The simultaneous prediction of yield and maturity date for wheat-maize by combining satellite images with crop model.

BACKGROUND: The simultaneous prediction of yield and maturity date has an important impact on ensuring food security. However, few studies have focused on simultaneous prediction of yield and maturity date for wheat-maize in the North China Plain (NCP). In this study, we developed the prediction model of maturity date and yield (PMMY) for wheat-maize using multi-source satellite images, an Agricultural Production Systems sIMulator (APSIM) model and a random forest (RF) algorithm. RESULTS: The results showed that the PMMY model using peak leaf area index (LAI) and accumulated evapotranspiration (ET) has the optimal performance in the prediction of maturity date and yield. The accuracy of the PMMY model using peak LAI and accumulated ET was higher than that of the PMMY model using only peak LAI or accumulated ET. In a single year, the PMMY model had good performance in the prediction of maturity date and yield. The latitude variation in spatial distribution of maturity date for WM was obvious. The spatial heterogeneity for yield of wheat-maize was not prominent. Compared with 2001-2005, the maturity date of the two crops in 2016-2020 advanced 1-2 days, while yield increased 659-706 kg ha-1. The increase in minimum temperature was the main meteorological factor for advance in the maturity date for wheat-maize. Precipitation was mainly positively correlated with maize yield, while the increase in minimum temperature and solar radiation was crucial to the increase in yield. CONCLUSION: The simultaneous prediction of yield and maturity can be used to guide agricultural production and ensure food security. © 2024 Society of Chemical Industry.

Climate Change Impact on Yield and Water Use of Rice-Wheat Rotation System in the Huang-Huai-Hai Plain, China.

Global climate change has had a significant impact on crop production and agricultural water use. Investigating different future climate scenarios and their possible impacts on crop production and water consumption is critical for proposing effective responses to climate change. In this study, based on daily downscaled climate data from 22 Global Climate Models (GCMs) provided by Coupled Model Intercomparison Project Phase 6 (CMIP6), we applied the well-validated Agricultural Production Systems sIMulator (APSIM) to simulate crop phenology, yield, and water use of the rice-wheat rotation at four representative stations (including Hefei and Shouxian stations in Anhui province and Kunshan and Xuzhou stations in Jiangsu province) across the Huang-Huai-Hai Plain, China during the 2041-2070 period (2050s) under four Shared Socioeconomic Pathways (i.e., SSP126, SSP245, SSP370, and SSP585). The results showed a significant increase in annual mean temperature (Temp) and solar radiation (Rad), and annual total precipitation (Prec) at four investigated stations, except Rad under SSP370. Climate change mainly leads to a consistent advance in wheat phenology, but inconsistent trends in rice phenology across four stations. Moreover, the reproductive growth period (RGP) of wheat was prolonged while that of rice was shorted at three of four stations. Both rice and wheat yields were negatively correlated with Temp, but positively correlated with Rad, Prec, and CO2 concentration ([CO2]). However, crop ET was positively correlated with Rad, but negatively correlated with [CO2], as elevated [CO2] decreased stomatal conductance. Moreover, the water use efficiency (WUE) of rice and wheat was negatively correlated with Temp, but positively correlated with [CO2]. Overall, our study indicated that the change in Temp, Rad, Prec, and [CO2] have different impacts on different crops and at different stations. Therefore, in the impact assessment for climate change, it is necessary to explore and analyze different crops in different regions. Additionally, our study helps to improve understanding of the impacts of climate change on crop production and water consumption and provides data support for the sustainable development of agriculture.

Simulation of Wheat Response to Future Climate Change Based on Coupled Model Inter-Comparison Project Phase 6 Multi-Model Ensemble Projections in the North China Plain.

