安徽省农村黑臭水体特征分析及识别

doi:10.16258/j.cnki.1674-5906.2024.08.010

生态环境学报 ›› 2024, Vol. 33 ›› Issue (8): 1257-1268.DOI: 10.16258/j.cnki.1674-5906.2024.08.010

• 研究论文【环境科学】 • 上一篇下一篇

安徽省农村黑臭水体特征分析及识别

张宝东¹(), 王彪¹^,^*(), 吴艳兰², 孟玉³, 徐升⁴, 钱贞兵⁴, 秦军⁴

1.安徽大学资源与环境工程学院，安徽合肥 230601
2.安徽大学人工智能学院，安徽合肥 230601
3.安徽省城建设计研究总院股份有限公司，安徽合肥 230071
4.安徽省生态环境监测中心，安徽合肥 230011

收稿日期:2024-04-11 出版日期:2024-08-18 发布日期:2024-09-25
通讯作者: *王彪。E-mail: wangbiao-rs@ahu.edu.cn
作者简介:张宝东（2001年生），男，硕士研究生，主要研究方向为资源环境遥感。E-mail: zbdsds@163.com
基金资助:
国家自然科学基金项目(41901282);国家自然科学基金项目(42101381);国家自然科学基金项目(41971311);安徽省自然科学基金项目(2308085MD126);合肥市自然科学基金项目(202323);水利水资源安徽省重点实验室开发研究基金项目(2023SKJ06)

Analysis and Identification of Characteristics of Rural Black and Odorous Water Bodies in Anhui Province

ZHANG Baodong¹(), WANG Biao¹^,^*(), WU Yanlan², MENG Yu³, XU Sheng⁴, QIAN Zhenbing⁴, QIN Jun⁴

1. School of Resources and Environmental Engineering, Anhui University, Hefei 230601, P. R. China
2. School of Artificial Intelligence, Anhui University, Hefei 230601, P. R. China
3. Anhui Urban Construction Design and Research Institute Co., LTD., Hefei 230071, P. R. China
4. Ecological Environment Monitoring Center of Anhui Province, Hefei 230011, P. R. China

Received:2024-04-11 Online:2024-08-18 Published:2024-09-25

摘要/Abstract

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

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

中图分类号:

张宝东, 王彪, 吴艳兰, 孟玉, 徐升, 钱贞兵, 秦军. 安徽省农村黑臭水体特征分析及识别[J]. 生态环境学报, 2024, 33(8): 1257-1268.

ZHANG Baodong, WANG Biao, WU Yanlan, MENG Yu, XU Sheng, QIAN Zhenbing, QIN Jun. Analysis and Identification of Characteristics of Rural Black and Odorous Water Bodies in Anhui Province[J]. Ecology and Environment, 2024, 33(8): 1257-1268.

图/表 16

参考文献 42

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波段	波段号	波谱范围/ nm	GF-2空间分辨率/m	GF-7空间分辨率/m
全色	Pan	450‒900	<0.8	<0.7
多光谱	Band1 (蓝)	450‒520	<3.2
	Band2 (绿)	520‒590		<2.8
	Band3 (红)	630‒690
	Band4 (近红外)	770‒890

波段	波段号	波谱范围/ nm	GF-2空间分辨率/m	GF-7空间分辨率/m
全色	Pan	450‒900	<0.8	<0.7
多光谱	Band1 (蓝)	450‒520	<3.2
	Band2 (绿)	520‒590		<2.8
	Band3 (红)	630‒690
	Band4 (近红外)	770‒890

地区	调查时间	调查数量
皖北地区	2023年1‒8月	168
皖中地区	2023年6‒9月	76
皖南地区	2023年7‒10月	57

地区	调查时间	调查数量
皖北地区	2023年1‒8月	168
皖中地区	2023年6‒9月	76
皖南地区	2023年7‒10月	57

监测指标	指标阈值
透明度/cm	<25
溶解氧质量浓度/(mg∙L⁻¹)	<2
氨氮质量浓度/(mg∙L⁻¹)	>15

安徽省农村黑臭水体特征分析及识别

Analysis and Identification of Characteristics of Rural Black and Odorous Water Bodies in Anhui Province

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参考文献 42

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环境因素	皮尔逊相关性	显著性
浮萍覆盖率	−0.825	0.000**
水体流通性	−0.094	0.654
温度	−0.594	0.000**
浮萍覆盖率×水体流通性		0.000**
浮萍覆盖率×温度		0.000**

水体编号	水体类型	颜色	气味	透明度	溶解氧	浮萍覆盖率	水体编号	水体类型	颜色	气味	透明度	溶解氧	浮萍覆盖率
01	沟渠	无色	微臭	40	0.11	100	14	塘	微黄	无味	28	0.56	97.86
02	塘	微黄	微臭	34	0.15	100	15	塘	无色	微臭	38	0.66	91.35
03	塘	微黄	微臭	34	0.27	98.41	16	塘	微黄	微臭	31	0.66	92.86
04	塘	无色	无味	42	0.27	100	17	塘	无色	无味	60	0.68	93.68
05	塘	微黄	微臭	31	0.29	96.23	18	塘	黄	微臭	30	0.87	93.75
06	塘	无色	无味	37	0.31	99.28	19	塘	微黄	无味	30	1.26	89.53
07	塘	无色	无味	43	0.31	100	20	塘	无色	微臭	34	1.39	90.55
08	塘	微黄	无味	37	0.34	98.60	21	塘	无色	无味	40	1.66	87.11
09	塘	微黄	无味	35	0.38	98.45	22	塘	微黄	无味	35	2.22	86.04
10	塘	微黄	微臭	34	0.39	97.64	23	塘	微黄	无味	29	2.33	81.11
11	塘	黄色	臭	30	0.43	98.43	24	塘	微黄	微臭	38	2.53	84.21
12	塘	无色	无味	50	0.46	97.12	25	塘	无色	微臭	40	3.16	86.32
13	塘	微黄	无味	38	0.54	98.05	26	塘	黄	无味	42	3.8	83.52

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地区	正确数	总数
安庆市	21	26
阜阳市	13	16
六安市	10	12

地区	正确数	总数
安庆市	21	26
阜阳市	13	16
六安市	10	12