2011 Vol. 21, No. 2
Display Method:
2011, 21(2): 129-148.
Abstract:
Stable isotope techniques have been proved useful as tools for studying the carbon (C) and nitrogen (N) biogeochemical cycles of ecosystem. This paper firstly introduced the basic principles and the distribution characteristics of stable isotope, then reviewed the recent advances and applications of stable isotope in the C and N biogeochemical cycles of ecosystem. By applying the 13C natural abundance technique, ecologists are able to understand the photosynthetic path and CO2 fixation of plants, the CO2 exchange and C balance status of ecosystem, the composition, distribution and turnover of soil organic C and the sources of organic matter in food webs, while by using the 13C labeled technique, the effects of elevated CO2 on the C processes of ecosystem and the sources and fate of organic matter in ecosystem can be revealed in detail. Differently, by applying the 15N natural abundance technique, ecologists are able to analyze the biological N2-fixation, the N sources of ecosystem, the N transformation processes of ecosystem and the N trophic status in food webs, while by using the 15N labeled technique, the sources, transformation and fate of N in ecosystem and the effects of N input on the ecosystem can be investigated in depth. The applications of both C and N isotope natural abundance and labeled techniques, combined with the elemental, other isotope (34S) and molecular biomarker information, will be more propitious to the investigation of C and N cycle mechanisms. Finally, this paper concluded the problems existed in current researches, and put forward the perspective of stable isotope techniques in the studies on C and N biogeochemical cycles of ecosystem in the future.
Stable isotope techniques have been proved useful as tools for studying the carbon (C) and nitrogen (N) biogeochemical cycles of ecosystem. This paper firstly introduced the basic principles and the distribution characteristics of stable isotope, then reviewed the recent advances and applications of stable isotope in the C and N biogeochemical cycles of ecosystem. By applying the 13C natural abundance technique, ecologists are able to understand the photosynthetic path and CO2 fixation of plants, the CO2 exchange and C balance status of ecosystem, the composition, distribution and turnover of soil organic C and the sources of organic matter in food webs, while by using the 13C labeled technique, the effects of elevated CO2 on the C processes of ecosystem and the sources and fate of organic matter in ecosystem can be revealed in detail. Differently, by applying the 15N natural abundance technique, ecologists are able to analyze the biological N2-fixation, the N sources of ecosystem, the N transformation processes of ecosystem and the N trophic status in food webs, while by using the 15N labeled technique, the sources, transformation and fate of N in ecosystem and the effects of N input on the ecosystem can be investigated in depth. The applications of both C and N isotope natural abundance and labeled techniques, combined with the elemental, other isotope (34S) and molecular biomarker information, will be more propitious to the investigation of C and N cycle mechanisms. Finally, this paper concluded the problems existed in current researches, and put forward the perspective of stable isotope techniques in the studies on C and N biogeochemical cycles of ecosystem in the future.
2011, 21(2): 149-158.
Abstract:
Wetland soils are characterized by alternating redox process due to the fluctuation of waterlogged conditions. Iron is an important redox substance, and its transfer and transformation in the wetland ecosystem could be an effective indicator for the environment changes. In this paper, we selected the Naoli River catchment in the Sanjiang Plain, Northeast China as the study area to analyze the dynamics of transfer and transformation of soil iron, and the relationship between iron content change and environmental factors. The results show that the total and crystalline iron contents reach the peak in the depth of 60 cm in soil profile, while the amorphous iron content is higher in the topsoil. In the upper reaches, from the low to high landscape positions, the total and crystalline iron contents decrease from 62.98 g/kg to 41.61 g/kg, 22.82 g/kg to 10.53 g/kg respectively, while the amorphous iron content increases from 2.42 g/kg to 8.88 g/kg. Amorphous iron content has positive correlation with organic matter and soil water contents, while negative correlation with pH. Moreover, both the crystalline and amorphous iron contents present no correlation with total iron content, indicating that environmental factors play a more important role in the transfer and transformation of iron other than the content of the total iron. Different redoximorphic features were found along the soil profile due to the transfer and transformation of iron. E and B horizons of wetland soil in the study area have a matrix Chroma 2 or less, and all the soil types can meet the criteria of American hydric soil indicators except albic soil.
