Do rainfed production systems have lower environmental impact over irrigated production systems?: On -farm mitigation strategies.

The intensive agriculture practices improved the crop productivity but escalated energy inputs (EI) and carbon foot print (CF) which contributes to global warming. Hence designing productive, profitable crop management practices under different production systems with low environmental impact (EI and CF) is the need of the hour. To identify the practices, quantification of baseline emissions and the major sources of emissions are required. Indian agriculture has diversified crops and production systems but there is dearth of information on both EI and CF of these production systems and crops. Hence the present study was an attempt to find hot spots and identify suitable strategies with high productivity, energy use efficiency (EUE) and carbon use efficiency (CUE). Energy and carbon balance of castor, cotton, chickpea, groundnut, maize, rice (both rainfed and irrigated), wheat, sugarcane (only irrigated), pigeon pea, soybean, sorghum, pearl millet (only rainfed) in different production systems was assessed. Field specific data on different crop management practices as well as grain and biomass yields were considered. Rainfed production systems had lower EI and CF than irrigated system. The nonrenewable sources of energy like fertilizer (64 %), irrigation (78 %), diesel fuel (75 %) and electricity (67 %) are the major source of energy input. Rainfed crops recorded higher CUE over irrigated condition. Adoption of technologies like efficient irrigation strategies (micro irrigation), enhancing fertilizer use efficiency (site specific nutrient management or slow release fertilizer), conservation agriculture (conservation or reduced tillage) rice cultivation methods (SRI or Direct seeded rice) were the mitigation strategies. These results will help policy makers and stake holders in adoption of suitable strategies for sustainable intensification.

Pest scenario of Helicoverpa armigera (Hub.) on pigeonpea during future climate change periods under RCP based projections in India.

Gram pod borer, Helicoverpa armigera (Hub.) is the major insect pest of pigeonpea and prediction of number of generations (no. of gen.) and generation time (gen. time) using growing degree days (GDD) approach during three future climate change periods viz., Near (NP), Distant (DP) and Far Distant (FDP) periods at eleven major pigeonpea growing locations of India was attempted. Multi-model ensemble of Maximum (Tmax) and Minimum (Tmin) temperature data of four Representative Concentration Pathways viz., RCP 2.6, 4.5, 6.0 and 8.5 of Coupled Model Inter comparison Project 5 (CMIP5) models was adopted here. The increase in projected Tmax and Tmin are significant during 3 climate change periods (CCPs) viz., the NP, DP and FDP over base line (BL) period under four RCP scenarios at all locations and would be higher (4.7-5.1 °C) in RCP 8.5 and in FDP. More number of annual (10-17) and seasonal (5-8) gens. are expected to occur with greater percent increase in FDP (8 to 38%) over base line followed by DP (7 to 22%) and NP (5to 10%) periods with shortened annual gen. time (4 to 27%) across 4 RCPs. The reduction of crop duration was substantial in short, medium and long duration pigeonpeas at all locations across 4 RCPs and 3 CCPs. The seasonal no.of gen. is expected to increase (5 to 35%) with shortened gen. time (4 to 26%) even with reduced crop duration across DP and FDP climate periods of 6.0 and 8.5 RCPs in LD pigeonpea. More no. of gen. of H. armigera with reduced gen. time are expected to occur at Ludhiana, Coimbatore, Mohanpur, Warangal and Akola locations over BL period in 4 RCPs when normal duration of pigeonpeas is considered. Geographical location (66 to 72%), climate period (11 to 19%), RCPs (5-7%) and their interaction (0.04-1%) is vital and together explained more than 90% of the total variation in future pest scenario. The findings indicate that the incidence of H. armigera would be higher on pigeonpea during ensuing CCPs in India under global warming context.

Evaluating area-specific adaptation strategies for rainfed maize under future climates of India.

This study investigates the spatio-temporal changes in maize yield under projected climate and identified the potential adaptation measures to reduce the negative impact. Future climate data derived from 30 general circulation models were used to assess the impact of future climate on yield in 16 major maize growing districts of India. DSSAT model was used to simulate maize yield and evaluate adaptation strategies during mid (2040-69) and end-centuries (2070-99) under RCP 4.5 and 8.5. Genetic coefficients were calibrated and validated for each of the study locations. The projected climate indicated a substantial increase in mean seasonal maximum (0.9-6.0 °C) and minimum temperatures (1.1-6.1 °C) in the future (the range denotes the lowest and highest change during all the four future scenarios). Without adaptation strategies, climate change could reduce maize yield in the range of 16% (Tumkur) to 46% (Jalandhar) under RCP 4.5 and 21% (Tumkur) to 80% (Jalandhar) under RCP 8.5. Only at Dharwad, the yield could remain slightly higher or the same compared to the baseline period (1980-2009). Six adaptation strategies were evaluated (delayed sowing, increase in fertilizer dose, supplemental irrigation, and their combinations) in which a combination of those was found to be effective in majority of the districts. District-specific adaptation strategies were identified for each of the future scenarios. The findings of this study will enable in planning adaptation strategies to minimize the negative impact of projected climate in major maize growing districts of India.