Global climate change results in more extreme temperature events, which poses a serious threat to wheat production in the North China Plain (NCP). Assessing the potential impact of temperature extremes on crop growth and yield is an important prerequisite for exploring crop adaptation measures to deal with changing climate. In this study, we evaluated the effects of heat and frost stress during wheat sensitive period on grain yield at four representative sites over the NCP using Agricultural Production System Simulator (APSIM)-wheat model driven by the climate projections from 20 Global Climate Models (GCMs) in the Coupled Model Inter-comparison Project phase 6 (CMIP6) during two future periods of 2031-2060 (2040S) and 2071-2100 (2080S) under societal development pathway (SSP) 245 and SSP585 scenarios. We found that extreme temperature stress had significantly negative impacts on wheat yield. However, increased rainfall and the elevated atmospheric CO2 concentration could partly compensate for the yield loss caused by extreme temperature events. Under future climate scenarios, the risk of exposure to heat stress around flowering had no great change but frost risk in spring increased slightly mainly due to warming climate accelerating wheat development and advancing the flowering time to a cooler period of growing season. Wheat yield loss caused by heat and frost stress increased by -0.6 to 4.2 and 1.9-12.8% under SSP585_2080S, respectively. We also found that late sowing and selecting cultivars with a long vegetative growth phase (VGP) could significantly compensate for the negative impact of extreme temperature on wheat yields in the south of NCP. However, selecting heat resistant cultivars in the north NCP and both heat and frost resistant cultivars in the central NCP may be a more effective way to alleviate the negative effect of extreme temperature on wheat yields. Our findings showed that not only heat risk should be concerned under climate warming, but also frost risk should not be ignored.

Using large-scale climate drivers to forecast meteorological drought condition in growing season across the Australian wheatbelt.

Recurring drought has caused large crop yield losses in Australia during past decades. Long-term drought forecasting is of great importance for the development of risk management strategies. Recently, large-scale climate drivers (e.g. El Niño-Southern Oscillation) have been demonstrated as useful in the application of drought forecasting. Machine learning-based models that use climate drivers as input are commonly adopted to provide drought forecasts as these models are easy to develop and require less information compared to physical-based models. However, few machine learning-based models have been developed to forecast drought conditions during growing season across all Australian cropping areas. In this study, we developed a growing season (Apr.-Nov.) meteorological drought forecasting model for each climate gauging location across the Australian wheatbelt based on multiple lagged (past) large-scale climate indices and the Random Forest (RF) algorithm. The Standardized Precipitation Index (SPI) was used as the response variable to measure the degree of meteorological drought. Results showed that the RF model could provide satisfactory drought forecasts in the eastern areas of the wheatbelt with Pearson's correlation coefficient r > 0.5 and normalized Root Mean Square Error (nRMSE) < 23%. Forecasted drought maps matched well with observed drought maps for three representative periods. We identified NINO3.4 sea surface temperature and Multivariate ENSO Index as the most influential indices dominating growing season drought conditions across the wheatbelt. In addition, lagged impacts of large-scale climate drivers on growing season drought conditions were long-lasting and the indices in previous year could also potentially affect drought conditions during current year. As large-scale climate indices are readily available and can be rapidly used to feed data driven models, we believe the proposed meteorological drought forecasting models can be easily extended to other regions to provide drought outlooks which can help mitigate adverse drought impacts.

Sources of uncertainty for wheat yield projections under future climate are site-specific.

Understanding sources of uncertainty in climate-crop modelling is critical for informing adaptation strategies for cropping systems. An understanding of the major sources of uncertainty in yield change is needed to develop strategies to reduce the total uncertainty. Here, we simulated rain-fed wheat cropping at four representative locations in China and Australia using eight crop models, 32 global climate models (GCMs) and two climate downscaling methods, to investigate sources of uncertainty in yield response to climate change. We partitioned the total uncertainty into sources caused by GCMs, crop models, climate scenarios and the interactions between these three. Generally, the contributions to uncertainty were broadly similar in the two downscaling methods. The dominant source of uncertainty is GCMs in Australia, whereas in China it is crop models. This difference is largely due to uncertainty in GCM-projected future rainfall change across locations. Our findings highlight the site-specific sources of uncertainty, which should be one step towards understanding uncertainties for more robust climate-crop modelling.

Impact of warming climate, sowing date, and cultivar shift on rice phenology across China during 1981-2010.

