International Society for Environmental Information Sciences 2010 Annual Conference (ISEIS) Scenario simulation of change of forest land in Poyang Lake watershed

AbstractForest land is the largest carbon storage of the terrestrial ecosystem for its giant biomass and plays a very important and irreplaceable role in mitigating and adapting to the global climate change. Much attention has been paid to its function and role in alleviating and adapting to the global climate change, Poyang Lake watershed as one of the most important wetland nature reserve in the world is also one of the regions where forest land is most densely distributed in China. The authors have studied the spatial dynamics of the forest land in this region during the past 20 years based on panel data of four periods (1988, 1995, 2000, 2005), and comprehensively characterized its changing patterns under the macroscopic context of rapid economic growth, social change and technical progress. A simultaneous equations model was established and the significance ranking of various factors was obtained in order to analyze the driving mechanism of the spatial-temporal process of the forest land. Three scenarios, i.e. economic priority, ecologic conservation and constant scenarios were designed according to the driving mechanism and trends of economic, policy and technical progress. The module functions of Dynamic of Land System (DLS) were employed and extended to develop possible scenarios of spatial-temporal explicit expression of the forest land

Impacts of economic development on ecosystem risk in the Yellow River Delta

AbstractWith the economic development and population growth, humans have changed ecosystems more rapidly and extensively to meet the rapidly growing demand for food, fresh water, timber, fiber and fuel. This has led to a substantial and largely irreversible loss of the biodiversity on earth. The ecosystem risk is created as a new concept to understand the environmental problems. Therefore, it is important to develop quantitative methods for regional ecosystem risk analysis. Yellow River Delta is the widest, most intact and youngest delta both in China and in the world; its ecosystem environment is much more vulnerable due to its special location and industrial structure. Therefore, it is very important to manage them wisely and strategically. Therefore, Yellow River Delta is selected as the case area to reveal the impacts of economic development on ecosystem risk in this study. This study selected the ecological quality index to show the potential ecosystem risk and estimated the impacts of economic development on ecosystem risk using the panel data model on the pixel level based on the GIS, RS technique. It's found that the economic development will have impacts on the ecological environment to a certain degree, however, these impacts can exchange to a greater degree with the development. Then more funds and advanced technologies can be used to promote the intensive development of land use, which may decrease the impacts of economic development on the environment. Therefore, we need to ensure the coordinated development of the economy and ecological environment. The research results provide meaningful decision-making information for the urbanization process and environmental protection in the Yellow River Delta

Scenario Analyses of Land Use Conversion in the North China Plain: An Econometric Approach

Scenario analysis and dynamic prediction of land use structure which involve many driving factors are helpful to investigate the mechanism of land use changes and even to optimize land use allocation for sustainable development. In this study, land use structure changes during 1988–2010 in North China Plain were discerned and the effects of various natural and socioeconomic driving factors on land use structure changes were quantitatively analyzed based on an econometric model. The key drivers of land use structure changes in the model are county-level net returns of land resource. In this research, we modified the net returns of each land use type for three scenarios, including business as usual (BAU) scenario, rapid economic growth (REG) scenario, and coordinated environmental sustainability (CES) scenario. The simulation results showed that, under different scenarios, future land use structures were different due to the competition among various land use types. The land use structure changes in North China Plain in the 40-year future will experience a transfer from cultivated land to built-up area, an increase of forestry, and decrease of grassland. The research will provide some significant references for land use management and planning in the study area

Possible Biogeophysical Effects of Cultivated Land Conversion in Northeast China in 2010–2030

There will be substantial cultivated land change in China as the society strives to meet the growing food demands, which will greatly influence the future climate. This study analyzed the possible biogeophysical effects of cultivated land change on the climate in Northeast China during 2010–2030 on the basis of simulation with the Weather Research and Forecast (WRF) model. Scenario analysis was first carried out on the possible changing trends of cultivated land. Then the climate effects of the cultivated land change were analyzed on the basis of the simulation with the WRF model. The simulation results indicate that the total cultivated land area in Northeast China will decrease during 2010–2030, mainly converting into urban and built-up land and forests due to the urbanization and governmental policies. Besides, the cultivated land change will lead to the increase of the sensible heat flux in the regions where a lot of cultivated land will change into urban and built-up land, while it will make the latent heat flux increase in the regions where the cultivated land will be mainly converted into forests through influencing the evapotranspiration. All these results can provide theoretical support for implementing the future land management in Northeast China

