Assessment and correction of three satellite rainfall estimate products for improving flood prevention in French Guiana

Beaufort, Aurélien; Gibier, Florian; Palany, Philippe
January 2019
International Journal of Remote Sensing;Jan2019, Vol. 40 Issue 1, p171
Academic Journal
The French Guiana (80 000 km2) is highly vulnerable to flooding during the rainy season but the hydrological prevision is limited because the region cannot be cover by a dense network of rain gauges. Meteorological satellites could be an alternative for the measurement of precipitation. The objective of this paper was to evaluate and improve the accuracy of daily satellite rainfall estimates (SRE) throughout the French Guiana between April 2015 and March 2016. Validation data were composed by 70 rain gauges managed by France and Suriname. Three satellite-based rainfall estimates have been tested: TRMM-TMPA 3B42 (Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis) V7, IMERG (Integrated Multi-satellitE Retrievals) for GPM (Global Precipitation Measurement) and STAR Satellite rainfall estimates Hydro-Estimator (HE). Better SRE were obtained by GPM with a clearly higher probability of detection of rainy days (>70%). During the rainy season, biases remained important and SRE appeared inaccurate for the monitoring and forecasting of floods. Biases correction methods were applied, and the additive correction methods by interpolation of biases (ADD_IDW) obtained the better performance (absolute biases <8 mm day−1; RMSE <12 mm day−1) for each satellite products. This simple method proved to be very effective to reduce biases close to 0 throughout the year. After ADD_IDW correction, performance levels of TRMM, GPM, and HE products were relatively close and these three satellite products could be implemented into cascade chains in operational framework ensuring the provision of corrected SRE in real time and thus guarantee a reinforced hydrological monitoring in French Guiana.


Related Articles

  • Statistical comparison of satellite-retrieved precipitation products with rain gauge observations over Bangladesh. Islam, Md. Atiqul // International Journal of Remote Sensing;May2018, Vol. 39 Issue 9, p2906 

    In this investigation, six satellite-derived precipitation products namely Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), Climate Prediction Centre (CPC) Morphing Technique (CMORPH), Integrated Multi-satellite Retrievals for Global...

  • Impact of sub-pixel rainfall variability on spaceborne precipitation estimation: evaluating the TRMM 2A25 product. Kirstetter, Pierre‐Emmanuel; Hong, Y.; Gourley, J. J.; Schwaller, M.; Petersen, W.; Cao, Qing // Quarterly Journal of the Royal Meteorological Society;Apr2015, Vol. 141 Issue 688 Part A, p953 

    Rain intensity spectra as seen by space sensors feed numerous applications at global scales ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. Rainfall variability at scales finer than what is resolved by current space sensors affects their...

  • The study of building-height inversion based on the shadow of high-resolution satellite images. Li Cong; Chen Zheng-chao; Cui Jia-jie; Wang Meng // Applied Mechanics & Materials;2014, Issue 556-562, p5107 

    With the rapid development of the remote-sensing technology, more and more high-resolution remote-sensing data that currently available for rapid-assessment of the earthquake, disaster investigation and the extraction of building information are arised. Researching on the building-height...

  • Assessing the impact of pre- GPM microwave precipitation observations in the Goddard WRF ensemble data assimilation system. Chambon, Philippe; Zhang, Sara Q.; Hou, Arthur Y.; Zupanski, Milija; Cheung, Samson // Quarterly Journal of the Royal Meteorological Society;Apr2014, Vol. 140 Issue 681, p1219 

    The forthcoming Global Precipitation Measurement ( GPM) Mission will provide next-generation precipitation observations from a constellation of satellites. Since precipitation by nature has large variability and low predictability at cloud-resolving scales, the impact of precipitation data on...

  • Downscaling CHIRPS precipitation data: an artificial neural network modelling approach. Retalis, Adrianos; Tymvios, Filippos; Katsanos, Dimitrios; Michaelides, Silas // International Journal of Remote Sensing;Jul2017, Vol. 38 Issue 13, p3943 

    The Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) is a high-resolution climatic database of precipitation embracing monthly precipitation climatology, quasi-global geostationary thermal infrared satellite observations from the Tropical Rainfall Measuring Mission (TRMM)...

  • On an Enhanced PERSIANN-CCS Algorithm for Precipitation Estimation. Mahrooghy, Majid; Anantharaj, Valentine G.; Younan, Nicolas H.; Aanstoos, James; Hsu, Kuo-Lin // Journal of Atmospheric & Oceanic Technology;Jul2012, Vol. 29 Issue 7, p922 

    By employing wavelet and selected features (WSF), median merging (MM), and selected curve-fitting (SCF) techniques, the Precipitation Estimation from Remotely Sensed Imagery using an Artificial Neural Networks Cloud Classification System (PERSIANN-CCS) has been improved. The PERSIANN-CCS...

  • Temporal and Spatial Assessment of Four Satellite Rainfall Estimates over French Guiana and North Brazil. Ringard, Justine; Linguet, Laurent; Becker, Melanie; Seyler, Frederique // Remote Sensing;Dec2015, Vol. 7 Issue 12, p16441 

    Satellite precipitation products are a means of estimating rainfall, particularly in areas that are sparsely equipped with rain gauges. The Guiana Shield is a region vulnerable to high water episodes. Flood risk is enhanced by the concentration of population living along the main rivers. A good...

  • Satellite images for extraction of flood disaster footprints and assessing the disaster impact: Brahmaputra floods of June–July 2012, Assam, India. Bhatt, C. M.; Srinivasa Rao, G.; Asiya Begum; Manjusree, P.; Sharma, S. V. S. P.; Prasanna, L.; Bhanumurthy, V. // Current Science (00113891);6/25/2013, Vol. 104 Issue 12, p1692 

    Satellite images provide information on the flood disaster footprints, which is essential for assessing the disaster impact and taking up flood mitigation activities. The Brahmaputra floods that occurred during June–July 2012 devastated a large part of Assam. This article discusses the...

  • Image Fusion-Based Change Detection for Flood Extent Extraction Using Bi-Temporal Very High-Resolution Satellite Images. Younggi Byun; Youkyung Han; Taebyeong Chae // Remote Sensing;Aug2015, Vol. 7 Issue 8, p10347 

    Change detection based on satellite images acquired from an area at different dates is of widespread interest, according to the increasing number of flood-related disasters. The images help to generate products that support emergency response and flood management at a global scale. In this...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics