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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. [ABSTRACT FROM AUTHOR]

With global climate warming, extreme climate events are becoming more frequent, posing a great threat to crop production. In this study, twelve extreme climate indices (ECIs) were defined to characterize climate events prone to occurring during key phenological stages of wheat. Additionally, eighteen Global Climate Models (GCMs) from the Coupled Model Inter-comparison Project phase 6 (CMIP6) were selected to analyze the spatial–temporal characteristics and trends of these ECIs under four emission scenarios of the future Shared Socioeconomic Pathway (SSP). The Delta Change Method (DCM) was used to correct the bias of GCM data, and the arithmetic mean and Independence Weighted Mean (IWM) were used to aggregate the results of different GCMs to improve the projection accuracy of ECIs. Overall, the IWM ensemble results can better reproduce historical changes of ECIs than multi-model arithmetic mean and any individual GCM. The results indicated that the ECIs across wheat growing area in China were significant spatial heterogeneity during the historical period from 1981 to 2010. Under future climate scenarios, the frequency of extreme high temperature events would significantly increase in most regions, and the intensity will increase by 0.13–0.99 ° and 0.44–2.41 ℃ during 2031–2060 and 2071–2100. However, the stress of extreme low temperature events during wheat growth periods would decrease. Although the changes of extreme precipitation events under different climate scenarios were not significant, these showed considerably spatial differences across wheat growing area. In order to maintain high and stable yield of wheat, it is important to take measures to mitigate the effects of future extreme climate events on wheat production. [ABSTRACT FROM AUTHOR]

Simple Summary: Quantitatively exploring the impact of climate change on crop production and water consumption (i.e., crop evapotranspiration during crop growth period, ET) is very important to achieve sustainable regional agricultural development. In this study, based on daily downscaled climate data from 22 Global Climate Models (GCMs), we applied the Agricultural Production Systems sIMulator (APSIM) to investigate the possible impact of climate change (e.g., temperature (Temp), solar radiation (Rad), precipitation (Prec) and CO2) on crop phenology, yield and water consumption for the rice (Oryza sativa L.) -wheat (Triticum aestivum L.) rotation. Due to the increase in Temp, the key phenological periods (flowering and maturity) of wheat in the future mainly tend to advance, while the phenological changes of rice show different trends at different sites. 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, climate change will have a significant impact on the crop growth process, yield and water consumption. 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. [ABSTRACT FROM AUTHOR]

Future extreme climate events will become more intense and frequent with global warming, which is a great threat to wheat productivity in the North China Plain (NCP). Projecting future changes in extreme climate events is an important prerequisite for exploring crop adaptation measures to climate variation. In this study, we calculated 11 extreme climate indices at different wheat growth stages that are sensitive to wheat yield across NCP. The future climate projections were sourced from thirteen Global Climate Models (GCMs) from the Coupled Model Inter‐comparison Project phase 6 (CMIP6) under two emission scenarios of future societal development pathway (SSP) 245 and SSP585. Daily climate data of thirteen GCMs were generated by using a statistically downscaled method. Two multi‐model ensemble methods, that is, arithmetic mean and independence weighted mean (IWM), were used to assess the performance of thirteen GCMs in reproducing historical changes of extreme climate indices. The IWM ensemble results could better reproduce historical changes of extreme climate indices than multi‐model arithmetic mean and any individual GCM. We found that the frequency and intensity of heat extremes were projected to increase over the 21st century for both scenarios, but those of cold extremes will decrease. Heat stress intensity (HSI) increases around 1.0°C for SSP245 scenario and 1.6°C for SSP585 scenario by the end of the 21st century. There was no significant change in extreme precipitation indices across the NCP, but the changes of extreme precipitation had strong spatial heterogeneity. Overall, wheat production in the NCP might have a higher frequency of exposure to extreme climate, especially under heat stress. Therefore, adopting effective adaptation measures to mitigate heat stress for wheat is the first priority in the NCP. [ABSTRACT FROM AUTHOR]

Climate change has had a considerable impact on potato production in Agro-Pastoral Ecotone (APE) in North China over the past several decades and it will continue to influence the growth of potato. Thus, understanding the impact of climate change on potato production is critical for future food security in this region. In this study, the calibrated APSIM-Potato model was used to assess the impact of future climate change on potato at Zhangbei (ZB) and Wuchuan (WC) experimental stations. The daily climate data were statistically downscaled from 32 global climate models under two Representative Concentration Pathways (RCP4.5 and RCP8.5). The results showed that potato yield under rainfed condition at ZB site respectively increased by 7.3% and 6.7% in the 2030s, 25.8% and 21.8% in the 2060s and 44.7% and 51.9% in 2090s under RCP4.5 and RCP8.5 scenarios. Potato yield under irrigated condition at WC site increased respectively by 5.5%, 10.0% and 15.1% in the 2030s, 2060s and 2090s under RCP4.5 scenario and by 5.7%, 20.9% and 41.1% under RCP8.5 scenario. Both evapotranspiration and water use efficiency increased under future climate change. Based on the statistical analysis, 70% of the variation in potato yield under rainfed condition at ZB site and 50% of it under irrigated condition at WC site were driven by future climate change. We concluded that rainfed potato yield will be enhanced more by future climate change than irrigation system. Our study filled the knowledge gap in understanding the potential effects of future climate change on potato production under different water management measures, and will be useful in developing adaptable strategies to enhance potato yield in the APE region under future climate change. [ABSTRACT FROM AUTHOR]

