江南雨季地理区域及起止时间的客观确定

本文基于国家气象信息中心整编的全国1 675个台站观测资料以及NCEP/NCAR的再分析资料,定义了候降水指数,利用旋转正交经验函数分解(REOF)法对全国候降水的季节进程进行了诊断分析,得到了表征气候态降水逐候进程的南、北方模态及各自的时间系数,发现REOF第二模态对应降水季节进程中的江南雨季。综合考虑我国南方(31°N以南、110°E以东区域)气候态降水的候进程、降水季节进程(4-6月降水指数减去6-8月降水指数)年际变率以及雨季(4-6月降水指数)降水年际变率的一致性,客观定义了江南雨季的地理范围。利用客观划定区域内的降水指数、925hPa经向风以及西北太平洋副热带高压500hPa脊线位置3个指标,制定了判定江南雨季起止时间的方法,进而对1961-2012年江南雨季起止时间进行了客观确定,给出了江南雨季起止时间序列。本文旨在为规范江南雨季的监测提供参考和借鉴,并为其预测提供科学基础。     

应用现场实测波浪资料直接计算沿岸输沙率

本文应用波能流守恒法则，导得可直接应用现场实测波浪资料计算沿岸输沙率关系式。通过两个实例计算，说明计算值与实际沿岸输沙率一致。     

Refining image-velocimetry performances for streamflow monitoring: Seeding metrics to errors minimization

River streamflow monitoring is currently facing a transformation due to the emerging of new innovative technologies. Fixed and mobile measuring systems are capable of quantifying surface flow velocities and discharges, relying on video acquisitions. This camera-gauging framework is sensitive to what the camera can “observe” but also to field circumstances such as challenging weather conditions, river background transparency, transiting seeding characteristics, among others. This short communication paper introduces the novel idea of optimizing image velocimetry techniques selecting the most informative sequence of frames within the available video. The selection of the optimal frame window is based on two reasonable criteria: (a) the maximization of the number of frames, subject to (b) the minimization of the recently introduced dimensionless seeding distribution index (SDI). SDI combines seeding characteristics such as seeding density and spatial clustering of tracers, which are used as a proxy to enhance the reliability of image velocimetry techniques. Two field case studies were considered as a proof-of-concept of the proposed framework, on which seeding metrics were estimated and averaged in time to select the proper application window. The selected frames were analysed using LSPIV to estimate the surface flow velocities and river discharge. Results highlighted that the proposed framework might lead to a significant error reduction. In particular, the computed discharge errors, at the optimal portion of the footage, were about 0.40% and 0.12% for each case study, respectively. These values were lower than those obtained, considering all frames available.     

云南雨季开始期的特征以及与南海季风和印度季风开始期的可能关系

应用EOF、Morlet小波分析方法对云南雨季开始期的时空特征及多尺度周期变化特征进行分析,使用相关分析初步分析印度季风和南海季风开始期与其关系.结果表明：（1）云南雨季开始期的EOF第一模态表明全省雨季开始期一致偏早（晚）,EOF第二模态表明滇中及以东、滇东北、滇东南、滇西南部分地区与滇西、滇西北、滇南大部分地区雨季开始期反相变化的空间分布特征.（2）云南雨季开始期存在着明显的周期性波动,连续小波变换分析表明云南雨季开始期存在2～4年和5～7年的振荡周期.（3）南海季风开始期与云南雨季开始期相关不好,印度季风开始期与云南雨季开始期存在很好的相关性.     

不同播期的优质小麦产量结构分析

对不同优质小麦品种不同播期的产量结构分析结果表明:河北-8901的各种产量结构表现出最为稳定的变化规律,即不同的播期处理对最后产量的影响度相对较小;郑麦-9405和郑麦-9023的产量结构在不同的播期表现出较大的波动。     

不同稻麦种植模式适应气候变化的效益比较分析

通过调查江苏省全球环境基金项目区农户和专家的投入产出,使用成本效益分析方法和IPCC推荐的温室气体估算方法评估比较了3种种植方式（人工插秧、机械插秧和直播）的水稻在麦稻轮作复种“两晚”模式（水稻晚收, 小麦晚播）下的社会、经济和生态效益。结果表明：水稻直播和机械插秧可以节省更多劳动力;农业机械燃油、施用化肥、稻田淹水等农作措施导致了大量人为温室气体排放;水稻种植方式为人工插秧的麦稻轮作模式能取得最优的经济和生态效益;“两晚”模式实施的关键是适时地利用近年来增加的农业气候资源。水稻人工插秧与麦稻“两晚”相配合的种植模式是减缓和适应气候变化的较优选择。     

