赣江流域土地利用方式对河流水质的影响

赣江是鄱阳湖的最大支流,是鄱阳湖水污染物的主要来源,查明流域土地利用方式对赣江水质的影响和鄱阳湖的水环境保护具有重要意义。基于2012年对赣江7个主要支流NH+4-N、TP、CODMn和DO浓度的每月测定结果,通过不同空间尺度和土地类型等级划分,利用相关分析和冗余分析研究土地利用方式对赣江流域河流水质的影响。研究结果表明,子流域的土地利用方式对TP的影响大于缓冲区;对CODMn的影响在丰水期大于缓冲区,在枯水期小于缓冲区;对NH+4-N的影响在丰水期与缓冲区接近,在枯水期小于缓冲区;DO受土地利用方式的影响较小。水田中的丘陵水田是赣江水体TP和丰水期CODMn的主要来源;平原水田是枯水期CODMn的主要来源。居民建设用地中的城镇用地是赣江水体TP、NH+4-N和丰水期CODMn的主要来源,农村用地是CODMn的主要来源。水域中的水库坑塘是赣江水体TP和丰水期NH+4-N、CODMn的主要来源。     

两类水质综合评价方法的特点及其在河流水环境管理中的作用

河流水质恶化已成为严峻的环境问题,针对河流开展水质综合评价对河流水环境管理具有重要意义。依据不同的评价目标,选择合理的综合评价的评估标准成为河流水质评价中重要的问题之一。通过基于期望值和阈值的水质健康综合评估法(ETI)和水质质量指数(WQI)两种水质综合评价方法对"引滦入津"工程重要水源地伊逊河水质进行评价,结果显示:1)伊逊河水质ETI评估结果为良好等级,WQI评估结果为一般等级;2)伊逊河采样点水质在ETI评价中分布于4个等级,WQI仅分布于2个等级;3)伊逊河自上游至下游水质显著降低,特别是ETI评估中由优秀等级转变为差等级;4)ETI和WQI评估结果显示极显著相关性(R=0.951,P0.01);5)通过逐步多元回归,ETI评估结果的主导因子是DO、EC、SS、BOD_5和TP(P0.05),WQI评估结果的主导因子是DO、SS、BOD_5、TP、TN和NH_3-N(P0.05)。进一步分析表明伊逊河水质恶化与其流域内土地利用情况密切相关。在河流水环境管理中,ETI作为一种水质相对值评估方法,能更好体现流域内水质差异的区分度,便于管理者迅速定位流域内亟需治理的河流或河段,同时能够根据河流自身特征制定管理目标,可作为河流管理绩效评估的有效手段;而WQI作为一种水质绝对值评估方法,更适用于河流水质时间变化评估,对河流经长期治理后的管理效果评价起到重要作用。     

Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China

Understanding the physical processes of point source (PS) and nonpoint source (NPS) pollution is critical to evaluate river water quality and identify major pollutant sources in a watershed. In this study, we used the physically-based hydrological/water quality model, Soil and Water Assessment Tool, to investigate the influence of PS and NPS pollution on the water quality of the East River (Dongjiang in Chinese) in southern China. Our results indicate that NPS pollution was the dominant contribution (>94%) to nutrient loads except for mineral phosphorus (50%). A comprehensive Water Quality Index (WQI) computed using eight key water quality variables demonstrates that water quality is better upstream than downstream despite the higher level of ammonium nitrogen found in upstream waters. Also, the temporal (seasonal) and spatial distributions of nutrient loads clearly indicate the critical time period (from late dry season to early wet season) and pollution source areas within the basin (middle and downstream agricultural lands), which resource managers can use to accomplish substantial reduction of NPS pollutant loadings. Overall, this study helps our understanding of the relationship between human activities and pollutant loads and further contributes to decision support for local watershed managers to protect water quality in this region. In particular, the methods presented such as integrating WQI with watershed modeling and identifying the critical time period and pollutions source areas can be valuable for other researchers worldwide.     