Investigating how climate affects multiple consecutive crop growth stages is helpful to provide guidance for adopting appropriate agronomic practices. Based on the observed data from 51 agro-meteorological stations across China during 1981–2010, we qualified the spatio-temporal variability of eight consecutive phenological stages of rice [sowing (SD), emergence (ED), transplanting (TPD), tillering (TD), booting (BD), heading (HD), milk ripe (MRD), and maturity date (MD)] and the durations of three growth phases [vegetative growth phase (VGP), reproductive growth phase (RGP), and whole growth phase (WGP)]. We also explored the correlation and sensitivity of each of the growth phases to three climatic factors [i.e., mean temperature (Tmean), precipitation (PRE), and sunshine hours (SSH)]. We found that SD, ED, and TPD of single rice advanced by 0.22, 0.15, and 1.15 days 10a−1, while TD, BD, HD, MRD, and MD delayed by 0.26, 1.14, 0.66, 2.47, and 1.50 days 10a−1, respectively. For early rice, the dates of all the phenological stages advanced to different extents, except MRD. For late rice, SD, ED, BD, and MRD delayed, while dates of the other phenological stages advanced. The durations of VGP, RGP, and WGP prolonged for both single rice and early rice, but these shortened for late rice. Overall, the durations of three growth phases were negatively correlated with Tmean, but positively correlated with PRE and SSH during corresponding growth phase across rice cultivation region. Sensitivity analysis indicated that increases in temperature tended to reduce duration of single-rice and double-rice VGP. Increases in PRE tended to increase duration of late-rice RGP, and increases in SSH tended to increase duration of single-rice RGP. The results indicated that climate change during the past three decades had a negative impact on rice growth and development. However, the observed phenological changes indicated that agronomic practice with long seasonal cultivar has mitigated these adverse effects. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

• Growth stage-specific ECIs are important in estimating wheat yield. • Coupling crop model with machine learning can improve yield estimation accuracy. • Feature selection can reduce computation cost without affecting accuracy. • APSIM with RF and GA was the optimal model in estimating wheat yield. Assessing the impact of climate extremes on crop production is an important prerequisite for exploring agronomic practices to deal with changing climate. Process-based crop models are effective tools to assess the effect of climate change on crop yield, but cannot accurately express the impact of extreme climate events on crop yield. In this study, we developed a series of hybrid models by incorporating the APSIM model outputs and the most informative growth stage-specific extreme climate indices (ECIs) selected by two feature selection techniques (stepwise regression, SR and genetic algorithm, GA) into two machine learning algorithms (random forest, RF and light gradient boosting machine, LGBM) to evaluate impacts of climate extremes on wheat yields in the North China Plain (NCP). The results showed that the RF model outperformed the LGBM model in estimating wheat yield regardless of input variables. Applying feature selection to two machine learning algorithms can greatly reduce computational cost without significantly affecting model accuracy. The APSIM+RF-GA hybrid model was the optimal model for estimating wheat yield with explained 93 % of the observed yield variation and the accuracy of the model is improved by 33 % compared with the APSIM model alone. Extreme low temperature events before flowering and extreme high temperature events after flowering are the main extreme climate events causing the loss of wheat yield. In addition, we evaluated the impact of future climate change on wheat yield using the APSIM+RF-GA hybrid model and the APSIM model, respectively. Yields projected using a single APSIM model increased at all stations but yields projected using APSIM+RF-GA model decreased at 12.5–28.1 % of stations in the NCP under future climate scenarios. Compared to the APSIM+RF hybrid model, the future yield projected using single APSIM model might be overestimated by 12.7–19.2 % because of underestimating the yield loss caused by climate extremes. The increase of heat stress after flowering and frost stress during floral initiation to flowering were the main factors for future yield loss. Using the machine learning algorithm to make an external modification to the outputs of the APSIM model could improve the accuracy of yield estimation under extreme climate conditions and the method is more suitable for projecting future crop yield. This study is conducive to developing adaptation strategies to alleviate the negative impacts of future climate extremes on crop production. [ABSTRACT FROM AUTHOR]

Our understanding of climate impacts and adaptations on crop growth and productivity can be accelerated by analyzing historical data over the past few decades. We used crop trial and climate data from 1981 to 2009 at 34 national agro-meteorological stations in the Huang-Huai-Hai Plain (HHHP) of China to investigate the impacts of climate factors during different growth stages on the growth and yields of winter wheat, accounting for the adaptations such as shifts in sowing dates, cultivars, and agronomic management. Maximum ( T max ) and minimum temperature ( T min ) during the growth period of winter wheat increased significantly, by 0.4 and 0.6 °C/decade, respectively, from 1981 to 2009, while solar radiation decreased significantly by 0.2 MJ/m 2 /day and precipitation did not change significantly. The trends in climate shifted wheat phenology significantly at 21 stations and affected wheat yields significantly at five stations. The impacts of T max and T min differed in different growth stages of winter wheat. Across the stations, during 1981–2009, wheat yields increased on average by 14.5% with increasing trends in T min over the whole growth period, which reduced frost damage, however, decreased by 3.0% with the decreasing trends in solar radiation. Trends in T max and precipitation had comparatively smaller impacts on wheat yields. From 1981 to 2009, climate trends were associated with a ≤ 30% (or ≤1.0% per year) wheat yield increase at 23 stations in eastern and southern parts of HHHP; however with a ≤ 30% (or ≤1.0% per year) reduction at 11 other stations, mainly in western part of HHHP. We also found that wheat reproductive growth duration increased due to shifts in cultivars and flowering date, and the duration was significantly and positively correlated with wheat yield. This study highlights the different impacts of T max and T min in different growth stages of winter wheat, as well as the importance of management (e.g. shift of sowing date) and cultivars shift in adapting to climate change in the major wheat production region. [ABSTRACT FROM AUTHOR]

