FY-1C可见光通道衰减分析及订正试验

利用FY-1C连续两年的遥感资料，以敦煌辐射校正场为分析区，系统分析了FY-1C可见光、近红外通道的衰减特征，开展了通道衰减订正试验。分析结果表明，FY-1C除可见光通道1衰减强烈外，其它各可见光、近红外通道衰减性能稳定。利用统计分析法，可以建立定标系数衰减订正量随时间的变化关系。订正后的定标系数与2000年辐射校正场外定标实验结果一致性很好。更新后的定标系数可以有效克服通道衰减带来的通道反射率测值误差，提高FY-1C可见光、近红外通道遥感资料定量应用的精度。     

芦苇化感组分对羊角月牙藻和雷氏衣藻生长特性的影响

研究了从芦苇(Phragmitis communis Trin)中分离得到的化感组分对羊角月牙藻(Selenastrum caprtcornutum)和雷氏衣藻(Chlamydomonas reinhardtii)生长特性的影响.在藻类生长的对数期向培养液中投加不同浓度的化感组分,分别测定并观察了培养期间受试藻种藻密度和藻细胞形态的变化情况.结果表明,该化感组分对羊角月牙藻藻密度的增长具有明显的抑制作用,半效应浓度(EC50.7d)值为0.60mg/L,同时使羊角月牙藻细胞内部结构改变,形态变大.投加6mg/L化感组分后,藻细胞平均宽度是对照组的1.5倍.该化感组分对雷氏衣藻藻密度的增长没有明显的抑制作用,但使其运动性能降低.     

三峡水库消落区植物群落演变趋势及优势植物适应策略

三峡水库周期性蓄水显著改变了消落区植物群落组成及多样性,植物群落的演变过程能反映和影响整个消落区生态系统的变化,但目前还缺乏长期连续的观测数据记录,因而本研究基于2009—2021年6月的固定样方长时间序列监测数据和优势植物叶片功能性状数据,分析了消落区3个高程(145～155、155～165和165～175m)区域植物群落多样性和优势植物重要值的变化趋势,通过冗余分析和蒙特卡罗检验揭示了水库运行特征参数和气象因子对消落区植物特征的影响。研究发现:1)消落区3个高程区域,优势植物差异明显,145～155和155～165 m区域以狗牙根、香附子和苍耳等为主,165～175 m区域以狗牙根、野胡萝卜和鬼针草等为主。145～155 m区域植物群落Shannon-Wiener多样性指数(1.47±0.47)和Pielou均匀度指数(0.67±0.07)显著低于165～175 m区域。2)2009—2021年期间,高程145～155和155～165 m区域Shannon-Wiener多样性指数和Pielou均匀度指数呈波动下降趋势,优势植物狗牙根和香附子的重要值呈增加趋势。3) RDA分析表明,...     

Comparison of soil moisture products from microwave remote sensing,land model,and reanalysis using global ground observations

High-quality soil moisture (SM) datasets are in great demand for climate, hydrology, and other fields, but detailed evaluation of SM products from various sources is scarce. Thus, using 670 SM stations worldwide, we evaluated and compared SM products from microwave remote sensing [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) (C- and X-bands) and European Space Agency's Climate Change Initiative (ESA CCI)], land surface model [Global Land Data Assimilation System (GLDAS)], and reanalysis data [ECMWF Re-Analysis-Interim (ERA-Interim) and National Centers for Environmental Prediction (NCEP)] under different time scales and various climates and land covers. We find that: (a) ESA CCI and GLDAS have the closest values to the in situ SM on the annual scale, whereas others overestimate the SM; ERA-Interim (averaged R = 0.58) and ESA CCI (averaged R = 0.54) correlate best with the in situ data, while GLDAS performs worst. (b) Overall, the deviations of each product vary in seasons. ESA CCI and ERA-Interim products are closer to the in situ SM at seasonal scales, and AMSR-E and NCEP perform worst in December–February and June–August, respectively. (c) Except for NCEP and ERA-Interim, others can well reflect the intermonthly variation of the in situ SM. (d) Under various climates and land covers, AMSR-E products are less effective in cold climates, whereas GLDAS and NCEP products perform poorly in arid or temperate and dry climates. Moreover, the Bias and R of each SM product differ obviously under different forest types, especially the AMSR-E products. In summary, SM from ESA CCI is the best, followed by ERA-Interim product, and precipitation is an important auxiliary data for selecting high-quality SM stations and improving the accuracy of SM from GLDAS. These results can provide a reference for improving the accuracy of the above SM products.     