甘肃黄土高原春季第一场透雨的时空分布特征

文中利用甘肃黄土高原1971—2000年56个站的降水资料，分析了春季第一场透雨日期的变化特征，用EOF和REOF方法对其做了分解，进行了透雨日期的气候分区。结果表明，透雨早的年份，春季降水偏多，20世纪90年代以来，透雨日期以偏迟为主。     

Discriminating transplanted and direct seeded rice using Sentinel-1 intensity data

Improved rice crop and water management practices that make the sustainable use of resources more efficient are important interventions towards a more food secure future. A remote sensing-based detection of different rice crop management practices, such as crop establishment method (transplanting or direct seeding), can provide timely and cost-effective information on which practices are used as well as their spread and change over time as different management practices are adopted. Establishment method cannot be easily observed since it is a rapid event, but it can be inferred from resulting observable differences in land surface characteristics (i.e. field condition) and crop development (i.e. delayed or prolonged stages) that take place over a longer time. To examine this, we used temporal information from Synthetic Aperture Radar (SAR) backscatter to detect differences in field condition and rice growth, then related those to crop establishment practices in Nueva Ecija (Philippines). Specifically, multi-temporal, dual-polarised, C-band backscatter data at 20m spatial resolution was acquired from Sentinel-1A every 12 days over the study area during the dry season, from November 2016 to May 2017. Farmer surveys and field observations were conducted in four selected municipalities across the study area in 2017, providing information on field boundaries and crop management practices for 61 fields. Mean backscatter values were generated per rice field per SAR acquisition date. We matched the SAR acquisition dates with the reported dates for land management activities and with the estimated dates for when the crop growth stages occurred. The Mann-Whitney U test was used to identify significant differences in backscatter between the two practices during the land management activities and crop growth stages. Significant differences in cross-polarised, co-polarised and band ratio backscatter values were observed in the early growing season, specifically during land preparation, crop establishment, rice tillering and stem elongation. These findings indicate the possibility to discriminate crop establishment methods by SAR at those stages, suggesting that there is more opportunity for discrimination than has been presented in previous studies. Further testing in a wider range of environments, seasons, and management practices should be done to determine how reliably rice establishment methods can be detected. The increased use of dry and wet direct seeding has implications for many remote sensing-based rice detection methods that rely on a strong water signal (typical of transplanting) during the early season.     

Understanding long-term (1982–2013) patterns and trends in winter wheat spring green-up date over the North China Plain

Monitoring the spring green-up date (GUD) has grown in importance for crop management and food security. However, most satellite-based GUD models are associated with a high degree of uncertainty when applied to croplands. In this study, we introduced an improved GUD algorithm to extract GUD data for 32 years (1982–2013) for the winter wheat croplands on the North China Plain (NCP), using the third-generation normalized difference vegetation index form Global Inventory Modeling and Mapping Studies (GIMMS3g NDVI). The spatial and temporal variations in GUD with the effects of the pre-season climate and soil moisture conditions on GUD were comprehensively investigated. Our results showed that a higher correlation coefficient (r = 0.44, p < 0.01) and lower root mean square error (22 days) and bias (16 days) were observed in GUD from the improved algorithm relative to GUD from the MCD12Q2 phenology product. In spatial terms, GUD increased from the southwest (less than day of year (DOY) 60) to the northeast (more than DOY 90) of the NCP, which corresponded to spatial reductions in temperature and precipitation. GUD advanced in most (78%) of the winter wheat area on the NCP, with significant advances in 37.8% of the area (p < 0.05). GUD occurred later at high altitudes and in coastal areas than in inland areas. At the interannual scale, the average GUD advanced from DOY 76.9 in the 1980s (average 1982–1989) to DOY 73.2 in the 1990s (average 1991–1999), and to DOY 70.3 after 2000 (average 2000–2013), indicating an average advance of 1.8 days/decade (r = 0.35, p < 0.05). Although GUD is mainly controlled by the pre-season temperature, our findings underline that the effect of the pre-season soil moisture on GUD should also be considered. The improved GUD algorithm and satellite-based long-term GUD data are helpful for improving the representation of GUD in terrestrial ecosystem models and enhancing crop management efficiency.