Excessive use of groundwater in irrigation (mainly for production of winter wheat) in the North China Plain (NCP) has resulted in markedly decreased groundwater levels. Alternative cropping systems may have potential to reduce groundwater use in the region. The APSIM (Agricultural Production System Simulator) farming systems model was used to simulate long-term (1981–2015) water use, net overdraft and crop yield for eight cropping systems. The wheat-maize double cropping system (WW–SM) in the study area resulted in overdrafts of 258 mm yr − 1 , about 100 mm yr − 1 more than estimated groundwater recharge. Although six of eight simulated systems reduced overdrafts below the estimated recharge value of 150 mm yr − 1 , a triple-cropping system consisting of winter wheat/summer maize followed by fallow and early maize (WW–SM/F–EM) in two years appears to be the most viable alternative. Annual grain yield under the triple cropping system was only 13% less than that under the current WW–SM double cropping system. Groundwater overdrafts under triple-cropping system were about equal to lateral recharge from the mountains, water brought in via the South-North Water Transfer (SNWT) project and water from other water-saving measures (e.g. plastic film mulching) in the region. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

As climate change could significantly influence crop phenology and subsequent crop yield, adaptation is a critical mitigation process of the vulnerability of crop growth and production to climate change. Thus, to ensure crop production and food security, there is the need for research on the natural (shifts in crop growth periods) and artificial (shifts in crop cultivars) modes of crop adaptation to climate change. In this study, field observations in 18 stations in North China Plain (NCP) are used in combination with Agricultural Production Systems Simulator (APSIM)-Maize model to analyze the trends in summer maize phenology in relation to climate change and cultivar shift in 1981-2008. Apparent warming in most of the investigated stations causes early flowering and maturity and consequently shortens reproductive growth stage. However, APSIM-Maize model run for four representative stations suggests that cultivar shift delays maturity and thereby prolongs reproductive growth (flowering to maturity) stage by 2.4−3.7 day per decade (d 10a). The study suggests a gradual adaptation of maize production process to ongoing climate change in NCP via shifts in high thermal cultivars and phenological processes. It is concluded that cultivation of maize cultivars with longer growth periods and higher thermal requirements could mitigate the negative effects of warming climate on crop production and food security in the NCP study area and beyond. [ABSTRACT FROM AUTHOR]

• Climate warming increases potato yield in North part China, while decrease in South. • Adjusting planting date would be effective for rainfed potato under climate warming. • "Double late" would be optimal to cope with climate warming for rainfed potato. • Optimal combination of PD and cultivar for irrigated potato would vary across China. • The yield would increase 2.6–65.2% under climate warming with optimal combination. Rising temperatures and varying precipitation patterns pose huge challenges to the global potato supply. Understanding the adaptation potential of potato to climate change is urgently needed to help develop effective measures for future agriculture and food security. In this study, we evaluated future potato yield changes under 1.5 °C and 2.0 °C warming scenarios, and explored potential adaptation strategies by optimizing planting dates (PD) and cultivars across China's potato production regions. Compared with the baseline period (1986–2015), potato yields would increase in North single (NS) and Central double (CD) cropping system zones, but would decrease in South winter (SW) and Southwest mixed (SWM) cropping system zones under the 1.5 °C warming scenario without considering adaptation measures. Under the 2.0 °C warming scenario, potato yield would increase across China's potato planting zones except for SWM. Adjusting PD would be more effective for increasing rainfed potato yield across China than changing cultivars under the two warming scenarios. Overall, late PD coupled with a late-maturing cultivar would be the optimal selection for rainfed potato production. For irrigated potato, adjusting PD would be more effective than changing cultivars in NS and SW, but the opposite would be true in CD. The optimization of a single measure would have little impact on yield in SWM. The optimum PD would be early PD in NS and late PD in SW and SWM. The optimum cultivar would be late-maturing in NS, CD, and SWM, and middle-maturing in SW. Under the optimal combination, rainfed and irrigated potato yield would increase by 3.4–44.2% and 2.6–49.3%, respectively, under the 1.5 °C warming scenario, and would increase by 7.1–51.6% and 8.5–65.2%, respectively, under the 2.0 °C warming scenario. Our study results provide valuable information for policymakers and stakeholders involved in potato production to aid in planning agricultural strategies to safeguard potato production. [ABSTRACT FROM AUTHOR]