Wetland soils are characterized by alternating redox process due to the fluctuation of waterlogged conditions. Iron is an important redox substance, and its transfer and transformation in the wetland ecosystem could be an effective indicator for the environment changes. In this paper, we selected the Naoli River catchment in the Sanjiang Plain, Northeast China as the study area to analyze the dynamics of transfer and transformation of soil iron, and the relationship between iron content change and environmental factors. The results show that the total and crystalline iron contents reach the peak in the depth of 60 cm in soil profile, while the amorphous iron content is higher in the topsoil. In the upper reaches, from the low to high landscape positions, the total and crystalline iron contents decrease from 62.98 g/kg to 41.61 g/kg, 22.82 g/kg to 10.53 g/kg respectively, while the amorphous iron content increases from 2.42 g/kg to 8.88 g/kg. Amorphous iron content has positive correlation with organic matter and soil water contents, while negative correlation with pH. Moreover, both the crystalline and amorphous iron contents present no correlation with total iron content, indicating that environmental factors play a more important role in the transfer and transformation of iron other than the content of the total iron. Different redoximorphic features were found along the soil profile due to the transfer and transformation of iron. E and B horizons of wetland soil in the study area have a matrix Chroma 2 or less, and all the soil types can meet the criteria of American hydric soil indicators except albic soil.
2011, 21(2): 159-166.
Abstract:
Coal fire burning around the world is an environmental catastrophe characterized by the emission of noxious gases, particulate matter, and condensation by-products. In this study, coal fire temperature is retrieved based on Landsat 5 TM images and Generalized Single-Channel Algorithm (GSCA), in Wuda coalfield, Inner Mongolia, China. Then coal fire zones are extracted by Jenks′ natural breaks and threshold methods based on temperature images. Changes of coal fire zones are analyzed from 1989 to 2008. The results are summarized as follows: 1) The coal fire temperature retrieval method based on Landsat 5 TM and the GSCA model is effective and feasible, because the temperature error is relatively small (from –2.9℃ to +2.6℃) between the measured temperature and the retrieved temperature. 2) The accuracy is relatively high to extract coal fire zones through the Jenks′ natural breaks and threshold methods, because 83.56% of surveyed area is located in the coal fire zones extracted in 2005. 3) The coal fire area increased 9.81 × 105 m2 from 1989 to 2005, and the annual growth is about 6.1 × 104 m2, with an annual increasing rate of 2.48%. The area of coal fire decreased by 8.1 × 105 m2 from 2005 to 2008.
Coal fire burning around the world is an environmental catastrophe characterized by the emission of noxious gases, particulate matter, and condensation by-products. In this study, coal fire temperature is retrieved based on Landsat 5 TM images and Generalized Single-Channel Algorithm (GSCA), in Wuda coalfield, Inner Mongolia, China. Then coal fire zones are extracted by Jenks′ natural breaks and threshold methods based on temperature images. Changes of coal fire zones are analyzed from 1989 to 2008. The results are summarized as follows: 1) The coal fire temperature retrieval method based on Landsat 5 TM and the GSCA model is effective and feasible, because the temperature error is relatively small (from –2.9℃ to +2.6℃) between the measured temperature and the retrieved temperature. 2) The accuracy is relatively high to extract coal fire zones through the Jenks′ natural breaks and threshold methods, because 83.56% of surveyed area is located in the coal fire zones extracted in 2005. 3) The coal fire area increased 9.81 × 105 m2 from 1989 to 2005, and the annual growth is about 6.1 × 104 m2, with an annual increasing rate of 2.48%. The area of coal fire decreased by 8.1 × 105 m2 from 2005 to 2008.
2011, 21(2): 167-175.
