Spatial and Temporal Evolution of the Static Water Level of the Cuauhtemoc Aquifer during the Years 1973, 1991 and 2000: A Geographical Approach


In hydrogeology it is of great interest to examine the temporal and spatial evolution of aquifers. There are different ways of modeling an aquifer: physical models, models based on analog and mathematical techniques. Usually, mathematical techniques involve complex operations difficult to understand for some people, such as differential or partial equations. In contrast, our method requires only a basic knowledge of geometry and trigonometry. Moreover, it is only necessary to know the static level of the aquifer at three different dates. Of course, the results may be limited compared to those that use advanced mathematical methods; however, our method provides a first approximation to determine the behavior of the aquifer through time. Overall, our results allowed us to follow the evolution of the aquifer in detail of various areas of increased extraction and in which removal has been increasing, but also of areas with a considerable recharge during the study period.

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Alatorre, L. , Díaz, R. , Miramontes, S. , Bravo, L. and Sánchez, E. (2014) Spatial and Temporal Evolution of the Static Water Level of the Cuauhtemoc Aquifer during the Years 1973, 1991 and 2000: A Geographical Approach. Journal of Geographic Information System, 6, 572-584. doi: 10.4236/jgis.2014.65047.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Shiklomanov, I. (1998) World Water Resources: Modern Assessment and Outlook for 21st Century. Federal Service of Rusia for Hidrometorology & Environment Monitoring State, Hidrological Institute, San Petesburgo.
[2] Oki, T. and Kanae, S. (2006) Global Hydrological Cycles and World Water Resources. Science, 313, 1068-1072.
[3] Cosgrove, W.J. and Rijsberman, F.R. (2000) World Water Vision: Making Water Everybody’s Business. Earthscan Publications Ltd., London.
[4] Struckmeier, M., Rubin, Y. and Jones, J.A. (2005) Groundwater-Reservoir for a Thirsty Planet? Planet Earth, International Union of Geological Sciences y United Nations Educational Scientific and Cultural Organisation, Leiden.
[5] Giordano, M. and Villholth, K.G. (2007) The Agricultural Groundwater Revolution: Setting the Stage. In: Giordano, M. and Villholth, K.G., Eds., The Agricultural Groundwater Revolution: Opportunities and Threats to Development, Cromwell Press, International Water Management Institute, Colombo, 1-4.
[6] Burke, J. and Moench, M. (2000) Groundwater and Society: Resources, Tensions and Opportunities. Naciones Unidas, Nueva York.
[7] Shah, T., Burke, J. and Villholth, K.G. (2007) Groundwater: A Global Assessment of Scale and Significance. In: Molden, D., Ed., Water for Food, Water for Life: A Comprehensive Assessment of Water Management in Agriculture, International Water Management Institute, Londres: Earthscan, Colombo, 395-423.
[8] CONAGUA (2011) Atlas del Agua en México. SEMARNAT-Gobierno Federal, 142 p.
[9] CONAGUA (2011) Estadísticas del Agua en México. Comisión Nacional del Agua.
[10] INEGI (2010) XII Censo general de Población y vivienda. Instituto Nacional de Geografía y Estadística.
[11] Marin, L.E. (2002) Perspectives on Mexican Ground Water Resources. Groundwater, 40, 570-571.
[12] Bauer, P., Gumbricht, T. and Kinzelbach, W. (2006) A Regional Coupled Surface Water/Groundwater Model of the Okavango Delta, Botswana. Water Resources Research, 42, Article ID: W04403.
[13] Carroll, R.W.H., Pohll, G.M. and Hershey, R.L. (2009) An Unconfined Groundwater Model of the Death Valley Regional Flow System and a Comparison to Its Confined Predecessor. Journal of Hydrology, 373, 316-328.
[14] Refsgaard, J.C., H?jberg, A.L., M?ller, I., Hansen, M. and S?ndergaard, V. (2010) Groundwater Modeling in Integrated Water Resources Management—Visions for 2020. Ground Water, 48, 633-648.
[15] Maxwell, R.M. and Kollet, S.J. (2008) Interdependence of Groundwater Dynamics and Land-Energy Feedbacks under Climate Change. Nature Geoscience, 1, 665-669.
[16] Scibek, J., Allen, D.M., Cannon, A.J. and Whitfield, P.H. (2007) Groundwater-Surface Water Interaction under Scenarios of Climate Change Using a High-Resolution Transient Groundwater Model. Journal of Hydrology, 333, 165-181.
[17] D’Agnese, F.A., Faunt, C.C., Hill, M.C. and Keith-Turner, A. (1999) Death Valley Regional Ground-Water Flow Model Calibration Using Optimal Parameter Estimation Methods and Geoscientific Information Systems. Advances in Water Resources, 22, 777-790.