• Climate warming increases potato yield in North part China, while decrease in South. • Adjusting planting date would be effective for rainfed potato under climate warming. • "Double late" would be optimal to cope with climate warming for rainfed potato. • Optimal combination of PD and cultivar for irrigated potato would vary across China. • The yield would increase 2.6–65.2% under climate warming with optimal combination. Rising temperatures and varying precipitation patterns pose huge challenges to the global potato supply. Understanding the adaptation potential of potato to climate change is urgently needed to help develop effective measures for future agriculture and food security. In this study, we evaluated future potato yield changes under 1.5 °C and 2.0 °C warming scenarios, and explored potential adaptation strategies by optimizing planting dates (PD) and cultivars across China's potato production regions. Compared with the baseline period (1986–2015), potato yields would increase in North single (NS) and Central double (CD) cropping system zones, but would decrease in South winter (SW) and Southwest mixed (SWM) cropping system zones under the 1.5 °C warming scenario without considering adaptation measures. Under the 2.0 °C warming scenario, potato yield would increase across China's potato planting zones except for SWM. Adjusting PD would be more effective for increasing rainfed potato yield across China than changing cultivars under the two warming scenarios. Overall, late PD coupled with a late-maturing cultivar would be the optimal selection for rainfed potato production. For irrigated potato, adjusting PD would be more effective than changing cultivars in NS and SW, but the opposite would be true in CD. The optimization of a single measure would have little impact on yield in SWM. The optimum PD would be early PD in NS and late PD in SW and SWM. The optimum cultivar would be late-maturing in NS, CD, and SWM, and middle-maturing in SW. Under the optimal combination, rainfed and irrigated potato yield would increase by 3.4–44.2% and 2.6–49.3%, respectively, under the 1.5 °C warming scenario, and would increase by 7.1–51.6% and 8.5–65.2%, respectively, under the 2.0 °C warming scenario. Our study results provide valuable information for policymakers and stakeholders involved in potato production to aid in planning agricultural strategies to safeguard potato production. [ABSTRACT FROM AUTHOR]

Highlights: [•] Cultivars renewal contributed to yield increase by 12.2-22.6% for 1980–2009. [•] Fertilization management contributed to yield increase by 2.1-3.6% for 1980–2009. [•] Climate change contributed to yield generally by −3.0 to 3.0% for 1980–2009. [•] Temperature increase increased yield by 3.0-6.0% but reduced it by 12.0% for rainfed wheat. [•] Decrease in solar radiation reduced yield by 3.0-12.0% across the stations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Potato is a staple food crop in the agro-pastoral ecotone (APE) of North China. However, the potato yield is low and highly variable due to limited water and nutrient availabilities in the region. Irrigation and nitrogen (N) fertilization have been used widely to enhance potato yield but result in negative environmental impacts in the APE. This study aims to explore the optimum combinations of irrigation and N fertilization for different potato production goals by using APSIM-Potato model calibrated well by field experiments with different combinations of irrigation and N fertilizer conducted at the typical site in the APE. Long-term (1981–2010) simulation for potato yield, water use efficiency (WUE), nitrogen use efficiency (NUE), economic profits and environmental impacts were analyzed under different combinations of irrigation (IR, based on the soil water deficit, ranged from 10 (IR 10) to 100 mm (IR 100) with the interval of 10 mm) and N fertilization (ranged from 0 (N 0) to 210 (N 210) kg ha−1 with the interval of 30 kg ha−1). Combination of IR 10 and N 210 maximized potato yields in the whole APE, and the yield was highest in the middle APE, with the value of 35.2 t ha−1, which was 6.7% and 2.1% higher than that in the eastern and western APE. However, such water and nitrogen managements would cause annual decline of groundwater table by 1.6 m and N loss by 10.9 kg ha−1. In order to achieve the highest WUE, the irrigation amounts should be 124, 107 and 132 mm in the eastern, middle and western APE, respectively, coupled with 90 kg ha−1 N fertilizer, and the highest WUEs were 89.6 kg ha−1 mm−1, 93.1 kg ha−1 mm−1 and 84.8 kg ha−1 mm−1 in the eastern, middle and western APE. For highest FNUE, the combination should be IR 10 and N 30 across APE, and the highest values were 959 kg ha−1 kg−1, 1092 kg ha−1 kg−1 and 1022 kg ha−1 kg−1 in the eastern, middle and western APE. Moreover, to get the highest income, the irrigation ranged from IR 50 to IR 10 and the amounts of N fertilizers ranged from 30 kg ha−1 to 120 kg ha−1, and the maximum incomes were 18,250 CNY ha−1, 20,060 CNY ha−1 and 19,660 CNY ha−1 in the eastern, middle and western APE. In all, the combination that maximized the income could contain the relative higher yield, WUE, NUE and lower environmental sequence. Our study would be helpful in determining the optimal amounts of irrigation and N fertilization for different goals of potato production in the APE. • Optimal irrigation and N for different potato production goals was recommended. • Irrigation applied if soil water deficit ≥10 mm and 210 kg ha−1 N maximized yield. • Requirement of irrigation and N for maximum WUE were different in the APE. • Irrigation applied if soil water deficit ≥10 mm and 20 kg ha−1 N maximized NUE. • Combinations of irrigation and N that maximized income varied across the APE. [ABSTRACT FROM AUTHOR]

