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Modeling spatio-temporal distribution of soil moisture by deep learning-based cellular automata model

Journal of Arid Land 2016年第5期8卷 734-748页

作者： SONG Xiaodong zhang ganlin LIU Feng LI Decheng ZHAO Yuguo YANG Jinling State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of Sciences

Soil moisture content （SMC） is a key hydrological parameter in agriculture,meteorology and climate change,and understanding of spatio-temporal distributions of SMC in farmlands is important to address the precise irrigation ***,the hybrid interaction of static and dynamic environmental parameters makes it particularly difficult to accurately and reliably model the distribution of *** present,deep learning wins numerous contests in machine learning and hence deep belief network （DBN） ,a breakthrough in deep learning is trained to extract the transition functions for the simulation of the cell state *** this study,we used a novel macroscopic cellular automata （MCA） model by combining DBN to predict the SMC over an irrigated corn field （an area of 22 km^2） in the zhangye oasis,Northwest *** and dynamic environmental variables were prepared with regard to the complex hydrological *** widely used neural network,multi-layer perceptron （MLP） ,was utilized for comparison to *** hybrid models （MLP-MCA and DBN-MCA） were calibrated and validated on SMC data within four months,*** to September 2012,which were automatically observed by a wireless sensor network （WSN） .Compared with MLP-MCA,the DBN-MCA model led to a decrease in root mean squared error （RMSE） by 18%.Thus,the differences of prediction errors increased due to the propagating errors of variables,difficulties of knowing soil properties and recording irrigation amount in *** sequential Gaussian simulation （s Gs） was performed to assess the uncertainty of soil moisture *** with a threshold of SMC for each grid cell,the local uncertainty of simulated results in the post processing suggested that the probability of SMC less than 25% will be difference in different areas at different time *** current results showed that the DBN-MCA model performs better than the MLP-MCA model,and the DBN-MCA model provides a powerful tool for predicti

关键词： soil moisture soil moisture sensor network macroscopic cellular automata (MCA) deep belief network (DBN) multi-layer perceptron (MLP) uncertainty assessment hydropedology

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Soil polygon disaggregation through similarity-based prediction with legacy pedons

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Journal of Arid Land 2016年第5期8卷 760-772页

作者： LIU Feng GENG Xiaoyuan ZHU A-xing Walter FRASER SONG Xiaodong zhang ganlin State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of Sciences Science and Technology Branch Agriculture and Agri-Food Canada School of Geography Nanjing Normal University Department of Geography University of Wisconsin-Madison

Conventional soil maps generally contain one or more soil types within a single soil *** their geographic locations within the polygon are not *** restricts current applications of the maps in site-specific agricultural management and environmental *** examined the utility of legacy pedon data for disaggregating soil polygons and the effectiveness of similarity-based prediction for making use of the under-or over-sampled legacy pedon data for the *** method consisted of three ***,environmental similarities between the pedon sites and each location were computed based on soil formative environmental ***,according to soil types of the pedon sites,the similarities were aggregated to derive similarity distribution for each soil ***,a hardening process was performed on the maps to allocate candidate soil types within the *** study was conducted at the soil subgroup level in a semi-arid area situated in Manitoba,*** on 186 independent pedon sites,the evaluation of the disaggregated map of soil subgroups showed an overall accuracy of 67% and a Kappa statistic of *** map represented a better spatial pattern of soil subgroups in both detail and accuracy compared to a dominant soil subgroup map,which was commonly used in *** predictions mainly occurred in the agricultural plain area and the soil subgroups that are very similar in taxonomy,indicating that new environmental covariates need to be *** concluded that the combination of legacy pedon data with similarity-based prediction is an effective solution for soil polygon disaggregation.