Abstract:
Drought is one of the major natural disasters causing huge agricultural losses annually. Regional agricultural drought risk assessment has great significance for reducing regional disaster and agricultural drought losses. Based on the fuzzy characteristics of agricultural drought risk, variable fuzzy sets model was used for comprehensively assessing agricultural drought risk of Liaoning Province in China. A multi-layers and multi-indices assessment model was established according to variable fuzzy sets theory, and agricultural drought risk of all 14 prefecture-level cities was respectively estimated in terms of dangerousness, vulnerability, exposure and drought-resistibility. By calculating the combination weights of four drought risk factors, agricultural drought risk grade of each city was obtained. Based on the assessment results, the spatial distribution maps of agricultural drought risk were drawn. The results shows that eastern cities have lower drought dangerousness than western cities in Liaoning Province totally. Most cities are located in low drought vulnerability region and high drought exposure region. Because of frequent and severe drought since 2000, most cities are located in lower drought-resistibility region. Comprehensive agricultural drought risk presents apparent spatial characteristics, escalating from the east to the west. Drought dangerousness is the most important factor influencing comprehensive agricultural drought risk. Through the spatial distribution maps of drought risk, decision makers could find out drought situation and make decisions on drought resistance conveniently.
Drought is one of the major natural disasters causing huge agricultural losses annually. Regional agricultural drought risk assessment has great significance for reducing regional disaster and agricultural drought losses. Based on the fuzzy characteristics of agricultural drought risk, variable fuzzy sets model was used for comprehensively assessing agricultural drought risk of Liaoning Province in China. A multi-layers and multi-indices assessment model was established according to variable fuzzy sets theory, and agricultural drought risk of all 14 prefecture-level cities was respectively estimated in terms of dangerousness, vulnerability, exposure and drought-resistibility. By calculating the combination weights of four drought risk factors, agricultural drought risk grade of each city was obtained. Based on the assessment results, the spatial distribution maps of agricultural drought risk were drawn. The results shows that eastern cities have lower drought dangerousness than western cities in Liaoning Province totally. Most cities are located in low drought vulnerability region and high drought exposure region. Because of frequent and severe drought since 2000, most cities are located in lower drought-resistibility region. Comprehensive agricultural drought risk presents apparent spatial characteristics, escalating from the east to the west. Drought dangerousness is the most important factor influencing comprehensive agricultural drought risk. Through the spatial distribution maps of drought risk, decision makers could find out drought situation and make decisions on drought resistance conveniently.
2011, 21(2): 176-184.
Abstract:
According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Markov chain model, the state transition probability matrixes can be adjusted. The steps of the historical state of the event, which was significantly related to the future state of the event, were determined by the autocorrelation technique, and the impact weights of the event historical state on the event future state were determined by the entropy technique. The presented model was applied to predicting annual precipitation and annual runoff states, showing that the improved model is of higher precision than those existing Markov chain models, and the determination of the state transition probability matrixes and the weights is more reasonable. The physical concepts of the improved model are distinct, and its computation process is simple and direct, thus, the presented model is sufficiently general to be applicable to the prediction problems in hydrology and water resources.
According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Markov chain model, the state transition probability matrixes can be adjusted. The steps of the historical state of the event, which was significantly related to the future state of the event, were determined by the autocorrelation technique, and the impact weights of the event historical state on the event future state were determined by the entropy technique. The presented model was applied to predicting annual precipitation and annual runoff states, showing that the improved model is of higher precision than those existing Markov chain models, and the determination of the state transition probability matrixes and the weights is more reasonable. The physical concepts of the improved model are distinct, and its computation process is simple and direct, thus, the presented model is sufficiently general to be applicable to the prediction problems in hydrology and water resources.
2011, 21(2): 185-194.
Abstract:
Polycyclic aromatic hydrocarbons (PAHs) contamination of topsoil in Benxi City, Northeast China was investigated in this study, and sampling sites were located in industrial area and residential area. Results demonstrate that there is high variability in the total PAHs concentrations, ranging from 783.00 ng/g to 729 076.29 ng/g dry weight in the topsoil of Benxi City and the pollution in industrial area is the most serious. The results also present that higher molecular weight PAHs (4–6 rings) contribute substantially (79.03%) to the overall content of PAHs. The PAHs sources were determined with factor analysis by nonnegative constraints, and the results show that PAHs originating from traffic tunnel, power plant, coke oven and residential emission sources, account for 27.10%, 40.81%, 20.11% and 11.98%, respectively, of the total. The PAHs pollution is the most serious around Benxi Iron and Steel Group Corporation, and the PAHs mainly originate from coke oven and traffic tunnel, with the average contribution rate of 57.40% and 42.60%, respectively. The source apportionment results are basically consistent with the industry distribution, and the geographical and climatic characteristics of the study area.
