渍水麦田土壤水分动态模型研究

根据土壤水分平衡原理,建立了一个反映土壤渍水、可与小麦生长模型耦合的土壤水分动态模型,尤其考虑了因地下水位较浅而引起的毛管上升水量和土壤导水率的变化对土壤含水量的影响。采用盆栽小麦水分试验资料验证了日蒸散量的模拟值,利用湖北荆州农业气象试验站和江苏金坛农业气象试验站的土壤水分历史资料对建立的模型进行了综合测试和验证,结果表明：蒸散量、地下水位和0～50 cm土壤含水量的模拟值与实测值具有较好的一致性,模型能可靠地预测多雨和渍水地区麦田土壤水分的变化动态     

全球冻融地区土壤是重要的N20释放源的综合分析

Ｎ２Ｏ是重要的温室气体之一，它是微生物硝化作用和脱氮化作用过程的产物。有多种释放源，其中土壤圈是重要的释放源之一。在影响Ｎ２Ｏ释放通量的诸多因素中温度是关键因素之一。本文根据土壤冻融加强有机质矿化作用，以及对微生物群体产生非生物应力的性质，结合冻融地区土壤和冻土带湿地所具有的特征，进行综合分析，论述冻融地区土壤是重要的Ｎ２Ｏ释放源。     

利用马氏过程模拟和预测土壤侵蚀的动态演变─—以安徽省岳西县为例

本文根据安徽省岳西县１９５８－１９８２－１９９２年三个时期的遥感资料所编制的土壤侵蚀图，用点数转化法定量地分析岳西县上述两个阶段侵蚀演变和浸蚀类型之间的相互转化状况，确定相应的初始状态下（１９５８和１９８２）的转移概率矩阵，应用马尔科夫过程摸拟和预测岳西县土壤侵蚀及其格局的动态演变过程和未来演变趋势。     

Circulation and fertility of waters in Concepcion Bay

The spatial and temporal distributions of oxygen, nutrients and pigments in the waters of Concepcion Bay, Chile (36°40′S, 73°01′W) are described for 1978–1979. Analysis of the seasonal fluctuations shows the upwelling of water poor in oxygen and rich in nutrients inside the bay during summer. The upwelled water fertilizes the bay and produces progressive eutrophication, causing mass mortalities, discoloured water and mineralization of organic matter.     

Soil respiration mapped by exclusively use of MODIS data for forest landscapes of Saskatchewan,Canada

Soil respiration (R_s) is of great importance to the global carbon balance. Remote sensing of R_s is challenging because of (1) the lack of long-term R_s data for model development and (2) limited knowledge of using satellite-based products to estimate R_s. Using 8-years (2002–2009) of continuous R_s measurements with nonsteady-state automated chamber systems at a Canadian boreal black spruce stand (SK-OBS), we found that R_s was strongly correlated with the product of the normalized difference vegetation index (NDVI) and the nighttime land surface temperature (LSTn) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The coefficients of the linear regression equation of this correlation between R_s and NDVI × LSTn could be further calibrated using the MODIS leaf area index (LAI) product, resulting in an algorithm that is driven solely by remote sensing observations. Modeled R_s closely tracked the seasonal patterns of measured R_s and explained 74–92% of the variance in R_s with a root mean square error (RMSE) less than 1.0 g C/m²/d. Further validation of the model from SK-OBS site at another two independent sites (SK-OA and SK-OJP, old aspen and old jack pine, respectively) showed that the algorithm can produce good estimates of R_s with an overall R² of 0.78 (p < 0.001) for data of these two sites. Consequently, we mapped R_s of forest landscapes of Saskatchewan using entirely MODIS observations for 2003 and spatial and temporal patterns of R_s were well modeled. These results point to a strong relationship between the soil respiratory process and canopy photosynthesis as indicated from the greenness index (i.e., NDVI), thereby implying the potential of remote sensing data for detecting variations in R_s. A combination of both biological and environmental variables estimated from remote sensing in this analysis may be valuable in future investigations of spatial and temporal characteristics of R_s.     

