Spatio-temporal analysis of the geographical centroids for three major crops in China from 1949 to 2014

Spatial distribution changes in major crops can reveal important information about cropping systems. Here, a new centroid method that applies physics and mathematics to spatial pattern analysis in agriculture is proposed to quantitatively describe the historical centroids of rice, maize and wheat in China from 1949 to 2014. The geographical centroids of the rice area moved 413.39 km in a 34.32° northeasterly (latitude 3.08°N, longitude 2.10°E) direction at a speed of 6.36 km/year from central Hunan province to Hubei province, while the geographical centroids of rice production moved 509.26 km in the direction of 45.44° northeasterly (latitude 3.22°N, longitude 3.27°E) at a speed of 7.83 km/year from central Hunan province to Henan province. The geographical centroids of the maize area and production moved 307.15 km in the direction of 34.33° northeasterly (latitude 2.29°N, longitude 1.56°E) and 308.16 km in the direction of 30.79° northeasterly (latitude 2.39°N, longitude 1.42°E), respectively. However, the geographical centroids of the wheat area and production were randomly distributed along the border of Shanxi and Henan provinces. We divided the wheat into spring wheat and winter wheat and found that the geographical centroids of the spring wheat area and production were distributed within Inner Mongolia, while the geographical centroids of winter wheat were distributed in Shanxi and Henan provinces. We found that the hotspots of crop cultivation area and production do not always change concordantly at a larger, regional scale, suggesting that the changing amplitude and rate of each crops’ yield differ between different regions in China. Thus, relevant adaptation measures should be taken at a regional level to prevent production damage in those with increasing area but decreasing production.     

2021年贵州省粮油作物生长季 农业气候评价

为了评估2021粮油作物生长季内气象条件对农业生产的影响,根据贵州84个观测站的气温、降水、日照3个气象要素的变化特点,结合作物生物学特性对气象的要求,并与历史同期气象条件进行对比,结论为：（1）夏收粮油农业气象条件利弊相当,属于正常气候年景：生长季内光热条件适宜;出苗期受秋绵雨影响,苗情偏弱;关键生育期前期,光温水匹配良好,利于产量形成,后期受两个旬的低温阴雨寡照天气影响,不利于灌浆,随后天气转好,作物恢复生长,气象条件有利于收获晾晒。（2）秋粮作物农业气象条件利大于弊,属于较好气候年景：生长季内光温水匹配良好,作物生长后期气象条件优于生长前期;营养生长期受2次低温阴雨寡照天气影响,苗情略偏弱,随后天气转好,生殖生长期光温充足,夏旱偏轻发生,利于秋粮作物生长发育和单产提升。     

地下水埋深对作物产量与水分利用效率的影响及作物系数变化

采用排水式蒸渗仪试验,研究不同地下水埋深对冬小麦和春玉米产量和水分利用效率的影响及其作物系数的变化,表明冬小麦和春玉米生育期的地下水位分别控制在1.5 m和1.0 m以下时产量和水分利用效率最为适宜,作物系数随地下水埋深的变化而变化,幅度可达到0.5～0.6,作物系数最大值处于1.2 m埋深处。研究结果可为地下水埋深较...     

Water Requirements and Irrigation Scheduling of Spring Maize Using GIS and CropWat Model in Beijing-Tianjin-Hebei Region

Due to the over use of available water resources, it has become very important to define appropriate strategies for planning and management of irrigated farmland. In this paper, Beijing-Tianjin-Hebei (Jing-Jin-Ji) region was chosen as the case study area for its special political and economic status and its severe water problem. To achieve effective planning, the information about crop water requirements, irrigation withdrawals, soil types and climatic conditions were obtained in the study area. In the meantime, a GIS method was adopted, which extends the capabilities of the crop models to a regional level. The main objectives of the study are: 1) to estimate the spatial distribution of the evapotranspiration of spring maize; 2) to estimate climatic water deficit; 3) to estimate the yield reduction of spring maize under different rainfed and irrigated conditions. Based on the water deficit analysis, recommended supplemental irrigation schedule was developed using CropWat model. Compared to the rainfed control, the two or three times of supplemental water irrigated to spring maize at the right time reduced the loss of yield, under different scenarios.     

华北平原冬小麦—夏玉米轮作区DLM与CLM5模型模拟对比研究

作物生长与气候的互馈是当前气候变化研究的热点之一。陆面模型作为一项重要的研究工具,其模型框架、算法设计及参数化方案的不同会直接导致模拟结果的不确定性。为探究陆面模型DLM(dynamic land model)和CLM5(community land model)在作物生长及农田热通量模拟方面的差异及原因,评估2个模型在华北平原作物研究中的适用程度,论文开展了冬小麦—夏玉米轮作站点的模拟对比研究。结果显示,DLM的夏玉米叶面积指数和生态系统总初级生产力的模拟值更高,与观测值更为接近;CLM5模型则在冬小麦模拟中略优。DLM的潜热模拟值与观测值的相关性普遍更高,可能反映了DLM采用的彭曼公式、双叶策略比CLM5采用基于水势梯度质量守恒、大叶策略的潜热计算方法更具优势。对于产量,模型当前的估测能力并不理想。总的来说,在默认设定下,2个模型的模拟结果能基本反映研究区农田站点内夏玉米和冬小麦的生长规律,但与实测值存在一定偏差。模型在该区域的适用性可能需要通过添加农田管理措施、算法优化和参数本地化等方式进一步提高。     

