Spatial and temporal hydro-climatic variability in Durango, Mexico - Návar, José (Tecnología y ciencias del agua, 2014)
This report presents information on the hydro-climate temporal and spatial variability for the State of Durango, Mexico. Annual rainfall data fitted the Gamma probabilistic density functions. The Gumbel-Fisher-Tipett density function fitted maximum daily precipitation. The log-Pearson Type III density function projected maximum annual discharge and daily maximum peakflows. Evapotranspiration was estimated by the Thornthwaite methodology. More than 80 climatic stations with data lasting longer than 30 years were used to fit probability density parameters. Geographical prediction equations; e.g. mean annual rainfall = Î± +Î²1 (Latitude) +Î²2 (Longitude) +Î²3 (Altitude) estimated the spatial variability of precipitation, temperature and evapotranspiration. Reconstructed and instrumental long- term (1860-2004) time series (precipitation and streamflow) data was temporally analyzed using ARIMA and linear and nonlinear regression techniques. Results showed mean annual temperature and evapotranspiration are spatially variable, diminishing with an increment in latitude and altitude. Mean annual precipitation on the other side increases with latitude and altitude but reduces with longitude. This trend was reversed for the Pacific Ocean physiographic region. Hydro-climatic data showed a lack of linear monotonic patterns indicating the time series are stationary in the first momentum. Oscillations of several time-scales: seasonal, inter-annual, 3-7 years; and 9-12- year were consistently noted on the modeled reconstructed and instrumental time series, spectral density analysis and correlograms for annual precipitation and streamflow data. Large-scale synoptic climate events such as the seasonal monsoon, the inter-annual variability, the El Niño Southern and the Pacific Decadal Oscillations appeared to explain temporal oscillations. Spatial variability was observed in hydro-climatic maps constructed using GIS techniques. This spatial and temporal information can be used in the decision making of water management resources at the local and State spatial scales; and in studies of productivity, forest wildfires, and floods of the State of Durango, Mexico.