Modeling the potential impact of climate change in northern Mexico using two environmental indicators
Modeling the deterioration of natural resources, especially water and soil that results from the global effects of climate change has become a powerful tool in the search for mitigation and adaptation measures. The objectives of this research were: (1) to model the potential impact of climate change...
| Autores: | , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | México |
| Recursos: | Universidad Autónoma Chapingo |
| Repositorio: | Redalyc-UACHP |
| OAI Identifier: | oai:redalyc.org:56528834004 |
| Acesso em linha: | https://www.redalyc.org/articulo.oa?id=56528834004 |
| Access Level: | acceso abierto |
| Palavra-chave: | Ciencias de la Tierra modeling Climate scenarios ecological zoning |
| Resumo: | Modeling the deterioration of natural resources, especially water and soil that results from the global effects of climate change has become a powerful tool in the search for mitigation and adaptation measures. The objectives of this research were: (1) to model the potential impact of climate change for the period 2010- 2039, and (2) to offer advice about future risks based on local radiative forcing or critical areas and taking into account two indicators of environmental quality, the aridity index (AI) and laminar wind erosion (LWE). Evaluation techniques for natural resources, similar to those applied by the Instituto Nacional de Ecología y Cambio Climático (National Institute of Ecology and Climate Change) were used for studies of ecological land use. The inputs include climate information (current and future), soil cover and edaphic properties related to the municipality of Gómez Palacio, Durango, Mexico (25.886o N, 103.476o W). According to calculations estimated from the anomalies for the mean annual rainfall and mean annual temperature, in a future climate change scenario, an average impact of approximately 63% would be caused by LWE, and the AI would change from its historical value of 9.3 to 8.7. It is estimated that the average impact on the AI in the future will be 0.53 ± 0.2. |
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