Assessment of groundwater recharge along the Guarani aquifer system outcrop zone in São Paulo State (Brazil): an important tool towards integrated management

Abstract

The quantification of the groundwater recharges represents useful and important information for water resource management. The volumes of infiltrated water are essential to maintain water storage in aquifers, as well as to the discharge of groundwater towards the rivers, especially in tropical areas. The outcrop zones of the Guarani Aquifer System (GAS) in São Paulo state (Brazil) are considered as their most important recharge areas; therefore, knowledge about recharge rates and processes is essential. They are also highly vulnerable to groundwater contamination, another important reason to protect them. This study aimed to estimate spatial and temporal variations of groundwater recharge in the mentioned GAS outcrop zones. Recharge rates were estimated using the Spatial Recharge (SR) method and then compared to other two traditional methods (base flow separation and water table fluctuation method). The SR method uses the spatial distribution of the evapotranspiration and rainfall from GLDAS and TRMM databases and the runoff after the Soil Conservation Service (SCS) empirical method. All three methods revealed similar estimates for groundwater recharge, ranging from 150 to 370 mm year−1 (about 17% of the total rainfall). Despite its intrinsic limitations, the SR method allowed robust recharge estimation with ability to cope with spatial and temporal variations, as well, especially in areas lacking hydrological monitoring programs. The SR method provides valuable information for water management policymakers and stakeholders to minimize impacts related to climatic variations and inappropriate land use on recharge processes.

This is a preview of subscription content, access via your institution.

Fig. 1

modified from Kirchheim et al. 2019)

Fig. 2

modified from DAEE-UNESP 1980): Upper Jacaré-Pepira (JP), Boa Esperança (BE), and Peixe (PX), and rivers and rain gauging stations, and monitoring wells

Fig. 3

modified from São Paulo (2010) and Digital Elevation Models (DEM) from Shuttle Radar Topography Mission (SRTM) showing reservoirs and river network

Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

References

  1. Albuquerque Filho JL (2011) Sistema Aquífero Guarani: Subsídios ao Plano de Desenvolvimento e Proteção Ambiental da Área de Afloramento do Sistema Aquífero Guarani no Estado de São Paulo. São Paulo/SP

  2. Anache JAA, Wendland E, Rosalem LMP et al (2019) Hydrological trade-offs due to different land covers and land uses in the Brazilian Cerrado. Hydrol Earth Syst Sci 23:1263–1279. https://doi.org/10.5194/hess-23-1263-2019

    Article  Google Scholar 

  3. Araújo LM, França AB, Potter PE (1999) Hydrogeology of the Mercosul aquifer system in the Paraná and Chaco-Paraná Basins, South America, and comparison with the Navajo-Nugget aquifer system, USA. Hydrogeol J 7:317–336. https://doi.org/10.1007/s100400050205

    Article  Google Scholar 

  4. Baalousha HM, Barth N, Ramasomanana FH, Ahzi S (2018) Groundwater recharge estimation and its spatial distribution in arid regions using GIS: a case study from Qatar karst aquifer. Model Earth Syst Environ. https://doi.org/10.1007/s40808-018-0503-4

    Article  Google Scholar 

  5. Bastola S, Murphy C, Sweeney J (2011) The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments. Adv Water Resour 34:562–576. https://doi.org/10.1016/j.advwatres.2011.01.008

    Article  Google Scholar 

  6. Batista LV, Gastmans D, Sánchez-Murillo R et al (2018) Groundwater and surface water connectivity within the recharge area of Guarani aquifer system during El Niño 2014–2016. Hydrol Process 32:2483–2495. https://doi.org/10.1002/hyp.13211

    Article  Google Scholar 

  7. Beaudoing H, Rodell M (2016) GLDAS Noah Land Surface Model L4 Monthly 0.25 x 0.25 degree V2.1. Nasa/Gsfc/Hsl 92:607–615. https://doi.org/10.5067/SXAVCZFAQLNO

    Article  Google Scholar 

  8. Biswal B, Kumar DN (2014) Study of dynamic behaviour of recession curves. Hydrol Process 28:784–792. https://doi.org/10.1002/hyp.9604

