Subjects: Geosciences >> Geography submitted time 2023-04-07 Cooperative journals: 《干旱区地理》
Abstract： Accurate monitoring of runoff from small and medium-sized rivers is of great significance for ecological stability in arid areas. However, it is difficult to accurately retrieve the flow of small and medium-sized rivers by remote sensing. Taking the Zhongfengchang river section of Kashi River in Nilka County, Xinjiang, China, as an example, this study constructed a power function relationship model between river width, water depth, and discharge based on the relationship fitting method and measured hydrological data, unmanned aerial vehicle data, and satellite data. Using the time series of satellite data, the runoff volume of the monitored river section was inferred 24 times in different periods. The results show that when the runoff rate is 0-50 m3 ·s −1 and 50-100 m3 ·s −1 , the inversion of the runoff rate based on the hydraulic geometry of the river width is optimal, with root mean square errors (RMSEs) of 7.15 m3 ·s −1 and 2.81 m3 ·s −1 , respectively; when the runoff rate is 100-200 m3 ·s −1 and > 200 m3 ·s −1 , the inversion of the hydraulic geometry based on water depth and river width is the best, with RMSEs of 13.37 m3 ·s−1 and 1.06 m3 ·s−1 , respectively. These findings provide a new method for the fine monitoring and management of runoff of small and medium-sized rivers in areas lacking hydrologic data and have high reference value for flood disaster prediction, hydropower resource development, and water ecosystem restoration.
Subjects: Geosciences >> Hydrology submitted time 2023-03-14 Cooperative journals: 《干旱区地理》
Abstract： Groundwater is important for regulating the water cycle and ecosystem in arid areas. Understanding and managing groundwater resources is the key to preventing the reduction of river baseflow, ground subsidence and water quality degradation. Therefore, this study analyzed the groundwater chemical parameters and hydrogenoxygen stable isotope characteristics of the Ebinur Lake Basin, Xinjiang, China, and explored the sources of groundwater recharge, dynamic changes of water chemical components in different regions by combining linear regression, two-terminal mixed model and GIS spatial analysis. The results showed that: (1) Different circulation processes of groundwater existed in different areas of the Ebinur Lake Basin, with the largest of hydrogen and oxygen isotopes (δ2 H and δ18O) in the middle and lower reaches of the Bortala and Jing Rivers, followed by the area around Lake Ebinur Basin, and the smallest in the upper Bortala River area. (2) Deuterium excess parameter (d-excess) parameter and hydrochemical composition of groundwater reflected different groundwater recharge mechanisms and influencing factors. Groundwater in the upper Bortala River area was mainly recharged by glacial snow melt water. The main sources of groundwater in the middle and lower reaches of the Bortala and Jing Rivers were surface water and precipitation, which were also greatly influenced by the nature of rock formations, farmland development and irrigation measures. Groundwater around Lake Ebinur Basin mainly came from snow and ice melt and precipitation. The middle and lower reaches and groundwater in the river and lake confluence areas are the key areas for pollution prevention and control and management. (3) Different hydraulic connections existed in underground aquifers. The electrical conductance (EC) of flow system I ranged from 210.00 μS·cm-1 to 2500.00 μS·cm-1 , and the d-excess ranged from 6.47‰ to 9.70‰. The EC of flow system II ranged from 141.60 μS·cm-1 to 5260.00 μS·cm-1 , and the d-excess ranged from 9.61‰ to 17.45‰. In conclusion, this study investigated the driving mechanisms of hydrogen and oxygen isotopes and water chemistry in groundwater in the Lake Ebinur Basin, which provided some theoretical reference for the rational use and scientific development of groundwater resources in the basin.
Subjects: Geosciences >> Geography submitted time 2019-11-15 Cooperative journals: 《干旱区地理》
Abstract：为了探讨既能保留光谱信息又能准确对土壤有机质含量进行快速检测。以新疆南部渭干河—库车绿洲内部73个土壤样点及其对应的高光谱数据为研究对象，采用小波变换与数学变换进行光谱数据预处理，分析各小波分解重构光谱在不同有机质含量与不同土壤类型下光谱曲线差异，通过相关分析确定最大小波分解层并筛选敏感波段，结合灰色关联分析与随机森林预测分类模型对各小波分解特征光谱进行重要性分析，最后基于最优特征光谱建立多元线性预测模型并进行分析。结果表明：（1） 耕作土壤与林地土壤光谱曲线波段相较盐渍土壤和荒漠土壤光谱曲线变化较为平缓，同时在水分吸收波段处，盐渍土壤光谱曲线吸收谷最深。（2） 小波变换分解光谱与土壤有机质含量的相关性随着分解层数增加呈现先减后增趋势，在第6层中，特征光谱曲线与敏感波段数量变化趋于稳定，确定为小波变换最大分解层。（3） 随机森林模型相比灰色关联分析对于各小波分解层因子的筛选符合预期，按照对土壤有机质含量影响从高到低排序为L3-(1/LgR)′、L4-(1/LgR)′、L6-(1/LgR)′、L5-(1/LgR)′、L2-(1/LgR)′、L0-1/LgR、L1-1/LgR。（4）在小波分解光谱中，中频范围特征光谱对干旱区土壤有机质含量的估测能力优于高频与低频范围特征光谱，同时基于L-MC建立的模型精度最高。研究表明：基于机器学习分类方法结合小波分解的土壤光谱有机质含量监测，可以有效的减少噪声波段干扰，并提高特征波段的分类预测精度。
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