| Various ecosystems on the surface of the earth are organically complex. Meanwhile, land-surface process(including eco-hydrology and other processes) is closely relevant to human life. As part of the earth system, closely related land-surface, atmosphere, oceans, and other systems interact with one other. In recent years, hydrological and land-surface modes have been utilized to describe quantitatively the active role of changes in land-surface processes in detailed studies on land-surface components. However, the uncertainty of various atmosphere drive datasets and modes has led to huge errors and ambiguous factors of the final output.To reduce the uncertainty of land-surface and hydrological mode outputs and to quantitatively describe the change process of the earth surface components at a regional scale, the purposes of this study are as follows. First, data assimilation and fusion as well as other means are utilized to reduce the uncertainty of the atmosphere-driving field and establis h the Xinjiang-oriented 1 km land-surface mode atmosphere driving datasets with high-resolution ratio and reliable quality. Second, computer programming and quality control methods are used, and the China Meteorological Administration Data Assimilation System(CLDAS) is introduced to establish grid-driving datasets that can directly direct various hydrological modes. The above two aspects lay a solid foundation for reducing the uncertainty of the atmosphere input of land-surface and hydrological modes to the maximum level. Moreover, this study utilizes the above atmospheric driving fields to drive the CLM and SWAT modes and precisely validates various components of the Xinjiang surface process. In addition, this study focuses on key verification and analysis of surface components in the Jing and Bo River Basins with fragile ecology, and establis hes land-surface component datasets in the said areas as well as in Xinjiang.Based on the above research objectives, detailed expected results and possible innovations are as follows.(1) The multiple-grid variation assimilation system, Space and Time Mesoscale Analysis System(STMAS), is based on the Earth System Science Research Laboratory of America National Oceanic and Atmospheric Administration. STMAS assimilates and fuses relevant multi-source atmospheric data and establishes the 1 km atmospheric driving field in Xinjiang as well as carries out localization c hecks on this driving field.Data fusion and assimilation techniques are utilized to fuse satellite observation, surface observation, products of numerical models, and other multivariate data of multi-channel sources and multi- resolution data. LAPS/STMAS system fusions are combined to establish the Xinjiang 1 km high-precision atmospheric forcing field(XJLDAS), considering factors of temperature, pressure, humidity, and wind speed. Moreover, data from National Automatic Meteorological Station(105 stations in Xinjiang) are used for the validation and evaluation of various indexes of assimilation results, such as deviation and root- mean-square error. Upon evaluating the assimilated mode-driving field data, the result of the driving data can well reflect the true conditions of the relevant surface meteorological factors. The establishment of this driving field provides better input data for various surface components of land-surface mode simulation in the later stage of this study.(2) Based on nested loop, bilinear interpolation, and various computer coding methods, the SWAT model is established, whose directly callable grid meteorological datasets(CMADS) can make up for the incomplete data obtained by traditional meteorological stations. The model lays a solid foundation for the study of high-resolution atmosphere dataset-driven and complicated hydrological model in C hina.This study selected the CLDAS data assimilation system of C hina Meteorological Administration and nested loop. Various optimized interpola tion algorithms are utilized to analyze various factors in CLDAS 2.0 data assimilation system(average temperature, average pressure, specific humidity, average wind speed, precipitation and solar radiation, and resolution ratio per hour). The analysis is based on grid point extraction, factor type conversion, format conversion, and other steps. Finally, the SWAT model and meteorological datasets are established, which can be directly driven by various hydrological modes(maximum and minimum temperature, average pressure, relative humidity, average wind speed, precipitation and solar radiation, and resolution ratio per day). We predict that this dataset can greatly improve the simulation precision of hydrological modes in China, especially in the western region, which lacks stations.(3) The land-surface mode atmospheric drive dataset established in the earlier stage and the CMADS grid dataset are used to drive the internationally and widely used CLM3.5 land-surface mode and SWAT mode, respectively. These met hods are used to analyze the mode output influence results of the two improved driving fields mentioned above and can further verify the necessity and importance of atmospheric data improvement.The Xinjiang Land Data Assimilated Datasets(XJLDAS) establis hed in this study adopts the international CLM3.5 model for validation and evaluation analyses on various relevant earth surface components in the research area. Moreover, the CMADS grid dataset is utilized to drive SWAT mode for simulation verification on relevant hydrological and land-surface components in the Xinjiang, Jing and Bo River Basins.(4) A multi-drive to multi- mode system can be created based on the Jing and Bo River Basin land-surface process component simulation system as well as the Jing and Bo River Basin land-surface process component datasets(2009–2013).Improved driving field is used to drive the multi- mode(XJLDAS+CLM3.5 and CMADS+SWAT) system to construct the Xinjiang, Jing and Bo River Basin land-surface process component simulation system. The Xinjiang, Jing and Bo River Basin land-surface process datasets are created based on the multi- mode set results. By analyzing various land-surface process components in the dataset(evapotranspiration, runoff, snow, and soil humidity), the characteristics of land-surface process components in the research area are analyzed in detail.(5)Study on the climate and hydrological changes in Jing and Bo River Basin based on the traditional observation station and CMADS.The land surface hydrological model and other simulation is important. However, it is necessary to research the climate and hydrological changes based on climate change and human activities. This analysis may clarify the temporal and spatial variation of the precipitation, temperature and runoff in Jing Bo River Basin, and can explain the model output at the same time. |
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