Hybrid data assimilation （DA） is a method seeing more use in recent hydrology and water resources research. In this study, a DA method coupled with the support vector machines （SVMs） and the ensemble Kalman filter...Hybrid data assimilation （DA） is a method seeing more use in recent hydrology and water resources research. In this study, a DA method coupled with the support vector machines （SVMs） and the ensemble Kalman filter （EnKF） technology was used for the prediction of soil moisture in different soil layers： 0-5 cm, 30 cm, 50 cm, 100 cm, 200 cm, and 300 cm. The SVM methodology was first used to train the ground measurements of soil moisture and meteorological parameters from the Meilin study area, in East China, to construct soil moisture statistical prediction models. Subsequent observations and their statistics were used for predictions, with two approaches： the SVM predictor and the SVM-EnKF model made by coupling the SVM model with the EnKF technique using the DA method. Validation results showed that the proposed SVM-EnKF model can improve the prediction results of soil moisture in different layers, from the surface to the root zone.展开更多
The paper investigates the ability to retrieve the true soil moisture profile by assimilating near-surface soil moisture into a soil moisture model with an ensemble Kalman filter （EnKF） assimilation scheme, includin...The paper investigates the ability to retrieve the true soil moisture profile by assimilating near-surface soil moisture into a soil moisture model with an ensemble Kalman filter （EnKF） assimilation scheme, including the effect of ensemble size, update interval and nonlinearities in the profile retrieval, the required time for full retrieval of the soil moisture profiles, and the possible influence of the depth of the soil moisture observation. These questions are addressed by a desktop study using synthetic data. The ＂true＂ soil moisture profiles are generated from the soil moisture model under the boundary condition of 0.5 cm d^-1 evaporation. To test the assimilation schemes, the model is initialized with a poor initial guess of the soil moisture profile, and different ensemble sizes are tested showing that an ensemble of 40 members is enough to represent the covariance of the model forecasts. Also compared are the results with those from the direct insertion assimilation scheme, showing that the EnKF is superior to the direct insertion assimilation scheme, for hourly observations, with retrieval of the soil moisture profile being achieved in 16 h as compared to 12 days or more. For daily observations, the true soil moisture profile is achieved in about 15 days with the EnKF, but it is impossible to approximate the true moisture within 18 days by using direct insertion. It is also found that observation depth does not have a significant effect on profile retrieval time for the EnKF. The nonlinearities have some negative influence on the optimal estimates of soil moisture profile but not very seriously.展开更多
The immobilization of soil contaminants (as one of the regulating ecosystem services) play</span><span style="font-family:"">s</span><span style="font-family:""> v...The immobilization of soil contaminants (as one of the regulating ecosystem services) play</span><span style="font-family:"">s</span><span style="font-family:""> very important role in environment. This regulatory service prevents groundwater contamination and the entry of contaminants into the food chain. The evaluation as well as the spatial distribution of this regulatory service is important for optimal land management in a specific region. Mapping system combining input layers</span><a name="OLE_LINK4"></a><span style="font-family:"">—</span><span></span><span style="font-family:"">slope topography, soil texture, climate region and land use (arable land, grassland)</span><span style="font-family:"">—</span><span style="font-family:"">were created for the analysis and the evaluation of potential of agroecosystem services. Filtering potential was calculated as accumulative function of soil sorption potential and potential of total content of inorganic pollutants evaluated according to The Slovak Soil Law. Calculated potential was categorised into five categories</span><span style="font-family:"">:</span><span style="font-family:""> very low, <span>low, medium, high and very high. Four model areas were selected for the analysis of pollutant filtration, as one of the regulatory agroecosystem services, which </span><span>are located in different climatic areas and different soil-ecological </span>conditions of Slovakia. The greatest differences among model regions can be found in relation to climatic conditions, land use and diversity of soil types. The warm, dry, and lowland region has a higher potential for pollutant filtration than the moderately warm or cold region. These results are consistent with the location of the soil, its properties, processes and functions within the concept of agro-ecosystem services.</span><span style="font-family:""> </span><span style="font-family:"">Based on the results, we can state that the high risk of inorganic contaminants is inherent in soils with low content and quality of organic substances, low pH value and high concentration of contaminants.展开更多
A novel time-domain identification technique is developed for the seismic response analysis of soil-structure interaction.A two-degree-of-freedom (2DOF) model with eight lumped parameters is adopted to model the frequ...A novel time-domain identification technique is developed for the seismic response analysis of soil-structure interaction.A two-degree-of-freedom (2DOF) model with eight lumped parameters is adopted to model the frequency- dependent behavior of soils.For layered soil,the equivalent eight parameters of the 2DOF model are identified by the extended Kalman filter (EKF) method using recorded seismic data.The polynomial approximations for derivation of state estimators are applied in the EKF procedure.A realistic identification example is given for the layered-soil of a building site in Anchorage,Alaska in the United States.Results of the example demonstrate the feasibility and practicality of the proposed identification technique.The 2DOF soil model and the identification technique can be used for nonlinear response analysis of soil-structure interaction in the time-domain for layered or complex soil conditions.The identified parameters can be stored in a database tor use in other similar soil conditions,lfa universal database that covers information related to most soil conditions is developed in the thture,engineers could conveniently perform time history analyses of soil-structural interaction.展开更多