不同时空尺度下土地利用对洱海入湖河流水质的影响

土地利用与入湖河流水质的关系存在时空差异。以洱海西部入湖河流及其小流域为研究对象,综合空间分析和数理统计手段,探讨两者随空间尺度和时间变化的关系,结果表明:选取的小流域、河岸带30m缓冲区、河岸带60m缓冲区和河岸带90m缓冲区4种尺度下,对入湖河流水质影响显著的土地利用类型为建设用地和植被(包括林地和牧草地),影响最大的空间尺度为小流域尺度,河岸带30m缓冲区次之;小流域尺度下,建设用地面积百分比与入湖河流COD和TP浓度呈正相关,植被面积百分比与NH_4~+-N浓度呈负相关,响应土地利用的主要水质指标为TN和TP,回归调整系数分别为0.624和0.579;季节性关联分析表明建设用地与COD、NH_4~+-N、TP的回归关系在雨季强于旱季,植被与COD、TP的回归关系在雨季强于旱季,雨季建设用地和植被面积变化引起COD浓度变化更快。在流域管理中,针对植被覆盖率低、建设用地占比高的白鹤溪和中和溪应重点加强雨季土地利用管控,增加植被覆盖率,合理开发建设用地。     

三峡库区古夫河水质时空分异特征

以湖北省神农架林区和兴山县境内长江三峡库区香溪河支流古夫河为研究对象,于2010年8月-2011年7月在整条河流中选取20个采样点,进行样本采集,并测定溶解氧、碱度、硬度、电导率、总磷、总氮、化学需氧量、二氧化硅、总有机碳共9项水质指标,运用多元统计方法,分析水质的时空分异特征.依据研究区土地利用类型差异,将20个采样点分成4组,即森林(A组)、耕地(B组)、水库(C组)和村镇(D组);根据该区域的水文节律,将5-10月归为湿季,其余月份为干季.判别分析和方差分析结果表明,古夫河水质具有时空显著性差异:总磷、二氧化硅、电导率、化学需氧量、总硬度和总碱度等指标具有空间显著性差异;总氮、化学需氧量、溶解氧、二氧化硅和总有机碳与季节存在显著相关性,所测9项水质指标在不同空间类别上呈现出显著的季节变化.主成分分析表明,不同空间类别上的干湿季节引起水质变化的主导因子是不同的:A组中,湿季主要体现为二氧化硅和总有机碳,干季主要体现为总磷、二氧化硅、总有机碳和化学需氧量,该组水质主要受地表径流、地质成因和风化作用等自然因素的影响;B组中,湿季主要体现为硬度和总有机碳,干季主要体现为总磷、化学需氧量、总碱度和总硬度,该组除了受自然因素的影响,还受如农业径流、未处理的生活污水排放等人为因素影响;C组中,湿季主要体现为二氧化硅、总氮和总磷,干季主要体现为总氮、总有机碳和二氧化硅,该组主要受农业径流、地表径流以及未经处理的生活污水等的影响;D组中湿季主要体现为二氧化硅、总氮和总磷,干季主要体现为碱度、硬度、总氮和总有机碳,该组主要受村镇生活污水和农业径流等的影响.结果表明,古夫河水质受自然和人为因素影响而发生变化,其中受人为因素影响更大.因此,加强水资源的管理和保护,改善水质,做好水源地的长期水质监测显得尤为重要.     

Assessing water quality of five typical reservoirs in lower reaches of Yellow River,China: Using a water quality index method

To assess water quality of reservoirs in lower reaches of Yellow River using the water quality index (WQI) method and try to compare water quality and main contaminations of mountain and Yellow River reservoirs, water samples were carried out over 6 years. Nine water variables were selected to participate WQI calculation by Principal Component Analysis (PCA). WQI values ranged from 17.8 to 77.8 in five reservoirs, which indicated “good” to “very poor” water quality of reservoirs. No significant differences in WQIs were found between mountain and Yellow River reservoirs. A major finding from our study is that mercury was the main contamination in 5 reservoirs, while TP (total phosphorus) and SO₄ were another main contaminations in mountain and Yellow River reservoirs, respectively. Application of the WQI is suggested to be a helpful tool that enables the public and decision makers to evaluate water quality of drinking reservoirs in lower reaches of Yellow River.     

流溪河水质的动态特征

流溪河是广州市的一条重要河流,广州市60%的供水都来自于该河。为探讨流溪河水质的动态特征,沿河设立7个监测断面,于2003年1～12月,每月进行一次采样,对主要水质参数进行了分析。结果表明,上游良口断面全年的水质状况明显好于下游的南岗断面。除pH值外,全年南岗断面的溶解氧、高锰酸盐指数、BOD₅、氨氮和总磷均不同程度地超二类水标准,其中以溶解氧超标最为严重,最高值仅为4.94mg·L^-1。污染源分布较多的河段,其枯水期的水质要较丰水期差。从良口断面到南岗断面,pH值和溶解氧呈下降趋势,高锰酸盐指数、BOD₅、氨氮和总磷呈上升趋势,表明流溪河下游水质较差,有机污染较严重。     