Determination of the factors governing soil erodibility using hyperspectral visible and near-infrared reflectance spectroscopy

Soil erodibility, which is difficult to estimate and upscaling, was determined in this study using multiple spectral models of soil properties (soil organic matter (SOM), water-stable aggregates (WSA) > 0.25 mm, the geometric mean radius (D_g)). Herein, the soil erodibility indicators were calculated, and soil properties were quantitatively analyzed based on laboratory simulation experiments involving two selected contrasting soils. In addition, continuous wavelet transformation was applied to the reflectance spectra (350–2500 nm) of 65 soil samples from the study area. To build the relationship, the soil properties that control erodibility were identified prior to the spectral analysis. In this study, the SOM, D_g and WSA >0.25 mm were selected to represent the most significant soil properties controlling erodibility and describe the erodibility indicator based on a logarithmic regression model as a function of SOM or WSA > 0.25 mm. Five, six and three wavelet features were observed to calibrate the estimated soil properties model, and the best performance was obtained with a combination feature regression model for SOM (R² = 0.86, p < 0.01), D_g (R² = 0.79, p < 0.01) and WSA >0.25 mm (R² = 0.61, p < 0.01), respectively. One part of the wavelet features captured amplitude variations in the broad shape of the reflectance spectra, and another part captured variations in the shape and depth of the soil dry substances. The wavelet features for the validated dataset used to predict the SOM, WSA >0.25 mm and D_g were not significantly different compared with the calibrated dataset. The synthesized spectral models of soil properties, and the formation of a new equation for soil erodibility transformed from the spectral models of soil properties are presented in this study. These results show that a spectral analytical approach can be applied to complex datasets and provide new insights into emerging dynamic variation with erodibility estimation.     

Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin,India

Drought is a natural phenomenon posing severe implications for soil, groundwater and agricultural yield. It has been recognized as one of the most pervasive global change drivers to affect the soil. Soil being a weakly renewable resource takes a long time to form, but it takes no time to degrade. However, the response of soil to drought conditions as soil loss is not manifested in the existing literature. Thus, this study makes a concerted effort to analyze the relationship between drought conditions and soil erosion in the middle sub-basin of the Godavari River in India. MODIS remote sensing data was utilized for driving drought indices during 2000–2019. Firstly, we constricted Temperature condition index (TCI) and Vegetation Condition Index (VCI) from Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) derived from MODIS data. TCI and VCI were then integrated to determine the Vegetation Health Index (VHI). Revised Universal Soil Loss Equation (RUSLE) was utilized for estimating soil loss. The relationship between drought condition and vegetation was ascertained using the Pearson correlation. Most of the northern and southern watersheds experienced severe drought condition in the sub-basin during 2000–2019. The mean frequency of the drought occurrence was 7.95 months. The average soil erosion in the sub-basin was estimated to be 9.88 t ha^?1 year^?1. A positive relationship was observed between drought indices and soil erosion values (r value being 0.35). However, wide variations were observed in the distribution of spatial correlation. Among various factors, the slope length and steepness were found to be the main drivers of soil erosion in the sub-basin. Thus, the study calls for policy measures to lessen the impact of drought and soil erosion.     

陆面模式中土壤冻融过程参数化研究进展

土壤冻融过程在寒区水文和气候系统中有着重要作用。陆面模式中土壤冻融过程的参数化对模式的设计和模拟结果有着关键作用。通过对广泛应用的Bucket，SIB，BATS，VIC，BEAS， LSM等几种主要的陆面模式中的冻融过程参数化方案进行了总结和比较。首先，详尽地描述了土壤冻融与气候变化的数值模拟研究，总结和评述了土壤冻融过程对气候变化的作用。其次，对几种主要的陆面过程模式在土壤水热参数化方案中对冻融过程的考虑及其特点进行了比较和讨论。还对冻结深度和冻结周期的预报模式进行了简介，最后对该领域当前面临的主要研究问题进行了探讨和阐述。     

Remineralization Ratios in the Subtropical North Pacific Gyre

Based on a new mixing model of two end-members, the water column remineralization ratios of P/N/C_org - O₂ = 1/13 ± 1/135 ± 18/170 ± 9 are obtained for the Hawaii Ocean Time-series (HOT) data set at station ALOHA. The traditional Redfield ratios of P/N/C_org/–O₂ = 1/16/106/138 have standard deviations of more than 50%, when they are based on the average composition of phytoplankton. Apparently, the remineralization processes in the water column have smoothed out the observed large variability of plankton compositions. A new molar formula for the remineralized plankton may be written as ₁₃₅H₂₈₀O₁₀₅N₁₃P or C₂₅(CH₂O)₁₀₁(CH₄)₉(NH₃)₁₃(H₃PO₄). Oxidation of this formula results inC₂₅(CH₂O)₁₀₁(CH₄)₉(NH₃)₁₃(H₃PO₄) + 170O₂ 135CO₂ + 132H₂O + 13NO₃ ^- + H₂PO₄ ^- + 14H⁺.For comparison, remineralization using Redfield's formula gives:(CH₂O)₁₀₆(NH₃)₁₆(H₃PO₄) + 138O₂ 106CO₂ + 122H₂O + 16NO₃ ^-+ H₂PO₄ ^- + 17H⁺