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Using SPEI in predicting water table dynamics in Argentinian plains

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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.

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Acknowledgements

Authors want to thank to Administración del Agua de la provincia de La Pampa (La Pampa province goverment), Servicio Meteorológico Nacional (in Spanish, SMN), Instituto de Hidrología de Llanuras (in Spanish, IHLLA), Secretaría de Infraestructura y Política Hídrica de la Nación ( SIPHN), Instituto Geográfico Nacional de la República Argentina (in Spanish, IGN), Instituto Nacional de Tecnología Agropecuaria (INTA) and the United States Geological Survey (USGS) for the data provided. In addition, the author’s thanks to the institutions of Consejo Nacional de Investigaciones Científicas y Técnicas (in Spanish, CONICET), Universidad Nacional del Sur (in Spanish, UNS) (Grant no. 24/G084) and Comisión de Investigaciones Científicas de la provincia de Buenos Aires (in Spanish, CIC). Special thanks to Lic. Christian Mancino (IHLLA) for the advice provided in the elaboration of the lithological profile. This research is carried out within the framework of research projects “Integrated study of Pampean shallow lakes” and “Hydrological vulnerability and environmental problems in hydrographic basins of plains (Argentina)”, both supported by UNS.

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Authors and Affiliations

  1. Departamento de Geografía y Turismo (DGyT), Universidad Nacional del Sur (UNS), 12 de octubre 1098, 4to. piso, 8000, Bahía Blanca, Buenos Aires, Argentina

    Vanesa Y. Bohn & M. Cintia Piccolo

  2. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bahía Blanca, Buenos Aires, Argentina

    Vanesa Y. Bohn

  3. Comisión de Investigaciones Científicas (CIC), La Plata, Buenos Aires, Argentina

    Raúl Rivas

  4. Instituto de Hidrología de Llanuras (IHLLA)-UNCPBA, Gral. Pinto N 399 (B7000GHG), Tandil, Buenos Aires, Argentina

    Raúl Rivas & Marcelo Varni

  5. Instituto Argentino de Oceanografía (IADO-CONICET), Bahía Blanca, Buenos Aires, Argentina

    M. Cintia Piccolo

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  1. Vanesa Y. Bohn
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  2. Raúl Rivas
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  4. M. Cintia Piccolo
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Correspondence to Vanesa Y. Bohn.

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Bohn, V.Y., Rivas, R., Varni, M. et al. Using SPEI in predicting water table dynamics in Argentinian plains. Environ Earth Sci 79, 469 (2020). https://doi.org/10.1007/s12665-020-09210-0

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