Polycyclic aromatic hydrocarbons (PAHs) contamination of topsoil in Benxi City, Northeast China was investigated in this study, and sampling sites were located in industrial area and residential area. Results demonstrate that there is high variability in the total PAHs concentrations, ranging from 783.00 ng/g to 729 076.29 ng/g dry weight in the topsoil of Benxi City and the pollution in industrial area is the most serious. The results also present that higher molecular weight PAHs (4–6 rings) contribute substantially (79.03%) to the overall content of PAHs. The PAHs sources were determined with factor analysis by nonnegative constraints, and the results show that PAHs originating from traffic tunnel, power plant, coke oven and residential emission sources, account for 27.10%, 40.81%, 20.11% and 11.98%, respectively, of the total. The PAHs pollution is the most serious around Benxi Iron and Steel Group Corporation, and the PAHs mainly originate from coke oven and traffic tunnel, with the average contribution rate of 57.40% and 42.60%, respectively. The source apportionment results are basically consistent with the industry distribution, and the geographical and climatic characteristics of the study area.
2011, 21(2): 195-203.
Abstract:
This study reports the geochemical characteristics of zinc (Zn), copper (Cu), lead (Pb), nickel (Ni), mercury (Hg), iron (Fe), and manganese (Mn) in the riparian sediment pore water of the Songhua River, Northeast China. In total, 36 pore water samples and 18 surface water samples from three typical sections were collected and analyzed in June 2009. Cluster analysis of heavy metals was performed to analyze the pollution sources of the metals. Results showed that Hg concentrations in the pore water were greater than those in the surface water, indicating a potential ability of Hg release from riparian sediment system to river water. However, concentrations of Fe and Mn in the surface water were greater than those in the pore water, demonstrating that the microenvironments of riparian and riverbed sediment systems were quite different. Variations of Zn, Cu, Pb and Ni between the surface and the pore water were different in each section. Most metals had similar horizontal and profile distribution characteristics in the three sections except for Zn and Ni. Hg, Fe and Mn concentrations in the pore water increased gradually with the increase in horizontal distance from water body, in contrast to this, Cu decreased, and Pb presented a fluctuating trend. With the increase in depth, Pb and Fe, Cu and Mn showed the same trends, and Hg showed a variable trend. The above distribution characteristics could mainly be attributed to the properties and the interactions of metals, pH and oxidation-reduction conditions, and the complex pollution sources and hydrologic regime in history. The probable sources of metals include the historical and ongoing discharge of industrial wastewater, mining activities, sewage irrigation for agricultural production, and atmospheric deposition from coal-fired plants.
This study reports the geochemical characteristics of zinc (Zn), copper (Cu), lead (Pb), nickel (Ni), mercury (Hg), iron (Fe), and manganese (Mn) in the riparian sediment pore water of the Songhua River, Northeast China. In total, 36 pore water samples and 18 surface water samples from three typical sections were collected and analyzed in June 2009. Cluster analysis of heavy metals was performed to analyze the pollution sources of the metals. Results showed that Hg concentrations in the pore water were greater than those in the surface water, indicating a potential ability of Hg release from riparian sediment system to river water. However, concentrations of Fe and Mn in the surface water were greater than those in the pore water, demonstrating that the microenvironments of riparian and riverbed sediment systems were quite different. Variations of Zn, Cu, Pb and Ni between the surface and the pore water were different in each section. Most metals had similar horizontal and profile distribution characteristics in the three sections except for Zn and Ni. Hg, Fe and Mn concentrations in the pore water increased gradually with the increase in horizontal distance from water body, in contrast to this, Cu decreased, and Pb presented a fluctuating trend. With the increase in depth, Pb and Fe, Cu and Mn showed the same trends, and Hg showed a variable trend. The above distribution characteristics could mainly be attributed to the properties and the interactions of metals, pH and oxidation-reduction conditions, and the complex pollution sources and hydrologic regime in history. The probable sources of metals include the historical and ongoing discharge of industrial wastewater, mining activities, sewage irrigation for agricultural production, and atmospheric deposition from coal-fired plants.