洱海入湖河流弥苴河下游氮磷季节性变化特征及主要影响因素

入湖河流携带污染物对洱海水环境的影响日益明显,对洱海入湖水量最大的河流——弥苴河下游水体氮磷进行了连续采样分析,以期为河口湿地建设和水质改善提供基础数据.结果表明:1)弥苴河水质介于地表水Ⅲ-Ⅴ类之间,主要污染物为氮和磷,其中总氮平均浓度为1.17 mg/L,最高浓度达到2.00 mg/L;总磷平均浓度为0.06 mg/L;2)弥苴河下游总氮、总磷浓度丰水期高于枯水期,并呈现出季节性变化规律;3)弥苴河下游水体总氮、总磷年均浓度远高于洱海水体总氮、总磷年均浓度,其中总氮高出2.10倍,总磷高出2.90倍;4)弥苴河下游河段非点源污染占据主导地位.     

Effects of Land Use,Topography and Socio-Economic Factors on River Water Quality in a Mountainous Watershed with Intensive Agricultural Production in East China

Understanding the primary effects of anthropogenic activities and natural factors on river water quality is important in the study and efficient management of water resources. In this study, analysis of Variance (ANOVA), Principal component analysis (PCA), Pearson correlations, Multiple regression analysis (MRA) and Redundancy analysis (RDA) were applied as an integrated approach in a GIS environment to explore the temporal and spatial variations in river water quality and to estimate the influence of watershed land use, topography and socio-economic factors on river water quality based on 3 years of water quality monitoring data for the Cao-E River system. The statistical analysis revealed that TN, pH and temperature were generally higher in the rainy season, whereas BOD₅, DO and turbidity were higher in the dry season. Spatial variations in river water quality were related to numerous anthropogenic and natural factors. Urban land use was found to be the most important explanatory variable for BOD₅, COD_Mn, TN, DN, NH₄ ⁺-N, NO₃ ⁻-N, DO, pH and TP. The animal husbandry output per capita was an important predictor of TP and turbidity, and the gross domestic product per capita largely determined spatial variations in EC. The remaining unexplained variance was related to other factors, such as topography. Our results suggested that pollution control of animal waste discharge in rural settlements, agricultural runoff in cropland, industrial production pollution and domestic pollution in urban and industrial areas were important within the Cao-E River basin. Moreover, the percentage of the total overall river water quality variance explained by an individual variable and/or all environmental variables (according to RDA) can assist in quantitatively identifying the primary factors that control pollution at the watershed scale.     

广东省水质现状及驱动因素

水质现状评估及其驱动因素分析是实现水生态保护、水资源利用和水污染治理的关键,对于水生态系统的可持续发展具有重要意义。以广东省七大流域为研究区,基于2019-2020年间的溶解氧（DO）、透明度（SDD）、悬浮物（SPM）、叶绿素a （Chla）、氨氮（NH₃N）、总氮（TN）、总磷（TP）7个指标的水质监测数据,综合运用单因子指数法（SI）和综合水质指数（WQI）评价方法,分丰水期（N=66）和枯水期（N=54）评估研究区的水质现状,并探讨水质参数与地形、气象、社会经济和土地覆被类型等驱动因素之间的相关关系。SI评估结果显示广东七大流域主要以工业污水、农业面源等造成的Chla和TN浓度超标、部分水体富营养化严重为主,同时伴有溶解氧浓度偏低的问题;WQI评估结果显示研究区有57%以上的采样点属于中等以下水质。Chla、SPM、NH₃N和TP浓度具有显著的季节和驱动因素差异：丰水期的Chla和TP浓度低于枯水期,但SPM和NH₃N浓度高于枯水期。枯水期DO、TN和WQI的显著性影响因子为丰水期的1/3左右;这种季节差异可能是流域内降雨、营养盐负荷和土地覆被类型导致的复杂地表径流及面源污染所致。珠江三角洲河网区、粤西诸河、韩江下游以及粤东诸河练江流域的水质问题突出。未来水生态系统的可持续发展研究可以借助长时间序列、多频次、高分辨率的遥感监测手段和多种数值模拟方法以及常规水质评估模型,探讨气候变化、河岸带产业结构和流域土地利用方式对面源污染的影响,以进一步厘清降雨强度、三产结构和土地利用方式转变对区域水质变化的影响。     

