The results of an investigation into the relationship between surface sediment subfossil chi- ronomid distribution and water quality are presented. Data from 30 lakes in the middle and lower reaches of the Yangtze Riv...The results of an investigation into the relationship between surface sediment subfossil chi- ronomid distribution and water quality are presented. Data from 30 lakes in the middle and lower reaches of the Yangtze River indicate that the nutrient gradi- ent was the major factor affecting the distribution of chironomids across these sites. Canonical corre- spondence analysis (CCA) revealed that of 12 sum- mer water environmental variables, total Phosphorus was most important, accounting for 20.1% of the variance in the chironomid data. This was significant enough to allow the development of quantitative in- ference models. A TP inference model was devel- oped using weighted averaging (WA), partial least squares (PLS) and weighted averaging partial least squares (WA-PLS). An optimal two-component WA-PLS model provided a high jack-knifed coeffi- cient of prediction for conductivity r 2jack = 0.76, with a low root mean squared error of prediction (RMSEPjack = 0.13). Using this model it is possible to produce long-term quantitative records of past water quality for lacustrine sites across the middle and lower reaches of the Yangtze River, which has important implications for future lake management and eco- logical restoration.展开更多
Purple soils are widely distributed in the Sichuan Hilly Basin and are highly susceptible to erosion, especially on the cultivated slopes. Quantitative assessment of the erosion rates is, however, difficult due to sma...Purple soils are widely distributed in the Sichuan Hilly Basin and are highly susceptible to erosion, especially on the cultivated slopes. Quantitative assessment of the erosion rates is, however, difficult due to small size of the plots of the manually-tilled land, the complex land use, and steep hillslopes. ^137Cs and ^210Pbex （excess ^210Pb） tracing techniques were used to investigate the spatial pattern of soil erosion rates associated with slope-land under hoe tillage in Neijiang of the Sichuan Hilly Basin. The ^137Cs and ^210Pbex inventories at the top of the cultivated slope were extremely low, and the highest inventories were found at the bottom of the cultivated slope. By combining the erosion rates estimates provided by both ^137Cs and 21~Pbex measurements, the weighted mean net soil loss from the study slope was estimated to be 3 100 t km^-2 year^-1, which was significantly less than 6 930 t km^-2 year^-1 reported for runoff plots on a 10° cultivated slope at the Suining Station of Soil Erosion. The spatial pattern of soil erosion rates on the steep agricultural land showed that hoe tillage played an important role in soil redistribution along the slope. Also, traditional farming practices had a significant role in reducing soil loss, leading to a lower net erosion rate for the field.展开更多
The purpose of this article was to analyze data associated with advances in wind energy across the United States. While governments, academia, and the private sector generally know patterns of wind turbine development...The purpose of this article was to analyze data associated with advances in wind energy across the United States. While governments, academia, and the private sector generally know patterns of wind turbine development (</span><i><span style="font-family:Verdana;">i.e.</span></i><span style="font-family:Verdana;"> turbine size and capacity growing in recent years), there is no known independent, reliable, and/or updated summary of these variables. Using data collected by the Lawrence Berkeley National Laboratory and partners, this study used descriptive statistics to show turbine development and growth patterns from </span><span style="font-family:Verdana;">1981-2019. The newly created United States Wind Turbine Database (USWTDB</span><span style="font-family:Verdana;">) represents the most comprehensive account of wind turbine information and was updated in January 2020. Variables I am interested in here are turbine manufacturer, state of project, turbine and project capacity, and turbine size. Findings provide empirical evidence to support the common, yet previously unrefined statements that wind turbines are growing larger in number, size and capacity. This growth is varied over spatial and temporal scales. I also provide evidence to show patterns of turbine manufacturing, with GE Wind dominating much of the US wind energy landscape today. I hope this work provides a timely resource for those interested in a variety of questions surrounding wind energy development in the United States. Perhaps more importantly, this analysis will hopefully inspire others to use what the USWTDB provides and answer larger questions surrounding wind energy futures.展开更多
As a tool for management, query, visualization and analysis of spatially referred information, GIS has been recognized as a method to aid the modeling of diffuse pollution and visualize the results in a spatial contex...As a tool for management, query, visualization and analysis of spatially referred information, GIS has been recognized as a method to aid the modeling of diffuse pollution and visualize the results in a spatial context. A common question in integrating diffuse pollution models and GIS is to choose a suitable coupling approach, in which the feature of diffuse pollution models should be taken into account. In this paper, we report on our experience in coupling a distributed diffuse pollution model with a GIS. A prototype of fully integrated system is developed in this paper. This system has high flexibility, extendibility and great data management efficiency. Differences in applicability of loose coupling, tight coupling and fully integrated approaches are addressed. It is concluded that the fully integrated approach can avoid tanglesome data exchange and routine execution and more robust than loose and tight coupling approaches and is suitable for distributed diffuse pollution modes.展开更多
