亚热带典型农业流域河流水质多元线性回归预测

doi:10.11934/j.issn.1673-4831.2017.06.004

生态与农村环境学报 ›› 2017, Vol. 33 ›› Issue (6): 509-518.doi: 10.11934/j.issn.1673-4831.2017.06.004

亚热带典型农业流域河流水质多元线性回归预测

宫殿林^1,2,3, 洪曦⁴, 曾冠军⁵, 王毅^1,2, 左双苗⁶, 刘新亮^1,2, 吴金水^1,2

1. 中国科学院亚热带农业生态研究所亚热带农业生态过程重点实验室, 湖南长沙 410125;
2. 中国科学院亚热带农业生态研究所长沙农业环境观测研究站, 湖南长沙 410125;
3. 中国科学院大学, 北京 100049;
4. 湖南省土壤肥料研究所, 湖南长沙 410125;
5. 湖南农业大学资源环境学院, 湖南长沙 410128;
6. 湖南省水利厅, 湖南长沙 410007

收稿日期:2016-07-28 出版日期:2017-06-25 发布日期:2017-06-15
通讯作者: 王毅,E-mail:wangyi@isa.ac.cn;左双苗,E-mail:553466318@qq.com E-mail:wangyi@isa.ac.cn553466318@qq.com
作者简介:宫殿林(1981-),男,黑龙江七台河人,硕士生,主要从事农业流域环境研究。E-mail:gongdianlin@163.com
基金资助:
国家科技支撑计划（2014BAD14B01）；城郊环保型高效农业关键技术研究与示范（2014BAD14B05）；湖南省水利科技项目（湘水科计[2016]-SB-01）；湖南省科协决策咨询研究计划

Prediction of Water Quality in Rivers in Agricultural Regions Typical of Subtropics in China Using Multivariate Linear Regression Model

GONG Dian-lin^1,2,3, HONG Xi⁴, ZENG Guan-jun⁵, WANG Yi^1,2, ZUO Shuang-miao⁶, LIU Xin-liang^1,2, WU Jin-shui^1,2

1. Key Laboratory of Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China;
2. Changsha Research Station for Agricultural & Environmental Monitoring, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China;
4. Hunan Institute of Soil and Fertilizer, Changsha 410125, China;
5. College of Resources and Environment, Hunan Agricultural University, Changsha 410128, China;
6. Hunan Provincial Water Resources Bureau, Changsha 410007, China

Received:2016-07-28 Online:2017-06-25 Published:2017-06-15

摘要/Abstract

摘要：

理解河流水体氮磷浓度与景观格局之间的关系是流域水环境质量科学管理的前提。选取湖南省长沙县石燕河流域，基于Pearson相关性分析、方差分解分析和多元线性回归方法，研究景观格局对流域出口水体氮磷浓度的影响并构建氮磷浓度预测模型。结果表明，流域出口水质长期处于劣V类，铵态氮（NH₄⁺-N）、硝态氮（NO₃^--N）、总氮（TN）、可溶性磷（DP）和总磷（TP）质量浓度分别为5.67~22.46、0.76~2.85、13.41~45.55、0.86~5.00和1.99~9.94 mg·L^-1；流域出口水体氮磷浓度与土地利用方式组成、景观格局指数、人口和养殖密度相关性显著（P<0.05）。流域出口水体TN和TP浓度与林地面积比例、养殖密度呈显著正相关（P<0.05），与农田、居民地面积比例和人口密度呈显著负相关（P<0.05）；TN和TP浓度与景观格局最大斑块指数（LPI）呈显著正相关（P<0.05），与景观斑块形状指数（LSI）呈显著负相关（P<0.05）；流域出口水体氮磷浓度可用土地利用方式组成（农田、居民地、茶园）和景观格局指数〔斑块密度（PD）、LPI、LSI、蔓延度（CONTAG）、景观分割度（DIVISION）〕的多元线性回归模型预测（校正后R²为0.132~0.320），且多元线性回归模型对NO₃^--N浓度的预测效果最佳。研究结果可为亚热带丘陵区农业流域水环境保护与景观合理规划、利用和管理提供科学依据。

关键词: 流域环境, 氮磷, 畜禽养殖, 面源污染, 土地利用

Abstract:

Knowledge about relationships of nitrogen (N) and phosphorus (P) concentrations in river water with landscape pattern is the premise of scientific management of catchment water environment. Shiyan River Catchment, in Changsha County, Hunan Province was selected as the object and Pearson correlation analysis, variation partitioning analysis, and multivariable linear regression analysis were applied to the exploration of effects of land use on N and P concentrations in river water at the catchment outlets and development of a model for predicting quality of the river water. Results show that 1) the water in the outlets has long been ruled into the category of Grade V minus in quality, as specified in the National Standard for Surface Water Quality (GB 3838-2002), with the concentration of ammonium-N (NH₄⁺-N), nitrate-N (NO₃^--N), total-N (TN), dissolved-P (DP), and total-P (TP) varying in the range of 5.67-22.46, 0.76-2.85, 13.41-45.55, 0.86-5.00, and 1.99-9.94 mg·L^-1, respectively; 2) N and P concentrations in the river water at the outlets of the catchment were significantly related to land use, landscape, population and livestock density (P<0.05), significantly and positively to proportion of forest land in area, and livestock density, and significantly and negatively to proportions of farmland and residential settlement in area, and population density. Besides they were also significantly and positively related to landscape maximum plaque index (LPI), and negatively to landscape shape index (LSI); 3) N and P concentrations in the river water could be predicted through analysis of land use patterns (farmland, residential area, tea garden, etc.) and landscape pattern indices[patch density (PD), LPI, LSI, contagion index(CONTAG), and landscape segmentation index (DIVISION)], using the multiple linear regression model (calibrated R²:0.132-0.320). The model worked particularly well for predicting NO₃^--N concentration in the river water. All the findings may serve as an important scientific basis for protection of the water environment and rational programming, utilization and management of the landscapes in agricultural catchments in the subtropical hilly regions of China.

Key words: catchment environment, nitrogen and phosphorus, livestock, non-point source pollution, land use

中图分类号:

X824

宫殿林, 洪曦, 曾冠军, 王毅, 左双苗, 刘新亮, 吴金水. 亚热带典型农业流域河流水质多元线性回归预测[J]. 生态与农村环境学报, 2017, 33(6): 509-518.

GONG Dian-lin, HONG Xi, ZENG Guan-jun, WANG Yi, ZUO Shuang-miao, LIU Xin-liang, WU Jin-shui. Prediction of Water Quality in Rivers in Agricultural Regions Typical of Subtropics in China Using Multivariate Linear Regression Model[J]. Journal of Ecology and Rural Environment, 2017, 33(6): 509-518.

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亚热带典型农业流域河流水质多元线性回归预测

Prediction of Water Quality in Rivers in Agricultural Regions Typical of Subtropics in China Using Multivariate Linear Regression Model

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