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Assessing Soil Water Retention Characteristics and Their Spatial Variability Using Pedotransfer Functions

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Pedosphere 2011年第4期21卷 413-422页

作者： LIAO Kai-Hua1, XU Shao-Hui2,.2, WU Ji-Chun1, JI Shu-Hua2 and LIN Qing2 XU Shao-Hui WU Ji-Chun JI Shu-Hua LIN Qing Department of Hydrosciences Nanjing University Nanjing 210093 (China) Department of Environmental Science Qingdao University Qingdao 266071 (China)

A total of 107 soil samples were taken from the city of Qingdao,Shandong Province,*** water retention data at 2.5,6,10,33,100,300,and 1 500 kPa matric potentials were measured using a pressure membrane *** linear regression (MLR) was used to develop pedotransfer functions (PTFs) for single point estimation and van Genuchten parameter estimation based on readily measurable soil properties,i.e.,MLR-based point (MLRP) PTF and MLR-based parametric (MLRV) *** double cross-validation method was used to evaluate the accuracy of PTF estimates and the stability of the PTFs developed in this *** performance of MLRP and MLRV PTFs in estimating water contents at matric potentials of 10,33,and 1 500 kPa was compared with that of two existing PTFs,the Rawls PTF and the Vereecken *** addition,geostatistical analyses were conducted to assess the capabilities of these PTFs in describing the spatial variability of soil water retention *** showed that among all PTFs only the Vereecken PTF failed to accurately estimate water retention *** the MLRP PTF can be used to predict retention characteristics through traditional statistical analyses,it failed to describe the spatial variability of soil water retention *** the MLRV and Rawls PTFs failed to describe the spatial variability of water contents at a matric potential of 10 kPa,they can be used to quantify the spatial variability of water contents at matric potentials of 33 and 1 500 kPa.

关键词： double cross-validation method multiple linear regression soil water content van Genuchten parameter

Gamma generalized linear model to investigate the effects of climate variables on the area burned by forest fire in northeast China

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Journal of Forestry Research 2015年第3期26卷 545-555页

作者： Futao Guo Guangyu Wang John L. Innes Xiangqing Ma Long Sun Haiqing Hu Fujian Agriculture and Forestry University Sustainable Forest Management Laboratory Faculty of Forestry University of British Columbia VancouverBC V6T 1Z4 Canada Faculty of Forestry Northeast Forestry University

The purpose of this study was to determine a suitable model for investigating the effects of climate factors on the area burned by forest fire in the Tahe forest region, Daxing＇an Mountains, in northeast China. The response variables were the area burned by lightning- caused fire, human-caused fire, and total burned area. The predictor variables were nine climate variables collected from the local weather station. Three regression models were utilized, including multiple linear regression, log- linear model （log-transformation on both response and predictor variables）, and gamma-generalized linear model. The goodness-of-fit of the models were compared based on model fitting statistics such as R2, AIC, and RMSE. The results revealed that the gamma-generalized linear model was generally superior to both multiple linear regressionmodel and log-linear model for fitting the fire data. Further, the best models were selected based on the criteria that the climate variables were statistically significant at at = 0.05. The gamma best models indicated that maximum wind speed, precipitation, and days that rainfall greater than 0.1 mm had significant impacts on the area burned by the lightning-caused fire, while the mean temperature and minimum relative humidity were the .main drivers of the burned area caused by human activities. Overall, the total burned area by forest fire was significantly influenced by days that rainfall greater than 0.1 mm and minimum rela- tive humidity, indicating that the moisture condition of forest stands determine the burned area by forest fire.