    Article  Google Scholar 

  9. Bloomfield JP, Allen DJ, Griffiths KJ (2009) Examining geological controls on baseflow index (BFI) using regression analysis: an illustration from the Thames Basin, UK. J Hydrol 373:164–176. https://doi.org/10.1016/j.jhydrol.2009.04.025

    Article  Google Scholar 

  10. Brutsaert W (2008) Long-term groundwater storage trends estimated from streamflow records: climatic perspective. Water Resour Res 44:1–7. https://doi.org/10.1029/2007WR006518

    Article  Google Scholar 

  11. Brutsaert W, Nieber JL (1977) Regionalized drought flow hydrographs from a mature glaciated plateau. Water Resour Res 13:637–643. https://doi.org/10.1029/WR013i003p00637

    Article  Google Scholar 

  12. Brutsaert W, Sugita M (2008) Is Mongolia’s groundwater increasing or decreasing? The case of the Kherlen River basin / Les eaux souterraines de Mongolie s’accroissent ou décroissent-elles? Cas du bassin versant la Rivière Kherlen. Hydrol Sci J 53:1221–1229. https://doi.org/10.1623/hysj.53.6.1221

    Article  Google Scholar 

  13. Caetano-Chang MR (1997) A Formação Pirambóia no centro-leste do estado de São Paulo. Habilitation Thesis, Instituto de Geociências e Ciências Exatas – Rio Claro, Universidade Estadual Paulista (UNESP), Rio Claro

  14. Cambraia Neto AJ, Rodrigues LN (2020) Evaluation of groundwater recharge estimation methods in a watershed in the Brazilian Savannah. Environ Earth Sci 79:1–14. https://doi.org/10.1007/s12665-020-8884-x

    Article  Google Scholar 

  15. Chiew FHS, McMahon TA (2010) Global ENSO-streamflow teleconnection, streamflow forecasting and interannual variability. Hydrol Sci J 47:505–522. https://doi.org/10.1080/02626660209492950

    Article  Google Scholar 

  16. Coelho CAS, Cardoso DHF, Firpo MAF (2016a) Precipitation diagnostics of an exceptionally dry event in São Paulo, Brazil. Theor Appl Climatol 125:769–784. https://doi.org/10.1007/s00704-015-1540-9

    Article  Google Scholar 

  17. Coelho CAS, de Oliveira CP, Ambrizzi T et al (2016b) The 2014 southeast Brazil austral summer drought: regional scale mechanisms and teleconnections. Clim Dyn 46:3737–3752. https://doi.org/10.1007/s00382-015-2800-1

    Article  Google Scholar 

  18. Collischonn W, Fan FM (2013) Defining parameters for Eckhardt’s digital baseflow filter. Hydrol Process 27:2614–2622. https://doi.org/10.1002/hyp.9391

    Article  Google Scholar 

  19. Cronshey R, McCuen R, Miller N, et al (1986) Urban hydrology for small watersheds. Washingtin, D.C.

  20. Crosbie RS, Binning P, Kalma JD (2005) A time series approach to inferring groundwater recharge using the water table fluctuation method. Water Resour Res. https://doi.org/10.1029/2004WR003077

    Article  Google Scholar 

  21. Crosbie RS, Scanlon BR, Mpelasoka FS et al (2013) Potential climate change effects on groundwater recharge in the High Plains Aquifer, USA. Water Resour Res 49:3936–3951. https://doi.org/10.1002/wrcr.20292

    Article  Google Scholar 

  22. Crosbie RS, Davies P, Harrington N, Lamontagne S (2015) Ground truthing groundwater-recharge estimates derived from remotely sensed evapotranspiration: a case in South Australia. Hydrogeol J 23:335–350. https://doi.org/10.1007/s10040-014-1200-7

    Article  Google Scholar 

  23. Cunha APMA, Zeri M, Leal KD et al (2019) Extreme drought events over Brazil from 2011 to 2019. Atmosphere (Basel). https://doi.org/10.3390/atmos10110642

