Natural disasters related to hydro‐meteorological events have increased during the last few decades, both in frequency and severity. Mexico is heavily exposed to climate change, but has also suffered in the past from climate variability (Blümel, 2009). The new risks oblige the government to develop mitigation processes, while the affected people are implementing strategies of adaptation and resilience‐building, mostly at the family and community level. This includes forced migration due to climate change into the slums of megacities or illegal immigration to the United States. The arid, semi‐arid and subhumid condition of 49.2 per cent of the territory of Mexico is seriously affected by climate change. In addition, poverty and the lack of jobs have created complex livelihood situations, in which young people leave rural areas, partly due to socio‐economic pull factors. In this paper, we address the functional relationships between climate patterns and migration processes in Mexico, highlighting the linkages between the origin of migrants, their economic activity and their vulnerability to extreme events and we discuss long‐term climate patterns. Agriculture still uses 78 per cent of the available water in Mexico. In the drylands the competition for water use requires an integrated policy to deal with the new threats from climate change, including mitigation from the top down and adaptation processes from the bottom up to reduce the social vulnerability of the rural population in the highly affected drylands of the central and northern parts of Mexico. The new policy for administering water resources, which promotes the efficient use of an increasingly scarce and polluted resource, still suffers from a lack of participation by the affected rural population. In this paper, we propose an integrated management system from the watershed onwards, involving socio‐economic, political, cultural and hydrological variables, to deal with the rising scarcity of water, and the uncertainty and complexity of climate change.

Rainfed areas in Mexico accounts for 14 million hectares where around 23 million people live and are located in places where there is a little climatic information. The severe drought that has impacted northern Mexico in the past several years as well as other parts of the country, has forced decision takers to look for improved tools and procedures to prevent and to cope with this natural hazard. For this paper, the methodology of the Food and Agricultural Organization of the United Nations (FAO) for estimating water balance variables was modified to provide crop yield estimations under rainfed agriculture in maize producer states of Mexico. The water balance accounts for the daily variation of soil water content having main input rainfall (Pp) and main output crop evapotranspiration (Eta). The algorithm computes crop yield using two distinctive approaches: 1) one based on surplus/deficit functions for each crop considered and 2) yield estimations based on soil water balance and water function productions of the crop being analyzed. For computing water balance and crop yields, a computer model is built that incorporates the FAO method for water balance (MODEL SICTOD: Computational System for Decision Taking, acronym in Spanish) which stochastically generate precipitation based on wet/dry transition probabilities using a first order Markov chain scheme. Maps of average crop yields were obtained after interpolating model outcomes for the main maize producer states of Mexico: Jalisco, Michoacan, Guerrero, Puebla Oaxaca and Chiapas. Different planting dates were analyzed, early (90 days of length period), intermediate (120 days of length period) and late (150 days of length period). Crop yield variability correlates to the transition probability on having a wet day following a dry day. Results have shown

El manejo tradicional del cultivo de papa es cada vez menos funcional debido a la alta variabilidad climática en las zonas productoras del noroeste de México, provocando aplicaciones excesivas de insumos, contaminación y baja rentabilidad. Para mejorar lo anterior, se generó una metodología que ayuda a acoplar la demanda nutrimental al clima, mediante funciones autoajustables basadas en el concepto grado día (oD) derivadas de las curvas de extracción. El trabajo se desarrolló en el norte de Sinaloa durante dos ciclos agrícolas otoño-invierno (OI): 2008-2009 y 2009-2010, en el INIFAP-CIRNO-CEVAF. En el primer ciclo se obtuvieron curvas base de extracción nutrimental (CB) para la variedad Alpha en riego por goteo; durante el segundo, se validaron las CB con la variedad Fianna en riego por superficie, mediante un experimento con tres tratamientos (T) en un arreglo en bloques completos al azar. El T1 fue la fertilización NPK de acuerdo a CB (245, 30, 350 kg ha-1), en el T2 se fertilizó usando CB+20% (294, 36, 420 kg ha-1) y el T3 consistió en CB-20% (196, 24, 280 kg ha-1). La extracción total de nutrimentos fue similar en los tres tratamientos, sin embargo, la tasa de absorción fue diferenciada en las etapas iniciales del cultivo. Debido a que en el rendimiento y calidad del tubérculo fue significativa la diferencia en el T2, en este se generaron las funciones matemáticas, obteniendo R2 mayores al 0.8. La metodología se probó con éxito en dos parcelas comerciales.

El trabajo se llevó a cabo en Gómez Palacio, Durango, México, con el objetivo de determinar la función de producción que relacione el rendimiento de canola (Brassica napus L.) con el nivel de hume-dad del suelo. Se aplicaron siete tratamientos de riego, consistentes de seis diferentes niveles de abatimiento de la humedad aprovechable residual del suelo al momento de regar (0, 12, 24, 36, 48 y 60 %), y un tratamiento adicional con sólo el riego de presiembra. Se utilizó un diseño experimental de bloques completos al azar con cuatro repeticiones. Las variables evaluadas fueron rendimiento de grano, eficiencia del uso de agua y lámina de agua consumida. Según la función de producción obtenida, es posible lograr un rendimiento de grano de 3.1 t ha-1, con una lámina de agua de 48 cm distribuida con riegos aplicados cuando la humedad aprovechable residual en el suelo baja a 35 %, equivalente a una tensión de humedad de -0.74 MPa.

The uncertainty of water availability is the main problem in planning for water resources in watersheds of agricultural drylands. Water availability for different uses depends on the runoff that is generated in the upper portion of the watersheds, where there are higher elevations and lower temperatures. Proximity to the ocean is a main factor that defines rainfall amounts. In this research we linked the effects of El Niño to a regional Standardized Precipitation Index (SPI) and the subsequent impact on runoff production and irrigation water allocation. Findings indicate the cascading impacts of the El Niño on the SPI, the SPI on the runoff discharge to the irrigation reservoir, and the final impact on the planted area within the irrigation district. An optimization procedure was applied to maximizing net income in agriculture under different water availability scenarios. The restrictions to the optimization model were:total available water, crop water demand, and available land. Local criteria for defining the maximum allowable planted area by crop also were taken into account. The analysis with various water availability scenarios demonstrated that with limited amounts of water for irrigation, forage area would be limited, thereby increasing the area of crops with lower water demands. In both scenarios the area of forage maize was reduced from 11 300 to 1 764 ha.Increasing irrigation water use efficiency may save water for expanding the irrigated area, or for other uses.