Climate change would exert significantly impact on crop yield by altering crop growth and development processes. Therefore, to ensure food security, it is necessary to assess the response and adaptation of crop phenology to the natural (mainly climate change) and artificial (including sowing date (SD) change and cultivar shift) factors. In this study, using field data from 113 agro-meteorological experiment stations across China, along with the Agricultural Production System Simulator (APSIM) oryza model, we investigated the trends of rice phenology in relation to climate change and agronomic factors (i.e., SD change and cultivar shift) from 1981 to 2010. We found that flowering date (FD) and maturity date (MD) of single-rice were delayed by 0.3 and 1.4 days 10a-1, respectively, but FD and MD of double-rice were advanced by 0.7-0.8 and 0.2-1.1 days 10a-1, respectively. Climate change advanced FD and MD of rice at representative stations except FD of late-rice, and shortened length of rice growth period. SD change of rice mainly affected duration of vegetative growth phase (VGP, from SD to FD), but had no significant impact on duration of reproductive growth phase (RGP, from FD to MD). Cultivar shift delayed FD and MD of rice at all representative stations except late-rice at Lianhua. Moreover, cultivar shift prolonged the duration of rice RGP by 0.2-2.8 days 10a-1. Overall, the results suggested that rice phenology was adapting to ongoing climate change by SD change and adoption of cultivars with longer RGP. Therefore, crop phenological characteristics should be sufficiently taken into account to develop adaptation strategies in the future.

Climate-associated rice yield change in the Northeast China Plain: A simulation analysis based on CMIP5 multi-model ensemble projection.

Multi-model ensemble climate projections in combination with crop models are increasingly used to assess the impact of future climate change on agricultural systems. In this study, we used a biophysical process-oriented CERES-Rice crop model driven by downscaled future climate data from 28 Global Climate Models (GCMs) under two emissions scenarios: representative concentration pathway (RCP) 4.5 and RCP8.5, for phase five of the Coupled Model Intercomparison Project (CMIP5) to project the effects of climate change on rice yields in three future time periods in the Northeast China Plain (NECP). The results showed that without consideration of CO2 effects, rice yield would increase by 1.3%, 1.3%, and 0.4% in the 2030s, 2060s, and 2090s, respectively, under the RCP4.5 scenario. Rice yield would change by +1.1%, -2.3%, and -10.7% in the 2030s, 2060s, and 2090s, respectively, under the RCP8.5 scenario. With consideration of CO2 effects, rice yield during the 2030s, 2060s, and 2090s would increase by 5.4%, 10.0%, and 11.6% under RCP4.5, and by 6.4%, 12.9%, and 15.6% under RCP8.5, respectively. The rice-growing season would be shortened by 2 to 5 weeks in the future. Overall, the future climate would have positive effects on rice yields in the NECP. Although uncertainties in our study on the impact of climate change on rice might arise from the choice of crop model and GCMs, the results are important for informing policy makers and developing appropriate strategies to improve rice productivity in China.

Attribution of hydrological change in Heihe River Basin to climate and land use change in the past three decades.

The contributions of climate and land use change (LUCC) to hydrological change in Heihe River Basin (HRB), Northwest China were quantified using detailed climatic, land use and hydrological data, along with the process-based SWAT (Soil and Water Assessment Tool) hydrological model. The results showed that for the 1980s, the changes in the basin hydrological change were due more to LUCC (74.5%) than to climate change (21.3%). While LUCC accounted for 60.7% of the changes in the basin hydrological change in the 1990s, climate change explained 57.3% of that change. For the 2000s, climate change contributed 57.7% to hydrological change in the HRB and LUCC contributed to the remaining 42.0%. Spatially, climate had the largest effect on the hydrology in the upstream region of HRB, contributing 55.8%, 61.0% and 92.7% in the 1980s, 1990s and 2000s, respectively. LUCC had the largest effect on the hydrology in the middle-stream region of HRB, contributing 92.3%, 79.4% and 92.8% in the 1980s, 1990s and 2000s, respectively. Interestingly, the contribution of LUCC to hydrological change in the upstream, middle-stream and downstream regions and the entire HRB declined continually over the past 30 years. This was the complete reverse (a sharp increase) of the contribution of climate change to hydrological change in HRB.

Contributions of cultivar shift, management practice and climate change to maize yield in North China Plain in 1981-2009.