    Article  Google Scholar 

  24. DAEE (2020) Banco de Dados Hidrológicos. http://www.hidrologia.daee.sp.gov.br/

  25. DAEE, UNESP (1980) Mapa Geológico do Estado de São Paulo (1:250.000)

  26. de Melo DCD, Wendland E (2017) Shallow aquifer response to climate change scenarios in a small catchment in the guarani aquifer outcrop zone. An Acad Bras Cienc 89:391–406. https://doi.org/10.1590/0001-3765201720160264

    Article  Google Scholar 

  27. de Melo DCD, Wendland E, Guanabara RC (2015) Estimativa de recarga subterrânea por meio de balanço hídrico na zona não saturada do solo. Rev Bras Cienc do Solo 39:1335–1343. https://doi.org/10.1590/01000683rbcs20140740

    Article  Google Scholar 

  28. Doble RC, Crosbie RS (2017) Review: current and emerging methods for catchment-scale modelling of recharge and evapotranspiration from shallow groundwater. Hydrogeol J 25:3–23. https://doi.org/10.1007/s10040-016-1470-3

    Article  Google Scholar 

  29. Eckhardt K (2005) How to construct recursive digital filters for baseflow separation. Hydrol Process 19:507–515. https://doi.org/10.1002/hyp.5675

    Article  Google Scholar 

  30. El Garouani A, Aharik K, El Garouani S (2020) Water balance assessment using remote sensing, Wet-Spass model, CN-SCS, and GIS for water resources management in Saïss Plain (Morocco). Arab J Geosci. https://doi.org/10.1007/s12517-020-05730-y

    Article  Google Scholar 

  31. Famiglietti JS (2014) The global groundwater crisis. Nat Clim Chang 4:945–948

    Article  Google Scholar 

  32. Ficklin DL, Luedeling E, Zhang M (2010) Sensitivity of groundwater recharge under irrigated agriculture to changes in climate, CO 2 concentrations and canopy structure. Agric Water Manag 97:1039–1050. https://doi.org/10.1016/j.agwat.2010.02.009

    Article  Google Scholar 

  33. Gastmans D, Chang HK, Hutcheon I (2010) Groundwater geochemical evolution in the northern portion of the Guarani Aquifer System (Brazil) and its relationship to diagenetic features. Appl Geochem 25:16–33. https://doi.org/10.1016/j.apgeochem.2009.09.024

    Article  Google Scholar 

  34. Gastmans D, Veroslavsky G, Kiang CH et al (2012) Hydrogeological conceptual model for Guarani Aquifer System: a tool for management [Modelo hidrogeológico conceptual del Sistema Acuífero Guaraní (SAG): Una herramienta para la gestión]. Bol Geol y Min 123:249–265

    Google Scholar 

  35. Gastmans D, Mira A, Kirchheim R et al (2017) Hypothesis of groundwater flow through geological structures in Guarani Aquifer System (GAS) using chemical and isotopic data. Procedia Earth Planet Sci 17:136–139

    Article  Google Scholar 

  36. Gebremichael M, Hossain F (2010) Satellite rainfall applications for surface hydrology. Springer, Netherlands, Dordrecht

    Google Scholar 

  37. Gemitzi A, Ajami H, Richnow HH (2017) Developing empirical monthly groundwater recharge equations based on modeling and remote sensing data—modeling future groundwater recharge to predict potential climate change impacts. J Hydrol 546:1–13. https://doi.org/10.1016/j.jhydrol.2017.01.005

    Article  Google Scholar 

  38. GESDISC (2016) TRMM (TMPA) Precipitation L3 1 day 0.25 degree x 0.25 degree V7

  39. Gómez D, Melo DCD, Rodrigues DBB et al (2018) Aquifer responses to rainfall through spectral and correlation analysis. JAWRA J Am Water Resour Assoc. https://doi.org/10.1111/1752-1688.12696

    Article  Google Scholar 

  40. Green TR, Taniguchi M, Kooi H et al (2011) Beneath the surface of global change: Impacts of climate change on groundwater. J Hydrol 405:532–560

    Article  Google Scholar 

  41. Hanson RT, Koczot KM, Martin P (2003) Simulation of ground-water/surface-water flow in the Santa Clara—Calleguas ground-water basin. Ventura County, California