关键词： legacy pedon data similarity-based prediction spatial disaggregation conventional soil maps

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Mapping Soil Organic Carbon Using Local Terrain Attributes： AComparison of Different Polynomial Models

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Pedosphere 2017年第4期27卷 681-693页

作者： SONG Xiaodong LIU Feng zhang ganlin LI Decheng ZHAO Yuguo YANG Jinling State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China

Local terrain attributes,which are derived directly from the digital elevation model,have been widely applied in digital soil *** study aimed to evaluate the mapping accuracy of soil organic carbon(SOC) concentration in 2 zones of the Heihe River in China,by combining prediction methods with local terrain attributes derived from different polynomial *** prediction accuracy was used as a benchmark for those who may be more concerned with how accurately the variability of soil properties is modeled in practice,rather than how morphometric variables and their geomorphologic interpretations are understood and *** this study,2 neighborhood types(square and circular) and 6 representative algorithms(Evans-Young,Horn,Zevenbergen-Thorne,Shary,Shi,and Florinsky algorithms) were *** general,35 combinations of first-and second-order derivatives were produced as candidate predictors for soil mapping using two mapping methods(i.e.,kriging with an external drift and geographically weighted regression).The results showed that appropriate local terrain attribute algorithms could better capture the spatial variation of SOC concentration in a region where soil properties are strongly influenced by the *** the different combinations of firstand second-order derivatives used,there was a best combination with a more accurate *** different prediction methods,the relative improvement in the two zones varied between 0.30% and 9.68%.The SOC maps resulting from the higher-order algorithms(Zevenbergen-Thorne and Florinsky) yielded less interpolation ***,it was concluded that the performance of predictive methods,which incorporated auxiliary variables,could be improved by attempting different terrain analysis algorithms.

关键词： cross-validation digital soil mapping geographically weighted regression kriging with an external drift mapping accuracy

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Nutrient Discharges from a Typical Watershed in the Hilly Area of Subtropical China

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Pedosphere 2003年第1期13卷 23-30页

作者： zhang ganlin, YANG JINLING and ZHAO YUGUOInstitute of Soil Science, the Chinese Academy of Sciences, Nanjing 210008 (China) Institute of SoilScience the Chinese Academy of sciences Nanjing 210008

Agriculture is still the biggest contributor of non-point source (NPS) pollution to water bodies andrunoff discharges of nutrients and other chemicals are one of the most important pathways. This studywas conducted during 1998～1999 in a typical watershed with complex agriculture and forestry systems aswell as dotted farmer villages, in a transitional region between the mid- and northern subtropical zones ofChina. Continuous sampling of stream water was performed regularly at a weekly frequency, with additionalsampling after all major rainfall events. The discharges of N and P nutrients and suspended materials weremeasured and the total and area-averaged annual discharges of all components were calculated. The resultsshowed an uneven seasonal distribution of nutrient discharges with summer storms contributing most tothe total fluxes. This study demonstrated a high dependence of runoff volume on rainfall but the overallrunoff coefficients were dependent on land use type and watershed size. The area-averaged annual dischargesvaried greatly among the sub-watersheds with different sizes and land use structures. This is the first studyestimating the area-averaged annual discharges of N and P in the hilly areas of subtropical China, which were1.5 g m-2 a-1 and 0.1 g m-2 a-1, respectively, providing important reference values for the assessment ofregional agricultural non-point source pollution.

关键词： discharge nutrients runoff subtropical china watershed

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Iron loss of paddy soil in China and its environmental implications

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Science China Earth Sciences 2022年第7期65卷 1277-1291页

作者： Liumei CHEN Dongbo ZHAO Guangzhong HAN Fei YANG Zitong GONG Xiaodong SONG Decheng LI ganlin zhang College of Resources and Environment Zunyi Normal UniversityZunyi 563006China State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China College of Geography and Resources Science Neijiang Normal UniversityNeijiang 641112China College of Advanced Agricultural Sciences University of the Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Lake Science and Environment Nanjing Institute of Geography and LimnologyChinese Academy of SciencesNanjing 210008China