Runoff and soil erosion in the integrated farming systems based on micro-watersheds under projected climate change scenarios and adaptation strategies in the eastern Himalayan mountain ecosystem (India).

Land degradation caused by soil erosion (SE) in forests converted into cropland under climate change, particularly with increased rainfall intensity, is of great concern to the agricultural sustainability of the tropical mountain ecosystem. We evaluated the response of six hilly micro-watersheds (HMW) under different Integrated Farming Systems (IFSs) to SE in multi-model climate change scenarios using the Water Erosion Prediction Project (WEPP) model. The IFSs were forestry (HMW1), abandoned shifting cultivation (HMW2), livestock with fodder crops (HMW3), agroforestry (HMW4), agri-horti-silvi-pastoral (HMW5), and horticulture (HMW6) established on a hilly slope (32.0-53.2%) of the eastern Himalayas (Meghalaya, India). The WEPP model was calibrated and validated with measured runoff and soil loss data of 24 years for each of the six IFSs. The projected annual SE (average) for all HMWs increased in all RCPs. The IFS based on shifting cultivation (HMW2) was the most vulnerable, with the highest percentage increase in SE (46-235%) compared to the baseline years (1976-2005) under RCP 8.5. The cultivated IFSs (HMW3 to HMW6) had 47.8-57.0% less runoff and 39.2-74.6% less soil loss than HMW2 under RCP 8.5. Of these, HMW6 followed by HMW4 and HMW5 were the most effective at minimizing soil loss. Simulation results showed a reduction in soil loss through adaptive strategies such as mulching with broom grasses, stones, field beans, and the introduction of subsurface drainage. Adoption of IFS based on horticulture and agroforestry with bio-mulching on steep slopes is an effective measure to control soil erosion in the eastern Himalaya (India).

A high-resolution assessment of climate change impact on water footprints of cereal production in India.

Water footprint (WF), a comprehensive indicator of water resources appropriation, has evolved as an efficient tool to improve the management and sustainability of water resources. This study quantifies the blue and green WF of major cereals crops in India using high resolution soil and climatic datasets. A comprehensive modelling framework, consisting of Evapotranspiration based Irrigation Requirement (ETIR) tool, was developed for WF assessment. For assessing climate change impact on WF, multi-model ensemble climate change scenarios were generated using the hybrid-delta ensemble method for RCP4.5 and RCP6.0 and future period of 2030s and 2050s. The total WF of the cereal crops are projected to change in the range of - 3.2 to 6.3% under different RCPs in future periods. Although, the national level green and blue WF is projected to change marginally, distinct trends were observed for Kharif (rainy season-June to September) and rabi (winter season-October to February) crops. The blue WF of paddy is likely to decrease by 9.6%, while for wheat it may increase by 4.4% under RCP4.5 during 2050s. The green WF of rabi crops viz. wheat and maize is likely to increase in the range of 20.0 to 24.1% and 9.9 to 16.2%, respectively. This study provides insights into the influences of climate change on future water footprints of crop production and puts forth regional strategies for future water resource management. In view of future variability in the WFs, a water footprint-based optimization for relocation of crop cultivation areas with the aim of minimising the blue water use would be possible management alternative.

Pest scenario of Spodoptera litura (Fab.) on groundnut under representative concentration pathways (RCPs) based climate change scenarios.

Multi-model ensemble of Maximum (Tmax) and Minimum (Tmin) temperature data of four Representative Concentration Pathways viz., RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 of Coupled Model Intercomparison Project 5 (CMIP5) models were generated for ten major groundnut growing locations of the India to predict the number of generations of Spodoptera litura (Fab.) using Growing Degree Days approach during three future climate viz., Near (NF), Distant (DF) and Very Distant (VDF) periods and were compared over 1976-2005 baseline period (BL). Projections indicate significant increase in Tmax (0.7-4.7 °C) and Tmin (0.7-5.1 °C) in NF, DF and VDF periods under the four RCP scenarios at the ten groundnut growing locations. Higher percent increase of the number of generations of S. litura was predicted to occur in VDF (6-38%) over baseline, followed by DF (5-22%) and NF (4-9%) periods with reduction of generation time (5-26%) across the four RCP scenarios. Reduction of crop duration was higher (12-22 days) in long duration groundnut than in medium and short duration groundnut. Decrease in crop duration was higher in VDF (12.1-20.8 days) than DF (8.26-13.15 days) and NF (4.46-6.15 days) climate change periods under RCP 8.5 scenario. Increase in number of generations of S. litura was predicted even with altered crop duration of groundnut. Among locations, more number of generations of S. litura with reduced generation time are likely at Vridhachalam and Tirupathi locations. Geographical location (74-77%) and climate period (15-19%), together explained over 90 percent of the total variation in the number of generations and generation time of S. litura. These findings suggest that the incidence of S. litura on groundnut could be higher in future.

