Haiming Yan

Systematic Modeling of Impacts of Land Use and Land Cover Changes on Regional Climate: A Review

There have been tremendous changes in the global land use pattern in the past 50 years, which has directly or indirectly exerted significant influence on the global climate change. Quantitative analysis for the impacts of land use and land cover changes (LUCC) on surface climate is one of the core scientific issues to quantitatively analyze the impacts of LUCC on the climate so as to scientifically understand the influence of human activities on the climate change. This paper comprehensively analyzed the primary scientific issues about the impacts of LUCC on the regional climate and reviewed the progress in relevant researches. Firstly, it introduced the influence mechanism of LUCC on the regional climate and reviewed the progress in the researches on the biogeophysical process and biogeochemical process. Then the model simulation of effects of LUCC on the regional climate was introduced, and the development from the global climate model to the regional climate model and the integration of the improved land surface model and the regional climate model were reviewed in detail. Finally, this paper discussed the application of the regional climate models in the development and management of agricultural land and urban land.

Evaluation of the Impacts of Land Use on Water Quality: A Case Study in The Chaohu Lake Basin

It has been widely accepted that there is a close relationship between the land use type and water quality. There have been some researches on this relationship from the perspective of the spatial configuration of land use in recent years. This study aims to analyze the influence of various land use types on the water quality within the Chaohu Lake Basin based on the water quality monitoring data and RS data from 2000 to 2008, with the small watershed as the basic unit of analysis. The results indicated that there was significant negative correlation between forest land and grassland and the water pollution, and the built-up area had negative impacts on the water quality, while the influence of the cultivated land on the water quality was very complex. Besides, the impacts of the landscape diversity on the indicators of water quality within the watershed were also analyzed, the result of which indicated there was a significant negative relationship between them. The results can provide important scientific reference for the local land use optimization and water pollution control and guidance for the formulation of policies to coordinate the exploitation and protection of the water resource.

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.

Scenario-Based Impact Assessment of Land Use/Cover and Climate Changes on Watershed Hydrology in Heihe River Basin of Northwest China

This study evaluated hydrological impacts of potential climate and land use changes in Heihe River Basin of Northwest China. The future climate data for the simulation with Soil and Water Assessment Tool (SWAT) were prepared using a dynamical downscaling method. The future land uses were simulated with the Dynamic Land Use System (DLS) model by establishing Multinomial Logistic Regression (MNL) model for six land use types. In 2006–2030, land uses in the basin will experience a significant change with a prominent increase in urban areas, a moderate increase in grassland, and a great decrease in unused land. Besides, the simulation results showed that in comparison to those during 1981–2005 the temperature and precipitation during 2006–2030 will change by

Prediction of Drought Risk Based on the WRF Model in Yunnan Province of China

Yunnan province is the core region of the drought in the Southwest China, which makes the region become the hot spot in the meteorological research. However, among the various influencing factors of the drought in Yunnan province, the influence of the land use/cover change (LUCC) on the drought has not been quantitatively analyzed. The LUCC in recent decades was first quantitatively analyzed in this study. Given the fact that severe drought in Yunnan province is mainly due to much-less-than-normal precipitation and much-warmer-than-normal surface temperature, this study focused on the future spatiotemporal heterogeneity of the temperature and precipitation, which have great impacts on the drought. Finally, the influencing factors of drought in Yunnan province were simulated with the Weather Research and Forecasting (WRF) model, and the risk of drought was spatially analyzed with the meteorological drought composite index. The results indicate that the large-area forest plays a more important role in alleviating the risk of drought than other vegetation types do. Besides, the changes of the landscape structure resulting from the urban expansion play a significant role in intensifying the risk of drought.

Impacts of Land Cover Change on the Near-Surface Temperature in the North China Plain

This study first tested and verified the ability of the Weather Research and Forecasting (WRF) model to simulate the near-surface temperature in the North China Plain. Then the static land cover data in the WRF were replaced, and thereafter the modified WRF model was used to explore the impacts of land cover change on the near-surface temperature in the North China Plain in year 1992 and year 2005. The results indicated that the land cover change in the North China Plain, which was characterized by the regional urbanization, had led to significant changes in the near-surface temperature, increasing the regional near-surface temperature by 0.03°C/year on average. The spatial pattern of the climate change basically corresponded to that of the land cover change; for example, the temperature increased most significantly in the regions mainly consisting of cities and built-up area. Besides, there were some variations in the degree and range of influence of the land cover change on the temperature among seasons. The result can provide important theoretical support for the adaptation to climate change, scientific land cover change management, and land use planning.