[18] Gustafson, G., Gylling, B. and Selroos, J.O. (2009) The ?sp? Task Force on Groundwater Flow and Transport of Solutes: Bridging the Gap between Site Characterization and Performance Assessment for Radioactive Waste Disposal in Fractured Rocks. Hydrogeology Journal, 17, 1031-1033.
[19] Tiedeman, C.R., Hill, M.C., D’Agnese, F.A. and Faunt, C.C. (2003) Methods for Using Groundwater Model Predictions to Guide Hydrogeologic Data Collection, with Application to the Death Valley Regional Groundwater Flow System. Water Resources Research, 39, 1010.
[20] Caruso, C. and Quarta, F. (1998) Interpolation Methods Comparison. Computers and Mathematics with Applications, 35, 109-126.
[21] Li, X.Y., Song, D.M. and Xiao, D.N. (2005) The Variability of Groundwater Mineralization in Minqin Oasis. Acta Geographica Sinica, 60, 319-327.
[22] Theodossiou, N. and Latinopoulos, P. (2006) Evaluation and Optimisation of Groundwater Observation Networks Using the Kriging Methodology. Environmental Modelling and Software, 21, 991-1000.
[23] Theodossiou, N. and Latinopoulos, P. (2007) Evaluation and Optimisation of Groundwater Observation Networks Using the Kriging Methodology. Environmental Modelling and Software, 22, 414.
[24] Hutchinson, M.F. (1995) Interpolating Mean Rainfall Using Thin Plate Smoothing Splines. International Journal of Geographical Information Systems, 9, 385-403.
[25] Collins, F.C. (1996) A Comparison of Spatial Interpolation Techniques in Temperature Estimation. Proceedings of the Third International Conference/Workshop on Integrating GIS and Environmental Modeling, Santa Barbara, 21-26 January 1996.
[26] Feng, J.M., Zhao, T.B. and Hang, Y.J. (2004) Intercomparison of Spatial Interpolation Based on Observed Precipitation Data. Climatic and Environmental Research, 9, 261-277.
[27] Fang, S.M., Qian, Z.T. and Li, Y.P. (2005) Comparison of Four Precipitation Spatial Interpolation Methods in Gansu. Journal of Arid Land Resources and Environment, 19, 47-50.
[28] Li, J., You, S.C. and Huang, J.F. (2006) Spatial Interpolation Method and Spatial Distribution Characteristics of Monthly Mean Temperature in China during 1961-2000. Ecology and Environment, 15, 109-114.
[29] Kenneth, K.E. (1996) Conceptualization and Characterization of Groundwater Systems Using Geographic Information Systems. Engineering Geology, 42, 111-118.
[30] Wang, J.L., Sun, J.S. and Zhang, J.Y. (2004) Crop Water Requirement Isoline Based on GIS and Geostatistics. Transactions of the CSAE, 20, 51-54.
[31] Wei, J.H., Wang, G.Q., Li, C.J. and Shao, J.L. (2003) Recent Advances Associated with GIS. Groundwater Resources Research, 2, 94-98.
[32] Xu, Y.Q. and Cai, Y.L. (2005) GIS-Based Analysis on Spatial-Temporal Change of Groundwater Level in the Hebei Plain. Acta Scientiarum Naturalium Universitatis Pekinensis, 41, 265-272.
[33] Sun, Y., Kang, S., Li, F. and Zhang, L. (2009) Comparison of Interpolation Methods for Depth to Groundwater and Its Temporaland Spatial Variations in the Minqin Oasis of Northwest China. Environmental Modelling and Software, 24, 1163-1170.
[34] CONAGUA (1991) Actualización del estudio geohidrológico, políticas de operación y proyecto de manejo del acuífero del Valle de Cuauhtémoc Chihuahua, Comisión Nacional del Agua. Contrato CNA-GRN-90-009, 186 p.
[35] CONAGUA (2000) Cuantificación de la extracción de agua subterránea en el acuífero de Cuauhtémoc Chihuahua, Comisión Nacional del Agua. Contrato GAS-011-PRO-2000. Tomo 1. 414 p.
[36] CONAGUA (2002) Determinación de la disponibilidad del agua en el acuífero de Cuauhtémoc. Estado de Chihuahua, México, D.F.
[37] Planchon, O. and Darboux, F. (2001) A Fast, Simple and Versatile Algorithm to Fill the Depressions of Digital Elevation Models. Catena, 46, 159-176.
[38] Aguilar-Torres, M.A., Carvajal-Ramírez, F., Aguilar-Torres, F.J. and Agüera, F. (2001) Evaluación de diferentes técnicas de interpolación espacial para la generación de modelos digitales de elevación del terreno agrícola. Mapping, 74, 72-88.
[39] Kravchenko, A. and Bullock, D. (1999) A Comparative Study of Interpolation Methods for Mapping Soil Properties. Agronomy Journal, 91, 393-400.
[40] Kravchenko, A.N. (2003) Influence of Spatial Structure on Accuracy of Interpolation Methods. Soil Science Society of America Journal, 67, 1564-1571.
[41] Schloeder, C.A., Zimmerman, N.E. and Jacobs, M.J. (2001) Comparison of Methods for Interpolating Soil Properties Using Limited Data. Soil Science Society of America Journal, 65, 470-479.

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