Improving agricultural water productivity, under rainfed or irrigated conditions, holds significant scope for addressing climate change vulnerability. It also offers adaptation capacity needs as well as water and food...Improving agricultural water productivity, under rainfed or irrigated conditions, holds significant scope for addressing climate change vulnerability. It also offers adaptation capacity needs as well as water and food security in the southern African region. In this study, evidence for climate change impacts and adaptation strategies in rainfed agricultural systems is explored through modeling predictions of crop yield, soil moisture and excess water for potential harvesting. The study specifically presents the results of climate change impacts under rainfed conditions for maize, sorghum and sunflower using soil-water-crop model simulations, integrated based on daily inputs of rainfall and evapotranspiration disaggregated from GCM scenarios. The research targets a vast farming region dominated by heavy clay soils where rainfed agriculture is a dominant practice. The potential for improving soil water productivity and improved water harvesting have been explored as ways of climate change mitigation and adaptation measures. This can be utilized to explore and design appropriate conservation agriculture and adaptation practices in similar agro-ecological environments, and create opportunities for outscaling for much wider areas. The results of this study can suggest the need for possible policy refinements towards reducing vulnerability and adaptation to climate change in rainfed farming systems.展开更多
Soil organic carbon （SOC） is an important indicator of soil degradation process. In this study, the long-term SOC evolution in Chinese mollisol farmland was simulated and predicted by validating, analyzing, processi...Soil organic carbon （SOC） is an important indicator of soil degradation process. In this study, the long-term SOC evolution in Chinese mollisol farmland was simulated and predicted by validating, analyzing, processing and assorting concerning data, based on clarifying parameters of Century model need, combined with best use of recorded data of field management, observed data of long-term experiments, climate, soil, and biology, and achieved results from Hailun Agro-Ecological Experimental Station, Chinese Academy of Sciences. The results were showed as follows： Before reclamation, SOC content was around 58.00 g kg^-1, SOC content dropped quickly in early years, and then decreased slowly after reclamation. SOC content was around 34.00 g kg^-1 with a yearly average rate of 8.91‰ decrease before long-term experiments was established. After a long-term experiment, SOC would change under different farming systems. Shift farming system changed as follows： By 20-year model simulation, SOC content decreased from 34.03 to 30.19 g kg^-1, with a yearly average rate of 5.97‰; by 100-year model simulation, SOC content decreased to 24.31 g kg^-1, with a yearly average rate of 3.36‰. Organic farming system changed as follows： By 20-year model simulation, SOC content decreased slowly from 34.03 to 33.39 g kg^-1, with a yearly average rate of 0.95‰, 5‰ less than that of shift farming system; by 100-year model simulation, SOC content decreased to 32.21 g kg^-1, with a yearly average rate of 0.55‰. ＂Petroleum＂ farming system changed as follows： By 20-year model simulation, SOC content decreased from 34.03 to 32.88 g kg^-1, with a yearly average rate of 1.72‰, much more than that of organic farming system; by 100-year model simulation, SOC content decreased to 30.89 g kg^-1, with a yearly average rate of 0.96‰. Combined ＂petroleum＂-organic farming system changed as follows： By 20-year model simulation, SOC content was increased slightly; by 100-year model simulation, SOC content increased from 34.03 to 34.41g kg^-1, with a yearly average rate of 0.11‰. The above results provided an optimal way for maintaining SOC in Chinese mollisol farmland： To increase, as much as possible within agro-ecosystem, soil organic matter returns such as crop stubble, crop litter, crop straw or stalk, and manure, besides applying chemical nitrogen and phosphorous, which increased system productivity and maintained SOC content as well. Also, the results provided a valuable methodology both for a study of CO2 sequestration capacity and for a target fertility determination in Chinese mollisol.展开更多
集电系统拓扑优化是大型海上风电场规划建设的核心问题,本质上是一个涉及多约束、多目标的复杂混合整数优化问题。针对该问题,提出了一种基于大语言模型(large language model,LLM)辅助的大型海上风电场集电系统拓扑优化方法。首先,基...集电系统拓扑优化是大型海上风电场规划建设的核心问题,本质上是一个涉及多约束、多目标的复杂混合整数优化问题。针对该问题,提出了一种基于大语言模型(large language model,LLM)辅助的大型海上风电场集电系统拓扑优化方法。首先,基于大语言模型辅助对风电机组群进行聚类,通过链式提示法使LLM理解优化目标,并利用LLM将大型海上风电场分割为若干小型区域,以降低优化问题维度,提升求解速度和质量。然后,构建集电系统拓扑优化模型,基于混合整数线性规划求解器,获得海上风电场的最优集电系统拓扑设计方案。最后,利用1个含有75台风电机组的大型海上风电场系统进行方法性能验证,仿真结果表明:与传统优化技术相比,所提方法获得的聚类风机数量更加均衡,在考虑拓扑功率损耗的同时,生成的拓扑方案经济性最优。LLM在集电系统拓扑辅助优化中具有较高的有效性,为海上风电场集电系统拓扑设计优化提供了一种新思路。展开更多
文摘Improving agricultural water productivity, under rainfed or irrigated conditions, holds significant scope for addressing climate change vulnerability. It also offers adaptation capacity needs as well as water and food security in the southern African region. In this study, evidence for climate change impacts and adaptation strategies in rainfed agricultural systems is explored through modeling predictions of crop yield, soil moisture and excess water for potential harvesting. The study specifically presents the results of climate change impacts under rainfed conditions for maize, sorghum and sunflower using soil-water-crop model simulations, integrated based on daily inputs of rainfall and evapotranspiration disaggregated from GCM scenarios. The research targets a vast farming region dominated by heavy clay soils where rainfed agriculture is a dominant practice. The potential for improving soil water productivity and improved water harvesting have been explored as ways of climate change mitigation and adaptation measures. This can be utilized to explore and design appropriate conservation agriculture and adaptation practices in similar agro-ecological environments, and create opportunities for outscaling for much wider areas. The results of this study can suggest the need for possible policy refinements towards reducing vulnerability and adaptation to climate change in rainfed farming systems.
