Search

The climate change impact and adaptation simulations from the Agricultural Model Intercomparison and Improvement Project (AgMIP) for wheat provide a unique dataset of multi-model ensemble simulations for 60 representative global locations covering all global wheat mega environments. The multi-model ensemble reported here has been thoroughly benchmarked against a large number of experimental data, including different locations, growing season temperatures, atmospheric CO2 concentration, heat stress scenarios, and their interactions. In this paper, we describe the main characteristics of this global simulation dataset. Detailed cultivar, crop management, and soil datasets were compiled for all locations to drive 32 wheat growth models. The dataset consists of 30-year simulated data including 25 output variables for nine climate scenarios, including Baseline (1980-2010) with 360 or 550 ppm CO2, Baseline +2oC or +4oC with 360 or 550 ppm CO2, a mid-century climate change scenario (RCP8.5, 571 ppm CO2), and 1.5°C (423 ppm CO2) and 2.0oC (487 ppm CO2) warming above the pre-industrial period (HAPPI). This global simulation dataset can be used as a benchmark from a well-tested multi-model ensemble in future analyses of global wheat. Also, resource use efficiency (e.g., for radiation, water, and nitrogen use) and uncertainty analyses under different climate scenarios can be explored at different scales. The DOI for the dataset is 10.5281/zenodo.4027033 (AgMIP-Wheat, 2020), and all the data are available on the data repository of Zenodo (http://doi.org/10.5281/zenodo.4027033). Two scientific publications have been published based on some of these data here.

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

This paper evaluates the usefulness of the Crop Water Stress Index (CWSI) for monitoring transpiration and water status in almond trees, and proposes a methodology for assessing crop yield derived from the relation between canopy temperature and transpiration. For this purpose, a Non-Water Stress Baseline (NWSB) was developed from canopy temperature measurements taken with Infrared Thermometers (IRT) installed permanently over well-watered trees for three years. Tree transpiration was measured continuously with sap flow probes installed in the same trees than the IRT sensors. The calculated CWSI was closely related to water potential and stomatal conductance measured during kernel filling, as well as with transpiration and the ratio kT/GC (the transpiration coefficient over the ground cover). Taking into consideration this relation and the water production function recently published, the seasonal CWSI was compared to final yield and the regression yielded good results (R2 = 0.80). An empirical relationship between the CWSI acquired remotely from two flights performed during the kernel filling stage and crop yield was determined for this orchard. The estimated yield from the proposed methodology was compared to ground-truth measurements of crop yield measured in 80 trees during 2014 and 2015. The result obtained a RMSE that yielded 1.54 kg/tree. This study thus demonstrates that CWSI is closely related to the transpiration and the ratio kT/GC. This relation settles the basis for the development of methodologies for estimating water-limited crop yield from thermal derived information.

Under localized irrigation, even when applying non-limiting amounts of water, there could be transpiration (T) limitations due to a limited wetted soil volume. To study under field conditions how drip-irrigated almond trees responded to a change in wetted soil volume, two treatments were established in summer 2012 in a drip irrigated almond orchard in Cordoba, Spain. One treatment (“Large volume”) was initially irrigated with micro-sprinklers (MS) to wet the entire ground surface, and then reverted to drip irrigation, while other was always kept under drip irrigation (“Small volume”). Continuous monitoring of T and measurements of soil moisture content, tree water status and trunk growth were carried out. Even though trees in both treatments were supplied with sufficient water, the MS application induced an increase in T and an improvement in water status in “Large volume” relative to “Small volume”. A reduction in the hydraulic resistance of the tree was also detected in “Large volume”, as well as an enhancement in canopy conductance and tree growth. We concluded that there are situations in the field where almond tree transpiration is limited by an insufficient wetted soil volume, even when supplied with adequate water, due to a high hydraulic resistance during times of high evaporative demand.

Increased water scarcity demands more efficient use of water in the agricultural sector which is the primary consumer of water. Precise determination of irrigation requirements based on specific crop parameters is needed for accurate water applications. We conducted a 4-year study on almond evapotranspiration using a large weighing lysimeter. Tree canopies changed from 3 to 48 % ground cover during the course of the study. Sap flow measurements made on the lysimeter tree provided a continuous record of tree transpiration. We propose to use the daily fraction of photosynthetically active radiation intercepted by the canopy (fIRd) as a predictor of almond orchard maximum transpiration. The transpiration coefficient (T/ETo or KT) was related to the fIRd of the last two years, and the ratio between fIRd and KT stayed more or less constant around a value of 1.2. Such value extrapolated to the size of a mature orchard with 85 % intercepted radiation gives a KT of around 1.0, a number above the standard recommendations, but fully compatible with the maximum Kc values of 1.1–1.15 recently reported.