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Climate changes and vegetation conditions are key factors affecting the hydrothermal processes of frozen soil in the Qinghai–Tibet Plateau. Due to the complex relationship between climate factors, vegetation conditions and hydrothermal processes, few studies analyze the individual influences of climate changes and vegetation conditions on hydrothermal processes. Compared to changes in climate, it is easier to control other influential factors of vegetation change, especially human activities. Thus, it is necessary to analyze the possible influence of vegetation change on hydrothermal processes in specific climate conditions; this analysis could provide technical support to inform future human activities on frozen soil. This study uses a vertical hydrothermal process model, the SHAW model, based on meteorological and soil observation data from 2020 to 2021, to model the influence of vegetation changes on the soil temperature and moisture simulations at each layer of frozen soil by changing the key input values that represent vegetation conditions from −100% to 100% at 10% intervals. The results show that: (1) the simulated values have a certain credibility since the simulated soil temperature and moisture are basically consistent with the observed values over time; (2) the performance of soil temperature simulations in the deep layer is better than that in the shallow layer, while the performances of both soil temperature and moisture simulations in the warm season are better than those in the cold season; (3) among the LAI, dry biomass and surface albedo, the LAI is the main vegetation factor that affects the soil temperature and moisture simulations of the SHAW model in the frozen soil; (4) both the soil temperature and moisture simulations show declining trends when the LAI decreases by a large extent (larger than 60%) or increases, and show increasing trends when the LAI decreases by a small extent (smaller than 50%); (5) the warm period and the freeze–thaw alternating period are, respectively, the key periods when the soil temperature and moisture are affected by vegetation changes. The results of this study can provide theoretical supports for the prediction of the hydrothermal processes of frozen soil under a changing vegetation environment in the future. [ABSTRACT FROM AUTHOR]

The long-term hydropower generation scheduling (LHGS) is one of the most important problems which aim to obtain a suitable scheme to maximize electrical benefits. In this paper, a gradient based Harmony search algorithm (GHS) is employed on the optimization of the cascade hydropower stations in the Jinsha River. Firstly, the original Harmony search algorithm (HS) is firstly improved by a dynamically adjustment strategy and global pitch adjustment strategy. Then random gradient strategy is adopted to improve the search speed of HS. In case study, the proposed GHS is used to solve the LHGS problem in the Jinsha River. Results show that GHS is effectiveness when dealing with LHGS problems.

Liu, J.; Xu, J.; Chen, J.; Hong, X., and Zhou, M., 2019. Spatio-temporal distribution characteristics of water quality in Miju River and Erhai Lake. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 31–38. Coconut Creek (Florida), ISSN 0749-0208. In the research related to the water resources management and prevention of pollution, it is of great practical significance to analyze the spatial and temporal distribution characteristics of the water quality. The present work deals with the study on the actual water quality monitoring data obtained from the Miju River monitoring sections in the Erhai Lake during 2011-2016. Six water quality indicators were selected for investigation using the comprehensive pollution index method and the principal component analysis method, in order to analyze the spatial and temporal distribution characteristics of water quality in the Miju River Basin. The results of the comprehensive pollution index method showed that the water quality of the Miju River has not changed much in the past 6 years, and the water body has only been slightly polluted. Additionally, the water quality of the Jiangweiqiao section was slightly inferior to that of the Yinqiaocun section. Principal component analysis method showed that the nitrogen pollution was the dominant factor in the wet season, followed by phosphorus, pH and dissolved oxygen. In the normal season, the dissolved oxygen and pH of the water were the main factors, followed by phosphorus and ammonia nitrogen. In the dry season, the dissolved oxygen, ammonia nitrogen and organic matter pollution were the main influencing factors followed by phosphorus and pH. The water quality of the Miju River in the past 3 years was slightly worse than that in the initial 3 years, and the overall performance of the water quality of the Miju River was relatively best during the dry season followed by the normal season, while the water quality was worst during the wet season. Furthermore, the water quality variation trends of Yinqiaocun and the Jiangweiqiao sections were observed to be similar. [ABSTRACT FROM AUTHOR]

In terms of land use zoning, requirements, a semantic similarity measurement model of geographic entity is proposed. Methods for area balance and optimization evaluation are put forward for land use zoning partition results based on a study of the patterns of small polygons; a model of land use zoning was constructed considering semantic similarity. These models are verified in a case study of land use zoning in Haiwei, Changjiang county, Hainan province, China. The results show that the proposed methods provide a reasonable and efficient land use zoning model. Land use zoning schemes produced by these models, not only can reflect human cognitive features but also can summarize land use characteristics, and technically support land use planning and land use regulation and management. [ABSTRACT FROM AUTHOR]