    Google Scholar 

  42. Healy RW (2010) Estimating groundwater recharge. Cambridge University Press, Cambridge

    Google Scholar 

  43. Healy RW, Cook PG (2002) Using groundwater levels to estimate recharge. Hydrogeol J 10:91–109. https://doi.org/10.1007/s10040-001-0178-0

    Article  Google Scholar 

  44. Hirata R, Conicelli BP, Pinhatti A et al (2015) O sistema Aquífero Guarani e a crise hídrica nas regiões de campinas e são paulo (sp). Rev USP 1:59–70

    Article  Google Scholar 

  45. Hirata R, Kirchheim RE, Manganelli A (2020) Diplomatic advances and setbacks of the guarani aquifer system in South America. Environ Sci Policy 114:384–393. https://doi.org/10.1016/j.envsci.2020.07.020

    Article  Google Scholar 

  46. Huffman GJ, Adler RF, Bolvin DT, Nelkin EJ (2010) The TRMM multi-satellite precipitation analysis (TMPA). Satellite rainfall applications for surface hydrology. Springer, Netherlands, pp 3–22

    Google Scholar 

  47. Huffman GJ, Stocker EF, Bolvin DT, et al (2019) GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V06, , Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC)

  48. Jan CD, Chen TH, Lo WC (2007) Effect of rainfall intensity and distribution on groundwater level fluctuations. J Hydrol 332:348–360. https://doi.org/10.1016/j.jhydrol.2006.07.010

    Article  Google Scholar 

  49. Jeong J, Park E, Han WS et al (2018) A generalized groundwater fluctuation model based on precipitation for estimating water table levels of deep unconfined aquifers. J Hydrol. https://doi.org/10.1016/j.jhydrol.2018.05.055

    Article  Google Scholar 

  50. Jones IC, Banner JL (2003) Estimating recharge thresholds in tropical karst island aquifers: Barbados, Puerto Rico and Guam. J Hydrol 278:131–143. https://doi.org/10.1016/S0022-1694(03)00138-0

    Article  Google Scholar 

  51. Jyrkama MI, Sykes JF (2007) The impact of climate change on spatially varying groundwater recharge in the grand river watershed (Ontario). J Hydrol 338:237–250. https://doi.org/10.1016/j.jhydrol.2007.02.036

    Article  Google Scholar 

  52. Kahsay GH, Gebreyohannes T, Gebremedhin MA et al (2018) Spatial groundwater recharge estimation in Raya basin, Northern Ethiopia: an approach using GIS based water balance model. Sustain Water Resour Manag. https://doi.org/10.1007/s40899-018-0272-2

    Article  Google Scholar 

  53. Kikuchi CP, Ferré TPA (2017) Analysis of subsurface temperature data to quantify groundwater recharge rates in a closed Altiplano basin, northern Chile. Hydrogeol J 25:103–121. https://doi.org/10.1007/s10040-016-1472-1

    Article  Google Scholar 

  54. Kim JH, Jackson RB (2012) A global analysis of groundwater recharge for vegetation, climate, and soils. Vadose Zo J. https://doi.org/10.2136/vzj2011.0021RA

    Article  Google Scholar 

  55. Kirchheim RE, Gastmans D, Chang HK, Gilmore TE (2019) The use of isotopes in evolving groundwater circulation models of regional continental aquifers: the case of the Guarani Aquifer System. Hydrol Process 33:2266–2278. https://doi.org/10.1002/hyp.13476

    Article  Google Scholar 

  56. Knisel WG Jr (1963) Baseflow recession analysis for comparison of drainage basins and geology. J Geophys Res 68:3649–3653. https://doi.org/10.1029/JZ068i012p03649

    Article  Google Scholar 

  57. Lacey GC, Grayson RB (1998) Relating baseflow to catchment properties in south-eastern Australia. J Hydrol 204:231–250. https://doi.org/10.1016/S0022-1694(97)00124-8

    Article  Google Scholar 

  58. Legesse D, Vallet-Coulomb C, Gasse F (2003) Hydrological response of a catchment to climate and land use changes in Tropical Africa: case study south central Ethiopia. J Hydrol 275:67–85. https://doi.org/10.1016/S0022-1694(03)00019-2