Possible Influence of the Cultivated Land Reclamation on Surface Climate in India: A WRF Model Based Simulation

Land use/cover change (LUCC) has become one of the most important factors for the global climate change. As one of the major types of LUCC, cultivated land reclamation also has impacts on regional climate change. Most of the previous studies focused on the correlation and simulation analysis of historical LUCC and climate change, with few explorations for the impacts of future LUCC on regional climate, especially impacts of the cultivated land reclamation. This study used the Weather Research and Forecasting (WRF) model to forecast the changes of energy flux and temperature based on the future cultivated land reclamation in India and then analyzed the impacts of cultivated land reclamation on climate change. The results show that cultivated land reclamation will lead to a large amount of land conversions, which will overall result in the increase in latent heat flux of regional surface as well as the decrease in sensible heat flux and further lead to changes of regional average temperature. Furthermore, the impact on climate change is seasonally different. The cultivated land reclamation mainly leads to a temperature decrease in the summer, while it leads to a temperature increase in the winter.

Land-Use-Oriented Conservation of Ecosystem Services

Ecosystem services suffer from both the human intervention, such as land-use zoning change, and the natural intervention, such as climate change. In this chapter, we first conducted land-use zoning for conserving ecosystem services in the middle reaches of the Heihe River Basin (HRB). Under the background of climate change, regulation services of ecosystem could be strengthened under proper land-use zoning policy to mitigate climate change. We conducted a case study in the middle reaches of the HRB to assess the ecosystem service conservation zoning under the change of land use associated with climate variations. The results show the spatial impact of land-use zoning on ecosystem services in the study area which are significant reference for the spatial optimization of land-use zoning in preserving the key ecosystem services to mitigate climate change. The research contributes to the growing literature in finely characterizing the ecosystem service zones altered by land-use change to alleviate the impact of climate change, as there is no such systematic ecosystem zoning method before. Further, we introduced ecosystem-based adaptation measures for climate change in Qinghai Province. The change of land surface can exert significant influence on the future climate change. We analyzed the effects of herdsmen’s adaptation to climate change on the livestock breeding, income, and land surface dynamics with a land surface parameterization scheme. The empirical analysis was first carried out on the impacts of the adaptation measures of herdsmen on their income in the context of the climate change with the positive mathematical programming (PMP) model on the basis of the household survey data in the Three-River Source Region, an ecologically fragile area in Qinghai Province, China. Then, the land surface parameterization process is analyzed based on the agent-based model (ABM), which involves the herdsmen’s adaptation measures on climate change, and it also provides reference for the land surface change projection. The result shows that the climate change adaptation measures will have a positive effect on increasing the amount of herdsman’s livestock and income as well as future land surface dynamics. Some suggestions on the land-use management were finally proposed, which can provide significant reference information for the land-use planning. Finally, we introduced how to build resilience to climate change for conserving ecosystem servers. The ecosystem resilience plays a key role in maintaining a steady flow of ecosystem services and enables quick and flexible responses to climate change, and maintaining or restoring the ecosystem resilience of forests is a necessary societal adaptation to climate change; however, there is a great lack of spatially explicit ecosystem resilience assessments. Drawing on principles of the ecosystem resilience highlighted in the literature, we built on the theory of dissipative structures to develop a conceptual model of the ecosystem resilience of forests. A hierarchical indicator system was designed with the influencing factors of the forest ecosystem resilience, including the stand conditions and the ecological memory, which were further disaggregated into specific indicators. Furthermore, indicator weights were determined with the analytic hierarchy process (AHP) and the coefficient of variation method. Based on the remote sensing data, forest inventory data, so forth, the resilience index of forests was calculated. The result suggests that there is a significant spatial heterogeneity of the ecosystem resilience of forests, indicating it is feasible to generate large-scale ecosystem resilience maps with this assessment model, and the results can provide a scientific basis for the conservation of forests, which is of great significance to the climate change mitigation.