科尔沁湿草甸参考作物蒸散发模拟分析     

李霞  刘廷玺  段利民  王冠丽  童新  周亚军  杨晓君 《中国沙漠》2020,40(2):134-143

为探明气候变化下干旱半干旱地区湿草甸参考作物蒸散发(ET₀)影响因子,使用FAO 56 P-M模型对科尔沁湿草甸ET₀进行模拟,利用涡度相关系统对模型的适用性进行评价,并通过通径分析及指标敏感性分析对ET₀的影响因子进行辨识。结果表明:(1)小时尺度模拟精度最高,日尺度次之,月尺度较差,小时尺度上晴、阴、雨3种天气条件下模拟效果不同,晴天最优,阴雨天较差。(2)ET₀年内变化呈单峰曲线状,生长季明显高于非生长季,集中在3—10月,占全年89.79%。生长季典型晴天ET₀逐小时分布特征遵循倒“U”单峰型变化规律。(3)通径分析结果显示,对ET₀的通径系数以及对回归方程估测可靠程度E的总贡献均表现为VPD(饱和水汽压差) > T_min(最低气温) > R_n(冠层表面净辐射)>u₂(2 m高度风速),即VPD为影响ET₀最重要的因子;指标敏感性分析中,在去除VPD后引起的E变化最大,说明ET₀对VPD的变化最为敏感,其次为u₂、T_min和R_n。  相似文献   

Sediment transfer in an extremely low-gradient,low-relief and highly buffered system: Darwin Harbour catchment,northern Australia     

M. Nawaz  R. Wasson 《Australian Journal of Earth Sciences》2020,67(3):351-359

Abstract

Sediment yields from and sediment transfer within catchments of very low relief and gradient, which make up about 50% of Earth’s surface, are poorly documented and their internal sediment dynamics are poorly known. Sediment sources, their proportionate contributions to valley floors and sediment yield, and storage are estimated using fallout radionuclides ²¹⁰Pb_(ex) and ¹³⁷Cs in the catchments that drain into Darwin Harbour, northern Australia, an example of this understudied catchment type that appears to be globally at the extreme end of this category of catchments. Unchannelled grassy valley floors (dambos, or seasonal wetlands) trap ～90% of the sediment delivered from hillslopes by sheet and rill erosion. Further down valley, small channels transport ～10% of the sediment that escapes from the dambos, and the remaining sediment comes from erosion of the channels. In this case, the fractional sediment storage is very high as a result of the existence of dambos, a landform that depends for its existence on low gradients.  相似文献   

基于遗传算法优化BP神经网络的玉米遥感估产方法     

于海洋  陈圣波  杨北萍  安秦 《世界地质》2020,39(1):208-214

以内蒙古自治区开鲁县玉米作物为研究对象,将生育期内玉米遥感影像所提取的多种植被指数和实地采样点的测产数据作为训练值,利用BP(back propagation)神经网络和遗传算法优化BP(GA-BP)神经网络估产模型,得出网络预测的玉米产量数值。通过决定系数R 2和均方根误差RMSE,比较实测产量与预测产量之间的精度,BP神经网络模型R^2为0.8452,RMSE(%)为28.37;遗传算法优化BP神经网络模型R^2为0.9850,RMSE(%)为6.70,表明遗传算法优化BP神经网络估产模型具有一定可行性和可信度。  相似文献   

Some remarks on Q-compensated sparse deconvolution without knowing the quality factor Q     

Xintao Chai  Ronghua Peng  Genyang Tang  Wei Chen  Jingnan Li 《Geophysical Prospecting》2019,67(8):2003-2021