基金grants from Dis-tinguished Young Scholar Fund of Heilongjiang Prov-ince (JC200718)the National 863 Program of China(2006AA10Z424)
文摘Soil organic carbon （SOC） is an important indicator of soil degradation process. In this study, the long-term SOC evolution in Chinese mollisol farmland was simulated and predicted by validating, analyzing, processing and assorting concerning data, based on clarifying parameters of Century model need, combined with best use of recorded data of field management, observed data of long-term experiments, climate, soil, and biology, and achieved results from Hailun Agro-Ecological Experimental Station, Chinese Academy of Sciences. The results were showed as follows： Before reclamation, SOC content was around 58.00 g kg^-1, SOC content dropped quickly in early years, and then decreased slowly after reclamation. SOC content was around 34.00 g kg^-1 with a yearly average rate of 8.91‰ decrease before long-term experiments was established. After a long-term experiment, SOC would change under different farming systems. Shift farming system changed as follows： By 20-year model simulation, SOC content decreased from 34.03 to 30.19 g kg^-1, with a yearly average rate of 5.97‰; by 100-year model simulation, SOC content decreased to 24.31 g kg^-1, with a yearly average rate of 3.36‰. Organic farming system changed as follows： By 20-year model simulation, SOC content decreased slowly from 34.03 to 33.39 g kg^-1, with a yearly average rate of 0.95‰, 5‰ less than that of shift farming system; by 100-year model simulation, SOC content decreased to 32.21 g kg^-1, with a yearly average rate of 0.55‰. ＂Petroleum＂ farming system changed as follows： By 20-year model simulation, SOC content decreased from 34.03 to 32.88 g kg^-1, with a yearly average rate of 1.72‰, much more than that of organic farming system; by 100-year model simulation, SOC content decreased to 30.89 g kg^-1, with a yearly average rate of 0.96‰. Combined ＂petroleum＂-organic farming system changed as follows： By 20-year model simulation, SOC content was increased slightly; by 100-year model simulation, SOC content increased from 34.03 to 34.41g kg^-1, with a yearly average rate of 0.11‰. The above results provided an optimal way for maintaining SOC in Chinese mollisol farmland： To increase, as much as possible within agro-ecosystem, soil organic matter returns such as crop stubble, crop litter, crop straw or stalk, and manure, besides applying chemical nitrogen and phosphorous, which increased system productivity and maintained SOC content as well. Also, the results provided a valuable methodology both for a study of CO2 sequestration capacity and for a target fertility determination in Chinese mollisol.
文摘集电系统拓扑优化是大型海上风电场规划建设的核心问题,本质上是一个涉及多约束、多目标的复杂混合整数优化问题。针对该问题,提出了一种基于大语言模型(large language model,LLM)辅助的大型海上风电场集电系统拓扑优化方法。首先,基于大语言模型辅助对风电机组群进行聚类,通过链式提示法使LLM理解优化目标,并利用LLM将大型海上风电场分割为若干小型区域,以降低优化问题维度,提升求解速度和质量。然后,构建集电系统拓扑优化模型,基于混合整数线性规划求解器,获得海上风电场的最优集电系统拓扑设计方案。最后,利用1个含有75台风电机组的大型海上风电场系统进行方法性能验证,仿真结果表明:与传统优化技术相比,所提方法获得的聚类风机数量更加均衡,在考虑拓扑功率损耗的同时,生成的拓扑方案经济性最优。LLM在集电系统拓扑辅助优化中具有较高的有效性,为海上风电场集电系统拓扑设计优化提供了一种新思路。
