Using stochastic space-time models to map extreme precipitation in southern Portugal

被引:20
作者
Costa, A. C. [1 ]
Durao, R. [2 ]
Pereira, M. J. [2 ]
Soares, A. [2 ]
机构
[1] Univ Nova Lisboa, ISEGI, P-1200 Lisbon, Portugal
[2] Inst Super Tecn, CERENA, Lisbon, Portugal
关键词
D O I
10.5194/nhess-8-763-2008
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The topographic characteristics and spatial climatic diversity are significant in the South of continental Portugal where the rainfall regime is typically Mediterranean. Direct sequential cosimulation is proposed for mapping an extreme precipitation index in southern Portugal using elevation as auxiliary information. The analysed index (R5D) can be considered a flood indicator because it provides a measure of medium-term precipitation total. The methodology accounts for local data variability and incorporates space-time models that allow capturing long-term trends of extreme precipitation, and local changes in the relationship between elevation and extreme precipitation through time. Annual gridded datasets of the flood indicator are produced from 1940 to 1999 on 800 m x 800 m grids by using the space-time relationship between elevation and the index. Uncertainty evaluations of the proposed scenarios are also produced for each year. The results indicate that the relationship between elevation and extreme precipitation varies locally and has decreased through time over the study region. In wetter years the flood indicator exhibits the highest values in mountainous regions of the South, while in drier years the spatial pattern of extreme precipitation has much less variability over the study region. The uncertainty of extreme precipitation estimates also varies in time and space, and in earlier decades is strongly dependent on the density of the monitoring stations network. The produced maps will be useful in regional and local studies related to climate change, desertification, land and water resources management, hydrological modelling, and flood mitigation planning.
引用
收藏
页码:763 / 773
页数:11
相关论文
共 53 条
[1]  
BOER EPJ, 2001, INT J APPL EARTH OBS, V3, P146, DOI DOI 10.1016/S0303-2434(01)85006-6
[2]   Uncertainty assessment of soil water content spatial patterns using geostatistical simulations: An empirical comparison of a simulation accounting for single attribute and a simulation accounting for secondary information [J].
Bourennane, H. ;
King, D. ;
Couturier, A. ;
Nicoullaud, B. ;
Mary, B. ;
Richard, G. .
ECOLOGICAL MODELLING, 2007, 205 (3-4) :323-335
[3]   Spatial variations in the average rainfall-altitude relationship in Great Britain: An approach using geographically weighted regression [J].
Brunsdon, C ;
McClatchey, J ;
Unwin, DJ .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2001, 21 (04) :455-466
[4]  
Corte-Real J, 1998, INT J CLIMATOL, V18, P619, DOI [10.1002/(SICI)1097-0088(199805)18:6<619::AID-JOC271>3.0.CO
[5]  
2-T, 10.1002/(SICI)1097-0088(199805)18:6&lt
[6]  
619::AID-JOC271&gt
[7]  
3.0.CO
[8]  
2-T]
[9]  
Costa ACM, 2008, QUANT GEO G, V15, P275
[10]  
COSTA AC, 2006, 7 INT S SPAT ACC ASS, P419