Iron(Fe)is an important element for the terrestrial and marine ecosystems through its biogeochemical cycling on the Earth’s *** has a long rice cultivation history,with extensive rice distribution across many types of paddy *** soils are the largest anthropogenic wetlands on earth with critical roles in ecosystem *** periodic artificial submergence and drainage during paddy soil evolution result in significant changes in soil moisture regime and redox conditions from the natural soils,which facilitate the increase of Fe solubility and ***,there is a lack of systematic assessment on the magnitude of the migration and loss amount of Fe from paddy *** order to quantify the Fe loss and assess the dynamic evolution of Fe in the soils after rice cultivation,seven paddy soil chronosequences derived from different landscapes(bog,plain,terrace)and parent materials(acidic,neutral,calcareous)with cultivation history from 0 to 2,000 yr were *** showed that the rates and trajectories of Fe evolution showed distinct patterns among the studied seven paddy soil ***,net losses of Fe from 1 m soil depth occurred at all studied paddy soil chronosequences regardless of the original landscapes and parent *** in the paddy soils derived from the calcareous lacustrine sediments in the bog area showed a slight accumulation during the initial stage(50 yr)of paddy cultivation,with a loss rate of0.026 kg m^(-2)yr^(-1) during the 50-to 500-yr time *** the paddy soils developed on the calcareous marine sediments in the plain area,Fe evolution was dominated by the internal movement in soil profiles through coupled reducing-eluviation reactions in the surface horizons and oxidation-illuviation in the subsurface horizons within 1,000 yr of paddy cultivation,with an averaged net loss rate of 0.029 kg m^(-2)yr^(-1) during the 1,000-to 2,000-yr time period of rice *** contrast,Fe in the paddy s

关键词： Soil-water interface Land-sea interface Paddy soil Soil Fe loss Biogeochemical cycle

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SOTER-Based Soil Water Erosion Simulation in Hainan Island

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Pedosphere 2003年第2期13卷 139-146页

作者： ZHAO YUGUO, zhang ganlin and GONG ZITONGInstitute of Soil Science, the Chinese Academy of Sciences, Nanjing 210008 (China) Institute of Soil Science the Chinese Academy of Sciences Nanjing 210008

The actual and potential water erosion rates of soils with different landcovers in Hainan Island, China, were estimated based on the universal soil loss equation (USLE) anda 1:200000 Soils and Terrain Digital Database (SOTER) database, from which soil water erosionfactors could be extracted. 92.8% of the whole island had a current erosion rate of lower than 500 tkm^(-2) a^(-1). Soil erosion risk was considered to be high because of its abundant *** vegetation cover, the potential soil erosion rate would be extremely high and 90.8% of theisland would have a soil erosion rate higher than 2500 t km^(-2) a^(-1). Relative erosionvulnerability of different soil zones, landform types, and lithological regions of the island wascompared by introducing a relative erosion hazard parameter a. Cambosols developed from siltstoneand mudstone in low hill regions were pinpointed as soils with the highest erosion risk in theisland.

关键词： hainan island soil erosion risk assessment SOTER USLE

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Regional Soil Mapping Using Multi-Grade Representative Sampling and a Fuzzy Membership-Based Mapping Approach

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Pedosphere 2017年第2期27卷 344-357页

作者： YANG Lin A-Xing ZHU ZHAO Yuguo LI Decheng zhang ganlin zhang Shujie Lawrence E. BAND State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences Nanjing 210008 (China) State Key Laboratory of Resources and Environment Information System Institute of Geographical Sciences and Resources Research Chinese Academy of Sciences Beijing 100101 (China) Key Laboratory of Virtual Geographic Environment (Nanjing Normal University) Ministry of Education Nanjing 210023 (China) Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application School of Geography Nanjing Normal University Nanjing 210023 (China) State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province) Nanjing 210023 (China) Department of Geography University of Wisconsin-Madison Madison WI 53706 (USA) China Academy of Urban Planning & Design Beijing 100037 (China) Institute for the Environment University of North Carolina Chapel Hill Chapel Hill NC 27599 (USA)

