Influence of available data on the geostatistical-based design of optimal spatiotemporal groundwater-level-monitoring networks

Author:

Júnez-Ferreira H. E.,Herrera G. S.,Saucedo E.,Pacheco-Guerrero A.

Funder

Consejo Nacional de Ciencia y Tecnolog?a

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Water Science and Technology

Reference56 articles.

1. Adhikary P, Dash CJ (2017) Comparison of deterministic and stochastic methods to predict spatial variation of groundwater depth. Appl Water Sci 7(1):339–348. https://doi.org/10.1007/s13201-014-0249-8

2. Ahmed SH, De Marsily G, Talbot A (1988) Combined use of hydraulic and electrical properties of an aquifer in a geostatistical estimation of transmissivity. Ground Water 26(1):78–86. https://doi.org/10.1007/s10661-007-9803-2

3. Alizadeh Z, Mahjouri N (2017) A spatiotemporal Bayesian maximum entropy-based methodology for dealing with sparse data in revising groundwater quality monitoring networks: the Tehran region experience. Environ Earth Sci 76:436. https://doi.org/10.1007/s12665-017-6767-6

4. Babu DK, Pinder GF, Niemi A, Ahlfeld DP, Stothoff SA (1997) Chemical transport by three-dimensional groundwater flows. Available at http://www.argusone.com/pub/PTC_Files/Ptc-hbk.pdf . Accessed December 2018

5. Becerra L (2009) Estimación de lluvia en el Distrito Federal utilizando datos de pluviógrafos y de radar meteorológico [Estimation of rainfall in the Federal District using rainfall and meteorological radar data]. MSc Thesis, UNAM, México. http://132.248.9.195/ptd2009/octubre/0650819/Index.html . Accessed 8 December 2018

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