Some characteristics of a daily rainfall regime based on the Dry Day Last Rain index (DDSLR)
| Autor: | Lana Pons, Francisco Javier, Burgueño, August, Martínez Santafé, Maria Dolors, Serra de Larrocha, Carina |
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| Přispěvatelé: | Universitat Politècnica de Catalunya. Departament de Física Aplicada, Universitat Politècnica de Catalunya. Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya. GIES - Geofísica i Enginyeria Sísmica |
| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: | |
| Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) Recercat. Dipósit de la Recerca de Catalunya instname |
| DOI: | 10.1007/s00704-011-0561-2 |
| Popis: | The Dry Day Since Last Rain index, DDSLR, quantifies for every recording day the number of consecutive preceding days with daily rainfall below a threshold. In essence, DDSLR may quantify the hydrologic stress generated by consecutive days of rainfall deficit taking into account some daily rainfall thresholds associated with the resolution of the pluviometer, evapotranspiration, runoff and thin layer saturation processes. A detailed analysis of DDSLR at daily and annual scales and for the whole recording period permits a complete description of the daily rainfall deficit regime and induced hydrologic stress. These characteristics have been derived for 0.1, 1.0, 5.0 and 10.0 mm/day thresholds for 93 years (1917–2009) of continuous daily rainfall records at the Fabra Observatory (Barcelona, NE Spain). Time trends on chronological series of DDSLR are determined and statistically tested for every calendar day. Fourier series analysis applied to four calendar day statistics (number of non-null DDSLR, average, standard deviation and maximum of DDSLR) leads to detection of the dominant periodicities, taking as fundamental periodicity the 365 days of the year. The best statistical model reproducing the empirical distribution of DDSLR, year by year, for every calendar day and for the whole recording period, is also investigated. Whatever the time scale considered, the Poisson-gamma model is assumed due to the non-negligible number of null DDSLR. Finally, time trends on extreme series of annual DDSLR, the appropriate statistical model for these series (the generalised logistic distribution, GLO), together with an estimation of DDSLR for several return periods, permit the description of the expected main future patterns of this index. In this way, current and next future hydrologic stress at the Fabra Observatory and neighbouring areas become characterised. |
| Databáze: | OpenAIRE |
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