Effects of climate change and agronomic practice on changes in wheat phenology

Phenological changes in crops affect efficient agricultural production and can be used as important biological indicators of local and regional climate change. Although crop phenological changes and their responses to climate change, especially temperature, have been investigated, the impact of agronomic practice such as cultivar shifts and planted date changes on crop phenology remains unclear. Here, we used a long-term dataset (1981–2010) of wheat phenology and associated local weather data from 48 agro-meteorological stations in four temperature zones in China to analyze phenological changes of spring and winter wheat. Trend analysis method was used to estimate changes in the date of growth stages and the duration of growth phases, while sensitivity analysis method was used to qualify the response of growth phase duration to mean temperature (T_mean), total precipitation (PRE), and total sunshine duration (SSD). Using the Crop Environment Resource Synthesis-wheat model, we isolated the impacts of climate change, cultivar selection, and sowing date on phenological change of wheat. Results show that phenological changes were greatest in the warm-temperate zone. Sensitivity analysis indicates that growth phase duration was generally negatively related to T_mean and positively related to PRE and SSD. The positive sensitivity response to T_mean occurred in the tillering to jointing and sowing to maturity growth periods in the warmer temperature zones, suggesting that warmer temperatures during the overwintering period hampered effective vernalization in winter wheat. Modeling results further indicate that reductions in wheat growth duration caused by climate change could be offset by the introduction of new cultivars with high thermal requirements and accelerated with delayed sowing date.     

A data-driven SVR model for long-term runoff prediction and uncertainty analysis based on the Bayesian framework

Accurate and reliable long-term forecasting plays an important role in water resources management and utilization. In this paper, a hybrid model called SVR-HUP is presented to predict long-term runoff and quantify the prediction uncertainty. The model is created based on three steps. First, appropriate predictors are selected according to the correlations between meteorological factors and runoff. Second, a support vector regression (SVR) model is structured and optimized based on the LibSVM toolbox and a genetic algorithm. Finally, using forecasted and observed runoff, a hydrologic uncertainty processor (HUP) based on a Bayesian framework is used to estimate the posterior probability distribution of the simulated values, and the associated uncertainty of prediction was quantitatively analyzed. Six precision evaluation indexes, including the correlation coefficient (CC), relative root mean square error (RRMSE), relative error (RE), mean absolute percentage error (MAPE), Nash-Sutcliffe efficiency (NSE), and qualification rate (QR), are used to measure the prediction accuracy. As a case study, the proposed approach is applied in the Han River basin, South Central China. Three types of SVR models are established to forecast the monthly, flood season and annual runoff volumes. The results indicate that SVR yields satisfactory accuracy and reliability at all three scales. In addition, the results suggest that the HUP cannot only quantify the uncertainty of prediction based on a confidence interval but also provide a more accurate single value prediction than the initial SVR forecasting result. Thus, the SVR-HUP model provides an alternative method for long-term runoff forecasting.     