The subsurface media are not perfectly elastic, thus anelastic absorption, attenuation and dispersion (aka Q filtering) effects occur during wave propagation, diminishing seismic resolution. Compensating for anelastic effects is imperative for resolution enhancement. Q values are required for most of conventional Q-compensation methods, and the source wavelet is additionally required for some of them. Based on the previous work of non-stationary sparse reflectivity inversion, we evaluate a series of methods for Q-compensation with/without knowing Q and with/without knowing wavelet. We demonstrate that if Q-compensation takes the wavelet into account, it generates better results for the severely attenuated components, benefiting from the sparsity promotion. We then evaluate a two-phase Q-compensation method in the frequency domain to eliminate Q requirement. In phase 1, the observed seismogram is disintegrated into the least number of Q-filtered wavelets chosen from a dictionary by optimizing a basis pursuit denoising problem, where the dictionary is composed of the known wavelet with different propagation times, each filtered with a range of possible values. The elements of the dictionary are weighted by the infinity norm of the corresponding column and further preconditioned to provide wavelets of different values and different propagation times equal probability to entry into the solution space. In phase 2, we derive analytic solutions for estimates of reflectivity and Q and solve an over-determined equation to obtain the final reflectivity series and Q values, where both the amplitude and phase information are utilized to estimate the Q values. The evaluated inversion-based Q estimation method handles the wave-interference effects better than conventional spectral-ratio-based methods. For Q-compensation, we investigate why sparsity promoting does matter. Numerical and field data experiments indicate the feasibility of the evaluated method of Q-compensation without knowing Q but with wavelet given.  相似文献   

基于散射计风场数据的台风强度诊断方法——以海洋二号卫星数据为例   总被引：2，自引：2，他引：0  

杨典  宋清涛  蒋兴伟  刘宇昕  刘圆 《海洋学报》2019,41(1):151-159

本文提出了一种基于散射计风场数据的台风定强方法。该方法定义了台风所在海区的一个圆形区域上的风速平均值来对台风进行定强，并使用海洋二号卫星散射计历史数据对该方法进行了验证。验证结果表明，该台风定强方法可以克服散射计反演台风风速过低的问题。与台风强度监测的历史记录比较的结果显示，在台风强度低于"强台风"这一强度等级时，该方法能够有效估算台风强度。  相似文献   

一种基于M估计的Robust-ELM滑坡位移预测方法     

高彩云  高宁 《大地测量与地球动力学》2019,39(2):153-157

采用传统ELM算法进行滑坡位移预测时，其网络输出权值由最小二乘估计得出，导致ELM抗差能力较差，从而造成网络训练参数不准确。为此，将M估计与ELM相结合，提出一种基于M估计的Robust-ELM滑坡变形预测方法。该方法利用加权最小二乘方法来取代最小二乘法计算ELM输出权值，以减少滑坡监测数据中粗差对ELM预测的干扰。分别以链子崖、古树屋滑坡体为例，将Robust-ELM进行了单维、多维粗差的抵御性验证。结果表明，该方法能够有效降低粗差对预测的影响，具有良好的抗差能力。  相似文献   

Intercomparison of measurements of bulk snow density and water equivalent of snow cover with snow core samplers: Instrumental bias and variability induced by observers     

J. Ignacio López-Moreno  Leena Leppänen  Bartłomiej Luks  Ladislav Holko  Ghislain Picard  Alba Sanmiguel-Vallelado  Esteban Alonso-González  David C. Finger  Ali N. Arslan  Katalin Gillemot  Aynur Sensoy  Arda Sorman  M. Cansaran Ertaş  Steven R. Fassnacht  Charles Fierz  Christoph Marty 《水文研究》2020,34(14):3120-3133

Manually collected snow data are often considered as ground truth for many applications such as climatological or hydrological studies. However, there are many sources of uncertainty that are not quantified in detail. For the determination of water equivalent of snow cover (SWE), different snow core samplers and scales are used, but they are all based on the same measurement principle. We conducted two field campaigns with 9 samplers commonly used in observational measurements and research in Europe and northern America to better quantify uncertainties when measuring depth, density and SWE with core samplers. During the first campaign, as a first approach to distinguish snow variability measured at the plot and at the point scale, repeated measurements were taken along two 20 m long snow pits. The results revealed a much higher variability of SWE at the plot scale (resulting from both natural variability and instrumental bias) compared to repeated measurements at the same spot (resulting mostly from error induced by observers or very small scale variability of snow depth). The exceptionally homogeneous snowpack found in the second campaign permitted to almost neglect the natural variability of the snowpack properties and focus on the separation between instrumental bias and error induced by observers. Reported uncertainties refer to a shallow, homogeneous tundra-taiga snowpack less than 1 m deep (loose, mostly recrystallised snow and no wind impact). Under such measurement conditions, the uncertainty in bulk snow density estimation is about 5% for an individual instrument and is close to 10% among different instruments. Results confirmed that instrumental bias exceeded both the natural variability and the error induced by observers, even in the case when observers were not familiar with a given snow core sampler.  相似文献   

