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Future frequent droughts threaten summer maize production in the North China Plain (NCP). A proper combination of irrigation and nitrogen (N) application can improve water and N use efficiency while maintaining summer maize yield. However, the optimal irrigation and N application strategies (OINASs) for summer maize during future drought years in the NCP require further exploration. This study applied the DSSAT‐CERES‐Maize model to investigate OINASs for summer maize for all drought years during 2021–2050 under three shared socioeconomic pathways (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5). The performance of the OINASs was subsequently evaluated against no irrigation and N application (CK) condition and a conventional irrigation and N application strategy (CINAS). The results highlight the following: (1) For all drought years under the three SSP scenarios, the base fertilizer rate should be 60 kg/hm2, after that the irrigation and N application are required during the jointing and heading periods. Under the SSP1‐2.6 scenario, the average values of irrigation and N application during each earlier period are 35.5 mm and 22 kg/hm2. Under the SSP2‐4.5 and SSP5‐8.5 scenarios, the average values are (34.5 mm, 23 kg/hm2) and (47.5 mm, 18 kg/hm2). (2) Under all SSP scenarios, the optimal irrigation amounts and N application rates are much lower than those under the CINAS. After applying OINASs for summer maize, an average of 1.16–1.22 billion kg of N and 2.98–5.19 billion m3 of freshwater will be saved per future drought year in the NCP. (3) Under all SSP scenarios, the summer maize yields under the OINASs are slightly and significantly greater than those under the CINAS and CK conditions. Moreover, both water and N use efficiencies improved under the OINASs compared with those under the CINAS, with more significant improvements in N use efficiency. The OINASs provide a practical way to ensure food security and environmental sustainability.
Future frequent droughts threaten summer maize production in the North China Plain (NCP). A proper combination of irrigation and nitrogen (N) application can improve water and N use efficiency while maintaining summer maize yield. However, the optimal irrigation and N application strategies (OINASs) for summer maize during future drought years in the NCP require further exploration. This study applied the DSSAT‐CERES‐Maize model to investigate OINASs for summer maize for all drought years during 2021–2050 under three shared socioeconomic pathways (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5). The performance of the OINASs was subsequently evaluated against no irrigation and N application (CK) condition and a conventional irrigation and N application strategy (CINAS). The results highlight the following: (1) For all drought years under the three SSP scenarios, the base fertilizer rate should be 60 kg/hm2, after that the irrigation and N application are required during the jointing and heading periods. Under the SSP1‐2.6 scenario, the average values of irrigation and N application during each earlier period are 35.5 mm and 22 kg/hm2. Under the SSP2‐4.5 and SSP5‐8.5 scenarios, the average values are (34.5 mm, 23 kg/hm2) and (47.5 mm, 18 kg/hm2). (2) Under all SSP scenarios, the optimal irrigation amounts and N application rates are much lower than those under the CINAS. After applying OINASs for summer maize, an average of 1.16–1.22 billion kg of N and 2.98–5.19 billion m3 of freshwater will be saved per future drought year in the NCP. (3) Under all SSP scenarios, the summer maize yields under the OINASs are slightly and significantly greater than those under the CINAS and CK conditions. Moreover, both water and N use efficiencies improved under the OINASs compared with those under the CINAS, with more significant improvements in N use efficiency. The OINASs provide a practical way to ensure food security and environmental sustainability.