流溪河流域景观空间特征与河流水质的关联分析

人类活动影响或改变流域景观空间结构,并有可能对河流水质产生不同程度的影响,以流溪河流域为研究区,分析流域景观空间格局特征与水质指数之间的相关关系。将流域划分为27个子流域,采集水样分析水质状况,所选用的水质指标有氨氮(NH3-N)、硝态氮-亚硝态氮(NO3-N+NO2-N)、总磷(TP)、化学需氧量(CODCr)。结果表明:1)该流域土地利用结构与水质具有显著相关性,其中居住用地对水质的影响作用最强,林地对河流水质具有净化功能,与水质指标之间的关系表现为负相关,园地与水质指标关系具有不确定性;2)流域景观特征从上游到下游之间表现为城市化增强的梯度,水质状况响应这个梯度变化表现为上游优于下游,人类活动及城市化发展引起的土地利用变化及土地管理方式对水质变化有显著影响;(3)景观破碎度与水质呈现显著正相关性,是影响水质的重要指标,景观聚集程度和斑块形状复杂程度与水质有负相关关系;子流域尺度和河岸带尺度景观空间特征对水质的影响差异不明显。     

A dynamic water quality index model based on functional data analysis

A water quality index (WQI) incorporates two shortcomings in the dynamic assessment of water quality, namely: (1) the sampling time series must be identical for each indicator and no missing data should occur, and (2) stationary weights cannot represent the changes in the pollutant importance. To solve these problems, the present study introduces the functional data analysis method into WQI research and establishes a dynamic WQI (D-WQI) model. D-WQI is a generalization of the conventional WQI. In the D-WQI model, the changes of water quality and pollutant importance are represented in the form of dynamic functional curves. The generation methods of the concentration curves, sub-index curves, dynamic weight curves, and WQI curves are discussed. As an illustration, the D-WQI model is applied in the water quality assessment of the Changjiang River in Sanjiangying in 2012. Result shows that the river can be classified as II (good) throughout the year, which can satisfy the requirement of the Chinese South-to-North Water Diversion Project.     

Influence of anthropogenic activities on water quality of a tropical stream ecosystem

Water samples were collected from three sites located in the middle reach of the Njoro River, Kenya, and analysed for total phosphorus (TP), orthophosphate, ammonia‐nitrogen, and nitrate‐nitrogen to evaluate stressor sources (e.g. factories and wastewater ponds) and the general stream water quality. The stream surface water was also analysed for biochemical oxygen demand (BOD₅) to provide an overview of organic matter loading. Mugo, Egerton Bridge and the canning factory sites of the Njoro River had low water quality which is likely to be due to poor farming, partially treated effluents and poor provision of sanitation facilities to the riparian communities. The concentrations of the selected nutrients did not differ significantly among the three sites, presumably due to pollution of the whole stream reach by the catchment nutrient sources. High phosphate concentrations (i.e. ～0.76 mgPO₄ l^?1 and ～0.87 mgTP l^?1) at Canning Factory were recorded during the low flow dry season. Nitrate‐nitrogen concentrations varied significantly with water discharge which explained between 63 and 87% of the nutrient variability in the three sites. BOD₅ differed significantly among the three sites, with historical effects of wastewater and factory effluent discharge being reflected in the results of Egerton Bridge and Canning Factory. The concentrations of ammonia‐nitrogen, TP and orthophosphate were higher in the wastewater than in the river water whereas nitrate‐nitrogen was lower. This study indicates that the Njoro River is stressed by nutrients from the activities within its catchment. With the increasing population, the nutrient load to the river will continue to increase and the water quality will continue to deteriorate. Reductions of nutrient loads into the river as well as provision of sanitation facilities to the riparian communities are needed to control further water degradation.     

