Spatial assessment of precipitation deficits in the Duero basin (central Spain) with multivariate extreme value statistics

Abstract

[1] Nonirrigated agriculture on the Iberian Peninsula is regularly affected by dry periods that can cause important losses. This paper focuses on the comparison of the classical Standard Precipitation Index (SPI) with a fragility index developed by the multivariate extreme value theory community, which is used to describe monthly precipitation deficits below 30.5 mm (about 1 mm/d) in the Spanish Duero basin. The multivariate extreme value model allows to capture relevant information concerning the dependence structure among extreme precipitation deficits. Maps of those extremal dependence summaries and of loadings of principal components of the SPI provide quantitative information for water management. In addition, jointly analyzing data from several stations improves the inference of uncertainty. Spatial patterns of extremal dependence emerged with respect to orographic features. Most severe dry spells occur in the southeast of the Duero basin. In central plain of the Duero basin, a predominantly agricultural area, a strong fragility index for severity of dry spells is particularly found in eastern regions. Results of the MEVT and SPI analysis point in the same direction. Beyond this, the MEVT assessment gives a quantitative measure of the dependence between stations and regions. Estimates of return periods for extreme dry spell severity are discussed. Deficits below 42.7 mm are also analyzed.Citation: Kallache, M., P. Naveau, and M. Vrac (2013), Spatial assessment of precipitation deficits in the Duero basin (central Spain) with multivariate extreme value statistics, Water Resour. Res., 49,[6716][6717][6718][6719][6720][6721][6722][6723][6724][6725][6726][6727][6728][6729][6730]

The evolution of climatic drought studies in Spain over the last few decades

“…Dry spell fractality and autoregressive methods have also been implemented to predict long dry spells (Lana et al, 2017), but are highly uncertain for Europe. Also, methods for the assessment of drought risk based on monthly precipitation data have been developed, with special focus on the spatial dependence on hazard probability (Kallache et al, 2013) and Bayesian approaches (Avilés et al, 2016).…”

Identifying the Drought Impact Factors and Developing Drought Scenarios Using the DSD Model

“…To manage water resources e ciently with a policy to reduce drought damage, it is necessary to analyze the drought in administrative divisions. Many studies have been conducted on the drought analysis of several watersheds (Maity et al, 2013; Kallache et al, 2013;Malik et al,2019), but drought studies focusing on administrative divisions are insu cient.…”

“…Many drought indices have been proposed and applied, including the SPI (Mckee et al, 1993) and the Palmer Drought Severity Index (PDSI; Palmer., 1965). SPI is based on precipitation and has been utilized in many studies due to its simplicity (Kallache et al, 2013;Tsakiris & Vangelis., 2004;Livada & Assimakopoulos., 2007;Guttman., 1998). The PDSI describes the moisture conditions and is widely used to measure the cumulative water balance.…”

“…Using the proposed method, the analysis focused on determining the trends and characteristics of drought due to space-time patterns. Kallache et al (2013) analyzed dry spells and spatial patterns using a multivariate extreme value model. The results indicated that the dry spells in subbasin are in uenced by the topography and spatial distance from other subbassins.…”