Abstract:

The management of black and odorous water bodies is crucial for improving rural living environments, a key task for rural revitalization, and is a primary target in the battle against rural pollution. The accurate identification of these water bodies is essential for effective management. Spectral reflectance thresholds are widely used to identify rural black and odorous waterbodies. However, these bodies are often covered by duckweed, posing challenges owing to their extensive distribution, difficulty in identification, and heavy task load. From January to October 2023, field surveys were conducted in 10 cities in the Anhui Province: Hefei, Wuhu, Ma’anshan, Huainan, Tongling, Bozhou, Xuancheng, Bengbu, Chuzhou, and Suzhou. For this purpose, 18 high-resolution remote sensing images and 301 water body samples were collected and analyzed. Water quality tests were conducted on the 180 samples. Through remote sensing, field surveys, correlation, and regression analyses, we explored the water quality, characteristics, and environmental impact factors of rural black and odorous water bodies, and their interrelationships. The results indicated the following: 1) Rural black and odorous water bodies are characterized by extensive duckweed coverage, low dissolved oxygen levels, and seasonal odor, and are mainly distributed around residential areas. 2) The ammonia nitrogen concentration and transparency of black and smelly water bodies in rural areas are affected by the environment, making it difficult to accurately reflect water conditions. A low concentration of dissolved oxygen is an obvious feature of duckweed-type black and odorous water bodies. Duckweed coverage significantly affected dissolved oxygen levels, followed by temperature and water circulation, all of which showed negative correlations. 3) In rural areas, when duckweed coverage rate exceeded 80.5% on the water surface from April to August, the predicted dissolved oxygen concentration was below the threshold. The results were validated at 54 points across the three regions of the Anhui Province, yielding an overall water quality verification accuracy of 81.5%. This method, which combines remote sensing to identify the surface features of water bodies with the surrounding environmental conditions, can reflect water quality and aid in identifying black and odorous water bodies. This study provides a valuable reference for the identification and monitoring of rural black and odorous water bodies.

Key words: Anhui Province, rural black and odorous water bodies, remote sensing features, water quality survey, environmental factors, correlation analysis

摘要：

黑臭水体治理是农村人居环境整治的重要内容，准确识别农村黑臭水体是治理的重要前提。目前多采用建立光谱反射率阈值等方法来确定农村黑臭水体，但大量农村黑臭水体表面被浮萍覆盖，面临着范围广、识别难、任务重等难点问题。针对安徽省农村黑臭水体，自2023年1-10月对省内的合肥市、芜湖市、马鞍山市、淮南市、铜陵市、亳州市、宣城市、蚌埠市、滁州市和宿州市共10个市黑臭水体进行实地调查，收集和整理18幅高分辨率遥感数据和301个实地采样水体，其中水质检测180个。通过遥感分析、实地调查、相关性和回归分析，探讨农村黑臭水体的水质、表征和环境影响因素以及它们之间的联系。结果表明，1）农村黑臭水体特征有大量浮萍覆盖、溶解氧浓度低、季节性黑臭，以及主要分布在居民区周边。2）农村黑臭水体氨氮浓度、透明度受环境影响难以准确反映水体情况，溶解氧浓度低为浮萍型黑臭水体的明显特征。浮萍覆盖率对溶解氧浓度影响极大，其次是温度和水体流通性，3个因素均为负相关。3）农村地区房前屋后水体在4-8月水面浮萍覆盖率超过80.5%时，预测水体溶解氧浓度低于阈值。将结果在安徽省3个地区共54个验证点进行水质验证，水质验证的总体准确率为81.5%。该研究可以通过遥感识别水体的表面特征，并结合周边环境来反映其水质情况，从而辅助识别黑臭水体，对于农村黑臭水体识别和监测工作有一定的参考意义。

关键词: 安徽省, 农村黑臭水体, 遥感特征, 水质调查, 环境因素, 相关性分析