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Mathematical techniques that predict the risk of forest fires use a hydro-climatic sub-model, which is generally fed with simple climatic variables such as rainfall, potential evapotranspiration, or the air relative humidity. In this research we report the effect of rainfall, pan evaporation (Et), and potential evapotranspiration (Etp), and the soil moisture content (θ), were related with the number of annual forest fires and the area annually burned by forest fires in the state of Durango, Mexico. A hydrologic, mass balance, physically-based model that feeds on climate, soil and plant cover variables as well as weighting factors was employed to calculate Etp and θ. In addition, the El Nino index was statistically related to the forest fire variables described above. The θ variable resulted to be better related than the simple climatic variables to the number of forest fires and the area burned by forest fires. El Nino index expressed during the November-December phase of the year t-1 explains above 30% of the total burned area variation during the dry season of January-May of temperate forests. It is recommended to use the soil moisture content estimated by the water balance as predictor variable in the fire risk assessment of temperate forests.

Modelación del contenido de agua de los suelos y su relación con los incendios forestales en la Sierra Madre Occidental de Durango, México