基于集合建模思想,在水体光谱特征分析与敏感波段选择基础上,集成多种遥感反演模型优势,构建了河流水体浊度多光谱遥感联合反演模型(Combined Model-BP,CM-BP)。选择汉江中下游典型河段为研究区,利用2012—2013年原位观测数据,以具有较高时间分辨率和空间分辨率的国产卫星数据作为多光谱遥感数据源,测试评估了CM-BP浊度遥感反演模型适用性,并与传统波段组合模型进行精度比较,基于反演结果分析了研究区浊度时空分布特征。结果表明:基于集合建模思想构建的CM-BP模型的反演精度、适应性及稳定性均高于波段组合模型;从光谱分辨率、时空分辨率等角度考虑,环境与灾害监测预报小卫星星座系统、高分一号卫星、资源三号等国产卫星多光谱遥感数据是河流水体水质反演优选数据源;国产卫星遥感数据可以满足河流水体水质高精度、实时性与大尺度等遥感反演需要,为河流水环境监测研究提供数据基础。

Inspired by combined modeling idea, we constructed a CM-BP (Combined Model-Back Propagation) for multispectral remote-sensing retrieval of river water turbidity by integrating the advantages of multiple remote-sensing retrieval models based on analyzing spectral characteristics of water bodies and selecting sensitive bands. With the in-situ observation data in 2012-2013 in typical reaches of the middle and lower Hanjiang River as a case study, we tested and assessed the applicability of the proposed CM-BP with domestic satellite data of high temporal and spatial resolutions as multispectral remote-sensing data sources. Furthermore, we compared the proposed CM-BP with traditional band-combined models in terms of retrieval precision, and meanwhile dissected the temporal and spatial distribution characteristics of the turbidity of Hanjiang River based on retrieval results. Results demonstrated that CM-BP boasts higher retrieval accuracy, applicability and stability than band-combined models. From the perspectives of spectral, temporal and spatial resolutions, multispectral remote-sensing data of Chinese domestic satellites like environment and disaster monitoring and forecasting small-satellite constellation, GF-1, and ZY-3 can be considered as optimal data sources for water quality retrieval of river. Remote-sensing data from Chinese domestic satellites meets the demand in high-accuracy, real-time and large-scale of remote-sensing retrieval of river water quality, thus providing a data basis for environmental monitoring studies of river.

湖泊水位是影响湖泊生态系统以及植被分布格局的重要因素，湖泊水位的异常波动通常是导致湖泊生态系统退化与失稳的主要控制因子。以梁子湖为研究对象，基于对研究区1981-2000年近20年降水量与湖泊水位数据的统计分析、频率分析、以及对应时期Landsat遥感影像数据解译与植被覆盖度估算，通过对丰水年、平水年与枯水年湖泊水位变化特征与湖岸植被分布格局的探讨，分析梁子湖水位波动对湖岸植被分布格局的影响及对应关系。结果显示：①梁子湖水位自然波动遵循春季低水位、夏季高水位的节律，春季枯水期平均水位为17.50 m，夏季丰水期平均水位为18.50 m；②年内丰水期高植被覆盖度（>60%）区域面积明显大于枯水期；③丰水年、平水年和枯水年的代表年份1983年、1992年与2000年枯水期湖水位分别为17.09、17.47以及17.50 m，与多年平均水位相同的2000年高植被覆盖度区域面积最大，表明春季湖水位保持在多年平均水位更有利于湖岸带植被萌发与生长；④1983年、1992年与2000年丰水期湖水位分别为20.71、19.15和16.73 m，高植被覆盖度区域面积表现为2000年>1992年>1983年，表明2000年夏季水位的异常降低，导致湖岸带扩张，湖泊水生植物疯长，植被覆盖度显著升高，可能引发水体生态失衡。由此可见，保护与维持河湖水位自然波动的节律是河湖生态系统保护的关键。

Lake water level is an important factor affecting the lake ecosystem and vegetation distribution pattern, and the abnormal fluctuation of lake water level is usually the main control factor leading to the instability and degradation of lake ecosystem. Based on the hydrological data and Landsat remote sensing data in recent 20 years from 1981 to 2000 in the Liangzi Lake, this study intended to revel the influence of water level fluctuations on vegetation distribution pattern of lake zone of the Liangzi Lake, through the discussion on the variation characteristics of lake water level and the distribution pattern of lake vegetation in the high, normal, and low flow years, by using statistical analysis, frequency analysis, remote sensing interpretation and vegetation coverage estimation. The results showed that: ①the natural fluctuation of water level in Liangzi Lake follows the rhythm of low water level in spring and high-water level in summer. The average water level in dry season of spring is 17.50 m and the average water level in wet season of summer is 18.50 m. ② The area of high vegetation coverage (>60%) in wet season was significantly larger than that in dry season. ③ The water levels in the high (1983), normal (1992), and low flow year (2000) were 17.09, 17.47 and 17.50 m respectively in the dry season, and the area of high vegetation coverage in 2000 with the same average water level was the largest. This indicates that maintaining the lake water level at the multi-year average water level in spring is more conducive to the germination and growth of vegetation lakeshore. ④ The lake water levels in 1983, 1992 and 2000 were 20.71, 19.15 and 16.73 m respectively in the wet season, with the area of high vegetation coverage showed 2000 > 1992 > 1983. It indicates that the abnormal decrease of water level during the wet season in 2000 summer led to the expansion of lakeshore zone and rapid growth of submerged plants in the lake. The significant increase of vegetation coverage may result in ecological imbalance of water. Therefore, protecting and maintaining the rhythm of natural fluctuation of lake water level is the key to river and lake ecosystem protection.