Crop production in the North China Plain (NCP) is heavily influenced by the unfolding climate change and water shortage. Groundwater overdraft for irrigation in this region has caused serious ecological and environmental problems. Cropping systems adjustment offers an effective approach for the sustainable use of groundwater. However, the assessment of the impacts of future climate change on crop production and water consumption under different cropping systems with/without straw mulching has not been reported in the NCP. In this study, we applied the well validated APSIM model to explore the implementation of five cropping systems (i.e., two maturities per year, 1Y2MS0; three maturities per two year without (with) straw mulching during the fallow period, 2Y3MS0 (2Y3MS1); and one maturity per year without (with) straw mulching during the fallow period, 1Y1MS0 (1Y1MS1)). Statistical downscaled daily climate data based on 33 global climate models (GCMs) were used to drive APSIM to simulate crop phenology, yield and water use under future climate change. We found that cropping system adjustment significantly reduced the amount of water required for irrigation, thereby decreasing groundwater overdraft to a certain extent. Straw mulching could have mitigating effect on groundwater overdraft. Multi-GCMs ensemble means show an increase in temperature, precipitation and solar radiation in the future. Under future climate change scenarios, the phenological date (e.g. flower and maturity dates) of maize and wheat were advanced due to climate warming. Our simulated results indicated that future climate change would have negative impact on maize yield across all cropping systems but have positive impact on wheat yield under most climate change scenarios. Both irrigation and groundwater overdraft reduced in the future due to decreased evapotranspiration and increased precipitation. We concluded that 2Y3MS1 would be the optimum cropping system to balance crop yield and groundwater overdraft. This knowledge can inform the development of improved regional impact assessments of the sustainability of multi-crop rotation systems. • Climate change has positive impact on wheat under most future climate scenarios. • Climate change has negative impact on maize under all the future climate scenarios. • Irrigation and groundwater overdraft decrease under future climate scenarios. • Straw mulching during fallow has a mitigating effect on groundwater overdraft. • 2Y3MS1 will be the optimum choice to balance water resources and food security. [ABSTRACT FROM AUTHOR]

• Future climate warming led to advance in wheat and maize phenology. • Future climate change had negative impact on maize but positive impact on wheat. • Crop water consumption was largely decreased under future climate scenarios. • Future climate change could mitigate groundwater overdraft across NCP. Climate change has already and will continue to exert a vital impact on crop yield and water use in the North China Plain (NCP). Currently, this plain is facing a dilemma between groundwater depletion and grain production demand. It is urgent to identify the impact of future climate change on crop yield and water consumption and then develop efficient adaptation strategies in the region. In this study, we used statistically downscaled daily climate data from 33 global climate models (GCMs) and two Representative Concentration Pathways (RCP4.5 and RCP8.5) for 61 stations distributed across the NCP and drove the well-validated APSIM model to simulate crop yield and water use for two future periods of 2031–2060 (2040s) and 2071–2100 (2080s). Data from all 33 GCMs show an increase in annual mean temperature and almost all the GCMs also show increases in annual mean solar radiation and annual total precipitation across the NCP. Future climate warming led to an advance in phenology for both winter wheat and summer maize, two typical crops in the NCP. However, the length of the reproductive growth period (RGP) of winter wheat was prolonged while that of summer maize was shortened under future climate scenarios across the NCP. Our simulated results show that future climate change had negative impacts on maize yield but positive impacts on wheat yield across the NCP. Mainly due to the shortening of the whole growth period, crop water consumption was largely decreased under future climate scenarios. The amount of irrigation required was also reduced mainly due to increased precipitation and decreased ET. Although future climate change would likely mitigate groundwater overdraft in most part of NCP, some areas in the northern NCP still had groundwater over-pumping in the future. Therefore, we suggest that it might be a good choice to change cropping system for reducing planting area of water-consuming crop (e.g. winter wheat) in those over-pumping areas to balance groundwater use and crop yield. [ABSTRACT FROM AUTHOR]

Global food production to meet growing demand is facing serious challenges from changing climate. Efficient adaptation is an important approach for mitigating the effects of changing climate on crop production and secure food supply in the future. Maize is a critically important source of food, feed and fuel, and is highly vulnerable to warming climate. In our study, using Agricultural Production Systems sIMulator (APSIM) model, we designed different features of maize ideotypes sown at various times to maximize the yield and water use efficiency (WUE) under future climate conditions in the North China Plain (NCP). The future climate projections were sourced from one Global Climate Model (GCM) from the Coupled Model Inter-comparison Project phase 6 (CMIP6) under a high emission scenario of future societal development pathway (SSP) 585. The selected GCM projected future mean maximum (minimum) temperature during maize growing season to increase by 1.9 °C and 3.7 °C (1.5 °C and 3.2 °C) in 2040s (2031–2060) and 2080s (2071–2100) respectively, compared to the baseline (1981–2010). The mean solar radiation during maize growing season increased by 3.9% and 6.5%, and total precipitation rose by 17.3% and 21% in 2040s and 2080s, respectively. Our simulated results indicated future maize yield without adaptation decreased slightly by 2.3% in 2040s and 2.4% in 2080s, but WUE significantly increased by 11.8% and 26.6% in 2040s and 2080s, respectively. We found that delayed sowing date was able to increase maize yield and WUE under the future climate conditions. When the ideotypic cultivar and optimum sowing date were adopted, simulated yield increased by 132% and 124% in 2040s and 2080s, respectively, and WUE rose by 85% and 117%, respectively. Our simulated results indicate maize ideotypes under future climate should have a longer reproductive growing period, faster potential grain filling rate, larger maximum grain numbers and larger radiation use efficiency. Maize ideotypes based on simulated results from APSIM models could provide breeders and/or plant scientists with a road map to choose the ideal target traits for increasing maize production and adapting future climate. • One GCM from CMIP6 under SSP585 scenario are selected for analysis. • Maize yield without adaptation under future climate change decrease slightly. • Delayed sowing date is able to increase maize yield and WUE. • Maize ideotypes have a longer reproductive growing period. • Maize ideotypes have larger RUE and potential grain filling rate. [ABSTRACT FROM AUTHOR]