High-resolution and detailed regional soil spatial distribution information is increasingly needed for ecological modeling and land resource management. For areas with no point data, regional soil mapping includes two steps： soil sampling and soil mapping. Because sampling over a large area is costly, efficient sampling strategies are required. A multi-grade representative sampling strategy, which designs a small number of representative samples with different representative grades to depict soil spatial variations at different scales, could be a potentially efficient sampling strategy for regional soil mapping. Additionally, a suitable soil mapping approach is needed to map regional soil variations based on a small number of samples. In this study, the multi-grade representative sampling strategy was applied and a fuzzy membership-weighted soil mapping approach was developed to map soil sand percentage and soil organic carbon （SOC） at 0-20 and 20-40 cm depths in a study area of 5 900 km2 in Anhui Province of China. First, geographical sub-areas were delineated using a parent lithology data layer. Next, fuzzy c-means clustering was applied to two climate and four terrain variables in each stratum. The clustering results （environmental cluster chains） were used to locate representative samples. Evaluations based on an independent validation sample set showed that the addition of samples with lower representativeness generally led to a decrease of root mean square error （RMSE）. The declining rates of RMSE with the addition of samples slowed down for 20-40 cm depth, but fluctuated for 0-20 cm depth. The predicted SOC maps based on the representative samples exhibited higher accuracy, especially for soil depth 20-40 cm, as compared to those based on legacy soil data. Multi-grade representative sampling could be an effective sampling strategy at a regional scale. This sampling strategy, combined with the fuzzy membership-based mapping approach, could be an optional effec

关键词： fuzzy clustering parent lithology representative grade samphng strategy soil spatial variations

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Mapping Soil Organic Carbon Stocks of Northeastern China Using Expert Knowledge and GIS-based Methods

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Chinese Geographical Science 2017年第4期27卷 516-528页

作者： SONG Xiaodong LIU Feng JU Bing ZHI Junjun LI Decheng ZHAO Yuguo zhang ganlin State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China

The main aim of this paper was to calculate soil organic carbon stock(SOCS) with consideration of the pedogenetic horizons using expert knowledge and GIS-based methods in northeastern China.A novel prediction process was presented and was referred to as model-then-calculate with respect to the variable thicknesses of soil horizons(MCV).The model-then-calculate with fixed-thickness(MCF),soil profile statistics(SPS),pedological professional knowledge-based(PKB) and vegetation type-based(Veg) methods were carried out for *** respect to the similar pedological information,nine common layers from topsoil to bedrock were grouped in the *** results suggested that the MCV method generated better performance than the other methods *** the comparison of polygon based approaches,the Veg method generated better accuracy than both SPS and PKB,as limited soil data were *** prediction of the pedogenetic horizons within MCV benefitted the regional SOCS estimation and provided information for future soil classification and understanding of soil *** intermediate product,that is,horizon thickness maps were fluctuant enough and reflected many details in *** linear mixed model indicated that mean annual air temperature(MAAT) was the most important predictor for the SOCS *** minimal residual of the linear mixed models was achieved in the vegetation type-based model,whereas the maximal residual was fitted in the soil type-based *** 95% of SOCS could be found in Argosols,Cambosols and *** largest SOCS was found in the croplands with vegetation of Triticum aestivum L.,Sorghum bicolor(L.) Moench,Glycine max(L.) Merr.,Zea mays *** Setaria italica(L.) ***.