An observation operator is a bridge linking the system state vector and observations in a data assimilation system. Despite its importance, the degree to which an observation operator influences the performance of dat...An observation operator is a bridge linking the system state vector and observations in a data assimilation system. Despite its importance, the degree to which an observation operator influences the performance of data assimilation methods is still poorly understood. This study aimed to analyze the influences of linear and nonlinear observation operators on the sequential data assimilation through soil temperature simulation using the unscented particle filter(UPF) and the common land model. The linear observation operator between unprocessed simulations and observations was first established. To improve the correlation between simulations and observations, both were processed based on a series of equations. This processing essentially resulted in a nonlinear observation operator. The linear and nonlinear observation operators were then used along with the UPF in three assimilation experiments: an hourly in situ soil surface temperature assimilation, a daily in situ soil surface temperature assimilation, and a moderate resolution imaging spectroradiometer(MODIS) land surface temperature(LST) assimilation. The results show that the filter improved the soil temperature simulation significantly with the linear and nonlinear observation operators. The nonlinear observation operator improved the UPF's performance more significantly for the hourly and daily in situ observation assimilations than the linear observation operator did, while the situation was opposite for the MODIS LST assimilation. Because of the high assimilation frequency and data quality, the simulation accuracy was significantly improved in all soil layers for hourly in situ soil surface temperature assimilation, while the significant improvements of the simulation accuracy were limited to the lower soil layers for the assimilation experiments with low assimilation frequency or low data quality.展开更多
The sugar and bioethanol industry generate large amounts of filter cake and vinasse, residues that are applied to sugarcane fields as conditioners and organic fertilizers. However, these may be significant sources of ...The sugar and bioethanol industry generate large amounts of filter cake and vinasse, residues that are applied to sugarcane fields as conditioners and organic fertilizers. However, these may be significant sources of greenhouse gases emissions to the atmosphere. This study assessed the impact of sugarcane straw biochar on the emissions of CO2, CH4and N2O promoted by filter cake and vinasse applied to soil, and its effects on the chemical properties and bacterial communities of a Typic Hapludox and a Quartzipsamment. A laboratory incubation was conducted for 100 days with both soils under five treatments: vinasse and filter cake amendment (FV), plus biochar at 10 (FV + B10), 20 (FV + B20) and 50 (FV + B50) Mg·ha-1, and a control. Soil pH, available P and exchangeable base contents increased with biochar added to sandy soil. Mineral N decreased with biochar addition to both soils. The FV treatment increased CO2 emissions by 5-fold and 2.4-fold in sandy and clayey soils, respectively, compared to the control. Moreover, FV +B10 increased CO2 emissions by 4% and 6.4% in sandy and clayey soils, respectively, compared to FV. Cumulative N2O emissions in FV were 537% and 125% higher in sandy and clayey soils, respectively, compared to the control. Nevertheless, increasing biochar amendment rates reduced N2O emissions from 24% to 34% in sandy soil, and from 14% to 56% in clayey soil. CH4 emissions were negligible. The effects of filter, vinasse and biochar amendments on soil amelioration were closely related to its buffering capacity. Temporal changes on bacterial community structure were more pronounced in the sandy soil compared to clayey, and indicated that N2O emission mitigation in clayey soil was directly related to biotic mechanisms, while abiotic mechanisms caused by biochar played a more important role in mitigating N2O emissions in sandy soil.展开更多
基金supported by the National Basic Research Program of China (the 973 Program,Grant No.2010CB951101)the Program for Changjiang Scholars and Innovative Research Teams in Universities,the Ministry of Education,China (Grant No. IRT0717)
文摘Hybrid data assimilation （DA） is a method seeing more use in recent hydrology and water resources research. In this study, a DA method coupled with the support vector machines （SVMs） and the ensemble Kalman filter （EnKF） technology was used for the prediction of soil moisture in different soil layers： 0-5 cm, 30 cm, 50 cm, 100 cm, 200 cm, and 300 cm. The SVM methodology was first used to train the ground measurements of soil moisture and meteorological parameters from the Meilin study area, in East China, to construct soil moisture statistical prediction models. Subsequent observations and their statistics were used for predictions, with two approaches： the SVM predictor and the SVM-EnKF model made by coupling the SVM model with the EnKF technique using the DA method. Validation results showed that the proposed SVM-EnKF model can improve the prediction results of soil moisture in different layers, from the surface to the root zone.