Development of a quantitative understanding of soil organic carbon （SOC） dynamics is vital for management of soil to sequester carbon （C） and maintain fertility, thereby contributing to food security and climate c...Development of a quantitative understanding of soil organic carbon （SOC） dynamics is vital for management of soil to sequester carbon （C） and maintain fertility, thereby contributing to food security and climate change mitigation. There are well-established process-based models that can be used to simulate SOC stock evolution; however, there are few plant residue C input values and those that exist represent a limited range of environments. This limitation in a fundamental model component （i.e., C input） constrains the reliability of current SOC stock simulations. This study aimed to estimate crop-specific and environment-specific plant-derived soil C input values for agricultural sites in France based on data from 700 sites selected from a recently established French soil monitoring network （the RMQS database）. Measured SOC stock values from this large scale soil database were used to constrain an inverse RothC modelling approach to derive estimated C input values consistent with the stocks. This approach allowed us to estimate significant crop-specific C input values （P 〈 0.05） for 14 out of 17 crop types in the range from 1.84 =h 0.69 t C ha-1 year-1 （silage corn） to 5.15 =k 0.12 t C ha-1 year-1 （grassland/pasture）. Furthermore, the incorporation of climate variables improved the predictions. C input of 4 crop types could be predicted as a function of temperature and 8 as a function of precipitation. This study offered an approach to meet the urgent need for crop-specific and environment-specific C input values in order to improve the reliability of SOC stock prediction.展开更多
基金This study was supported by the National Natural Science Foundation of China （Grant No. 40402015） the State Key Basic Research and Development Plan of China （Grant No. 2004CB720205）the Knowledge Innovation Project of the CAS （Grant No. KZCX1-SW-12）.
文摘The results of an investigation into the relationship between surface sediment subfossil chi- ronomid distribution and water quality are presented. Data from 30 lakes in the middle and lower reaches of the Yangtze River indicate that the nutrient gradi- ent was the major factor affecting the distribution of chironomids across these sites. Canonical corre- spondence analysis (CCA) revealed that of 12 sum- mer water environmental variables, total Phosphorus was most important, accounting for 20.1% of the variance in the chironomid data. This was significant enough to allow the development of quantitative in- ference models. A TP inference model was devel- oped using weighted averaging (WA), partial least squares (PLS) and weighted averaging partial least squares (WA-PLS). An optimal two-component WA-PLS model provided a high jack-knifed coeffi- cient of prediction for conductivity r 2jack = 0.76, with a low root mean squared error of prediction (RMSEPjack = 0.13). Using this model it is possible to produce long-term quantitative records of past water quality for lacustrine sites across the middle and lower reaches of the Yangtze River, which has important implications for future lake management and eco- logical restoration.
基金Project supported by the Ministry of Science and Technology of China (No. 2003CB415201)National Natural Science Foundation of China (No. 40671120)+1 种基金the International Atomic Energy Agency (Nos. 12322/RO and UK-12094)the Young Scientist Foundation of Sichuan Province (No.06ZQ026-030)
文摘Purple soils are widely distributed in the Sichuan Hilly Basin and are highly susceptible to erosion, especially on the cultivated slopes. Quantitative assessment of the erosion rates is, however, difficult due to small size of the plots of the manually-tilled land, the complex land use, and steep hillslopes. ^137Cs and ^210Pbex （excess ^210Pb） tracing techniques were used to investigate the spatial pattern of soil erosion rates associated with slope-land under hoe tillage in Neijiang of the Sichuan Hilly Basin. The ^137Cs and ^210Pbex inventories at the top of the cultivated slope were extremely low, and the highest inventories were found at the bottom of the cultivated slope. By combining the erosion rates estimates provided by both ^137Cs and 21~Pbex measurements, the weighted mean net soil loss from the study slope was estimated to be 3 100 t km^-2 year^-1, which was significantly less than 6 930 t km^-2 year^-1 reported for runoff plots on a 10° cultivated slope at the Suining Station of Soil Erosion. The spatial pattern of soil erosion rates on the steep agricultural land showed that hoe tillage played an important role in soil redistribution along the slope. Also, traditional farming practices had a significant role in reducing soil loss, leading to a lower net erosion rate for the field.