关键词： Lightning-caused fire Human-caused fire multiple linear regression Log-linear model Daxing'anmountains

Application of Geochemistry and VNIR Spectroscopy in Mapping Heavy Metal Pollution of Stream Sediments in the Takab Mining Area, NW of Iran

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Acta Geologica Sinica(English Edition) 2018年第6期92卷 2382-2394页

作者： Parisa PIROOZFAR Samad ALIPOUR Soroush MODABBERI David COHEN Department of Geology Faculty of SciencesUrmia University School of Geology University of Tehran School of Biological Earth and Environmental SciencesNew South Wales University

This study considered the possibility of using visible and near infrared(VNIR) spectral absorption feature parameters(SAFPs) in predicting the concentration and mapping the distribution of heavy metals in sediments of the Takab area. In total, 60 sediment samples were collected along main streams draining from the mining districts and tailing sites, in order to measure the concentration of As, Co, V, Cu, Cr, Ni, Hg, Ti, Pb and Zn and the reflectance spectra(350–2500 nm). The quantitative relationship between SAFPs(Depth500 nm, R610/500 nm, R1344/778 nm, Area500 nm, Depth2200 nm, Area2200 nm, Asym2200 nm) and geochemical data were assessed using stepwise multiple linear regression(SMLR) and enter multiple linear regression(EMLR) methods. The results showed a strong negative correlation between Ni and Cr with Area2200 nm, a significant positive correlation between As and Asym2200 nm, Ni and Co with Depth2200 nm, as well as Co, V and total values with Depth500 nm. The EMLR method eventuated in a significant prediction result for Ni, Cr, Co and As concentrations based on spectral parameters, whereas the prediction for Zn, V and total value was relatively weak. The spatial distribution pattern of geochemical data showed that mining activities, along with the natural weathering of base metal occurrences and rock units, has caused high concentrations of heavy metals in sediments of the Sarough River tributaries.

关键词： heavy metals SAFPs VNIR spectroscopy multiple linear regression Takab Iran

QSPR Studies on the Octanol/water Partition Coefficient (lgK_(ow)) of Substituted Anilines with 2D and 3D Methods

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Chinese Journal of Structural Chemistry 2013年第3期32卷 387-395页

作者：李小林刘红玲王遵尧于红霞 State Key Laboratory of Pollution Control and Resource Reuse School of the EnvironmentNanjing University

Octanol/water partition coefficient （Kow） is a crucial property for evaluating the environmental behavior and fate of organic compound. Herein, some quantitative structure-property relationship （QSPR） studies were performed to estimate and predict the lgK ow of substituted anilines. 2D method （multiple linear regression, MLR） and 3D method （comparative molecular field analysis, CoMFA） were applied in this study. Successful 2D and 3D models yielded the correlation coefficient （R2） values of 0.981 and 0.966 and the Leave-One-Out （LOO） cross-validated correlation coefficient （q2） values of 0.933 and 0.820, respectively. The developed models have a highly predictive ability in both internal and external validation. In addition, the results were interpreted in terms of physical and chemical meanings of descriptors and field contribution maps. It showed that the steric and electrostatic properties are the primary factors that govern the lgK ow of substituted anilines. The information obtained from the QSPR models would be helpful to the interpretation of structural features pertinent to the lgK ow of substituted anilines, which may be helpful in estimating the organic compounds＇ potential harm to the environment.

关键词： octanol/water partition coefficient substituted anilines quantitative structure- property relationship multiple linear regression comparative molecular field analysis

QSPR Analysis of the Patterns Scheme Parameters for the Prediction of Monomer Reactivity Ratios

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Chinese Journal of Chemistry 2011年第1期29卷 41-47页

作者： Yi, Bing Tan, Zhengde Yu, Xinliang College of Chemistry and Chemical Engineering Hunan Institute of Engineering Xiangtan Hunan 411104 China Key Laboratory of Environmentally Friendly Chemistry andApplications of Ministry of Education College of Chemistry Xiangtan University Xiangtan Hunan 411105 China