Cotton canopy reflectance under variable solar zenith angles: Implications of use in evapotranspiration models     

Christopher M. U. Neale  Maria P. Gonzalez-Dugo  Angelica Serrano-Perez  Isidro Campos  Luciano Mateos 《水文研究》2021,35(6):e14162

Evapotranspiration (ET) is an important parameter in hydrologic processes and modelling. In agricultural watersheds with competing uses of fresh water including irrigated agriculture, estimating crop evapotranspiration (ET_c) accurately is critical for improving irrigation system and basin water management. The use of remote sensing-based basal crop coefficients is becoming a common method for estimating crop evapotranspiration for multiple crops over large areas. The Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI), based on reflectance in the red and near-infrared bands, are commonly used for this purpose. In this paper, we examine the effects of row crop orientation and soil background darkening due to shading and soil surface wetness on these two vegetation indices through modelling, coupled with a field experiment where canopy reflectance of a cotton crop at different solar zenith angles, was measured with a portable radiometer. The results show that the NDVI is significantly more affected than the SAVI by background shading and soil surface wetness, especially in north–south oriented rows at higher latitudes and could lead to a potential overestimation of crop evapotranspiration and irrigation water demand if used for basal crop coefficient estimation. Relationships between the analysed vegetation indices and canopy biophysical parameters such as crop height, fraction of cover and leaf area index also were developed for both indices.  相似文献   

基于低成本单频u-blox接收机的GPS/BDS定向性能分析     

李江卫  马立烨  吴仁攀  孙伟  吴多 《大地测量与地球动力学》2019,39(3):279-284

针对高精度GNSS定向应用场景，通过实验对比对低成本单频u-blox接收机的数据质量和解算精度。结果表明，u-blox接收机GPS、BDS观测值的信噪比略低于测量型接收机；伪距精度分别为0.91 m、0.56 m，相位精度分别为1.35 cm、1.20 cm。在静态观测环境下，u-blox的定向精度可以达到航向0.2°/m和俯仰0.4°/m；动态环境下解算结果稍差，但也可以达到航向0.3°/m和俯仰0.6°/m，略低于高成本测量型接收机单频数据的实时动态定向精度。  相似文献   

Statistical characterization of frost zones: Case of tea freeze damage in the Kenyan highlands     

《International Journal of Applied Earth Observation and Geoinformation》2020

Frequent frost occurrences in the Kenyan highlands have had devastating effects on agricultural productivity. With inadequate management systems to mitigate the impacts, farmers have often had to bear the burden of losses resulting from frost damage. While agriculture in Kenya remains dependent on weather and climate, the agricultural economy of Kenya continues to suffer, underscoring the need for building local knowledge as basis for development of early warning systems. The current paper attempts to delineate frost zones by statistically characterizing them based on known risk factors related to topography (elevation, convexity, aspect, upslope flow length) and Land Surface Temperature (LST) derived from Moderate Resolution Imaging Spectroradiometer (MODIS). Through binary logistic regression, a logistic regression model was developed utilizing observation data (frost occurrence and non-occurrence) as a binary dependent variable to estimate the probability of frost occurrence. Assuming a 0.5 probability cut-off threshold between frost occurrence and non-occurrence, an overall accuracy of 81% with area under Receiver Operating Characteristics (ROC) Curve of 0.88 was obtained. No evidence of lack of model fit was detected. This model outperforms the currently operational model that utilizes MODIS LST alone to detect frost zones in the Kenyan tea plantations. It provides an improved method for effective delineation of frost zones by incorporating local topographic characteristics.  相似文献