Impact of SST Anomaly Events over the Kuroshio-Oyashio Extension on the “Summer Prediction Barrier”

The "summer prediction barrier"(SPB) of SST anomalies(SSTA) over the Kuroshio–Oyashio Extension(KOE) refers to the phenomenon that prediction errors of KOE-SSTA tend to increase rapidly during boreal summer, resulting in large prediction uncertainties. The fast error growth associated with the SPB occurs in the mature-to-decaying transition phase,which is usually during the August–September–October(ASO) season, of the KOE-SSTA events to be predicted. Thus, the role of KOE-SSTA evolutionary characteristics in the transition phase in inducing the SPB is explored by performing perfect model predictability experiments in a coupled model, indicating that the SSTA events with larger mature-to-decaying transition rates(Category-1) favor a greater possibility of yielding a more significant SPB than those events with smaller transition rates(Category-2). The KOE-SSTA events in Category-1 tend to have more significant anomalous Ekman pumping in their transition phase, resulting in larger prediction errors of vertical oceanic temperature advection associated with the SSTA events. Consequently, Category-1 events possess faster error growth and larger prediction errors. In addition, the anomalous Ekman upwelling(downwelling) in the ASO season also causes SSTA cooling(warming), accelerating the transition rates of warm(cold) KOE-SSTA events. Therefore, the SSTA transition rate and error growth rate are both related with the anomalous Ekman pumping of the SSTA events to be predicted in their transition phase. This may explain why the SSTA events transferring more rapidly from the mature to decaying phase tend to have a greater possibility of yielding a more significant SPB.     

Construction and Application of a Climate Risk Index for China

In the context of global warming, China is facing with increasing climate risks. It is imperative to develop quantitative indices to reflect the climate risks caused by extreme weather/climate events and adverse climatic conditions in association with different industries. Based on the observations at 2288 meteorological stations in China and the meteorological disasters data, a set of indices are developed to measure climate risks due to water-logging, drought, high temperature, cryogenic freezing, and typhoon. A statistical method is then used to construct an overall climate risk index (CRI) for China from these individual indices. There is a good correspondence between these indices and historical climatic conditions. The CRI, the index of water-logging by rain, and the high temperature index increase at a rate of 0.28, 0.37, and 0.65 per decade, respectively, from 1961 to 2016. The cryogenic freezing index is closely related to changes in the consumer price index for food. The high temperature index is correlated with the consumption of energy and electricity. The correlation between the yearly growth in claims on household property insurance and the sum of the water-logging index and the typhoon index in the same year is as high as 0.70. Both the growth rate of claims on agricultural insurance and the annual growth rate of hospital inpatients are positively correlated with the CRI. The year-on-year growth in the number of domestic tourists is significantly negatively correlated with the CRI in the same year. More efforts are needed to develop regional CRIs.     

水化蒙脱石在浓电解质溶液中的特征及对溶液电导率的影响

经水化的蒙脱石,具有特殊的性能.本文通过经纯水水化的蒙脱石和未经纯水水化的蒙脱石,在浓Nil_4Cl溶液中的行为及对溶液电导率的影响,说明蒙脱石经纯水水化,在其表面形成较厚的水化膜,在浓NH_4Cl溶液中不易被NH_4~(+)离子“剥离”掉,表现出具有特殊的胶体性能.     

塔里木盆地东河1油藏低渗层层序控制特征及其对注气开发的影响

通过测井和岩心分析,将塔里木东河1油藏东河砂岩段从下到上划分为前滨-上临滨-下临滨相带,并进一步划分出11个准层序。经岩相学分析,将砂岩段低渗层分为钙质胶结低渗层、杂基充填低渗层和混合低渗层。钙质胶结低渗层主要分布在准层序内部,以方解石胶结砂岩为主,受成岩作用控制;杂基充填低渗层主要分布在准层序边界处,多为海侵背景下的滞后沉积产物;混合低渗层在准层序内部及边界均有分布,但数量很少,无明显规律性,砂粒间主要由杂基和方解石胶结物混合充填,充填物含量低。结合测压资料认为,发育在准层序边界处的杂基低渗层保留了更多的初始沉积特征,易形成横向连续性好的低渗层,是注气开发的重点关注对象。