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We combine nanophotonics and cold atom research in a new apparatus enabling the delivery of single-atom tweezer arrays in the vicinity of photonic crystal waveguides.

 

Soil erosion by wind has been found to be negatively related to soil water content, as evidenced by that for a given area, such a soil erosion can be much less in a wet than a dry year. However, few studies have examined the functional relationship between wind erosion and soil moisture, primarily due to lack of field measured data. The objectives of this study were to: 1) measure wind erosion in field using a portable wind tunnel devised and made by the authors; and 2) use the measured data to calibrate/validate a wind erosion model previously developed by the authors. The study was conducted in the steppe grassland within the Balaguer watershed located in north China. As part of a larger project funded by National Science Foundation, this study focused on soil conditions with a minimal vegetation coverage to understand the functional relationship between wind erosion, soil moisture, and climate. These conditions are similar with those when the grassland degrades and ultimately becomes deserted. Field samples were analyzed in laboratory to determine the soil characteristics (e.g., moisture content, texture, hydraulic conductivity, and organic content). In this conference, we will present our portable wind tunnel, measured data, and the wind erosion model and its predictions. 

Most of the Eurasian steppe grasslands, including the Balagaer River watershed located in north China, have an arid/semiarid climatic, and thus a vulnerable ecohydrologic, condition. The grass growth in such a region is critical to combat negative eco-environmental issues such as land desertification and the subsequent degradation of pasture productivity. How to predict responses of grass growth to climatic variations and human activities (e.g., grazing) is important for the utilization and protection of steppe grasslands. However, the information of such predictions is yet incomplete in existing literature. Taking the Balagaer River watershed as a test bed, this study parameterized a WOFOST (WOrld FOod STudies) simulation model to predict the potential plant growth as influenced by climate and human. The model is calibrated by manually adjusting various eco-physiological parameters, whose initial values were estimated using existing literature, field experiments, and remote sensing techniques. The soil-water parameters (e.g., porosity and saturated hydraulic conductivity) were determined by analyzing least-disturbed soil samples, while the physiological parameters (e.g., assimilation rate) of the dominant vegetation species of Stipa Grandis and Leymus Chinensis were determined by laboratory analyses of grass samples as well as from literature. The grazing frequency and intensity by sheep, horses, and cows were modeled as possible management scenarios. The model was driven by historical climate data recorded in a past half century at a weather station within the watershed. This study firstly expanded the WOFOST’s application to tracing dynamics of steppe grasses, while its results would likely be used to understand the threshold conditions for possibly irreversible degradation of steppe grasslands. In this presentation, we will highlight our successes, challenges, and solutions in parameterizing such a WOFOST model, and show the simulation results. 

The accelerating degradation of native grasslands is becoming a threat to the world’s biome supply and has raised serious environmental concerns such as desertification and dust storm. Given that the steppe grasslands, such as those located in the Inner Mongolia Plateau of north China, have a dry climatic condition, the grass growth closely relies on available soil water, which in turn depends on precipitation prior to the growing season (in particular from May to July). However, our understanding of steppe hydrology and water consumption by grasses is incomplete. In this study, the agro-hydrologic Soil Water Plant Atmosphere (SWAP) model was used to mimic the long-term variations in soil water and vegetation growth in a typical steppe grassland of north China to further understand how alterations of hydrologic processes are related to grassland degradation. A field experiment was conducted to collect the data needed to set up the model. The SWAP model was calibrated using continuous observations of soil moisture and soil temperature at various depths for a simulation period of 2014 to 2017. The results indicated that the SWAP model can be used to simulate the responses of soil moisture and vegetation growth to climates. Moreover, this study examines the water balance and chronological variations of precipitation, evapotranspiration, soil water, and runoff. This study will add new knowledge of steppe hydrologic processes into existing literature.