Identifying potential zones for rainwater harvesting interventions for sustainable intensification in the semi-arid tropics.

Decentralized rainwater harvesting (RWH) is a promising approach to mitigate drought in the drylands. However, an insufficient understanding of its impact on hydrological processes has resulted in poor resource planning in this area. This study is a meta-analysis of 25 agricultural watersheds representing a range of rainfall and soil types in the semi-arid tropics. Rainfall-runoff-soil loss relationship was calculated at daily, monthly and yearly levels, and the impact of RWH interventions on surface runoff and soil loss was quantified. A linear relationship was observed between daily rainfall and surface runoff up to 120 mm of rainfall intensity, which subsequently saw an exponential increase. About 200-300 mm of cumulative rainfall is the threshold to initiate surface runoff in the Indian semi-arid tropics. Rainwater harvesting was effective in terms of enhancing groundwater availability (2.6-6.9 m), crop intensification (40-100%) and farmers' incomes (50-200%) in different benchmark watersheds. An average of 40 mm of surface runoff was harvested annually and it reduced soil loss by 70% (3 ton/ha/year compared to 1 ton/ha/year in non-intervention stage. The study further quantified runoff at 25th, 50th and 75th percentiles, and found that more than 70% of the area in the Indian semi-arid tropics has high to medium potential for implementing RWH interventions.

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub-Saharan Africa.

Smallholder farmers in sub-Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low-input systems is currently lacking. We evaluated the impact of varying [CO2 ], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi-arid Rwanda, hot subhumid Ghana and hot semi-arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in-season soil water content from 2-year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2 ], temperature and rainfall. Without N fertilizer input, maize (a) benefited less from an increase in atmospheric [CO2 ]; (b) was less affected by higher temperature or decreasing rainfall; and (c) was more affected by increased rainfall because N leaching was more critical. The model intercomparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation approaches across SSA, because the impact of climate change in low input systems will be modified if farmers intensify maize production with balanced nutrient management.

An integrated research framework combining genomics, systems biology, physiology, modelling and breeding for legume improvement in response to elevated CO2 under climate change scenario.

How unprecedented changes in climatic conditions will impact yield and productivity of some crops and their response to existing stresses, abiotic and biotic interactions is a key global concern. Climate change can also alter natural species' abundance and distribution or favor invasive species, which in turn can modify ecosystem dynamics and the provisioning of ecosystem services. Basic anatomical differences in C3 and C4 plants lead to their varied responses to climate variations. In plants having a C3 pathway of photosynthesis, increased atmospheric carbon dioxide (CO2) positively regulates photosynthetic carbon (C) assimilation and depresses photorespiration. Legumes being C3 plants, they may be in a favorable position to increase biomass and yield through various strategies. This paper comprehensively presents recent progress made in the physiological and molecular attributes in plants with special emphasis on legumes under elevated CO2 conditions in a climate change scenario. A strategic research framework for future action integrating genomics, systems biology, physiology and crop modelling approaches to cope with changing climate is also discussed. Advances in sequencing and phenotyping methodologies make it possible to use vast genetic and genomic resources by deploying high resolution phenotyping coupled with high throughput multi-omics approaches for trait improvement. Integrated crop modelling studies focusing on farming systems design and management, prediction of climate impacts and disease forecasting may also help in planning adaptation. Hence, an integrated research framework combining genomics, plant molecular physiology, crop breeding, systems biology and integrated crop-soil-climate modelling will be very effective to cope with climate change.

Accelerating genetic gains in legumes for the development of prosperous smallholder agriculture: integrating genomics, phenotyping, systems modelling and agronomy.

Grain legumes form an important component of the human diet, provide feed for livestock, and replenish soil fertility through biological nitrogen fixation. Globally, the demand for food legumes is increasing as they complement cereals in protein requirements and possess a high percentage of digestible protein. Climate change has enhanced the frequency and intensity of drought stress, posing serious production constraints, especially in rainfed regions where most legumes are produced. Genetic improvement of legumes, like other crops, is mostly based on pedigree and performance-based selection over the past half century. To achieve faster genetic gains in legumes in rainfed conditions, this review proposes the integration of modern genomics approaches, high throughput phenomics, and simulation modelling in support of crop improvement that leads to improved varieties that perform with appropriate agronomy. Selection intensity, generation interval, and improved operational efficiencies in breeding are expected to further enhance the genetic gain in experimental plots. Improved seed access to farmers, combined with appropriate agronomic packages in farmers' fields, will deliver higher genetic gains. Enhanced genetic gains, including not only productivity but also nutritional and market traits, will increase the profitability of farming and the availability of affordable nutritious food especially in developing countries.