Two quantitative structure-property relationship （QSPR） models were developed to correlate radical chemical structure and the reactivity parameters u and v, respectively, of the revised patterns scheme for the prediction of monomers reactivity ratios. The radicals with structure C1H3--C2HR3· （formed from C1H2=C2HR3 and Ho） were calculated using the UB3LYP density functional theory （DFF） methods with a 6-31G（d） basis set. The calculated quantum chemical descriptors were used to construct QSPR models for the reactivity parameters （u, v） by applying the genetic algorithm （GA） method, together with multiple linear regression （MLR） analysis. Correlation coeffi- cients for the training sets are 0.941 for the parameter u and 0.947 for the parameter v; correlation coefficients for the test sets are 0.947 for u and 0.934 for v. The results suggest that calculating quantum chemical descriptors from radicals to develop models for parameters u and v is feasible.

关键词： density functional calculations genetic algorithm multiple linear regression quantum chemistry,radicals structure-property relations

Diffusion tensor imaging with multiple diffusion-weighted gradient directions

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Neural Regeneration Research 2011年第1期6卷 66-71页

作者： Shan Jiang Meixia Liu Tong Han Weihua Liu School of Mechanical Engineering Tianjin University Tianjin 300072 China Medical Image Evaluation Center Tianjin Huanhu Hospital Tianjin 300060 China

Diffusion tensor MRI （DT-MRI or DTI） is emerging as an important non-invasive technology for elucidating intemal brain structures. It has recently been utilized to diagnose a series of diseases that affect the integrity of neural systems to provide a basis for neuroregenerative studies. Results from the present study suggested that neural tissue is reconstructed with multiple diffusion-weighted gradient directions DTI, which varies from traditional imaging methods that utilize 6 gradient directions. Simultaneously, the diffusion tensor matrix is obtained by multiple linear regressions from an equation of echo signal intensity. The condition number value and standard deviation of fractional anisotropy for each scheme can be used to evaluate image quality. Results demonstrated that increasing gradient direction to some extent resulted in improved effects. Therefore, the traditional 6 and 15 directions should not be considered optimal scan protocols for clinical DTI application. In a scheme with 20 directions, the condition number and standard deviation of fractional anisotropy of the encoding gradients matrix were significantly reduced, and resulted in more clearly and accurately displayed neural tissue. Results demonstrated that the scheme with 20 diffusion gradient directions provided better accuracy of structural renderings and could be an optimal scan protocol for clinical DTI application.

关键词： diffusion tensor imaging neural tissue tensor matrix multiple linear regression condition number

Sea surface temperature retrieval based on simulated microwave polarimetric measurements of a one-dimensional synthetic aperture microwave radiometer

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Acta Oceanologica Sinica 2021年第3期40卷 122-133页

作者： Mengyan Feng Weihua Ai Wen Lu Chengju Shan Shuo Ma Guanyu Chen College of Meteorology and Oceanography National University of Defense TechnologyNanjing 211101China Zhejiang University of Water Resources and Electric Power Hangzhou 310000China PLA Troop 32033 Haikou 570100China

Compared with traditional real aperture microwave radiometers,one-dimensional synthetic aperture microwave radiometers have higher spatial *** this paper,we proposed to retrieve sea surface temperature using a one-dimensional synthetic aperture microwave radiometer that operates at frequencies of 6.9 GHz,10.65 GHz,18.7 GHz and 23.8 GHz at multiple incidence *** used the ERA5 reanalysis data provided by the European Centre for Medium-Range Weather Forecasts and a radiation transmission forward model to calculate the model brightness *** brightness temperature measured by the spaceborne one-dimensional synthetic aperture microwave radiometer was simulated by adding Gaussian noise to the model brightness ***,a backpropagation(BP)neural network algorithm,a random forest(RF)algorithm and two multiple linear regression algorithms(RE1 and RE2)were developed to retrieve sea surface temperature from the measured brightness temperature within the incidence angle range of 0°-65°.The results show that the retrieval errors of the four algorithms increase with the increasing Gaussian *** BP achieves the lowest retrieval errors at all incidence *** retrieval error of the RE1 and RE2 decrease first and then increase with the incidence angle and the retrieval error of the RF is contrary to that of RE1 and RE2.

