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Integrating Remote Sensing and Proximal Sensors for the Detection of soil moisture and Salinity Variability in Coastal Areas

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Journal of Integrative Agriculture 2013年第4期12卷 723-731页

作者： GUO Yan SHI Zhou ZHOU Lian-qing JIN Xi TIAN Yan-feng TENG Hong-fen Institute of Agricultural Remote Sensing and Information Technology Application College of Environmental and Resource Sciences Zhejiang University

soil moisture and salinity are two crucial coastal saline soil variables, which influence the soil quality and agricultural productivity in the reclaimed coastal region. Accurately characterizing the spatial variability of these soil parameters is critical for the rational development and utilization of tideland resources. In the present study, the spatial variability of soil moisture and salinity in the reclaimed area of Hangzhou gulf, Shangyu City, Zhejiang Province, China, was detected using the data acquired from radar image and the proximal sensor EM38. soil moisture closely correlates radar scattering coefficient, and a simplified inversion model was built based on a backscattering coefficient extracted from multi-polarization data of ALOS/PALSAR and in situ soil moisture measured by a time domain reflectometer to detect soil moisture variations. The result indicated a higher accuracy of soil moisture inversion by the HH polarization mode than those by the HV mode. soil salinity is reflected by soil apparent electrical conductivity （ECa）. Further, ECa can be rapidly detected by EM38 equipment in situ linked with GPS for characterizing the spatial variability of soil salinity. Based on the strong spatial variability and interactions of soil moisture and salinity, a cokriging interpolation method with auxiliary variable of backscattering coefficient was adopted to map the spatial variability of ECa. When compared with a map of ECa interpolated by the ordinary kriging method, detail was revealed and the accuracy was increased by 15.3%. The results conclude that the integrating active remote sensing and proximal sensors EM38 are effective and acceptable approaches for rapidly and accurately detecting soil moisture and salinity variability in coastal areas, especially in the subtropical coastal zones of China with frequent heavy cloud cover.

关键词： remote sensing proximal sensor soil moisture salinity backscattering coefficient soil apparent electricalconductivity (ECa)

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Modeling regional landslide susceptibility using dynamic soil moisture profiles

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Journal of Mountain Science 2018年第8期15卷 1807-1824页

作者： RAY Ram L JACOBS Jennifer M DOUGLAS Ellen M Cooperative Agricultural Research Center College of Agriculture and Human Sciences Prairie View A&M University Department of Civil Engineering University of New Hampshire Environmental Earth and Ocean Sciences Department University of Massachusetts Boston

A landslide susceptibility mapping study was performed using dynamic hillslope hydrology. The modified infinite slope stability model that directly includes vadose zone soil moisture(SM) was applied at Cleveland Corral, California, US and Krishnabhir, Dhading, Nepal. The variable infiltration capacity(VIC-3L) model simulated vadose zone soil moisture and the wetness index hydrologic model simulated groundwater(GW). The GW model predictions had a 75% NASH-Sutcliffe efficiency when compared to California's in-situ GW measurements. The model performed best during the wet season. Using predicted GW and VIC-3L vadose zone SM, the developed landslide susceptibility maps showed very good agreement with mapped landslides at each study region. Previous quasi-dynamic model predictions of Nepal's hazardous areas during extreme rainfall events were enhanced to improve the spatial characterization and provide the timing of hazardous conditions.

关键词： Landslide susceptibility Vadose zone soil moisture Infiltration eapacity VIC-3L Groundwater

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A Multimodel Ensemble-based Kalman Filter for the Retrieval of soil moisture Profiles

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Advances in Atmospheric Sciences 2011年第1期28卷 195-206页

作者：张述文李得勤邱崇践 Key Laboratory for Semi-Arid Climate Change of the Ministry of Education College of Atmospheric Sciences Lanzhou University Key Laboratory of Arid Climate Change and Reducing Disaster of Gansu Province

With the combination of three land surface models （LSMs） and the ensemble Kalman filter （EnKF）, a multimodel EnKF is proposed in which the multimodel background superensemble error covariance matrix is estimated by two different algorithms： the Simple Model Average （SMA） and the Weighted Average Method （WAM）. The two algorithms are tested and compared in terms of their abilities to retrieve the true soil moisture profile by respectively assimilating both synthetically-generated and actual near-surface soil moisture measurements. The results from the synthetic experiment show that the performances of the SMA and WAM algorithms were quite different. The SMA algorithm did not help to improve the estimates of soil moisture at the deep layers, although its performance was not the worst when compared with the results from the single-model EnKF. On the contrary, the results from the WAM algorithm were better than those from any single-model EnKF. The tested results from assimilating the field measurements show that the performance of the two multimodel EnKF algorithms was very stable compared with the single-model EnKF. Although comparisons could only be made at three shallow layers, on average, the performance of the WAM algorithm was still slightly better than that of the SMA algorithm. As a result, the WAM algorithm should be adopted to approximate the multimodel background superensemble error covariance and hence used to estimate soil moisture states at the relatively deep layers.