Using the detailed field experiment data from 1981 to 2009 at four representative agro-meteorological experiment stations in China, along with the Agricultural Production System Simulator (APSIM) rice-wheat model, we evaluated the impact of sowing/transplanting date on phenology and yield of rice-wheat rotation system (RWRS). We also disentangled the contributions of climate change, modern cultivars, sowing/transplanting density and fertilization management, as well as changes in each climate variables, to yield change in RWRS, in the past three decades. We found that change in sowing/transplanting date did not significantly affect rice and wheat yield in RWRS, although alleviated the negative impact of climate change to some extent. From 1981 to 2009, climate change jointly caused rice and wheat yield change by −17.4 to 1.5 %, of which increase in temperature reduced yield by 0.0-5.8 % and decrease in solar radiation reduced it by 1.5-8.7 %. Cultivars renewal, modern sowing/transplanting density and fertilization management contributed to yield change by 14.4-27.2, −4.7- −0.1 and 2.3-22.2 %, respectively. Our findings highlight that modern cultivars and agronomic management compensated the negative impacts of climate change and played key roles in yield increase in the past three decades. [ABSTRACT FROM AUTHOR]

Highlights: [•] Experiment data on phenology and yield at 120 stations between 1981and 2009 were used. [•] Crop system dynamics were accounted for when quantifying climatic impacts on yield. [•] Anthesis date and maturity date advanced and whole growth period was shortened. [•] Reproductive growth duration was prolonged despite of negative impact of climate. [•] Climate change increased yield in northern China however reduced it southern China. [Copyright &y& Elsevier]

Abstract 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 CO 2 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 CO 2 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. Graphical abstract Unlabelled Image Highlights • The future climate will have positive impacts on rice yields in Northeast China. • Increased radiation and elevated CO 2 concentration are the main reason for future rice yield increase in Northeast China. • High latitude areas have a large yield increase than the low latitude regions in Northeast China. [ABSTRACT FROM AUTHOR]

The North China Plain (NCP) has a severe water shortage. About 70% groundwater has been exploited for irrigation. Winter wheat – summer maize and pears are typical representative cereal crops and commercial fruit trees in this area, respectively. Water budget for the typical cropland and orchard ecosystems has a significant importance for agricultural production, especially in the NCP. Therefore, evapotranspiration (ET) and water balance were studied in the annual winter wheat – summer maize rotation (cropland) and pear orchard. Latent and sensible heat fluxes were measured by eddy covariance. Annual ET for pear trees was 764 mm and for both crops was 690 mm. The difference of ET between these two ecosystems was about equal to one irrigation. Transpiration was the main loss with the mean proportion of 63% for crops and 76% for pear trees. Wheat growth period is in the dry season and requires much more irrigation than maize. Mainly transpiration (80%) occurred from April through September in the both ecosystems which was also the growing period for pear trees. The annual precipitation was 469 mm and 444 mm in the pear orchard and cropland, respectively, although 80% of it occurred from June to September. Compared with the precipitation, annual mean water deficit was 294 mm for the pear trees and 244 mm for crops. The water shortage was severe in May while surplus water presented in July and August. Energy and ET fluxes were determined by atmospheric demand and the response of plants as controlled by plant phenology and crop selection. As the water shortage situation becomes more serious in the NCP, sustainability of the agricultural ecosystems could be improved by changing crop planting patterns, specifically, increasing the area ratio of maize to pear trees. [ABSTRACT FROM AUTHOR]

