Climate-change impacts and adaptation for Pakistan’s irrigated agriculture

Pakistan is one of the most vulnerable counties in terms climate-change impacts on its agricultural productivity. Agriculture is not only the largest sector in Pakistan’s economy, the food security of its over 220 million inhabitants also strongly depends on its production. As Pakistan’s arid croplands are extensively irrigated, agricultural productivity is affected by increasing temperatures (projected to increase up to 6°C between 2000 and 2100 under a limited climate-change mitigation scenario), changes in water availability (i.e. river streamflow and groundwater resources) and atmospheric carbon dioxide concentrations ([CO2]; affecting both crop productivity and water use efficiency). Here we present the impacts of climate change on Pakistan’s primary cereal crops: wheat and rice. Impacts are quantified by combining several climate-change scenarios with a process-based coupled hydrological-crop model, VIC-WOFOST. VIC-WOFOST comprehensively estimates changes in crop growth, water resources and their interactions under climate change. Moreover, the role of elevated [CO2] on agricultural productivity and sustainable water use is specifically assessed. We then explore the possibilities and limitations of agricultural adaptation to enable sustainable food security for Pakistan under various climate-change and population growth scenarios. Our results show that climate-change will severely affect Pakistan’s agriculture, especially due increased temperatures and crop heat stress. However, climate-change adaptation can potentially mitigate some of these effects, especially for wheat production. Moreover, with sufficient agricultural adaptation, climate-change can even be beneficial for Pakistan’s agriculture due to the benefits of elevated [CO2]. While our study is focussed on Pakistan, it indicates pathways for sustainable food production under climate change that may also be important for other regions that strongly depend on irrigated agriculture

Examining wheat yield sensitivity to temperature and precipitation changes for a large ensemble of crop models using impact response surfaces

Impact response surfaces (IRSs) depict the response of an impact variable to changes in two explanatory variables as a plotted surface. Here, IRSs of spring and winter wheat yields were constructed from a 25-member ensemble of process-based crop simulation models. Twenty-one models were calibrated by different groups using a common set of calibration data, with calibrations applied independently to the same models in three cases. The sensitivity of modelled yield to changes in temperature and precipitation was tested by systematically modifying values of 1981-2010 baseline weather data to span the range of 19 changes projected for the late 21st century at three locations in Europe

Evidence for increasing global wheat yield potential

Wheat is the most widely grown food crop, with 761 Mt produced globally in 2020. To meet the expected grain demand by mid-century, wheat breeding strategies must continue to improve upon yield-advancing physiological traits, regardless of climate change impacts. Here, the best performing doubled haploid (DH) crosses with an increased canopy photosynthesis from wheat field experiments in the literature were extrapolated to the global scale with a multi-model ensemble of process-based wheat crop models to estimate global wheat production. The DH field experiments were also used to determine a quantitative relationship between wheat production and solar radiation to estimate genetic yield potential. The multi-model ensemble projected a global annual wheat production of 1050 +/- 145 Mt due to the improved canopy photosynthesis, a 37% increase, without expanding cropping area. Achieving this genetic yield potential would meet the lower estimate of the projected grain demand in 2050, albeit with considerable challenges

Global wheat production with 1.5 and 2.0°C above pre‐industrial warming

Efforts to limit global warming to below 2°C in relation to the pre‐industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre‐industrial period) on global wheat production and local yield variability. A multi‐crop and multi‐climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by −2.3% to 7.0% under the 1.5°C scenario and −2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980–2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter‐annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer—India, which supplies more than 14% of global wheat. The projected global impact of warming <2°C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade

Probabilistic assessment of adaptation options from an ensemble of crop models: a case study in the Mediterranean

Effective adaptation of agricultural systems to climate change has to: Consider local specificities; provide sound and practical information and deal with the uncertainty We present a methodology for assessing different aspects of adaptation. Our study case is adaptation of winter wheat in the Mediterranean

Wheat yield sensitivity to climate change across a European transect for a large ensemble of crop models

The sensitivity of a 26 member ensemble of process based wheat simulation models to perturbations in baseline temperature and precipitation was examined to construct impact response surfaces (IRS) of simulated yields

Similar estimates of temperature impacts on global wheat yield by three independent methods

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify ‘method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.<br/