcast over longer lead times.

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“…To enable real-time VIC modeling, the latest version of TRMM Multisatellite Precipitation Analysis (TMPA) real-time (RT) product (3B42RTv7) was utilized. Note that, although several satellite-based precipitation research products like CHIRPS [66] have been made available after controlling data quality against in situ rain-gauge measurements, these products are barely accessible in real time due to the long time lag (several days or months) used for quality control. In contrast, the TMPA-RT data can provide quasi-global (50 • S-50 • N), 0.25 • , 3-hourly near real-time precipitation measurements (only with 9-hour time lag) since March 2000 [29].…”

Section: Meteorological Forcingsmentioning

confidence: 99%

Satellite-Based Operational Real-Time Drought Monitoring in the Transboundary Lancang–Mekong River Basin

Zhang

et al. 2020

Remote Sensing

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Existing gauging networks are sparse and not readily available in real-time over the transboundary Lancang–Mekong River (LMR) basin, making it difficult to accurately identify drought. In this study, we aimed to build an operational real-time Lancang–Mekong drought monitor (LMDM), through combining satellite real-time data and the Variable Infiltration Capacity (VIC) hydrological model at a 0.25° spatial resolution. Toward this, three VIC runs were conducted: (1) a 60-year (1951–2010) historical simulation driven by Princeton’s global meteorological forcing (PGF) for yielding ‘normal’ conditions (PGF-VIC), wherein the VIC was calibrated with 20-year observed streamflow at six hydrological stations; (2) a short-period (2011–2014) simulation to bridge the gap between the historical and the real-time modeling; (3) the real-time (2015–present) simulation driven by bias-corrected satellite data, wherein the real-time soil moisture (SM) estimate was expressed as percentile (relative to the ‘normal’) for drought monitoring. Results show that VIC can successfully reproduce the observed hydrographs, with the Nash–Sutcliffe efficiency exceeding 0.70 and the relative bias mostly within 15%. Assessment on the performance of LMDM shows that the real-time SM estimates bear good spatial similarity to the reference, with the correlation coefficient beyond 0.80 across >70% of the domain. In terms of drought monitoring, the LMDM can reasonably reproduce the two recorded droughts, implying extreme droughts covering the Lower LMR during 2004/05 and widespread severe 2009/10 drought across the upper domain. The percentage drought area implied by the LMDM and the reference is close, corresponding to 66% and 60%, 43% and 40%, and 44% and 36% for each typical drought month. Since January 2015, the LMDM was running in an operational mode, from which the 2016 unprecedented drought was successfully identified in Mekong Delta. This study highlights the LMDM’s capability for reliable real-time drought monitoring, which can serve as a valuable drought early warning prototype for other data-poor regions.

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Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia)

Cited by 31 publications

References 38 publications

Multi-satellite precipitation products for meteorological drought assessment and forecasting in Central India

Multi-satellite precipitation products for meteorological drought assessment and forecasting in Central India

GPM Annual and Daily Precipitation Data for Real-Time Short-Term Nowcasting: A Pilot Study for a Way Forward in Data Assimilation

Satellite-Based Operational Real-Time Drought Monitoring in the Transboundary Lancang–Mekong River Basin

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