Climate Change is real and its implications are going to be borne by the poorest of the poor. If climatic change is accompanied by an increase in climate variability, many agricultural Producers will experience define hardships and increased risk. The Sat regions, which have economies largely based on weather-sensitive agricultural productions systems, are particularly vulnerable to climate change...............................

Nutrient imbalance and soil moisture stress are the major abiotic constraints limiting productivity of cool season food legumes. These constraints are more pronounced in the semi-arid tropics and sub-tropics which are the principal production zones of chickpea, lentil and faba bean. The legumes are generally grown on residual moisture as a mono crop and consequently face drought especially during the reproductive phase. In recent years, chickpea, lentil, peas and faba bean have been grown in some areas with an irrigated/assured water supply under intensive cropping to sustain cereal based systems. An increased water supply favourably influences productivity in dry environments. Faba bean, French beans and peas show a relatively better response to irrigation. The pod initiation stage is considered most critical with respect to moisture stress. Excessive moisture often has a negative effect on podding and seed yield. Eighty to ninety percent of the nitrogen requirements of leguminous crops is met from N2 fixation hence a dose of 15–25 kg N ha-1 has been recommended. However, in new cropping systems like rice-chickpea, higher doses of 30–40 kg N ha-1 are beneficial. Phosphorus deficiency is wide spread and good responses occur to 20 to 80 kg P2O5 ha-1, depending on the nutrient status of soil, cropping systems and moisture availability. Response to potassium application is localized. The use of 20–30 kg S ha-1 and some of the micronutrients such as Zn, B, Mo and Fe have improved productivity. Band placement of phosphatic fertilizers and use of bio-fertilizers has enhanced the efficiency of applied as well as native P. Foliar applications of some micronutrients have been effective in correcting deficiencies. Water use efficiency has been improved with some management practices such as changed sowing time, balanced nutrition, mulching and tillage.

Food-energy-water (FEW) systems are increasingly vulnerable to natural hazards and climate change risks, yet humans depend on these systems for their daily needs, wellbeing, and survival. We investigated how adaptations related to FEW vulnerabilities are occurring and what the global community can learn about the interactions across these adaptations. We conducted a global analysis of a data set derived from scientific literature to present the first large scale assessment (n = 1,204) of evidence-based FEW-related climate adaptations. We found that the most frequently reported adaptations to FEW vulnerabilities by continent occurred in Africa (n = 495) and Asia (n = 492). Adaptations targeting food security were more robustly documented than those relevant to water and energy security, suggesting a greater global demand to address food security. Determining statistically significant associations, we found a network of connections between variables characterizing FEW-related adaptations and showed interconnectedness between a variety of natural hazards, exposures, sectors, actors, cross-cutting topics and geographic locations. Connectivity was found between the vulnerabilities food security, water, community sustainability, and response to sea level rise across cities, settlements, and key infrastructure sectors. Additionally, generalized linear regression models revealed potential synergies and tradeoffs among FEW adaptations, such as a necessity to synergistically adapt systems to protect food and water security and tradeoffs when simultaneously addressing exposures of consumption and production vs. poverty. Results from qualitative thematic coding showcased that adaptations documented as targeting multiple exposures are still limited in considering interconnectivity of systems and applying a nexus approach in their responses. These results suggest that adopting a nexus approach to future FEW-related adaptations can have profound benefits in the management of scarce resources and with financial constraints.

Non-irrigated (rainfed) agriculture is the major crop production system worldwide. It occupies large proportion of total land areas in Asia (88 %) and Africa (99 %). In some important food legume growing countries in South Asia, r

This publication is a product of an ongoing collaborative research project between the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) and the International Food Policy Research Institute (IFPRI). The project aims to introduce dryland crops into the updated IMPACT model and undertake strategic analysis of future opportunities and challenges for SAT agriculture. We would like to extend our sincere thanks to Mark Rosegrant, for providing the necessary background material for the training workshop from which this technical manual has been developed. Special thanks are to Siet Meijer for sharing her experience and offering the training at ICRISAT Patancheru (India), which was very useful in introducing the different variants of the IMPACT model to ICRISAT staff. We also appreciate the coordination and cooperation rendered by our staff to make the training program a success. We thank the Learning System Unit for providing us the necessary logistical support for the training.

This study aims at analyzing the impact of water and soil conservation strategies on households’ food security in the North-western part of Benin. It was conducted in the municipalities of Boukombé and Ouaké. Three villages were studied. From random way, 180 producers were investigated. The causes of soil degradation, water and soil conservation strategies, available food supply and food consumption frequency were collected. Degradation factors were analyzed using discourse analysis and prioritized using the Friedman test. Food supply and frequency of consumption were compared between beneficiaries and non-beneficiaries of the projects using the Student t test. Land degradation is caused by socio-cultural factors (overexploitation of lands, trees’ cutting, late bush fires, grazing, agroforestry and monoculture) and natural factors (heavy rains and steep gradient of the soils). The first three factors are respectively the exploitation of land, trees’ cutting and late bush fires practice in both towns. Food reserves before the new crops were not affected by exogenous strategies released by the erosion control projects. But the frequency of food consumption is improved statistically among project beneficiaries than non-beneficiaries. This confirms the theory of Boserup.