The impact of climate change on crop yield is compounded by cultivar shifts and agronomic management practices. To determine the relative contributions of climate change, cultivar shift, and management practice to changes in maize (Zea mays L.) yield in the past three decades, detailed field data for 1981-2009 from four representative experimental stations in North China Plain (NCP) were analyzed via model simulation. The four representative experimental stations are geographically and climatologically different, represent the typical cropping system in the study area, and have more complete weather/crop records for the period of 1981-2009. The results showed that while the shift from traditional to modern cultivar increased yield by 23.9-40.3 %, new fertilizer management increased yield by 3.3-8.6 %. However, the trends in climate variables for 1981-2009 reduced maize yield by 15-30 % in the study area. Among the main climate variables, solar radiation had the largest effect on maize yield, followed by temperature and then precipitation. While a significant decline in solar radiation in 1981-2009 (maybe due to air pollution) reduced yield by 12-24 %, a significant increase in temperature reduced yield by 3-9 %. In contrast, a non-significant increase in precipitation during the maize growth period increased yield by 0.9-3 % at three of the four investigated stations. However, a decline in precipitation reduced yield by 3 % in the remaining station. The study revealed that although the shift from traditional to modern cultivars and agronomic management practices contributed most to the increase in maize yield, the negative impact of climate change was large enough to offset 46-67 % of the trend in the observed yields in the past three decades in NCP. The reduction in solar radiation, especially in the most critical period of maize growth, limited the process of photosynthesis and thereby further reduced maize yield.

Single rice growth period was prolonged by cultivars shifts, but yield was damaged by climate change during 1981-2009 in China, and late rice was just opposite.

Based on the crop trial data during 1981-2009 at 57 agricultural experimental stations across the North Eastern China Plain (NECP) and the middle and lower reaches of Yangtze River (MLRYR), we investigated how major climate variables had changed and how the climate change had affected crop growth and yield in a setting in which agronomic management practices were taken based on actual weather. We found a significant warming trend during rice growing season, and a general decreasing trend in solar radiation (SRD) in the MLRYR during 1981-2009. Rice transplanting, heading, and maturity dates were generally advanced, but the heading and maturity dates of single rice in the MLRYR (YZ_SR) and NECP (NE_SR) were delayed. Climate warming had a negative impact on growth period lengths at about 80% of the investigated stations. Nevertheless, the actual growth period lengths of YZ_SR and NE_SR, as well as the actual length of reproductive growth period (RGP) of early rice in the MLRYR (YZ_ER), were generally prolonged due to adoption of cultivars with longer growth period to obtain higher yield. In contrast, the actual growth period length of late rice in the MLRYR (YZ_LR) was shortened by both climate warming and adoption of early mature cultivars to prevent cold damage and obtain higher yield. During 1981-2009, climate warming and decrease in SRD changed the yield of YZ_ER by -0.59 to 2.4%; climate warming during RGP increased the yield of YZ_LR by 8.38-9.56%; climate warming and decrease in SRD jointly reduced yield of YZ_SR by 7.14-9.68%; climate warming and increase in SRD jointly increased the yield of NE_SR by 1.01-3.29%. Our study suggests that rice production in China has been affected by climate change, yet at the same time changes in varieties continue to be the major factor driving yield and growing period trends.

Observed changes in winter wheat phenology in the North China Plain for 1981-2009.

Climate change in the last three decades could have major impacts on crop phenological development and subsequently on crop productivity. In this study, trends in winter wheat phenology are investigated in 36 agro-meteorological stations in the North China Plain (NCP) for the period 1981-2009. The study shows that the dates of sowing (BBCH 00), emergence (BBCH 10) and dormancy (start of dormancy) are delayed on the average by 1.5, 1.7 and 1.5 days/decade, respectively. On the contrary, the dates of greenup (end of dormancy), anthesis (BBCH 61) and maturity (BBCH 89) occur early on the average by 1.1, 2.7 and 1.4 days/decade, respectively. In most of the investigated stations, GP2 (dormancy to greenup), GP3 (greenup to anthesis) and GP0 (entire period from emergence to maturity) of winter wheat shortened during the period 1981-2009. Due, however, to early anthesis, grain-filling stage occurs at lower temperatures than before. This, along with shifts in cultivars, slightly prolongs GP4 (anthesis to maturity). Comparison of field-observed CERES (Crop Environment Resource Synthesis)-wheat model-simulated dates of anthesis and maturity suggests that climate warming is the main driver of the changes in winter wheat phenology in the NCP. The findings of this study further suggest that climate change impact studies should be strengthened to adequately account for the complex responses and adaptations of field crops to this global phenomenon.