River flow prediction in data scarce regions: soil moisture integrated satellite rainfall products outperform rain gauge observations in West Africa
Luca BroccaChristian MassariThierry PellarinPaolo FilippucciLuca CiabattaStefania CamiciYann H. KerrDiego Fernández-Prieto
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Abstract Satellite precipitation products have been largely improved in the recent years particularly with the launch of the global precipitation measurement (GPM) core satellite. Moreover, the development of techniques for exploiting the information provided by satellite soil moisture to complement/enhance precipitation products have improved the accuracy of accumulated rainfall estimates over land. Such satellite enhanced precipitation products, available with a short latency (< 1 day), represent an important and new source of information for river flow prediction and water resources management, particularly in developing countries in which ground observations are scarcely available and the access to such data is not always ensured. In this study, three recently developed rainfall products obtained from the integration of GPM rainfall and satellite soil moisture products have been used; namely GPM+SM2RAIN, PRISM-SMOS, and PRISM-SMAP. The prediction of observed daily river discharge at 10 basins located in Europe (4), West Africa (3) and South Africa (3) is carried out. For comparison, we have also considered three rainfall products based on: (1) GPM only, i.e., the Early Run version of the Integrated Multi-Satellite Retrievals for GPM (GPM-ER), (2) rain gauges, i.e., the Global Precipitation Climatology Centre, and (3) the latest European Centre for Medium-Range Weather Forecasts reanalysis, ERA5. Three different conceptual and lumped rainfall-runoff models are employed to obtain robust and reliable results over the 3-year data period 2015–2017. Results indicate that, particularly over scarcely gauged areas (West Africa), the integrated products outperform both ground- and reanalysis-based rainfall estimates. For all basins, the GPM+SM2RAIN product is performing the best among the short latency products with mean Kling–Gupta Efficiency (KGE) equal to 0.87, and significantly better than GPM-ER (mean KGE = 0.77). The integrated products are found to reproduce particularly well the high flows. These results highlight the strong need to disseminate such integrated satellite rainfall products for hydrological (and agricultural) applications in poorly gauged areas such as Africa and South America.Runoff pollution have become a serious issue in terms of water pollution in porous areas, especially in urban backfilled soil. The transport and distribution of runoff water and nutrients in the surface runoff and the subsurface runoff of backfilled soil runoff systems are determined using simulated rainfall and the results indicate that the flow patterns of runoff are different from those of surface runoff and subsurface runoff. The rate of surface runoff flow increases in the beginning and reaches a stable state with a delay of 10 min to rainfall, while the flow rate of subsurface runoff is consistent during the whole runoff period. Most of the pollutants (90% of total suspended solids, 88% of total phosphorus, and 78% of total nitrogen) are carried in the surface runoff, which directly results in polluting the surface‐receiving water. The results of the present study will provide information related to the management of runoff pollution in the backfilled soil runoff system.
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ABSTRACT It is known that the El Niño – Southern Oscillation ( ENSO ) episodes have a great influence on South American precipitation and its extreme events during austral autumn (from March until May, MAM ) and winter (from June until August, JJA ) that occur after the ENSO peak (normally this happens on austral summer). Recent papers have studied the two types of ENSO and their influence on atmosphere–ocean system. This study analysed the influence of Central and East equatorial Pacific ENSO on South American seasonal/monthly mean precipitation and its extreme events during MAM and JJA . The composites of precipitation anomalies, during these two types of ENSO , show that there are different, even opposite patterns over South America. In MAM , there is an increased precipitation in southeastern South America and a decrease in the northeast South America during East El Niño ( EEN ) and an increased precipitation in central Brazil during Central El Niño ( CEN ). In JJA , the signs of anomaly precipitation are opposite between CEN (less precipitation) and EEN (more precipitation) over southeastern South America. The extreme precipitation events show patterns consistent with the precipitation anomaly patterns, but, normally, the changes in the frequency of extremes precipitation events affect more extensive areas than the total precipitation. If monthly or seasonal atmospheric anomalies in a certain region during one of the types of ENSO are similar (opposite) to the atmospheric anomalies associated with extreme precipitation events in this region, then there is enhancement (suppression) of the frequency of extreme events in this region during this type of ENSO .
Anomaly (physics)
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Wet season
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Satellite based precipitation product (GSMaP-MVK) can be reliably used to estimate the Areal Mean Precipitation error based on “Sample Design method” (Esdd) with the effort to mitigate the problem of sparse data, especially severe in poorly gauged river basins. In addition, the satellite-gauge merging precipitation would reduce significantly the magnitude gaps between the satellite rainfall estimations and the rain gauge data. In this study, the capability of satellite-gauge merging precipitation using GSMaP-MVK and local dense rain gauge data with bias reduction approach to evaluate the AMP is investigated. The main finding is that satellite-gauge blending data which incorporates a dense rain gauge measurements shows the better capability to evaluate AMP using Esdd index than the original satellite only precipitation estimations. However, Esdd quantification performances of satellite-gauge blending precipitation are inferior to the original satellite only precipitation product GSMaP-MVK when the number of blended rain gauges is not large enough.
Keywords: areal mean precipitation; remote sensed precipitation product; satellite-gauge merging; rainfall runoff simulations.
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A radar quantitative precipitation estimation group system is described in this paper which is established based on rain gauge adjustment techniques and is aimed to apply to meteorological operations.It provides hourly precipitation field in 10 minute interval and 1 km×1 km spacial resolution.Evaluation results by use of the data in the past three years show that the more the adjustment rain gauges,the higher the estimated precipitation accuracy. The relative error of hourly estimation during the year 2003 is about 40%,and even lower than 20%for the total precipitation in a precipitation event.The longer and larger the rain event lasts and covers,the higher the accuracy as well if the density of rain gauge station keeps fixed.
Quantitative precipitation estimation
Quantitative precipitation forecast
Weather radar
Precipitation types
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