    Article  Google Scholar 

  59. Li A, Hegde M (2020) Giovanni: The Bridge Between Data and Science v 4.34. In: EarthDATA. https://giovanni.gsfc.nasa.gov/giovanni/. Accessed 3 Sept 2020

  60. Li B, Rodell M, Kumar S et al (2019) Global GRACE data assimilation for groundwater and drought monitoring: advances and challenges. Water Resour Res. https://doi.org/10.1029/2018WR024618

    Article  Google Scholar 

  61. Lucas M, Wendland E (2016) Recharge estimates for various land uses in the Guarani aquifer system outcrop area. Hydrol Sci J 61:1253–1262. https://doi.org/10.1080/02626667.2015.1031760

    Article  Google Scholar 

  62. Lucas M, Oliveira PTS, Melo DCD, Wendland E (2015) Evaluation of remotely sensed data for estimating recharge to an outcrop zone of the Guarani Aquifer System (South America). Hydrogeol J 23:961–969. https://doi.org/10.1007/s10040-015-1246-1

    Article  Google Scholar 

  63. Manna F, Cherry JA, McWhorter DB, Parker BL (2016) Groundwater recharge assessment in an upland sandstone aquifer of southern California. J Hydrol 541:787–799. https://doi.org/10.1016/j.jhydrol.2016.07.039

    Article  Google Scholar 

  64. Marengo JA, Nobre CA, Seluchi ME et al (2015) A seca e a crise hídrica de 2014–2015 em São Paulo. Rev USP 106:31–44

    Article  Google Scholar 

  65. Mattiuzi CDP, Kirchheim R, Collischonn W, Fan FM (2016) Estimativa de recarga subterrânea a partir da Separação de escoamento de base na bacia hidrográfica do Rio Ibicuí (América do Sul). Águas Subterrâneas 29:285. https://doi.org/10.14295/ras.v29i3.28487

  66. Meyboom P (1961) Estimating ground-water recharge from stream hydrographs. J Geophys Res 66:1203. https://doi.org/10.1029/JZ066i004p01203

    Article  Google Scholar 

  67. Milani EJ (1998) Evolução Tectono-Estratigráfica da Bacia do Paraná e seu Relacionamento com a Geodinâmica Fanerozóica do Gondwana Sul-Ocidental. PhD Thesis, Instituto de Geociências – Univ. Federal do Rio Grande do Sul, Porto, Alegre

  68. Moeck C, Brunner P, Hunkeler D (2016) The influence of model structure on groundwater recharge rates in climate-change impact studies. Hydrogeol J 24:1171–1184. https://doi.org/10.1007/s10040-016-1367-1

    Article  Google Scholar 

  69. Mutzner R, Bertuzzo E, Tarolli P et al (2013) Geomorphic signatures on Brutsaert base flow recession analysis. Water Resour Res 49:5462–5472. https://doi.org/10.1002/wrcr.20417

    Article  Google Scholar 

  70. Niazi A, Bentley LR, Hayashi M (2017) Estimation of spatial distribution of groundwater recharge from stream baseflow and groundwater chloride. J Hydrol 546:380–392. https://doi.org/10.1016/j.jhydrol.2017.01.032

    Article  Google Scholar 

  71. Nitcheva O (2018) Hydrology models approach to estimation of the groundwater recharge: case study in the Bulgarian Danube watershed. Environ Earth Sci 77:464. https://doi.org/10.1007/s12665-018-7605-1

    Article  Google Scholar 

  72. OAS (2009) Guarani Aquifer: strategic action program. 224

  73. Peel MC, Finlayson BL, McMahon TA (2007) Updated world map of the Köppen-Geiger climate classification. Hydrol Earth Syst Sci 11:1633–1644. https://doi.org/10.5194/hess-11-1633-2007

    Article  Google Scholar 

  74. R CoreTeam (2019) R: A language and environment for statistical computing

  75. Rabelo JL, Wendland E (2009) Assessment of groundwater recharge and water fluxes of the Guarani Aquifer System, Brazil. Hydrogeol J 17:1733–1748. https://doi.org/10.1007/s10040-009-0462-y