Exploring Niches for Short-Season Grain Legumes in Semi-Arid Eastern Kenya - Coping with the Impacts of Climate Variability.

Climate variability is the major risk to agricultural production in semi-arid agroecosystems and the key challenge to sustain farm livelihoods for the 500 million people who inhabit these areas worldwide. Short-season grain legumes have great potential to address this challenge and help to design more resilient and productive farming systems. However, grain legumes display a great diversity and differ widely in growth, development, and resource use efficiency. Three contrasting short season grain legumes common bean (Phaseolus vulgaris L.), cowpea (Vigna unguiculata (L.) Walp.] and lablab [Lablab purpureus (L.) Sweet] were selected to assess their agricultural potential with respect to climate variability and change along the Machakos-Makueni transect in semi-arid Eastern Kenya. This was undertaken using measured data [a water response trial conducted during 2012/13 and 2013/14 in Machakos, Kenya] and simulated data using the Agricultural Production System sIMulator (APSIM). The APSIM crop model was calibrated and validated to simulate growth and development of short-season grain legumes in semi-arid environments. Water use efficiency (WUE) was used as indicator to quantify the production potential. The major traits of adaptation include early flowering and pod and seed set before the onset of terminal drought. Early phenology together with adapted canopy architecture allowed more optimal water use and greater partitioning of dry matter into seed (higher harvest index). While common bean followed a comparatively conservative strategy of minimizing water loss through crop transpiration, the very short development time and compact growth habit limited grain yield to rarely exceed 1,000 kg ha-1. An advantage of this strategy was relatively stable yields independent of in-crop rainfall or season length across the Machakos-Makueni transect. The growth habit of cowpea in contrast minimized water loss through soil evaporation with rapid ground cover and dry matter production, reaching very high grain yields at high potential sites (3,000 kg ha-1) but being highly susceptible to in-season drought. Lablab seemed to be best adapted to dry environments. Its canopy architecture appeared to be best in compromising between the investment in biomass as a prerequisite to accumulate grain yield by minimizing water loss through soil evaporation and crop transpiration. This lead to grain yields of up to 2,000 kg ha-1 at high potential sites and >1,000 kg ha-1 at low potential sites. The variance of observed and simulated WUE was high and no clear dependency on total rainfall alone was observed for all three short-season grain legumes, highlighting that pattern of water use is also important in determining final WUEbiomass and WUEgrain. Mean WUEgrain was lowest for cowpea (1.5-3.5 kggrain ha-1 mm-1) and highest for lablab (5-7 kggrain ha-1 mm-1) reflecting the high susceptibility to drought of cowpea and the good adaptation to dry environments of lablab. Results highlight that, based on specific morphological, phonological, and physiological characteristics, the three short-season grain legumes follow different strategies to cope with climate variability. The climate-smart site-specific utilization of the three legumes offers promising options to design more resilient and productive farming systems in semi-arid Eastern Kenya.

Temporal change in land use by irrigation source in Tamil Nadu and management implications.

Interannual variation in rainfall throughout Tamil Nadu has been causing frequent and noticeable land use changes despite the rapid development in groundwater irrigation. Identifying periodically water-stressed areas is the first and crucial step to minimizing negative effects on crop production. Such analysis must be conducted at the basin level as it is an independent water accounting unit. This paper investigates the temporal variation in irrigated area between 2000-2001 and 2010-2011 due to rainfall variation at the state and sub-basin level by mapping and classifying Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day composite satellite imagery using spectral matching techniques. A land use/land cover map was drawn with an overall classification accuracy of 87.2%. Area estimates between the MODIS-derived net irrigated area and district-level statistics (2000-2001 to 2007-2008) were in 95% agreement. A significant decrease in irrigated area (30-40%) was observed during the water-stressed years of 2002-2003, 2003-2004, and 2009-2010. Major land use changes occurred three times during 2000 to 2010. This study demonstrates how remote sensing can identify areas that are prone to repeated land use changes and pin-point key target areas for the promotion of drought-tolerant varieties, alternative water management practices, and new cropping patterns to ensure sustainable agriculture for food security and livelihoods.