In Mexico, poverty has forced people to live almost on the water of rivers. This situation along with the occurrence of floods is a serious problem for the local governments. In order to protect their lives and goods, it is very important to account with a mathematical tool that may reduce the uncertainties in computing the design events for different return periods.In this paper, the Logistic model for bivariate extreme value distribution with Weibull-2 and Mixed Weibull marginals is proposed for the case of flood frequency analysis. A procedure to estimate their parameters based on the maximum likelihood method is developed. A region in Northwestern Mexico with 16 gauging stations has been selected to apply the model and regional at-site quantiles were estimated. A significant improvement occurs, measured through the use of a goodness-of-fit test, when parameters are estimated using the bivariate distribution instead of its univariate counterpart. Results suggest that it is very important to consider the Mixed Weibull distribution and its bivariate option when analyzing floods generated by a mixture of two populations.

Meteorological drought has been an inevitable natural disaster throughout Mexican history and the northern and northwestern parts of Mexico (i.e., the studied area), where the mean annual precipitation (MAP) is less than 500 mm, have suffered even more from droughts in the past. The aim of this study was to conduct a meteorological drought analysis of the available MAP data (1950-2013) from 649 meteorological stations selected from the studied area and to predict the drought features under the different IPCC-prescribed climate change scenarios. To determine the long-term drought features, we collected 1×10 4 synthetic samples using the periodic autoregressive moving average (PARMA) model for each rainfall series. The simulations first consider the present prevailing precipitation conditions (i.e., the average from 1950 to 2013) and then the precipitation anomalies under IPCC-prescribed RCP 4.5 scenario and RCP 8.5 scenario. The results indicated that the climate changes under the prescribed scenarios would significantly increase the duration and intensity of droughts. The most severe impacts may occur in the central plateau and in the Baja California Peninsula. Thus, it will be necessary to establish adequate protective measures for the sustainable management of water resources in these regions.

No abstract

The aim of this study is to identify temporal and spatial variability patterns of annual and seasonal rainfall in Mexico. A set of 769 weather stations located in Mexico was examined. The country was divided into 12 homogeneous rainfall regions via principal component analysis. A Pettitt test was conducted to perform a homogeneity analysis for detecting abrupt changes in mean rainfall levels, and a Mann‐Kendall test was conducted to examine the presence of monotonically increasing/decreasing patterns in the data. In total, 14.4% of the annual series was deemed nonstationary. Fourteen percent of the samples were nonstationary in the winter and summer, and 9% were nonstationary in the spring and autumn. According to the results, the nonstationarity of some seasonal rainfall series may be associated with the presence of atmospheric phenomena (e.g., El Niño/Southern Oscillation, Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation, and North Atlantic Oscillation). A rainfall frequency analysis was performed for the nonstationary annual series, and significant differences in the return levels xfalse^T can be expected for the scenarios analyzed. The identification of areas that are more susceptible to changes in rainfall levels will improve water resource management plans in the country, and it is expected that these plans will take into account nonstationary theory.

RESUMENLa escasez de información en el análisis de frecuencias de lluvias máximas diarias puede generar estimadores ineficaces para propósitos de diseño. Una forma de reducir estos errores es la aplicación de técnicas regionales, las cuales requieren que las estaciones involucradas pertenezcan a la misma región homogénea. En este trabajo se realiza una delimitación de regiones homogéneas de precipitación empleando un método multivariado basado en las técnicas de análisis de componentes principales y de agrupamiento jerárquico ascendente. La metodología propuesta se aplicó a una región del noroeste de México. Se concluyó que sólo se requieren los coeficientes de variación de los momentos-L y de la latitud, longitud y altitud de cada estación climatológica para definir las regiones homogéneas de precipitación, y que la inclusión o exclusión de información en las técnicas regionales tiene un impacto directo en la estimación de eventos asociados a diferentes periodos de retorno. ABSTRACTLack of data in maximum daily rainfall frequency analysis can generate inefficient estimates for design purposes. An approach to diminish these errors is to apply regional estimation techniques, which require that all stations be located at the same homogeneous region. In this paper, a delineation of homogeneous precipitation regions was made based on the multivariate methods of principal component analysis and hierarchical ascending clustering. A region in northwestern Mexico was selected to apply this methodology. It was concluded that only the coefficients of variation of the L-moments, along with latitude, longitude and altitude at each climatological station are sufficient to define the homogeneous rainfall regions, and that either the inclusion or exclusion of information in the regional techniques has a direct impact on the estimation of events associated to different return periods.