    Article  Google Scholar 

  76. Riedel T, Weber TKD (2020) Review: The influence of global change on Europe’s water cycle and groundwater recharge. Hydrogeol J 28:1939–1959. https://doi.org/10.1007/s10040-020-02165-3

    Article  Google Scholar 

  77. Rodell M, Houser PR, Jambor U et al (2004) The global land data assimilation system. Bull Am Meteorol Soc 85:381–394. https://doi.org/10.1175/BAMS-85-3-381

    Article  Google Scholar 

  78. Rossi M (2017) Mapa Pedológico do Estado de São Paulo: revisado e ampliado. Instituto Florestal, São Paulo

    Google Scholar 

  79. Rozante J, Vila D, Barboza Chiquetto J et al (2018) Evaluation of TRMM/GPM blended daily products over Brazil. Remote Sens 10:882. https://doi.org/10.3390/rs10060882

    Article  Google Scholar 

  80. Sánchez-Murillo R, Brooks ES, Elliot WJ et al (2015) Baseflow recession analysis in the inland Pacific Northwest of the United States. Hydrogeol J 23:287–303. https://doi.org/10.1007/s10040-014-1191-4

    Article  Google Scholar 

  81. Santhi C, Allen PM, Muttiah RS et al (2008) Regional estimation of base flow for the conterminous United States by hydrologic landscape regions. J Hydrol 351:139–153. https://doi.org/10.1016/j.jhydrol.2007.12.018

    Article  Google Scholar 

  82. São Paulo (2010) Mapa de cobertura da terra do Estado de São Paulo na escala de 1:100.000. Secretaria de Meio ambiente do Estado de São Paulo, São Paulo

  83. Scanlon BR, Healy RW, Cook PG (2002) Choosing appropriate techniques for quantifying groundwater recharge. Hydrogeol J 10:18–39. https://doi.org/10.1007/s10040-001-0176-2

    Article  Google Scholar 

  84. Scibek J, Allen DM, Cannon AJ, Whitfield PH (2007) Groundwater–surface water interaction under scenarios of climate change using a high-resolution transient groundwater model. J Hydrol 333:165–181. https://doi.org/10.1016/J.JHYDROL.2006.08.005

    Article  Google Scholar 

  85. SGB-CPRM (2020) RIMAS: Rede Integrada de Monitoramento das Águas Subterrâneas. http://rimasweb.cprm.gov.br/layout/apresentacao.php. Accessed 3 Sep 2020

  86. Sindico F, Hirata R, Manganelli A (2018) The Guarani Aquifer System: from a Beacon of hope to a question mark in the governance of transboundary aquifers. J Hydrol Reg Stud 20:49–59. https://doi.org/10.1016/j.ejrh.2018.04.008

    Article  Google Scholar 

  87. Smakhtin VU (2001) Low flow hydrology: a review. J Hydrol 240:147–186. https://doi.org/10.1016/S0022-1694(00)00340-1

    Article  Google Scholar 

  88. Smerdon BD (2017) A synopsis of climate change effects on groundwater recharge. J Hydrol 555:125–128

    Article  Google Scholar 

  89. Soares PC (1975) Divisão estratigráfica do Mesozóico no Estado de São Paulo. Rev Bras Geociências 5:229–251

    Article  Google Scholar 

  90. Soares PC, Sinelli O, Penalva F et al (1973) Geologia do nordeste do Estado de São Paulo. Congr Bras Geol 1:209–2036

    Google Scholar 

  91. Sophocleous M (2002) Interactions between groundwater and surface water: the state of the science. Hydrogeol J 10:52–67. https://doi.org/10.1007/s10040-001-0170-8

    Article  Google Scholar 

  92. Tanco R, Kruse E (2001) Prediction of seasonal water-table fluctuations in La Pampa and Buenos Aires, Argentina. Hydrogeol J 9:339–347. https://doi.org/10.1007/s100400100143