柳江流域不同水文季节水质对附生硅藻群落的影响研究

为研究溶解氧(DO)、化学需氧量(CODMn)、氨氮(NH4+-N)、汞(Hg)、铅(Pb)、砷(As)和镉(Cd)在枯水期和丰水期变化对附生硅藻群落结构的影响, 分别于 2017 年 3 月和 6 月对柳江流域进行了调查分析, 旨在为深入研究柳江流域硅藻群落分布特征奠定基础, 以期为该流域水质的利用和管理提供理论依据。柳江流域共鉴定出附生硅藻 137 种, 隶属于 6 目 9 科 34 属。各采样点硅藻丰富度变化范围为 13-42 种, 呈现为丰水期高于枯水期。硅藻优势种组成在枯、丰水期分别有 5 种和 8 种, 具有明显的季节演替。聚类分析(Cluster analysis)显示, 硅藻群落结构在时空分布上存在差异, 枯水期可分为 3 个类群, 基本呈现在干流及支流段的上游、中游和下游; 丰水期可分为 2 个类群, 大致分布在流域的中下游和上游。其中, 在枯水期, Cyclotella fottii、Cyclotella. stelligera、Achnanthes minutissima 和 Cymbella laveis 在上游为优势种, A. minutissima 和 Nitzschia valdecostata 在中游丰度较高, 下游优势种为 Navicula cryptocephala、Amphora montana 和 A. minutissima 等; 在丰水期, 中下游优势种主要以 Nitzschia palea 为主, 上游优势种为 A. minutissima、A. montana 和 Achnanthes petersenii 等。主成分分析(Principle component analysis, PCA)和冗余分析(Redundancy analysis, RDA)显示, 枯水期水质因子对硅藻群落的影响为 Pb>Cd>Hg>As>CODMn>DO, 丰水期为 As>DO>CODMn>NH4+-N>Cd。结果表明, 水质因子 Cd、As、DO 和 CODMn 在枯水期和丰水期都对硅藻群落结构的变化起着重要作用, 但重金属因子在枯水期对硅藻影响较大, 而溶解氧在丰水期对硅藻影响较大。     

长江上游坡地景观特征对河流水质的影响

景观组成及景观格局特征决定了污染物的来源和地表景观的拦截消纳潜力,地表坡降会加剧土壤侵蚀,坡地景观特征是影响河流水质的重要因素。研究基于长江上游重庆段2015年水质监测数据和30 m空间分辨率土地利用数据,提取河岸带100 m、200 m、300 m、500 m、1000 m和子流域6种空间尺度上景观格局和景观组成,并进一步将景观组成分为总地类、缓坡地类和陡坡地类三种不同坡度尺度,再采用相关分析和冗余分析（RDA）等方法定量探讨了坡地景观特征（坡地景观组成、景观格局）对河流水质的多时空尺度影响。结果表明：坡地景观特征对2015年长江上游重庆段河流水质的影响具有空间尺度效应;坡地景观特征对河流水质的影响在河岸带尺度强于子流域尺度,其中关键尺度为河岸带100 m至300 m,最有效尺度为河岸带200 m。坡地景观特征影响水质的季节差异随空间尺度不同而变化,在河岸带100 m至300 m尺度为汛期强于非汛期,在河岸带1000 m尺度相反,在子流域尺度无季节差异。建设用地面积比与溶解氧（DO）和高锰酸盐指数（COD_Mn）正相关,耕地面积百分比与氨氮（NH₄⁺-N）参数正相关,两者为水质污染"源景观",且缓坡耕地对水质的解释率高于总地类耕地;林地与水质参数呈负相关,对缓解水质恶化具有积极作用;集聚度（COHESION）、聚合度（AI）指标与NH₄⁺-N参数及斑块密度（PD）、边缘密度（ED）与DO、COD_Mn参数均呈正相关。在集水区尤其是河岸带300 m范围内,严格把控建设用地污水收集与处理,种植河岸带防护林,采取横坡耕种方式,并通过优化景观结构（如种植植物篱）以增强景观拦截力以减少污染物的集中输出,从而改善河流水质。     

七项河流附着硅藻指数在东江的适用性评估

综合运用因子分析、聚类分析、箱型图分析等统计方法评估了河流附着硅藻生物指数(Biological Diatom Index,IBD)、硅藻营养化指数(Trophic Diatom Index,TDI)、斯雷德切克指数(Sládecˇek’s Index,SLA)、特定污染敏感指数(Specific Polluosensitivity Index,IPS)、硅藻属指数(Generic Diatom Index,IDG)、戴斯指数(Descy Index,DESCY)和欧盟硅藻指数(European Economic Community Index,CEE)在东江流域河流水质评价中的适用性。结果显示:SLA与IPS,CEE显著相关(P<0.05),CEE与TDI不相关,其余指标间均极显著相关(P<0.01)。SLA与13项水质理化指标均无相关性,TDI与含氯度(Cl)显著负相关,CEE与溶解氧(DO)、电导率(Cond.)、总氮(TN)显著正相关(P<0.05),其余指标与氨氮(NH4-N)、pH不存在线性相关,与五日生化需氧量(BOD5)、高锰酸盐指数(CODKMnO4)、亚硝氮(NO2-N)、硝氮(NO3-N),总磷(TP)具极显著相关性(P<0.01)。13项水质理化指标中主成分负荷贡献大于50%的八项理化参数DO、BOD5、CODKMnO4、TN、NO3-N、NO2-N、TP和SiO2将试验区水质分为四组。IPS、IBD、IDG和CEE与水质物化分类一致性较好。IPS、IBD、IDG和CEE的逐步判别分析(引入P=0.20,剔除P=0.25)显示IPS和CEE都只选出了NO2-N,分类判别的正确率分别为55.6%和48.1%;IBD引入了NO2-N,CODKMnO4和DO 3个解释变量,判别正确率74.1%;IDG引入BOD5和NO3-N两个变量,分组正确率63.0%。硅藻群落聚类显示,IBD和IDG在水质物化分类的箱型图中呈现出明显合理的趋势。以上研究表明IBD和IDG硅藻指数最适合用于东江河流水质生物监测与评价。     

