气候变化领域集成服务门户(CCPortal): Which rainfall score is more informative about the performance in river discharge simulation? A comprehensive assessment on 1318 basins over Europe

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DOI	10.5194/hess-24-4869-2020
	Which rainfall score is more informative about the performance in river discharge simulation? A comprehensive assessment on 1318 basins over Europe
	Camici S.; Massari C.; Ciabatta L.; Marchesini I.; Brocca L.
发表日期	2020
ISSN	1027-5606
起始页码	4869
结束页码	4885
卷号	24 期号:10
英文摘要	The global availability of satellite rainfall products (SRPs) at an increasingly high temporal and spatial resolution has made their exploitation in hydrological applications possible, especially in data-scarce regions. In this context, understanding how uncertainties transfer from SRPs to river discharge simulations, through the hydrological model, is a main research question. SRPs' accuracy is normally characterized by comparing them with ground observations via the calculation of categorical (e.g. threat score, false alarm ratio and probability of detection) and/or continuous (e.g. bias, root mean square error, Nash-Sutcliffe index, Kling-Gupta efficiency index and correlation coefficient) performance scores. However, whether these scores are informative about the associated performance in river discharge simulations (when the SRP is used as input to a hydrological model) is an under-discussed research topic. This study aims to relate the accuracy of different SRPs both in terms of rainfall and in terms of river discharge simulation. That is, the following research questions are addressed: Is there any performance score that can be used to select the best performing rainfall product for river discharge simulation? Are multiple scores needed? And, which are these scores? To answer these questions, three SRPs, namely the Tropical Rainfall Measurement Mission (TRRM) Multi-satellite Precipitation Analysis (TMPA), the Climate Prediction Center MORPHing (CMORPH) algorithm and the SM2RAIN algorithm applied to the Advanced SCATterometer (ASCAT) soil moisture product (SM2RAIN-ASCAT) have been used as input into a lumped hydrologic model, "Modello Idrologico Semi-Distribuito in continuo"(MISDc), for 1318 basins over Europe with different physiographic characteristics. Results suggest that, among the continuous scores, the correlation coefficient and Kling-Gupta efficiency index are not reliable indices to select the best performing rainfall product for hydrological modelling, whereas bias and root mean square error seem more appropriate. In particular, by constraining the relative bias to absolute values lower than 0.2 and the relative root mean square error to values lower than 2, good hydrological performances (Kling-Gupta efficiency index on river discharge greater than 0.5) are ensured for almost 75% of the basins fulfilling these criteria. Conversely, the categorical scores have not provided suitable information for addressing the SRP selection for hydrological modelling. © 2020 Author(s).
语种	英语
scopus关键词	Climate models; Efficiency; Errors; Hydrology; Mean square error; Meteorological instruments; Rain; Soil moisture; Climate prediction centers; Comprehensive assessment; Correlation coefficient; Lumped hydrologic modeling; Probability of detection; Root mean square errors; Satellite precipitation; Tropical rainfall measurement missions; Rivers; assessment method; hydrological modeling; performance assessment; rainfall; river basin; river discharge; TRMM; weather forecasting; Europe
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159285
作者单位	Camici, S., National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy; Massari, C., National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy; Ciabatta, L., National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy; Marchesini, I., National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy; Brocca, L., National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy
推荐引用方式 GB/T 7714	Camici S.,Massari C.,Ciabatta L.,et al. Which rainfall score is more informative about the performance in river discharge simulation? A comprehensive assessment on 1318 basins over Europe[J],2020,24(10).
APA	Camici S.,Massari C.,Ciabatta L.,Marchesini I.,&Brocca L..(2020).Which rainfall score is more informative about the performance in river discharge simulation? A comprehensive assessment on 1318 basins over Europe.Hydrology and Earth System Sciences,24(10).
MLA	Camici S.,et al."Which rainfall score is more informative about the performance in river discharge simulation? A comprehensive assessment on 1318 basins over Europe".Hydrology and Earth System Sciences 24.10(2020).