Data classification methods in GIS for groundwater recharge estimation in Mexico
DOI:
https://doi.org/10.54167/tch.v19iEspecial.2020Keywords:
classification methods, GIS, thematic maps, groundwater recharge, MexicoAbstract
This study evaluated five data classification methods in ArcMap 10.5 to analyze the mean annual groundwater recharge in thirteen hydrologic-administrative regions of Mexico. Recharge data (hm³/year) were obtained from CONABIO’s Geoportal (2008) and normalized using specific recharge (mm/year) to allow comparisons among regions of different sizes. The analysis was based on interval, class, and range. Choropleth maps were generated using equal intervals, equal frequency/quantiles, manual classification, natural breaks/Jenks, and geometric intervals, with a maximum of five classes. The results revealed differences in spatial representation: equal intervals simplified interpretation (each class covering 4,816hm3/year) but did not reflect the concentration of low values; quantiles distributed values evenly, although they grouped heterogeneous data (e.g., 7,566 and 25,316 hm3/year) ; manual classification sacrificed intermediate detail and displayed only two broad intervals (8,000 and 18,000 hm3/year); natural breaks/Jenks and geometric intervals represented variability and skewed data with greater accuracy. Areas of high recharge (Yucatán Peninsula: 213.2 mm/year) and low recharge (Baja California: 8.4 mm/year) were identified. The study concludes that no single ideal method exists; the choice depends on the objectives, the nature of the data, and the target audience. The combined application of multiple methods enhances interpretation and supports more informed groundwater management.
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