Use of the water quality index and dissolved oxygen deficit as simple indicators of watersheds pollution

The use of the water quality index (WQI) and the dissolved oxygen deficit (D) as simple indicators of the watersheds pollution was investigated and compared in the Municipality of Las Rozas (north-west of Madrid, Spain). The quality of the water in Guadarrama and Manzanares rivers and Paris Park ponds, the main watersheds of this area was investigated during 2 years (from September 2001 to September 2003). It was found that the WQI was very useful for the classification of the waters monitored. The WQI was 70, which corresponds to “good” quality water at the sampling point 1 (entrance of Las Rozas) and decreased to around 64 (medium quality) at the sampling point 6 (outlet of Las Rozas) in the case of Guadarrama River. The WQI was around 65 in the influents of Manzanares River. Finally, in Paris Park the WQI ranged from around 72–55, which corresponded to a classification from “good” to “medium” quality, respectively. A high linear relationship between the WQI and the dissolved oxygen deficit (D) was found. Therefore, a fast determination of WQI may be carried out knowing the values of D, which are easily obtainable by field measurements. It was found an influence of the climate conditions on the values of WQI and D.     

Spatial variation in ciliate communities with respect to water quality in the Delhi NCR stretch of River Yamuna,India

The River Yamuna emerges from Saptarishi Kund, Yamunotri and merge with River Ganges at Allahabad, India. Anthropogenic stress has affected the water quality of the river Yamuna drastically in the stretch traversing Delhi and its satellite towns (National Capital Region, NCR). In the present study, effect of water quality on the microbial life in the River Yamuna was analyzed using ciliate communities (Protista, Ciliophora) as bio-indicators. Water samples were collected from six sampling sites chosen according to the levels of pollution along the river and water quality was analysed using standard physicochemical factors. As the river traverses Delhi NCR, water quality deteriorates considerably as indicated by the Water Quality Index at the selected sampling sites. Seventy-four ciliate species representing nine classes were recorded. Based on the Shannon diversity index, maximum species diversity was found at the point where the river enters Delhi. The saprobity index showed the river water was beta-mesosaprobic when the river enters Delhi and alpha-mesosaprobic at downstream sites after the first major drain outfall. Significant relationship between the spatial variation in ciliate communities and abiotic parameters indicate that ciliates can be used as effective bioindicators of pollution in the River Yamuna.     

青弋江流域土地利用/景观格局对水质的影响

研究不同空间尺度的景观组成与结构对水质的影响对于水质保护具有重要意义。青弋江为长江下游最长的支流,人类活动可能通过多种方式对水质产生影响。以青弋江流域为研究对象,基于Google Earth遥感数据和水质实测数据,采用冗余分析(RDA)和Spearman相关性分析,探讨了土地利用/景观格局对水质的影响。研究结论为:(1)以采样点为中心建立的100、200、500、1000、2000 m 5种尺度缓冲区中,500 m半径圆形缓冲区景观组成对水质的解释率最高,枯水期与丰水期对水质的解释率分别为46.30%和43.10%。(2)土地利用类型中,耕地和建设用地面积与NH₄⁺-N、TP、EC呈正相关,对水质具有负面效应;林地面积与DO呈正相关,对污染物起到净化作用;土地利用综合程度指数与污染指标呈正相关,表明人类活动强的区域,水质变差。(3)景观格局指数中,PRD在丰水期与NH₄⁺-N、TP浓度为负相关,相关系数分别为-0.656、-0.540,表明随斑块丰富度密度的增大,流域生态系统更加稳定;LPI与DO浓...