Irrigation of the conventional double cropping system of winter wheat and summer maize has caused serious problems regarding water resources and the environment on the Beijing-Tianjin-Hebei plain (HP), China. Reducing or replacing high water consumption crops (such as winter wheat) is the most impactful way to effectively save water in the HP region. In this study, crop coefficient and vegetation remote sensing data were used to estimate evapotranspiration ( ET a ) for winter wheat and summer maize on the HP from 2009 to 2013. For early maize, ET a and yield were based on the results from the APSIM (Agricultural Production System Simulator) crop model, which had been calibrated and validated using field experimental data. The effects on groundwater conservation and grain yield were estimated at the regional scale for the conventional winter wheat (WW) and summer maize (SM) double cropping system (Y 1 M 2 ) and three alternative cropping systems: three harvests in two years system (Y 2 M 3 , 1st year: WW-SM; 2nd year: early maize), four harvests in three years system (Y 3 M 4 , 1st year: WW-SM; the next two years: early maize), as well as a continuous early maize monoculture system (Y 1 M 1 ). The results showed that: (1) Relative to Y 1 M 2 , the water savings in each alternative cropping system exceeded 50% of the groundwater overdraft on the HP. The evapotranspirations of Y 2 M 3 , Y 3 M 4 and Y 1 M 1 decreased by 14%, 19% and 29% over that of Y 1 M 2 (740 mm), respectively. The economic water use efficiencies (WUE e ) of the alternative cropping systems were 7% –16% greater than that of Y 1 M 2 . The groundwater drop by Y 1 M 2 (0.59 m year − 1 ) was higher than that by Y 2 M 3 (0.20 m year − 1 ) and Y 3 M 4 (0.07 m year − 1 ), and the drop by Y 1 M 1 was negative, indicating a groundwater rise of 0.20 m. The groundwater overdraft in Y 1 M 2 was 160 mm (3.83 billion m 3 ), and the alternative cropping systems were more sustainable, with groundwater overdrafts that were less than the recharge value of 128 mm on the HP. (2) In comparison with Y 1 M 2 , the total yield was reduced by 2.28, 3.04 and 4.56 billion kg a − 1 (or 7.7%, 10.2% and 15.3%) for Y 2 M 3 , Y 3 M 4 and Y 1 M 1 , respectively, which accounted for < 15% of the regional total or < 1% of the national total. It is important to note that the yield loss of the alternative cropping systems was below the net grain export amount in Hebei province, so the grain supply and demand could be roughly balanced. (3) In summary, Y 2 M 3 is a preferred alternative cropping system over Y 1 M 2 in the near future because of the advantages of high WUE e , economic return, mitigated groundwater level decline and balance between wheat supply and demand on the HP. Y 1 M 1 , which had the least water use and highest WUE e and economic return, is an option for the most serious groundwater overdraft area despite a contradiction between the traditional dietary habit and complete abandonment of wheat. Y 3 M 4 is recommended as the transitional cropping system between Y 2 M 3 and Y 1 M 1 . The method in this study is applicable to relevant regional research, and the results can be of use to the government when formulating policies on cropping systems and groundwater management. [ABSTRACT FROM AUTHOR]

• Variation of irrigated potato yield to planting date was more higher than rainfed. • Potato water requirement decreased with delaying planting date. • Potato water deficit decreased with delaying planting date. • Total water footprint of rainfed potato was highest under early planting date. • Total water footprint of irrigated potato decreased with delaying planting date. Reducing the water footprint per unit of crop production reduces the pressure on the limited freshwater resources. This study used data from a four-year field experiment conducted in the agro-pastoral ecotone (APE) of Northern China, to calibrate and validate the APSIM-Potato model, and determine the impacts of planting dates on the water footprint (WF) of potatoes under rain-fed and irrigated conditions. Results showed that the rain-fed potato yields were 14.6, 18.9, and 19.9 t ha−1, under the early, normal, and late planting dates, respectively, and the irrigated yields were 19.7, 31.8, and 30.9 t ha−1 under the three planting daets. The blue WF of the potatoe were -25.6–0 m3 t −1, -27.2–0 m3 t −1, and -26.4–0 m3 t −1 in early, normal, and late planting dates, respectively, under rainfed condition, and the value was highest in normal planting date. Green WF of the potato was 24.4 m3 t −1, 16.0 m3 t −1, and 13.5 m3 t −1 under early, normal, and late planting dates, respectively. The total WF was 20.3 m3 t −1 under the early planting dates, which was 50.3% and 87.9% higher than that under normal and late planting dates, respectively. Under the irrigated conditions, early planting exhibited the highest blue WF (33.2–77.9 m3 t −1), followed by normal (32.1–67.4 m3 t −1), and late planting dates (26.6–61.3 m3 t −1). The green WF was 104.9 m3 t −1 under the early planting dates, which was 48.8% and 45.9% higher than that under normal and late planting dates. Furthermore, the total WF of potatoes decreased with delayed planting, with the average values of 161.1, 117.8, and 114.2 m3 t −1 under early, normal, and late planting dates, respectively. These findings suggest the potential of reducing potato WF across the APE by adjusting the planting dates. [ABSTRACT FROM AUTHOR]

Extensive studies had been conducted to investigate the impacts of climate change on maize growth and yield in recent decades; however, the dynamics of crop husbandry in response and adaptation to climate change were not taken into account. Based on field observations spanning from 1981 to 2009 at 167 agricultural meteorological stations across China, we found that solar radiation and temperature over the observed maize growth period had decreasing trends during 1981–2009, and maize yields were positively correlated with these climate variables in major production regions. The decreasing trends in solar radiation and temperature during maize growth period were mainly ascribed to the adoption of late maturity cultivars with longer reproductive growth period (RGP). The adoption of late maturing cultivars with longer RGP contributed substantially to grain yield increase during the last three decades. The climate trends during maize growth period varied among different production areas. During 1981–2009, decreases in mean temperature, precipitation and solar radiation over maize growth period jointly reduced yield most by 13.2–17.3% in southwestern China, by contrast in northwestern China increases in mean temperature, precipitation and solar radiation jointly increased yield most by 12.9–14.4%. Our findings highlight that the adaptations of maize production system to climate change through shifts of sowing date and genotypes are underway and should be taken into accounted when evaluating climate change impacts. [ABSTRACT FROM AUTHOR]