Phenological development is the single most important attribute of crop adaptation to shifting climates. Climate change may alter the rate of phenological development and the amount and distribution of rainfall during the growing season. These changes may in turn result in mismatch between water demand by crops and water availability from rainfall. This paper illustrates how an understanding of the impact of climate shifts on key crops will enable the Asia-Pacific farmers, community workers and policy agencies to better prepare and adapt to climate change. Strategies include changes to existing policy and practices, for example, timing of planting, managing rainwater resources, use of new varieties, disease management protocols, alternate crops and shift in geographic distribution of crops. An international project is described which combines a new analysis of realized changes in meteorological parameters, and use of estimates from published work on future climates to assess temporal shifts in crop phenology, likely shifts in the pattern of rain and water availability, mismatch between crop phenology and water availability, and the expected consequences of this mismatch for food security.

Smallholder irrigation is an important pathway towards better livelihoods and food security in sub-Saharan Africa. This article assesses the contribution of farmer-friendly soil and water monitoring tools, and agricultural innovation platforms, towards household income and food security in two small-scale irrigation schemes in Tanzania. Quantitative and qualitative data from farmer’s field books, household surveys and focus groups were used to assess the impacts of the two interventions. The two interventions together contributed to enhancing smallholders’ food security and household income in the two schemes, as did the agricultural innovation platform on its own.

This paper presents an exhaustive review of global croplands and their water use, for the end of last millennium, mapped using remote sensing and non-remote sensing approaches by world’s leading researchers on the subject. A comparison at country scale of global cropland area estimated by these studies had a high R2-value of 0.89–0.94. The global cropland area estimates amongst different studies are quite close and range between 1.47–1.53 billion hectares. However, significant uncertainties exist in determining irrigated areas which, globally, consume nearly 80% of all human water use. The estimates show that the total water use by global croplands varies between 6,685 to 7,500 km3 yr−1 and of this around 4,586 km3 yr−1 is by rainfed croplands (green water use) and the rest by irrigated croplands (blue water use). Irrigated areas use about 2,099 km3 yr−1 (1,180 km3 yr−1 of blue water and the rest from rain that falls over irrigated croplands). However, 1.6 to 2.5 times the blue water required by irrigated croplands is actually withdrawn from reservoirs or pumping of ground water, suggesting an irrigation efficiency of only between 40–62 percent. The weaknesses, trends, and future directions to precisely estimate the global croplands are examined. Finally, the paper links global croplands and their water use to a paradigm for ensuring future food security.

Cropland products are of great importance in water and food security assessments, especially in South Asia, which is home to nearly 2 billion people and 230 million hectares of net cropland area. In South Asia, croplands account for about 90% of all human water use. Cropland extent, cropping intensity, crop watering methods, and crop types are important factors that have a bearing on the quantity, quality, and location of production. Currently, cropland products are produced using mainly coarse-resolution (250–1000 m) remote sensing data. As multiple cropland products are needed to address food and water security challenges, our study was aimed at producing three distinct products that would be useful overall in South Asia. The first of these, Product 1, was meant to assess irrigated versus rainfed croplands in South Asia using Landsat 30 m data on the Google Earth Engine (GEE) platform. The second, Product 2, was tailored for major crop types using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m data. The third, Product 3, was designed for cropping intensity (single, double, and triple cropping) using MODIS 250 m data. For the kharif season (the main cropping season in South Asia, Jun–Oct), 10 major crops (5 irrigated crops: rice, soybean, maize, sugarcane, cotton; and 5 rainfed crops: pulses, rice, sorghum, millet, groundnut) were mapped. For the rabi season (post-rainy season, Nov–Feb), five major crops (three irrigated crops: rice, wheat, maize; and two rainfed crops: chickpea, pulses) were mapped. The irrigated versus rainfed 30 m product showed an overall accuracy of 79.8% with the irrigated cropland class providing a producer’s accuracy of 79% and the rainfed cropland class 74%. The overall accuracy demonstrated by the cropping intensity product was 85.3% with the producer’s accuracies of 88%, 85%, and 67% for single, double, and triple cropping, respectively. Crop types were mapped to accuracy levels ranging from 72% to 97%. A comparison of the crop-type area statistics with national statistics explained 63–98% variability. The study produced multiple-cropland products that are crucial for food and water security assessments, modeling, mapping, and monitoring using multiple-satellite sensor big-data, and Random Forest (RF) machine learning algorithms by coding, processing, and computing on the GEE cloud.