The rising air temperature and shifting precipitation patterns threaten crop production and water distribution worldwide. The coastal region of China, specifically the Huaibei and Shandong Plains, is recognized as one of the most vulnerable areas among those impacted due to the complex interplay of land, sea, and atmospheric dynamics. The study utilized traditional trend analysis methods (Mann-Kendall and Sen's Slope) along with an innovative polygon trend analysis (IPTA) to predict the baseline arithmetic mean and standard deviation of the monthly precipitation trend. Moreover, the latest version of the Long Ashton Research Station Weather Generator (LARS-WG 7) model was used to predict average mean monthly precipitation and maximum and minimum temperatures for two future times: midterm 2050 (2041–2060) and long-term 2080 (2071–2090). The performance of each GCM incorporated in LARS-WG was evaluated independently and compared to a multi-model ensemble. All of the meteorological stations that were analyzed using the MK method (except for Suzhou, Dangshan, and Mengcheng) showed a significant decreasing trend in the arithmetic mean of monthly precipitation in March. However, for the majority of the remaining months, the study indicated a non-significant decreasing trend. In contrast, the IPTA method demonstrated a significant decreasing trend in most months, highlighting its superior ability to detect hidden trends compared to the MK method. The projections showed that mean annual precipitation is likely to increase at all meteorological stations in the Huaibei Plains and Shandong Plains during two periods: 2050 (2041–2060) and 2080 (2071–2090). A maximum increase in average mean annual precipitation is projected at the highest emission scenario (ssp585) as compared to the medium (ssp245) and low emission (ssp126) scenarios, and at the long-term period 2080 (2071-2090) as compared to the mid-term period 2050 (2041-2060). The mean annual precipitation in the Shandong Plain is projected to increase by 10.4%, 14.5%, and 14.8% under the ssp126, ssp245, and ssp585 scenarios, respectively. Similarly, in the Huaibei Plain, the projected increases are 10.9%, 13.6%, and 15.1% under the ssp126, ssp245, and ssp585 scenarios, respectively. The anticipated increase in mean precipitation per decade is expected to be 2.0% (= 1.96 mm/decade) in the Huaibei Plain and 1.31% (= 0.63 mm/decade) in the Shandong Plain. Both maximum and minimum temperatures are projected to increase persistently across all meteorological stations during two time periods: 2050 (2041–2060) and 2080 (2071–2090) under three different SSPs (ssp126, ssp245, and ssp585). The long-term period 2080 (2071–2090) is projected to experience the highest increase in both maximum and minimum temperatures, surpassing the increases observed in the midterm period 2050 (2041–2060). Among the different SSPs, the greatest increase in both maximum and minimum temperature was projected under the highest forcing emission scenario, SSP 585. With a persistent increase in air temperature and precipitation patterns fluctuating under a future climate scenario in the coastal area of China, climate change can influence all aspects of life, especially water resource distribution and agricultural water management. This study provides valuable insight for water resources planners and agricultural experts in the coastal region of China, as this area is a very vulnerable area to climate change and is also the main staple food-producing area in China.
Precipitation plays a critical role in the hydrological cycle and significantly influences the biodiversity of the Earth’s ecosystems. It also regulates socioeconomic systems by impacting agricultural production and water resources. Analyzing climate-driven changes in precipitation patterns is essential for understanding the hydrological cycle’s response to global warming. This study analyzed the projections of five general circulation models (GCMs) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to evaluate variations in the seasonal and annual patterns of future precipitation over the northern highlands of Pakistan (NHP). The analysis focused on precipitation variations projected for the near future (2021–2050), in comparison to the historical climate (1985–2014), utilizing two combined scenarios from the Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP2-4.5 and SSP5-8.5). This study employed the multi-model ensemble (MME) approach, which demonstrated notable seasonal and annual variations in precipitation across the NHP. The average annual precipitation is expected to decrease in both scenarios, with SSP2-4.5 expecting a reduction of −21.42% and SSP5-8.5 expecting a decrease of −22.43%, compared to the historical average precipitation. In both scenarios, the seasonal precipitation patterns are similar. However, the changes are more noticeable in the spring and summer. Both SSPs predict a 15% decrease in summer precipitation, while SSP2-4.5 and SSP5-8.5 predict a 5% and 4% decrease in spring precipitation, respectively. These changes can result in more frequent and intense periods of drought, which might adversely impact agriculture, human health, the environment, hydropower generation, and the surrounding ecosystem. This study provides important insights into projected seasonal and annual precipitation changes over the NHP, which is particularly susceptible to the effects of climate change. Thus, it is crucial to understand these predicted changes in precipitation in order to develop strategies for adapting to the climate, assuring water security, and promoting sustainable agricultural practices in this area.
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