关键词： multimodel EnKF soil moisture land data assimilation land surface model

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Interrelationship of soil moisture and temperature to sylvatic plague cycle among prairie dogs in the Western United States

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Integrative Zoology 2021年第6期16卷 852-867页

作者： Cassandra D.PAULING Deborah L.FINKE Deborah M.ANDERSON Department of Veterinary Pathobiology University of MissouriColumbiaMissouriUSA Division of Plant Sciences University of MissouriColumbiaMissouriUSA

Plague,caused by Yersinia pestis,is a flea-borne disease that is endemic in areas throughout the world due to its successful maintenance in a sylvatic cycle,mainly in areas with temperate *** rodents are thought to play a key role in the enzootic maintenance as well as epizootic outbreaks of *** the United States,prairie dogs(Cynomys),rodents(Muridae),and ground squirrels(Spermophilus)are susceptible to infection and are parasitized by fleas that transmit *** particular,prairie dogs can experience outbreaks that rapidly spread,which can lead to extirpation of colonies.A number of ecological parameters,including climate,are associated with these *** this study,we asked whether soil parameters,primarily moisture and temperature,are associated with outbreaks of plague in black-tailed prairie dogs and Gunnison’s prairie dogs in the Western United States,and at what depth these associations were *** collected publicly available county-level information on the occurrence of population declines or colony extirpation,while historical soil data was collected from SCAN and USCRN stations in counties and states where prairie dogs have been *** analysis suggests that soil moisture at lower depths correlates with colony die-offs,in addition to temperature near the surface,with key differences within the landscape ecology that impact the occurrence of ***,the model suggests that the burrow environment may play a significant role in the epizootic spread of disease amongst black-tailed and Gunnison’s prairie dogs.

关键词： plague prairie dogs soil moisture soil temperature sylvatic cycle Yersinia pestis

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SLOPE LITHOLOGIC PROPERTY, soil moisture CONDITION AND REVEGETATION IN DRY-HOT VALLEY OF JINSHA RIVER

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Chinese Geographical Science 2005年第2期15卷 186-192页

作者： XIONGDong-hong ZHOUHong-yi YANGZhong ZHANGXin-bao ChengduInstituteofMountainHazardsandEnvironment ChineseAcademyofSciences＆MinistryofWaterConservancyChengdu610041P.R.China ChengduInstituteofMountainHazardsandEnvironment ChineseAcademyofSciences＆MinistryofWaterConservancyChengdu610041P.R.China／／GraduateSchoolofChineseAcademyofSciericesBeijing100039P.R.China

The dry-hot valley of the Jinsha River is one of the typical eco-fragile areas in Southwest China, as well as a focus of revegetation study in the upper and middle reaches of the Changjiang River. Due to its extremely dry and hot climate, severely degraded vegetation and the intense soil and water loss, there are extreme difficulties in vegetation restoration in this area and no great breakthrough has ever been achieved on studies of revegetation over the last several decades. Through over ten years’ research conducted in the typical areas-the Yuanmou dry-hot valley, the authors found that the lithologic property is one of the crucial factors determining soil moisture conditions and vegetation types in the dry-hot valley, and the rainfall infiltration capability is also one of the key factors affecting the tree growth. Then the revegetation zoning based on different slopes was conducted and revegetation patterns for different zones were proposed.

关键词： revegetation lithologic property soil moisture plant growth dry-hotvalley Jinsha River

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Estimating purple-soil moisture content using Vis-NIR spectroscopy

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Journal of Mountain Science 2020年第9期17卷 2214-2223页