The Simple Biosphere Model (SiB2) and the 2 × 2 km resolution National Land use/Land Cover database were used to investigate the effects of Land Use/Cover Change (LUCC) on land surface energy balance and climate in Jilin Province, northeast China, from 1990 to 2005. The spatial patterns of the components of surface energy balance (i.e., net radiation ( R), latent heat (LH), sensible heat (SH), and albedo ( α)) and climate (i.e., canopy temperature ( T), diurnal temperature range (DTR)), as well as the roles of land cover type in variations of energy balance and climate, were investigated. The results showed that there were general similar trends in R, LH, SH, and α in the LUCC process. The spatial patterns of T and DTR also showed consistent relationships with LUCC processes. Leaf area index (LAI) and canopy conductance ( g) were found to be the key factors in controlling the spatial patterns of the components of surface energy balance and T. Using linear correlation method, the gaps of the components of surface energy balance were well-explained by the differences of LAI and g, and R had a better correlation with T and DTR, in the process of LUCC. The surface energy partitioning of R into LH and SH could not only dampen or strengthen the temperature difference, but also change the relative size of albedo-based R when the albedo gap was small, between land cover types. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

China ranks the first in total planting area and production of potato (Solanum tuberosum L.) over the world. However, high potato yield depends on a large amount of irrigation that raises a series of environment problems. Assessing the water-saving potential across China's potato planting regions is of importance for maintaining sustainable development of potato production. In this study, we firstly evaluated the potential yields, rainfed yields, and their gaps of potato across different potato planting regions, and then presented optimal agronomic management options (planting date, cultivar maturity, and irrigation schedule) by considering both yield and water use efficiency of potato under the limitation of available water resources with validated APSIM-Potato model. Along the distribution of growth period solar radiation, potential yield of potato was highest in the North Single planting region (NS), followed by the Central Double planting region (CD), Southwest Mixed planting region (SWM), and South Winter planting region (SW). However, rainfed yield of potato was highest in CD followed by NS, SW, and SWM along the distribution of the reproductive growth period precipitation. Under the limitation of available water resources, most potato planting regions should select middle−late maturing cultivars while optimal planting dates varied among regions with earlier planting in north China and later planting in south China compared with normal planting date. Based on the optimization of planting date, cultivar maturity, and irrigation schedule, there is a large water-saving potential in China's potato planting regions. Average irrigation amount could be decreased by 66% in SW, 49% in SWM, 40% in NS, and 29% in CD, respectively, relative to irrigation quota. Our study suggests that optimizing planting date, cultivar maturity, and irrigation management could realize win-win of yield and water use efficiency and provide a scientific support for water-saving irrigation of potato production in China. [Display omitted] • Achieving potential potato yield needs 126–381 mm irrigation across China. • Later planting with earlier maturing cultivar is recommended from north to south. • There is a large water-saving potential in China's potato planting regions. [ABSTRACT FROM AUTHOR]

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. Unlabelled Image • A machine learning-based model was developed to predict drought. • Lagged large-scale climate indices were adopted as input predictors. • Growing season drought across all Australian cropping areas was predicted. • Forecasted drought maps matched well with observed drought maps. • NINO3.4 SST and MEI were identified as the most influential indices. [ABSTRACT FROM AUTHOR]

Early and reliable seasonal crop yield forecasts are crucial for both farmers and decision-makers. Commonly-used methods for seasonal yield forecasting are based on process-based crop models or statistical regression-based models. Both have limitations, particularly in regard to accounting for growth stage-specific climate extremes (such as drought, heat, and frost). In this study, we firstly developed a hybrid yield forecasting approach by blending of multiple growth stage-specific indicators, i.e. APSIM (a process-based crop model)-simulated biomass, and climate extremes, NDVI (Normalized Difference Vegetation Index), and SPEI (Standardized Precipitation and Evapotranspiration Index) before forecasting dates, using a regression model (random forest or multiple linear regression). Plot-scale wheat yield (2008–2017) in the southeastern Australian wheat belt was dynamically forecasted at the end of several targeted growth stages as the growing season progressed to harvest. Results showed that the forecasting accuracy increased significantly for both systems as forecast time approached harvest time. The forecasting system based on random forest outperformed the forecasting system based on multiple linear regression at each forecasting event. Satisfactory yield forecasts occurred at one month (~35 days) prior to harvest (r = 0.85, LCCC = 0.81, MAPE = 17.6%, RMSE = 0.70 t ha−1, and ROC score = 0.90), and at two months before harvest (r = 0.62, LCCC = 0.53, MAPE = 27.1%, RMSE = 1.01 t ha−1, and ROC score = 0.88). In addition, drought events throughout the growing season were identified as the main factor causing yield losses in the wheat belt during the past decade. With the increasing availability of farming-related data, we expect that the yield forecasting system proposed in our study may be widely extended to other comparable cropping regions to produce sufficiently accurate wheat yield forecasts for stakeholders to develop strategic decisions in their respective roles. [ABSTRACT FROM AUTHOR]