Attribution of Maize Yield Increase in China to Climate Change and Technological Advancement Between 1980 and 2010

Crop yields are affected by climate change and technological advancement. Objectively and quantitatively evaluating the attribution of crop yield change to climate change and technological advancement will ensure sustainable development of agriculture under climate change. In this study, daily climate variables obtained from 553 meteorological stations in China for the period 1961-2010, detailed observations of maize from 653 agricultural meteorological stations for the period 1981-2010, and results using an Agro-Ecological Zones (AEZ) model, are used to explore the attribution of maize (Zea mays L.) yield change to climate change and technological advancement. In the AEZ model, the climatic potential productivity is examined through three step-by-step levels: photosynthetic potential productivity, photosynthetic thermal potential productivity, and climatic potential productivity. The relative impacts of different climate variables on climatic potential productivity of maize from 1961 to 2010 in China are then evaluated. Combined with the observations of maize, the contributions of climate change and technological advancement to maize yield from 1981 to 2010 in China are separated. The results show that, from 1961 to 2010, climate change had a significant adverse impact on the climatic potential productivity of maize in China. Decreased radiation and increased temperature were the main factors leading to the decrease of climatic potential productivity. However, changes in precipitation had only a small effect. The maize yields of the 14 main planting provinces in China increased obviously over the past 30 years, which was opposite to the decreasing trends of climatic potential productivity. This suggests that technological advancement has offset the negative effects of climate change on maize yield. Technological advancement contributed to maize yield increases by 99.6%-141.6%, while climate change contribution was from-41.4% to 0.4%. In particular, the actual maize yields in Shandong, Henan, Jilin, and Inner Mongolia increased by 98.4, 90.4, 98.7, and 121.5 kg hm^-2 yr^-1 over the past 30 years, respectively. Correspondingly, the maize yields affected by technological advancement increased by 113.7, 97.9, 111.5, and 124.8 kg hm^-2 yr^-1, respectively. On the contrary, maize yields reduced markedly under climate change, with an average reduction of-9.0 kg hm^-2 yr^-1. Our findings highlight that agronomic technological advancement has contributed dominantly to maize yield increases in China in the past three decades.     

郑州市夏玉米生长季土壤水分变化特征分析

利用线性趋势估计、Mann—Kendall检验等方法对1981—2010年郑州市夏玉米生育期内土壤湿度的年际及垂直变化特征进行了分析,结果表明：近30a来郑州地区夏玉米生长季土壤水分呈显著的下降趋势,0—40cm、40—100am下降速率分别为-3．34％／10a和-5．94％／10a;0—40em在1986年形成一个突变点,40一100CIYI在1998年形成一个突变点,突变点后土壤湿度下降明显;夏玉米生育期内,土壤湿度随生育进程的推进不断增加,到乳熟期后维持在较高水平,同一生育阶段由浅及深各层土壤湿度变异系数逐步减小;各层次土壤湿度的垂直分布基本呈现上干下湿的状态,各生育阶段各层土壤湿度多表现为乳熟期的〉抽雄期的〉拔节期的〉出苗期的。     

Cartographie des accidents régionaux et identification de leur rôle dans l'hydrodynamique souterraine en zone de socle. Cas de la région de Dimbokro-Bongouanou (Côte d'Ivoire)

Abstract

This paper reviews current knowledge of the potential impacts of climate change on water resources in Africa and the possible limits, barriers or opportunities for adaptation to climate change in internationally-shared river basins. Africa faces significant challenges to water resources management in the form of high variability and regional scarcity, set within the context of generally weak institutional capacity. Management is further challenged by the transboundary nature of many of its river basins. Climate change, despite uncertainty about the detail of its impacts on water resources, is likely to exacerbate many of these challenges. River basins, and the riparian states that share them, differ in their capacities to adapt. Without appropriate cooperation adaptation may be limited and uneven. Further research to examine the factors and processes that are important for cooperation to lead to positive adaptation outcomes and the increased adaptive capacity of water management institutions is suggested.     

Maize drought disaster risk assessment of China based on EPIC model

Abstract

Digital Agriculture is one of the important applications of Digital Earth. As the global climate changes and food security becomes an increasingly important issue, agriculture drought comes to the focus of attention. China is a typical monsoon climate country as well as an agricultural country with the world's largest population. The East Asian monsoon has had a tremendous impact upon agricultural production. Therefore, a maize drought disaster risk assessment, in line with the requirements of sustainable development of agriculture, is important for ensuring drought disaster reduction and food security. Meteorology, soil, land use, and agro-meteorological observation information of the research area were collected, and based on the concept framework of ‘hazard-inducing factors assessment (hazard)-vulnerability assessment of hazard-affected body (vulnerability curve)-risk assessment (risk),’ importing crop model EPIC (Erosion-Productivity Impact Calculator), using crop model simulation and digital mapping techniques, quantitative assessment of spatio-temporal distribution of maize drought in China was done. The results showed that: in terms of 2, 5, 10, and 20 year return periods, the overall maize drought risk decreased gradually from northwest to southeast in the maize planting areas. With the 20 year return period, high risk value regions (drought loss rate ≥0.5) concentrate in the irrigated maize region of Northwest china, ecotone between agriculture and animal husbandry in Northern China, Hetao Irrigation Area, and north-central area of North China Plain, accounting for 6.41% of the total maize area. These results can provide a scientific basis for the government's decision-making in risk management and drought disaster prevention in China.