2011, 21(2): 204-210.
Abstract:
Vulnerability is a new field and analytical tool in the study of urban safety. Analysis and assessment of vulnerability provide a new basis for urban planning. This study constructed a quantitative index system for assessing vulnerability, based on the city′s sensitivity and emergency response capacity. City size, density, and spatial form influence a city′s sensitivity to crises and risks, to which vulnerability is positively related. Levels of socio-economic development, infrastructures, and emergency management contribute to a city′s emergency response capacity, with which vulnerability is inversely associated. Vulnerability of 19 large Chinese cities was assessed. Harbin and Shenzhen demonstrated the highest and lowest vulnerability among 19 cities, while Beijing, Shanghai and Guangzhou ranked the 5th, the 9th and the 12th. Spatially, northern cities tended to be more vulnerable than southern cities. And the differences in vulnerability among cities were explored based on cities′ physical geography conditions, level of socio- economic development, infrastructures, regional status, history of disaster, history of urban planning and development, government policies, etc.
Vulnerability is a new field and analytical tool in the study of urban safety. Analysis and assessment of vulnerability provide a new basis for urban planning. This study constructed a quantitative index system for assessing vulnerability, based on the city′s sensitivity and emergency response capacity. City size, density, and spatial form influence a city′s sensitivity to crises and risks, to which vulnerability is positively related. Levels of socio-economic development, infrastructures, and emergency management contribute to a city′s emergency response capacity, with which vulnerability is inversely associated. Vulnerability of 19 large Chinese cities was assessed. Harbin and Shenzhen demonstrated the highest and lowest vulnerability among 19 cities, while Beijing, Shanghai and Guangzhou ranked the 5th, the 9th and the 12th. Spatially, northern cities tended to be more vulnerable than southern cities. And the differences in vulnerability among cities were explored based on cities′ physical geography conditions, level of socio- economic development, infrastructures, regional status, history of disaster, history of urban planning and development, government policies, etc.
2011, 21(2): 211-221.
Abstract:
Under the theoretical framework of the New Trade Theory and the New Economic Geography, Home Market Effects (HMEs) is considered to be important sources of comparative advantage and significant reasons for industry agglomeration. Through the analysis on the input-output tables in China, the paper confirms the existence of HMEs for the manufacturing industries and their export trades on the national and provincial level in China. Several conclusions have been drawn in this study. Firstly, there exist prominent HMEs for manufacturing industries related with nondurable goods and materials in China. Secondly, 10 of the 15 kinds of manufacturing industries considered in this study display the existence of HMEs. Thirdly, the comparative advantage of factor endowment for the export trade of manufacturing industries is declining, while HMEs for them are increasing. Fourthly, among the 30 provincial regions studied in this paper, 11 regions show the existence of HMEs, most of which are located in the eastern coast region. This paper illustrates the simultaneous existence of the comparative advantage of factor endowment and scale economies of HMEs for China's manufacturing industries. HMEs will not only be the new dynamic for the increase of manufacturing industries and their export trade, but also be the primary power for urban economic growth, industry improvement, and urban space expansion for China.
Under the theoretical framework of the New Trade Theory and the New Economic Geography, Home Market Effects (HMEs) is considered to be important sources of comparative advantage and significant reasons for industry agglomeration. Through the analysis on the input-output tables in China, the paper confirms the existence of HMEs for the manufacturing industries and their export trades on the national and provincial level in China. Several conclusions have been drawn in this study. Firstly, there exist prominent HMEs for manufacturing industries related with nondurable goods and materials in China. Secondly, 10 of the 15 kinds of manufacturing industries considered in this study display the existence of HMEs. Thirdly, the comparative advantage of factor endowment for the export trade of manufacturing industries is declining, while HMEs for them are increasing. Fourthly, among the 30 provincial regions studied in this paper, 11 regions show the existence of HMEs, most of which are located in the eastern coast region. This paper illustrates the simultaneous existence of the comparative advantage of factor endowment and scale economies of HMEs for China's manufacturing industries. HMEs will not only be the new dynamic for the increase of manufacturing industries and their export trade, but also be the primary power for urban economic growth, industry improvement, and urban space expansion for China.