作者： GOU Yu WEI Jie LI Jin-lin HAN Chen TU Qing-yan LIU Chun-hong School of Geography and Tourism Science Chongqing Normal UniversityChongqing 401331China Chongqing Key Laboratory of Surface Process and Environment Remote Sensing in the Three Gorges Reservoir Area Chongqing 401331China

soil moisture is essential for plant growth in terrestrial *** study investigated the visible-near infrared(Vis-NIR)spectra of three subgroups of purple soils(calcareous,neutral,and acidic)from western Chongqing,China,containing different water *** relationship between soil moisture and spectral reflectivity(R)was analyzed using four spectral transformations,and estimation models were established for estimating the soil moisture content(SMC)of purple soil based on stepwise multiple linear regression(SMLR)and partial least squares regression(PLSR).We found that soil spectra were similar for different moisture contents,with reflectivity decreasing with increasing moisture content and following the order neutral>calcareous>acidic purple soil(at constant moisture content).Three of the four spectral transformations can highlight spectral sensitivity to SMC and significantly improve the correlation between the reflectance spectra and *** and PLSRmethods provide similar prediction *** PLSR-based model using a first-order reflectivity differential(R?)is more effective for estimating the SMC,and gave coefficient of determination(v2),root mean square errors of validation(RMSEV),and ratio of performance to inter-quartile distance(RPIQ)values of 0.946,1.347,and 6.328,respectively,for the calcareous purple soil,and 0.944,1.818,and 6.569,respectively,for the acidic purple *** neutral purple soil,the best prediction was obtained using the SMLR method with R?transformation,yieldingv2,RMSEV and RPIQ values of 0.973,0.888 and 8.791,*** general,PLSR is more suitable than SMLR for estimating the SMC of purple soil.

关键词： Purple soil soil moisture Vis-NIR spectroscopy Stepwise multiple linear regression Partial least squares regression

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Effects of Temperature,soil moisture,soil Type and Their Interactions on soil Carbon Mineralization in Zoigê Alpine Wetland,Qinghai-Tibet Plateau

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Chinese Geographical Science 2011年第1期21卷 27-35页

作者： GAO Junqin OUYANG Hua LEI Guangchun XU Xingliang ZHANG Mingxiang Beijing Forestry University Beijing 100083 China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China

Wetland stores substantial amount of carbon and may contribute greatly to global climate change debate. However, few researches have focused on the effects of global climate change on carbon mineralization in Zoige alpine wetland, Qinghai-Tibet Plateau, which is one of the most important peatlands in China. Through incubation experiment, this paper studied the effects of temperature, soil moisture, soil type （marsh soil and peat soil） and their interactions on CO2 and CH4 emission rates in Zoige alpine wetland. Results show that when the temperature rises from 5℃ to 35℃, CO2 emission rates increase by 3.3-3.7 times and 2.4-2.6 times under non-inundation treatment, and by 2.2-2.3 times and 4.1-4.3 times under inundation treatment in marsh soil and peat soil, respectively. Compared with non-inundation treatment, CO2 emission rates decrease by 6%-44%, 20%-60% in marsh soil and peat soil, respectively, under inundation treatment. CO2 emission rate is significantly affected by the combined effects of the temperature and soil type （p 〈 0.001）, and soil moisture and soil type （p 〈 0.001）, and CH4 emission rate was significantly affected by the interaction of the temperature and soil moisture （p 〈 0.001）. Q10 values for CO2 emission rate are higher at the range of 5 ℃-25℃ than 25 ℃-35℃, indicating that carbon mineralization is more sensitive at low temperature in Zoige alpine wetland.

关键词： alpine wetland carbon mineralization marsh soil peat soil soil moisture Qinghai-Tibet Plateau

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Effects of soil Hydraulic Properties on soil moisture Estimation

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Journal of Meteorological Research 2023年第1期37卷 58-74页

作者： Xiaolei FU Haishen LYU Zhongbo YU Xiaolei JIANG Yongjian DING Donghai ZHENG Jinbai HUANG Hongyuan FANG College of Hydraulic Science and Engineering Yangzhou UniversityYangzhou 225009 Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resources Nanjing University of Information Science&TechnologyNanjing 210044 State Key Laboratory of Hydrology–Water Resources and Hydraulic Engineering Hohai UniversityNanjing 210098 Joint International Research Laboratory of Global Change and Water Cycle Hohai UniversityNanjing 210098 Yangtze Institute for Conservation and Development Hohai UniversityNanjing210098 State Key Laboratory of Cryospheric Science Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000 Institute of Tibetan Plateau Research Chinese Academy of SciencesBeijing 100101