关键词： soil organic carbon stock model-then-calculate random forest linear mixed model northeastern China

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Most root-derived carbon inputs do not contribute to long-term global soil carbon storage

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Science China Earth Sciences 2023年第5期66卷 1072-1086页

作者： Guocheng WANG Liujun XIAO Ziqi LIN Qing zhang Xiaowei GUO Annette COWIE Shuai zhang Mingming WANG Songchao CHEN ganlin zhang Zhou SHI Wenjuan SUN Zhongkui LUO Institute of Agriculture Remote Sensing and Information Technology College of Environmental and Resource SciencesZhejiang UniversityHangzhou310058China LAPC Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China School of Atmospheric Sciences Guangdong Province Key Laboratory for Climate Change and Natural Disaster StudiesSun Yat-sen UniversityZhuhai519082China New South Wales Department of Primary Industries University of New EnglandArmidaleNSW2351Australia State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing210008China Academy of Ecological Civilization Zhejiang UniversityHangzhou310058China Key Laboratory of Environment Remediation and Ecological Health Ministry of EducationZhejiang UniversityHangzhou310058China State Key Laboratory of Vegetation and Environmental Change Institute of BotanyChinese Academy of SciencesBeijing100093China Key Laboratory of Agricultural Remote Sensing and Information System Zhejiang ProvinceHangzhou310058China

Plant root-derived carbon(C)inputs(I_(root))are the primary source of C in mineral bulk ***,a fraction of I_(root)may lose quickly(I_(loss),e.g.,via rhizosphere microbial respiration,leaching and fauna feeding)without contributing to long-term bulk soil C storage,yet this loss has never been quantified,particularly on a global *** this study we integrated three observational global data sets including soil radiocarbon content,allocation of photo synthetically assimilated C,and root biomass distribution in 2,034 soil profiles to quantify I_(root)and its contribution to the bulk soil C *** show that global average I_(root)in the 0-200 cm soil profile is 3.5 Mg ha^(-1)yr^(-1),~80%of which(i.e.,I_(loss))is lost rather than co ntributing to long-term bulk soil C storage.I_(root)decreases exponentially with soil depth,and the top 20 cm soil contains>60%of total I_(root).Actual C input contributing to long-term bulk soil storage(i.e.,I_(root)-I_(loss))shows a similar depth distribution to I_(root).We also map I_(loss)and its depth distribution across the *** results demonstrate the global significance of direct C losses which limit the contribution of I_(root)to bulk soil C storage;and provide spatially explicit data to facilitate reliable soil C predictions via separating direct C losses from total root-derived C inputs.

关键词： Carbon inputs Root biomass Soil organic carbon Depth distribution Bulk soil carbon Radiocarbon

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Mapping Soil Texture Based on Field Soil Moisture Observations at a High Temporal Resolution in an Oasis Agricultural Area

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Pedosphere 2016年第5期26卷 699-708页

作者： YANG Renmin LIU Feng zhang ganlin ZHAO Yuguo LI Decheng YANG Jinling YANG Fei YANG Fan State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008(China) University of Chinese Academy of Sciences Beijing 100049(China)

Due to the almost homogeneous topography in low relief areas, it is usually difficult to make accurate predictions of soil properties using topographic covariates. In this study, we examined how time series of field soil moisture observations can be used to estimate soil texture in an oasis agricultural area with low relief in the semi-arid region of northwest China. Time series of field-observed soil moisture variations were recorded for 132 h beginning at the end of an irrigation event during which the surface soil was *** correlation between two time-adjacent soil moisture conditions was used to select the factors for fuzzy c-means clustering. In each of the ten generated clusters, soil texture of the soil sample with the maximum fuzzy membership value was taken as the cluster centroid. Finally, a linearly weighted average was used to predict soil texture from the centroids. The results showed that soil moisture increased with the increase of clay and silt contents, but decreased with the increase of sand content. The spatial patterns of soil moisture changed during the entire soil drying phase. We assumed that these changes were mainly caused by spatial heterogeneity of soil texture. A total of 64 independent samples were used to evaluate the prediction accuracy. The root mean square error(RMSE)values of clay, silt and sand were 1.63, 2.81 and 3.71, respectively. The mean relative error(RE) values were 9.57% for clay, 3.77% for silt and 12.83% for sand. It could be concluded that the method used in this study was effective for soil texture mapping in the low-relief oasis agricultural area and could be applicable in other similar irrigation agricultural areas.

关键词： digital soil mapping fuzzy c-means clustering low relief particle-size distribution semi-arid region water content

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