Using SPEI in predicting water table dynamics in Argentinian plains
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ORIGINAL ARTICLE
Using SPEI in predicting water table dynamics in Argentinian plains Vanesa Y. Bohn1,2 · Raúl Rivas3,4 · Marcelo Varni4 · M. Cintia Piccolo1,5 Received: 25 October 2019 / Accepted: 14 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Response time of the water table (WT) to rainfall is a relevant parameter for optimal management of water resources in plains. This study explores the response time of WT to climatological variability. WT dynamics were analyzed for a period of 10 years in 7 stations located in the Argentinean Pampean Region: Laboulaye (LAB), Arias, General Pico (GP), Azul, Dolores (DOL), Junín and Barrow. Statistical standard methods were applied on WT data series provided by the National Meteorological Service (in Spanish, SMN) and La Pampa province government. Standardized Precipitation and Evapotranspiration Index (SPEI) was applied in multiple temporal scales. Modeled SPEI data were correlated to WT and water table depth (WTD; in situ data) using the Pearson method. Results indicated that WTD response time is spatially variable in the study region when considering the rainfall and evapotranspiration balance (represented by the temporal behavior of the SPEI). These results allowed for the definition of a second-degree–function theoretical method of WTD that explains its variations for different extreme conditions. Multivariate statistical analysis was used to analyze the similarities of WTD evolution among the 5 stations for the 1986–1990 period. Highest statistical connections were found between GP and LAB, GP and DOL and between DOL and LAB stations, which indicated similarities in their dynamic and the maximum (WTD ~ 3.3 m) and mean (WTD ~ 2 m) WTD values measured during the studied period. Surface water coverage data, obtained through digital processing of satellite images of high spatial resolution, validates the relations between climatological variables and WTD showing increases (km2) during the periods in which the WTD was lowest and vice versa. The method presented in this investigation allows the use of SPEI to the prediction of WTD in zones, where it is difficult to measure it. Keywords Response time · Rainfall-evapotranspiration · Pearson correlation · Clustering
Introduction
* Vanesa Y. Bohn [email protected] 1
Departamento de Geografía y Turismo (DGyT), Universidad Nacional del Sur (UNS), 12 de octubre 1098, 4to. piso, 8000 Bahía Blanca, Buenos Aires, Argentina
2
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bahía Blanca, Buenos Aires, Argentina
3
Comisión de Investigaciones Científicas (CIC), La Plata, Buenos Aires, Argentina
4
Instituto de Hidrología de Llanuras (IHLLA)-UNCPBA, Gral. Pinto N 399 (B7000GHG), Tandil, Buenos Aires, Argentina
5
Instituto Argentino de Oceanografía (IADO-CONICET), Bahía Blanca, Buenos Aires, Argentina
Droughts and floods are complex phenomena whose identification, monitoring, and analysis are difficult. In agricultural countries, the losses because
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