2011, 21(2): 222-229.
Abstract:
In recent years, great economic output of land has been achieved in economic-technological development areas in China, but the intensity of land use in some of these areas is very low. The degree of the low intensity of land use needs to be evaluated. The current method of comprehensive evaluation and grading by one index system has the limitations due to the existence of differences between regions and industries. This paper evaluates industrial land use intensity by Total Factor Productivity (TFP) analysis, which not only measures the intensity but also illustrates the efficiency of input factors. This method is applied to the Beijing Economic-technological Development Area (BDA). A comparison analysis on factor use efficiency and input structure of capital and labor between industries is also carried out in the absence of a labor-income ratio.
In recent years, great economic output of land has been achieved in economic-technological development areas in China, but the intensity of land use in some of these areas is very low. The degree of the low intensity of land use needs to be evaluated. The current method of comprehensive evaluation and grading by one index system has the limitations due to the existence of differences between regions and industries. This paper evaluates industrial land use intensity by Total Factor Productivity (TFP) analysis, which not only measures the intensity but also illustrates the efficiency of input factors. This method is applied to the Beijing Economic-technological Development Area (BDA). A comparison analysis on factor use efficiency and input structure of capital and labor between industries is also carried out in the absence of a labor-income ratio.
2011, 21(2): 230-240.
Abstract:
Wetland research has become a hot spot linking multiple disciplines presently. Wetland classification and mapping is the basis for wetland research. It is difficult to generate wetland data sets using traditional methods because of the low accessibility of wetlands, hence remote sensing data have become one of the primary data sources in wetland research. This paper presents a case study conducted at the core area of Honghe National Nature Reserve in the Sanjiang Plain, Northeast China. In this study, three images generated by airship, from Thematic Mapper and from SPOT 5 were selected to produce wetland maps at three different wetland landscape levels. After assessing classification accuracies of the three maps, we compared the different wetland mapping results of 11 plant communities to the airship image, 6 plant ecotypes to the TM image and 9 landscape classifications to the SPOT 5 image. We discussed the different characteristics of the hierarchical ecosystem classifications based on the spatial scales of the different images. The results indicate that spatial scales of remote sensing data have an important link to the hierarchies of wetland plant ecosystems displayed on the wetland landscape maps. The richness of wetland landscape information derived from an image closely relates to its spatial resolution. This study can enrich the ecological classification methods and mapping techniques dealing with the spatial scales of different remote sensing images. With a better understanding of classification accuracies in mapping wetlands by using different scales of remote sensing data, we can make an appropriate approach for dealing with the scale issue of remote sensing images.
Wetland research has become a hot spot linking multiple disciplines presently. Wetland classification and mapping is the basis for wetland research. It is difficult to generate wetland data sets using traditional methods because of the low accessibility of wetlands, hence remote sensing data have become one of the primary data sources in wetland research. This paper presents a case study conducted at the core area of Honghe National Nature Reserve in the Sanjiang Plain, Northeast China. In this study, three images generated by airship, from Thematic Mapper and from SPOT 5 were selected to produce wetland maps at three different wetland landscape levels. After assessing classification accuracies of the three maps, we compared the different wetland mapping results of 11 plant communities to the airship image, 6 plant ecotypes to the TM image and 9 landscape classifications to the SPOT 5 image. We discussed the different characteristics of the hierarchical ecosystem classifications based on the spatial scales of the different images. The results indicate that spatial scales of remote sensing data have an important link to the hierarchies of wetland plant ecosystems displayed on the wetland landscape maps. The richness of wetland landscape information derived from an image closely relates to its spatial resolution. This study can enrich the ecological classification methods and mapping techniques dealing with the spatial scales of different remote sensing images. With a better understanding of classification accuracies in mapping wetlands by using different scales of remote sensing data, we can make an appropriate approach for dealing with the scale issue of remote sensing images.
2011, 21(2): 241-248.