基金the National Natural Science Foundation of China(Grant Nos.40475012,90202014, 2001CB309404).
文摘The paper investigates the ability to retrieve the true soil moisture profile by assimilating near-surface soil moisture into a soil moisture model with an ensemble Kalman filter （EnKF） assimilation scheme, including the effect of ensemble size, update interval and nonlinearities in the profile retrieval, the required time for full retrieval of the soil moisture profiles, and the possible influence of the depth of the soil moisture observation. These questions are addressed by a desktop study using synthetic data. The ＂true＂ soil moisture profiles are generated from the soil moisture model under the boundary condition of 0.5 cm d^-1 evaporation. To test the assimilation schemes, the model is initialized with a poor initial guess of the soil moisture profile, and different ensemble sizes are tested showing that an ensemble of 40 members is enough to represent the covariance of the model forecasts. Also compared are the results with those from the direct insertion assimilation scheme, showing that the EnKF is superior to the direct insertion assimilation scheme, for hourly observations, with retrieval of the soil moisture profile being achieved in 16 h as compared to 12 days or more. For daily observations, the true soil moisture profile is achieved in about 15 days with the EnKF, but it is impossible to approximate the true moisture within 18 days by using direct insertion. It is also found that observation depth does not have a significant effect on profile retrieval time for the EnKF. The nonlinearities have some negative influence on the optimal estimates of soil moisture profile but not very seriously.
文摘The immobilization of soil contaminants (as one of the regulating ecosystem services) play</span><span style="font-family:"">s</span><span style="font-family:""> very important role in environment. This regulatory service prevents groundwater contamination and the entry of contaminants into the food chain. The evaluation as well as the spatial distribution of this regulatory service is important for optimal land management in a specific region. Mapping system combining input layers</span><a name="OLE_LINK4"></a><span style="font-family:"">—</span><span></span><span style="font-family:"">slope topography, soil texture, climate region and land use (arable land, grassland)</span><span style="font-family:"">—</span><span style="font-family:"">were created for the analysis and the evaluation of potential of agroecosystem services. Filtering potential was calculated as accumulative function of soil sorption potential and potential of total content of inorganic pollutants evaluated according to The Slovak Soil Law. Calculated potential was categorised into five categories</span><span style="font-family:"">:</span><span style="font-family:""> very low, <span>low, medium, high and very high. Four model areas were selected for the analysis of pollutant filtration, as one of the regulatory agroecosystem services, which </span><span>are located in different climatic areas and different soil-ecological </span>conditions of Slovakia. The greatest differences among model regions can be found in relation to climatic conditions, land use and diversity of soil types. The warm, dry, and lowland region has a higher potential for pollutant filtration than the moderately warm or cold region. These results are consistent with the location of the soil, its properties, processes and functions within the concept of agro-ecosystem services.</span><span style="font-family:""> </span><span style="font-family:"">Based on the results, we can state that the high risk of inorganic contaminants is inherent in soils with low content and quality of organic substances, low pH value and high concentration of contaminants.