Examination of the Quantitative Relationship between Vegetation Canopy Height and LAI

Accurate estimation of vegetation biophysical variables such as the vegetation canopy height (H) is of great importance to the applications of the land surface models. It is difficult to obtain the data of H at the regional scale or larger scale, but the remote sensing provides the most useful and most effective method. The leaf area index (LAI) is closely related to the H, and we analyzed its relationship with the correlation analysis based on the dataset at 86 site-years of field measurements from sites worldwide in this study. The result indicates that there is significant positive exponent correlation between these two parameters and the change of LAI would exert great impacts on H. The higher the LAI is, the higher the H is, and vice versa. Besides, the coefficients of different land cover types are very heterogeneous, and LAI of the needleleaf forest shows strong correlation with H, while that of the cropland shows weak correlation with H. The results may provide certain reference information for the extraction of the data of H at the regional scale with the remote sensing data

Seasonal and Interannual Variation in Energy Balance in the Semiarid Grassland Area of China

Near surface energy budget changes have been proved to be induced by the land cover conversion through changing the surface physical properties, which can further impact the regional climate change. This study applies the DLS model to simulate the land cover under the business as usual (BAU) scenario and then analyses the seasonal and interannual variation of energy balance in the semiarid grassland area of China based on the simulated land cover with the Weather Research and Forecasting (WRF) model. The results indicate that the grassland will show a growing trend under the BAU scenario. Downward long wave radiation and downward short wave radiation will all have small-scale increase with time going by, while the surface net radiation will decrease from 2030 to 2050. However, there is obvious seasonal variation. Summer has the highest downward long wave radiation and downward short wave radiation, followed by spring and autumn. The lowest are in winter. As for the net surface radiation, there is obvious decrease in southeast of study area due to returning cropland to grassland. Those research conclusions can offer valuable information for the land use planning and relieving the effects of land cover change on climate change at the semiarid grassland area

Analysis of the Temporal and Spatial Distribution of Lake and Reservoir Water Quality in China and Changes in Its Relationship with GDP from 2005 to 2010

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Land Cover Mapping Based on Multisource Spatial Data Mining Approach for Climate Simulation: A Case Study in the Farming-Pastoral Ecotone of North China

The land use and land cover change (LUCC) is one of the prime driving forces of climate change. Most attention has been paid to the influence of accuracy of the land cover data in numerous climate simulation projects. The accuracy of the temporal land use data from Chinese Academy of Sciences (CAS) is higher than 90%, but the high-precision land cover data is absent. We overlaid land cover maps from different sources, and the grids with consistent classification were selected as the sample grids. By comparing the results obtained with different decision tree classifiers with the WEKA toolkit for data mining, it was found that the C4.5 algorithm was more suitable for converting land use data of CAS classification to land cover data of IGBP classification. We reset the decision rules with Net Primary Productivity (NPP) and Normalized Difference Vegetation Index (NDVI) as the indicators. The accuracy of the reclassified land cover data was proven to reach 83.14% through comparing with the Terrestrial Ecosystem Monitoring Sites and high resolution images. Therefore, it is feasible to produce the temporal land cover data with this method, which can be used as the parameters of dynamical downscaling in the regional climate simulation

Impacts of Vegetation Change on the Regional Surface Climate: A Scenario-Based Analysis of Afforestation in Jiangxi Province, China

The afforestation is one of the most noticeable human activities that affect the climate through influencing not only the carbon sink but also the thermal properties of the land surface. This research accessed the potential effects of artificial vegetation change on the regional climate in Jiangxi Province, China. Based on simulation with the Weather Research and Forecasting (WRF) model, a comparative analysis was carried out on the future temperature and precipitation under four hypothetical vegetation cover scenarios. The simulation results indicated that the vegetation change would have significant effects on the regional climate. The simulated effects of annual average temperature showed a decreasing order: evergreen broadleaf > evergreen needleleaf > deciduous needleleaf > deciduous broadleaf, and the effects of annual average precipitation of the evergreen forests would be bigger than those of the deciduous forests. The deciduous forests play a positive role in decreasing the annual average temperature, while the evergreen forests promote the annual average temperature rise. Besides, the expansion of deciduous forests may result in severe drought in the summer in Jiangxi Province. These conclusions are of important policy implication to the future afforestation in Jiangxi Province, China, and other regions of the world