Accurate quantification of soil moisture is essential to understand the land surface *** hydraulic properties influence water transport in soil and thus affect the estimation of soil ***,some soil hydraulic properties are only observable at a few field *** this study,the effects of soil hydraulic properties on soil moisture estimation are investigated by using the one-dimensional(1-D)Richards equation at ELBARA,which is part of the Maqu monitoring network over the Tibetan Plateau(TP),*** moisture assimilation experiments are then conducted with the unscented weighted ensemble Kalman filter(UWEnKF).The results show that the soil hydraulic properties significantly affect soil moisture *** soil hydraulic conductivity(Ksat)is optimized based on its observations in each soil layer with a genetic algorithm(GA,a widely used optimization method in hydrology),and the 1-D Richards equation performs well using the optimized *** the range of Ksat for a complete soil profile is known for a particular soil texture(rather than for arbitrary layers within the horizon),optimized Ksat for each soil layer can be obtained by increasing the number of generations in GA,although this increases the computational cost of *** performs well with optimized Ksat,and improves the accuracy of soil moisture simulation more than that with calculated ***,better soil moisture estimation can be obtained by using optimized saturated volumetric soil moisture content *** summary,an accurate soil profile can be obtained by using soil moisture assimilation with optimized soil hydraulic properties.

关键词： soil moisture one-dimensional(1-D)Richards equation unscented weighted ensemble Kalman filter(UWEnKF) soil hydraulic properties genetic algorithm

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The soil moisture of China in a High Resolution Climate-Vegetation Model

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Advances in Atmospheric Sciences 2005年第5期22卷 720-729页

作者：丹利季劲钧张培群 Laboratory for Climate Study National Climate Center START Regional Center for Temperate East Asia and Key Laboratory of Regional Climate-Environment for Temperate East Asia Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029

The spatial distribution of soil moisture, especially the temporal variation at seasonal and interannual scales, is difficult for many land surface models （LSMs） to capture partly due to the deficiencies of the LSMs and the highly spatial variability of soil moisture, which makes it problematic to simulate the moisture for climate studies. However the soil moisture plays an important role in influencing the energy and hydrological cycles between the land and air, so it should be considered in land surface models. In this paper, a soil moisture simulation in China with a T213 resolution （about 0.5625°× 0.5625°） is compared to the observational data, and its relationship to precipitation is explored. The soil moisture distribution agrees roughly with the observations, and the soil moisture pattern reflects the variation and intensity of the precipitation. In particular, for the 1998 summer catastrophic floods along the Yangtze River, the soil moisture remains high in this region from July to August and represents the flood well. The seasonal cycle of soil moisture is roughly consistent with the observed data, which is a good calibration for the ground simulation capacity of the Atmosphere-Vegetation Interaction Model （AVIM） with respect to this tough problem for land surface models.

关键词： soil moisture precipitation AVIM NCEP 2 seasonal cycle

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Improvement of soil moisture Simulation in Eurasia by the Beijing Climate Center Climate System Model from CMIP5 to CMIP6

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Advances in Atmospheric Sciences 2021年第2期38卷 237-252页

作者： Yinghan SANG Hong-Li REN Xueli SHI Xiaofeng XU Haishan CHEN School of Atmospheric Sciences Nanjing University of Information Science&TechnologyNanjing 210044China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Laboratory for Climate Studies&CMA-NJU Joint Laboratory for Climate Prediction Studies National Climate CenterChina Meteorological AdministrationBeijing 100081China China Meteorological Administration Beijing 100081China

This study provides a comprehensive evaluation of historical surface soil moisture simulation(1979-2012)over Eurasia at annual and seasonal time scales between two medium-resolution versions of the Beijing Climate Center Climate System Model(BCC-CSM)—one that is currently participating in phase 6 of the Coupled Model Intercomparison Project(CMIP6),i.e.,BCC-CSM2-MR,and the other,BCC-CSM1.1m,which participated in *** show that BCC-CSM2-MR is more skillful in reproducing the climate mean states and standard deviations of soil moisture,with pattern correlations increased and biases reduced ***-CSM2-MR performs better in capturing the first two primary patterns of soil moisture anomalies,where the period of the corresponding time series is closer to that of reference *** show that BCC-CSM2-MR performs at a high level among multiple models of CMIP6 in terms of centered pattern correlation and“amplitude of variation”(relative standard deviation).In general,the centered pattern correlation of BCC-CSM2-MR,ranging from 0.61 to 0.87,is higher than the multi-model mean of CMIP6,and the relative standard deviation is 0.75,which surmounts the overestimations in most of the CMIP6 *** to the vital role played by precipitation in land-atmosphere interaction,possible causes of the improvement of soil moisture simulation are further related to precipitation in *** results indicate that a better description of the relationship between soil moisture and precipitation and a better reproduction of the climate mean precipitation by the model may result in the improved performance of soil moisture simulation.

关键词： BCC-CSM soil moisture CMIP6 historical simulation Eurasia

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