Permafrost plays a critical role in soil hydrology. Thus, the degradation of permafrost under warming climate conditions may affect the alpine grassland ecosystem on the Qinghai-Tibetan Plateau. Previous space-for-time studies using plot and basin scales have reached contradictory conclusions. In this study, we applied a process-based ecosystem model (DOS-TEM) with a state-of-the-art permafrost hydrology scheme to examine this issue. Our results showed that 1) the DOS-TEM model could properly simulate the responses of soil thermal and hydrological dynamics and of ecosystem dynamics to climate warming and spatial differences in precipitation; 2) the simulated results were consistent with plot-scale studies showing that warming caused an increase in maximum unfrozen thickness, a reduction in vegetation and soil carbon pools as a whole, and decreases in soil water content, net primary production, and heterotrophic respiration; and 3) the simulated results were also consistent with basin-scale studies showing that the ecosystem responses to warming were different in regions with different combinations of water and energy constraints. Permafrost prevents water from draining into water reservoirs. However, the degradation of permafrost in response to warming is a long-term process that also enhances evapotranspiration. Thus, the degradation of the alpine grassland ecosystem on the Qinghai-Tibetan Plateau (releasing carbon) cannot be mainly attributed to the disappearing waterproofing function of permafrost.
[1] Soil surface temperature is a critical boundary condition for the simulation of soil temperature by environmental models. It is influenced by atmospheric and soil conditions and by vegetation cover. In sophisticated land surface models, it is simulated iteratively by solving surface energy budget equations. In ecosystem, permafrost, and hydrology models, the consideration of soil surface temperature is generally simple. In this study, we developed a methodology for representing the effects of vegetation cover and atmospheric factors on the estimation of soil surface temperature for alpine grassland ecosystems on the QinghaiTibetan Plateau. Our approach integrated measurements from meteorological stations with simulations from a sophisticated land surface model to develop an equation set for estimating soil surface temperature. After implementing this equation set into an ecosystem model and evaluating the performance of the ecosystem model in simulating soil temperature at different depths in the soil profile, we applied the model to simulate interactions among vegetation cover, freeze-thaw cycles, and soil erosion to demonstrate potential applications made possible through the implementation of the methodology developed in this study. Results showed that (1) to properly estimate daily soil surface temperature, algorithms should use air temperature, downward solar radiation, and vegetation cover as independent variables; (2) the equation set developed in this study performed better than soil surface temperature algorithms used in other models; and (3) the ecosystem model performed well in simulating soil temperature throughout the soil profile using the equation set developed in this study. Our application of the model indicates that the representation in ecosystem models of the effects of vegetation cover on the simulation of soil thermal dynamics has the potential to substantially improve our understanding of the vulnerability of alpine grassland ecosystems to changes in climate and grazing regimes.Citation: Yi, S., N. Li, B. Xiang, X. Wang, B. Ye, and A. D. McGuire (2013), Representing the effects of alpine grassland vegetation cover on the simulation of soil thermal dynamics by ecosystem models applied to the Qinghai-Tibetan Plateau,
This paper describes the use of the Chinese Gaofen-1 (GF-1) satellite imagery to automatically extract tertiary Linear Archaeological Traces of Tuntian Irrigation Canals (LATTICs) located in the Miran site. The site is adjacent to the ancient Loulan Kingdom at the eastern margin of the Taklimakan Desert in western China. GF-1 data were processed following atmospheric and geometric correction, and spectral analyses were carried out for multispectral data. The low values produced by spectral separability index (SSI) indicate that it is difficult to distinguish buried tertiary LATTICs from similar backgrounds using spectral signatures. Thus, based on the textual characteristics of high-resolution GF-1 panchromatic data, this paper proposes an automatic approach that combines joint morphological bottom and hat transformation with a Canny edge operator. The operator was improved by adding stages of geometric filtering and gradient vector direction analysis. Finally, the detected edges of tertiary LATTICs were extracted using the GIS-based draw tool and converted into shapefiles for archaeological mapping within a GIS environment. The proposed automatic approach was verified with an average accuracy of 95.76% for 754 tertiary LATTICs in the entire Miran site and compared with previous manual interpretation results. The results indicate that GF-1 VHR PAN imagery can successfully uncover the ancient tuntian agricultural landscape. Moreover, the proposed method can be generalized and applied to extract linear archaeological traces such as soil and crop marks in other geographic locations.
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