Abstract:
Taking a typical inland wetland of Honghe National Nature Reserve (HNNR), Northeast China, as the study area, this paper studied the application of L-band Synthetic Aperture Radar (SAR) image in extracting eco-hydrological information of inland wetland. Landsat-5 TM and ALOS PALSAR HH backscatter images were first fused by using the wavelet-IHS method. Based on the fused image data, the classification method of support vector machines was used to map the wetland in the study area. The overall mapping accuracy is 77.5%. Then, the wet and dry aboveground biomass estimation models, including statistical models and a Rice Cloudy model, were established. Optimal parameters for the Rice Cloudy model were calculated in MATLAB by using the least squares method. Based on the validation results, it was found that the Rice Cloudy model produced higher accuracy for both wet and dry aboveground biomass estimation compared to the statistical models. Finally, subcanopy water boundary information was extracted from the HH backscatter image by threshold method. Compared to the actual water borderline result, the extracted result from L-band SAR image is reliable. In this paper, the HH-HV phase difference was proved to be valueless for extracting subcanopy water boundary information.
Taking a typical inland wetland of Honghe National Nature Reserve (HNNR), Northeast China, as the study area, this paper studied the application of L-band Synthetic Aperture Radar (SAR) image in extracting eco-hydrological information of inland wetland. Landsat-5 TM and ALOS PALSAR HH backscatter images were first fused by using the wavelet-IHS method. Based on the fused image data, the classification method of support vector machines was used to map the wetland in the study area. The overall mapping accuracy is 77.5%. Then, the wet and dry aboveground biomass estimation models, including statistical models and a Rice Cloudy model, were established. Optimal parameters for the Rice Cloudy model were calculated in MATLAB by using the least squares method. Based on the validation results, it was found that the Rice Cloudy model produced higher accuracy for both wet and dry aboveground biomass estimation compared to the statistical models. Finally, subcanopy water boundary information was extracted from the HH backscatter image by threshold method. Compared to the actual water borderline result, the extracted result from L-band SAR image is reliable. In this paper, the HH-HV phase difference was proved to be valueless for extracting subcanopy water boundary information.
2011, 21(2): 249-256.
Abstract:
Air entrapment is an important consideration in environments with shallow water tables and sandy soil, like the condition of highly conductive sandy soils and flat topography in Florida, USA. It causes water table rises in soils, which are significantly faster and higher than those in soils without air entrapment. Two numerical models, Integrated Hydrologic Model (IHM) and HYDRUS-1D (a single-phase, one-dimensional Richards′ equation model) were tested at an area of west central Florida to help further understanding the shallow water table behavior during a long term air entrapment. This investigation employed field data with two modeling approaches to quantify the variation of air pressurization values. It was found that the air pressurization effect was responsible at time up to 40 cm of water table rise being recorded by the observation well for these two models. The values of air pressurization calculated from IHM and HYDRUS-1D match the previously published values. Results also indicated that the two numerical models did not consider air entrapment effect (as the predictive parameters remain uncertain) and thus results of depth to water table from these models did not compare to the observations for these selected periods. Incorporating air entrapment in prediction models is critical to reproduce shallow water table observations.
Air entrapment is an important consideration in environments with shallow water tables and sandy soil, like the condition of highly conductive sandy soils and flat topography in Florida, USA. It causes water table rises in soils, which are significantly faster and higher than those in soils without air entrapment. Two numerical models, Integrated Hydrologic Model (IHM) and HYDRUS-1D (a single-phase, one-dimensional Richards′ equation model) were tested at an area of west central Florida to help further understanding the shallow water table behavior during a long term air entrapment. This investigation employed field data with two modeling approaches to quantify the variation of air pressurization values. It was found that the air pressurization effect was responsible at time up to 40 cm of water table rise being recorded by the observation well for these two models. The values of air pressurization calculated from IHM and HYDRUS-1D match the previously published values. Results also indicated that the two numerical models did not consider air entrapment effect (as the predictive parameters remain uncertain) and thus results of depth to water table from these models did not compare to the observations for these selected periods. Incorporating air entrapment in prediction models is critical to reproduce shallow water table observations.
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