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Aridity Analysis Using a Prospective Geospatial Simulation Model in This Mid-Century for the Northwest Region of Mexico

Author

Listed:
  • Lidia Yadira Perez-Aguilar

    (Facultad de Ciencias de la Tierra y el Espacio, Universidad Autónoma de Sinaloa, Culiacán 80013, Mexico)

  • Wenseslao Plata-Rocha

    (Facultad de Ciencias de la Tierra y el Espacio, Universidad Autónoma de Sinaloa, Culiacán 80013, Mexico)

  • Sergio Alberto Monjardin-Armenta

    (Facultad de Ciencias de la Tierra y el Espacio, Universidad Autónoma de Sinaloa, Culiacán 80013, Mexico)

  • Cuauhtémoc Franco-Ochoa

    (Facultad de Ciencias de la Tierra y el Espacio, Universidad Autónoma de Sinaloa, Culiacán 80013, Mexico)

Abstract

Aridity is a condition in which there is a moisture deficit in the air and soil that affects large areas of the earth’s surface worldwide. It is a global problem caused mainly by factors related to climatic events and human actions. In the arid regions of Mexico, prolonged periods of drought are very common and water scarcity is the predominant feature. The main objective of this study is to develop a prospective geospatial simulation model for arid zones in the short and medium term (2030 and 2050) for the northwestern region of Mexico. A retrospective analysis of the variables that cause aridity was conducted based on historical data from satellite information obtained from various sources between 1985 and 2020, taking 2020 as the reference year; from this information the rate of change per year was obtained, followed by the simulated rates of change for the years 2030 and 2050. A methodology used to obtain arid zones using multicriteria evaluation techniques, weighted linear combination, and Geographic Information Systems. In order to generate the prospective model for arid zones, the variables were modeled to adjust the rate of change for each of them, with the same methodology subsequently applied to obtain the base year (2020), and aridity suitability maps were obtained for the years 2030 and 2050. The main results indicate that the prospective scenarios point to an increase in arid regions of 0.38% and 0.70%, respectively, which is equivalent to an area of approximately 240,164.63 km 2 and 241,760.75 km 2 , respectively. This will cause a decrease in the subhumid–dry and humid regions of 0.10% and 0.19%, respectively, for the projected years. Statistical and geospatial aridity indicators were also generated at different levels, which helps to better understand the problem of aridity in vulnerable regions.

Suggested Citation

  • Lidia Yadira Perez-Aguilar & Wenseslao Plata-Rocha & Sergio Alberto Monjardin-Armenta & Cuauhtémoc Franco-Ochoa, 2022. "Aridity Analysis Using a Prospective Geospatial Simulation Model in This Mid-Century for the Northwest Region of Mexico," Sustainability, MDPI, vol. 14(22), pages 1-22, November.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:15223-:d:974819
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    References listed on IDEAS

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    1. Sergio Alberto Monjardin-Armenta & Wenseslao Plata-Rocha & Carlos Eduardo Pacheco-Angulo & Cuauhtémoc Franco-Ochoa & Jesus Gabriel Rangel-Peraza, 2020. "Geospatial Simulation Model of Deforestation and Reforestation Using Multicriteria Evaluation," Sustainability, MDPI, vol. 12(24), pages 1-20, December.
    2. Aiguo Dai, 2011. "Drought under global warming: a review," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 2(1), pages 45-65, January.
    3. Ankita P. Dadhich & Rohit Goyal & Pran N. Dadhich, 2021. "Assessment and Prediction of Groundwater using Geospatial and ANN Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(9), pages 2879-2893, July.
    4. Jose Marengo & Mauro Bernasconi, 2015. "Regional differences in aridity/drought conditions over Northeast Brazil: present state and future projections," Climatic Change, Springer, vol. 129(1), pages 103-115, March.
    5. Bakhtiar Feizizadeh & Thomas Blaschke, 2013. "GIS-multicriteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia lake basin, Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(3), pages 2105-2128, February.
    6. Hasan Zabihi & Mohsen Alizadeh & Philip Kibet Langat & Mohammadreza Karami & Himan Shahabi & Anuar Ahmad & Mohamad Nor Said & Saro Lee, 2019. "GIS Multi-Criteria Analysis by Ordered Weighted Averaging (OWA): Toward an Integrated Citrus Management Strategy," Sustainability, MDPI, vol. 11(4), pages 1-17, February.
    7. Overmars, Koen P. & Verburg, Peter H., 2006. "Multilevel modelling of land use from field to village level in the Philippines," Agricultural Systems, Elsevier, vol. 89(2-3), pages 435-456, September.
    8. L. Lin & A. Gettelman & Q. Fu & Y. Xu, 2018. "Simulated differences in 21st century aridity due to different scenarios of greenhouse gases and aerosols," Climatic Change, Springer, vol. 146(3), pages 407-422, February.
    9. Evan Girvetz & Chris Zganjar, 2014. "Dissecting indices of aridity for assessing the impacts of global climate change," Climatic Change, Springer, vol. 126(3), pages 469-483, October.
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