文摘A novel time-domain identification technique is developed for the seismic response analysis of soil-structure interaction.A two-degree-of-freedom (2DOF) model with eight lumped parameters is adopted to model the frequency- dependent behavior of soils.For layered soil,the equivalent eight parameters of the 2DOF model are identified by the extended Kalman filter (EKF) method using recorded seismic data.The polynomial approximations for derivation of state estimators are applied in the EKF procedure.A realistic identification example is given for the layered-soil of a building site in Anchorage,Alaska in the United States.Results of the example demonstrate the feasibility and practicality of the proposed identification technique.The 2DOF soil model and the identification technique can be used for nonlinear response analysis of soil-structure interaction in the time-domain for layered or complex soil conditions.The identified parameters can be stored in a database tor use in other similar soil conditions,lfa universal database that covers information related to most soil conditions is developed in the thture,engineers could conveniently perform time history analyses of soil-structural interaction.
基金supported by the National Key Research and Development Program of China(Grants No.2016YFC0402706 and 2016YFC0402710)the National Natural Science Foundation of China(Grants No.51709046 and41323001)the Open Foundation of the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,Hohai University(Grant No.2015490311)
文摘An observation operator is a bridge linking the system state vector and observations in a data assimilation system. Despite its importance, the degree to which an observation operator influences the performance of data assimilation methods is still poorly understood. This study aimed to analyze the influences of linear and nonlinear observation operators on the sequential data assimilation through soil temperature simulation using the unscented particle filter(UPF) and the common land model. The linear observation operator between unprocessed simulations and observations was first established. To improve the correlation between simulations and observations, both were processed based on a series of equations. This processing essentially resulted in a nonlinear observation operator. The linear and nonlinear observation operators were then used along with the UPF in three assimilation experiments: an hourly in situ soil surface temperature assimilation, a daily in situ soil surface temperature assimilation, and a moderate resolution imaging spectroradiometer(MODIS) land surface temperature(LST) assimilation. The results show that the filter improved the soil temperature simulation significantly with the linear and nonlinear observation operators. The nonlinear observation operator improved the UPF's performance more significantly for the hourly and daily in situ observation assimilations than the linear observation operator did, while the situation was opposite for the MODIS LST assimilation. Because of the high assimilation frequency and data quality, the simulation accuracy was significantly improved in all soil layers for hourly in situ soil surface temperature assimilation, while the significant improvements of the simulation accuracy were limited to the lower soil layers for the assimilation experiments with low assimilation frequency or low data quality.
文摘The sugar and bioethanol industry generate large amounts of filter cake and vinasse, residues that are applied to sugarcane fields as conditioners and organic fertilizers. However, these may be significant sources of greenhouse gases emissions to the atmosphere. This study assessed the impact of sugarcane straw biochar on the emissions of CO2, CH4and N2O promoted by filter cake and vinasse applied to soil, and its effects on the chemical properties and bacterial communities of a Typic Hapludox and a Quartzipsamment. A laboratory incubation was conducted for 100 days with both soils under five treatments: vinasse and filter cake amendment (FV), plus biochar at 10 (FV + B10), 20 (FV + B20) and 50 (FV + B50) Mg·ha-1, and a control. Soil pH, available P and exchangeable base contents increased with biochar added to sandy soil. Mineral N decreased with biochar addition to both soils. The FV treatment increased CO2 emissions by 5-fold and 2.4-fold in sandy and clayey soils, respectively, compared to the control. Moreover, FV +B10 increased CO2 emissions by 4% and 6.4% in sandy and clayey soils, respectively, compared to FV. Cumulative N2O emissions in FV were 537% and 125% higher in sandy and clayey soils, respectively, compared to the control. Nevertheless, increasing biochar amendment rates reduced N2O emissions from 24% to 34% in sandy soil, and from 14% to 56% in clayey soil. CH4 emissions were negligible. The effects of filter, vinasse and biochar amendments on soil amelioration were closely related to its buffering capacity. Temporal changes on bacterial community structure were more pronounced in the sandy soil compared to clayey, and indicated that N2O emission mitigation in clayey soil was directly related to biotic mechanisms, while abiotic mechanisms caused by biochar played a more important role in mitigating N2O emissions in sandy soil.