文摘The purpose of this article was to analyze data associated with advances in wind energy across the United States. While governments, academia, and the private sector generally know patterns of wind turbine development (</span><i><span style="font-family:Verdana;">i.e.</span></i><span style="font-family:Verdana;"> turbine size and capacity growing in recent years), there is no known independent, reliable, and/or updated summary of these variables. Using data collected by the Lawrence Berkeley National Laboratory and partners, this study used descriptive statistics to show turbine development and growth patterns from </span><span style="font-family:Verdana;">1981-2019. The newly created United States Wind Turbine Database (USWTDB</span><span style="font-family:Verdana;">) represents the most comprehensive account of wind turbine information and was updated in January 2020. Variables I am interested in here are turbine manufacturer, state of project, turbine and project capacity, and turbine size. Findings provide empirical evidence to support the common, yet previously unrefined statements that wind turbines are growing larger in number, size and capacity. This growth is varied over spatial and temporal scales. I also provide evidence to show patterns of turbine manufacturing, with GE Wind dominating much of the US wind energy landscape today. I hope this work provides a timely resource for those interested in a variety of questions surrounding wind energy development in the United States. Perhaps more importantly, this analysis will hopefully inspire others to use what the USWTDB provides and answer larger questions surrounding wind energy futures.
文摘As a tool for management, query, visualization and analysis of spatially referred information, GIS has been recognized as a method to aid the modeling of diffuse pollution and visualize the results in a spatial context. A common question in integrating diffuse pollution models and GIS is to choose a suitable coupling approach, in which the feature of diffuse pollution models should be taken into account. In this paper, we report on our experience in coupling a distributed diffuse pollution model with a GIS. A prototype of fully integrated system is developed in this paper. This system has high flexibility, extendibility and great data management efficiency. Differences in applicability of loose coupling, tight coupling and fully integrated approaches are addressed. It is concluded that the fully integrated approach can avoid tanglesome data exchange and routine execution and more robust than loose and tight coupling approaches and is suitable for distributed diffuse pollution modes.
基金Supported by the Soil Scientific Interest Group (GIS Sol) of Francefinanced by the "Groupement d'Intrêt Scientifique Sol". Jeroen Meersmans' postdoctoral position was funded by the French Environment and Energy Management Agency (ADEME)funded by the EU projects "Greenhouse gas management in European land use systems (GHG-Europe)" (FP7-ENV-2009-1-244122) and "CARBO-Extreme" (FP7-ENV-2008-1-226701)
文摘Development of a quantitative understanding of soil organic carbon （SOC） dynamics is vital for management of soil to sequester carbon （C） and maintain fertility, thereby contributing to food security and climate change mitigation. There are well-established process-based models that can be used to simulate SOC stock evolution; however, there are few plant residue C input values and those that exist represent a limited range of environments. This limitation in a fundamental model component （i.e., C input） constrains the reliability of current SOC stock simulations. This study aimed to estimate crop-specific and environment-specific plant-derived soil C input values for agricultural sites in France based on data from 700 sites selected from a recently established French soil monitoring network （the RMQS database）. Measured SOC stock values from this large scale soil database were used to constrain an inverse RothC modelling approach to derive estimated C input values consistent with the stocks. This approach allowed us to estimate significant crop-specific C input values （P 〈 0.05） for 14 out of 17 crop types in the range from 1.84 =h 0.69 t C ha-1 year-1 （silage corn） to 5.15 =k 0.12 t C ha-1 year-1 （grassland/pasture）. Furthermore, the incorporation of climate variables improved the predictions. C input of 4 crop types could be predicted as a function of temperature and 8 as a function of precipitation. This study offered an approach to meet the urgent need for crop-specific and environment-specific C input values in order to improve the reliability of SOC stock prediction.