Impact of arsenic-polluted groundwater on soil and produce quality: a food chain study.

The experiment was conducted to assess the impact of arsenic (As)-contaminated groundwater irrigation on soil health and crop quality. Geo-referenced groundwater, soil, and crop produce samples were collected from the middle Gangetic plains of Maner block of Patna and were analyzed for As content. The result showed that long-term application of As-contaminated groundwater (0.017 to 0.677 mg L-1) buildup significant amount of As in the soil (0.41 to 8.66 mg kg-1). A significant correlation (r2 = 0.922) was also observed between As content in groundwater and the soil. The content of As in groundwater also affected crop quality and accumulated metal content in different crop parts. Total As content in crop samples ranged from 0.010 to 0.963 µg g-1 of dry weight. The average As content in crop followed order: oilseeds > cereals > vegetables > pulses. Therefore, produce quality should be monitored frequently for As uptake as there is a great chance of As accumulation in food crops. Hence, these approaches are useful for the formulation of policy guidelines for the management of As-containing groundwater and routine risk assessment of As-contaminated soils.

Trends and probabilistic stability index for evaluating groundwater quality: The case of quaternary alluvial and quartzite aquifer system of India.

This study proposed a novel groundwater-quality stability index (GQSI), which considers probabilistic estimate of reliability and resilience based on multi-year dataset. The developed index is validated and optimized adopting optimum index factor approach. The vulnerabilities of different groundwater quality parameters are also computed to provide an insight about the deviations of their concentrations from the safe drinking water limits. The application of the developed stability index is demonstrated through a case study in quaternary alluvial and quartzite aquifer system of India. In addition, trends in the groundwater quality parameters are identified by using variance-corrected Mann-Kendall test, and trends are quantified by using Sen's slope estimation test. Box-whisker plots revealed that EC and TDS mostly exceed their maximum permissible limits prescribed for drinking water in the southern and southwest hard-rock formations. Whereas, most parameters do not cross their maximum desirable limits in the central and northern alluvial formations. Increasing trends of potassium and bicarbonate, and decreasing trends of carbonate, calcium, sulfate, and fluoride are found prominent. The GQSI values indicated high stability of groundwater quality under older alluvium geology and low stability under the gneiss and mica-schist. Results of the GQSI are found in agreement with that of groundwater-quality index (GQI) at 84% sites, which proved adequacy of the developed GQSI. Also, three classes ('low'/'poor', 'moderate', and 'high'/'good') of both the GQSI and GQI showed a good coherence at 83, 78, and 87% sites. However, GQSI is more advantageous than GQI due to former's statistical framework, consistency and comparability over different areas. Three optimum index factors, i.e., TDS, pH and nitrate, are found to have the maximum impact on overall groundwater quality with their largest variations. Results of the optimum groundwater-quality stability index (OGQSI) and GQSI closely matched with each other, and a significant linear relationship (R2 = 0.70) existed between them. Therefore, OGQSI is a cost-effective approach for adequate monitoring and satisfactory evaluation of the groundwater quality in low-income nations.

Climate change impacts on irrigated rice and wheat production in Gomti River basin of India: a case study.

Potential future impacts of climate change on irrigated rice and wheat production and their evapotranspiration and irrigation requirements in the Gomti River basin were assessed by integrating a widely used hydrological model "Soil and Water Assessment Tool (SWAT)" and climate change scenario generated from MIROC (HiRes) global climate model. SWAT model was calibrated and validated using monthly streamflow data of four spatially distributed gauging stations and district wise wheat and rice yields data for the districts located within the basin. Simulation results showed an increase in mean annual rice yield in the range of 5.5-6.7, 16.6-20.2 and 26-33.4 % during 2020s, 2050s and 2080s, respectively. Similarly, mean annual wheat yield is also likely to increase by 13.9-15.4, 23.6-25.6 and 25.2-27.9 % for the same future time periods. Evapotranspiration for both wheat and rice is projected to increase in the range of 3-9.6 and 7.8-16.3 %, respectively. With increase in rainfall during rice growing season, irrigation water allocation for rice is likely to decrease (<5 %) in future periods, but irrigation water allocation for wheat is likely to increase by 17.0-45.3 % in future periods.