关键词： one-dimensional synthetic aperture microwave radiometer sea surface temperature retrieval neural network random forest multiple linear regression

Statistical Analysis of Leaf Water Use Efficiency and Physiology Traits of Winter Wheat Under Drought Condition

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Journal of Integrative Agriculture 2012年第1期11卷 82-89页

作者： WU Xiao-li BAO Wei-kai Chengdu Institute of Biology Chinese Academy of Sciences Chengdu 610041 P.R. China Graduate University Chinese Academy of Sciences Beijing 100039 P.R. China

Five statistical methods including simple correlation, multiple linear regression, stepwise regression, principal components, and path analysis were used to explore the relationship between leaf water use efficiency （WUE） and physiological traits （photosynthesis rate, stomatal conductance, transpiration rate, intercellular CO2 concentration, etc.） of 29 wheat cultivars. The results showed that photosynthesis rate, stomatal conductance, and transpiration rate were the most important leaf WUE parameters under drought condition. Based on the results of statistical analyses, principal component analysis could be the most suitable method to ascertain the relationship between leaf WUE and relative physiological traits. It is reasonable to assume that high leaf WUE wheat could be obtained by selecting breeding materials with high photosynthesis rate, low transpiration rate, and stomatal conductance under dry area.

关键词： leaf water use efficiency multiple linear regression path analysis principal components simple correlation stepwise regression wheat genotype

Alternative approaches for estimating missing climate data:application to monthly precipitation records in South- Central Chile

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Forest Ecosystems 2018年第4期5卷 390-399页

作者： Alonso Barrios Guillermo Trincado Rene Garreaud Escuela de Graduados Facultad de Ctencias Forestales y Recursos Naturales Universidad Austral de ChileBox 567ValdiviaChile Departamento de Ciencias Forestales Facuitad de Ingenieria ForestalUnlversidad del Tolima Box 6299 Ibague Colombia Instituto de Bosques y Sociedad Facultad de Ciencias Forestales y Recursos NaturalesUniversidad Austraide ChileBox 567 ValdiviaChile Departamento de Geofistca Facultad de Ciencias Fisicas y MatematicasUniversidad de ChileSantiagoChile

Background: Over the last decades interest has grown on how climate change impacts forest resources. However,one of the main constraints is that meteorological stations are riddled with missing climatic data. This study compared five approaches for estimating monthly precipitation records: inverse distance weighting(IDW), a modification of IDW that includes elevation differences between target and neighboring stations(IDW_m), correlation coefficient weighting(CCW), multiple linear regression(MLR) and artificial neural networks(ANN).Methods: A complete series of monthly precipitation records(1995-2012) from twenty meteorological stations located in central Chile were used. Two target stations were selected and their neighboring stations, located within a radius of25 km(3 stations) and 50 km(9 stations), were identified. Cross-validation was used for evaluating the accuracy of the estimation approaches. The performance and predictive capability of the approaches were evaluated using the ratio of the root mean square error to the standard deviation of measured data(RSR), the percent bias(PBIAS), and the NashSutcliffe efficiency(NSE). For testing the main and interactive effects of the radius of influence and estimation approaches,a two-level factorial design considering the target station as the blocking factor was ***: ANN and MLR showed the best statistics for all the stations and radius of influence. However, these approaches were not significantly different with IDW_m. Inclusion of elevation differences into IDW significantly improved IDW_m estimates. In terms of precision, similar estimates were obtained when applying ANN, MLR or IDW_m, and the radius of influence had a significant influence on their estimates, we conclude that estimates based on nine neighboring stations located within a radius of 50 km are needed for completing missing monthly precipitation data in regions with complex ***: It is concluded that approaches based on ANN

关键词： Climatological data Cross-validation Artificial neural networks multiple linear regression