    Article  Google Scholar 

  93. Teramoto EH, Chang HK (2018) Métodos WTF e simulação numérica de fluxo para estimativa de recarga exemplo Aquífero Rio Claro em Paulínia. Águas Subterrâneas 32:173–180 https://doi.org/10.14295/ras.v32i2.28943

  94. Tinker CJ, Kirchheim RE (2016) The Guarani Aquifer Agreement (Acordo Aquífero Guarani): Protection and Management of Transboundary Underground Water Resources in a Regional Context. In: Derani C, Scholz MC (eds) Mudanças climáticas e recursos genéticos: regulamentação jurídica na COP21. FUNJAB, Florianópolis/SC

  95. Vives L, Rodríguez L, Gómez A (2008) Modelacion Numérica Regional del Sistema Acuífero Guaraní. Informe Técnico—Consórcio Guarani, Montevideo (UY)

  96. Vogel RM, Kroll CN (1992) Regional geohydrologic-geomorphic relationships for the estimation of low-flow statistics. Water Resour Res 28:2451–2458. https://doi.org/10.1029/92WR01007

    Article  Google Scholar 

  97. Wahr J, Swenson S, Zlotnicki V, Velicogna I (2004) Time-variable gravity from GRACE: first results. Geophys Res Lett. https://doi.org/10.1029/2004GL019779

    Article  Google Scholar 

  98. Wendland E, Barreto C, Gomes LH (2007) Water balance in the Guarani Aquifer outcrop zone based on hydrogeologic monitoring. J Hydrol 342:261–269. https://doi.org/10.1016/J.JHYDROL.2007.05.033

    Article  Google Scholar 

  99. Wendland E, Gomes LH, Troeger U (2015) Recharge contribution to the Guarani aquifer system estimated from the water balance method in a representative watershed. An Acad Bras Cienc 87:595–609. https://doi.org/10.1590/0001-3765201520140062

    Article  Google Scholar 

  100. Westenbroek SM, Kelson VA, Dripps WR, Hunt RJ, Bradbury KR (2010) SWB—A modified Thornthwaite-Mather Soil-Water-Balance code for estimating groundwater recharge: US Geological Survey Techniques and Methods 6-A31. pp 60. https://doi.org/10.1017/CBO9781107415324.004

  101. Winograd IJ, Riggs AC, Coplen TB (1998) The relative contributions of summer and cool-season precipitation to groundwater recharge, Spring Mountains, Nevada, USA. Hydrogeol J 6:77–93. https://doi.org/10.1007/s100400050135

    Article  Google Scholar 

  102. Xie Y, Crosbie R, Simmons CT et al (2018) Uncertainty assessment of spatial-scale groundwater recharge estimated from unsaturated flow modelling. Hydrogeol J 27:379–393. https://doi.org/10.1007/s10040-018-1840-0

    Article  Google Scholar 

  103. Yang L, Qi Y, Zheng C et al (2018) A modified water-table fluctuation method to characterize regional groundwater discharge. Water 10:503. https://doi.org/10.3390/w10040503

    Article  Google Scholar 

  104. Zhang J, Wang W, Wang X et al (2019) Seasonal variation in the precipitation recharge coefficient for the Ordos Plateau, Northwest China. Hydrogeol J 27:801–813. https://doi.org/10.1007/s10040-018-1891-2

    Article  Google Scholar 

Download references

Acknowledgements

This work was funded by a grant from the São Paulo Research Foundation (FAPESP) under Process 2018/06666-4. First author (L.V.S) thanks FAPESP for the scholarship provided under the processes no. 2017/13576-9. We would also like to thank Prof. Dr. James Lamoreaux, Editor-in-Chief of the Environmental Earth Sciences, and two anonymous reviewers that have significantly improved this manuscript with their beneficial comments and criticisms.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Didier Gastmans.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Santarosa, L.V., Gastmans, D., Sitolini, T.P. et al. Assessment of groundwater recharge along the Guarani aquifer system outcrop zone in São Paulo State (Brazil): an important tool towards integrated management. Environ Earth Sci 80, 95 (2021). https://doi.org/10.1007/s12665-021-09382-3

Download citation

Keywords

  • Aquifer recharge
  • Guarani aquifer system
  • Remote-sensing data
  • GIS-based recharge