流域景观格局与河流水质的多变量相关分析

流域内的景观格局改变是人类活动的宏观表现,会对河流水质产生显著影响,因此明确影响水质变化的关键景观因子,对于深入了解景观对水质的影响机制具有重要的研究价值。选择广东省淡水河流域为研究对象,以2007年ALOS卫星影像以及水质监测数据为基础,运用空间分析和多变量分析方法,分析淡水河流域景观格局与河流水质的相关关系。用包括流域和河岸带尺度的景观组成和空间结构信息的景观指数表征景观格局,用Spearman秩相关分析、多元线性逐步回归模型和典型相关分析(CCA)研究景观指数和水质指标的相关关系。研究结果表明:林地、城镇用地和农业用地占淡水河流域总面积超过90%,其中城镇用地超过20%。多元线性逐步回归分析和CCA结果说明水质指标受到多个景观指数的综合影响,反映了景观格局对水质的复杂影响机制。流域景观格局对河流水质有显著影响,流域尺度的景观指数比河岸带尺度的景观指数对水质影响更大。城镇用地比例是影响耗氧污染物和营养盐等污染物浓度最重要的景观指数,林地和农业用地对水质的影响较小。另外,景观破碎化对pH值、溶解氧和重金属等水质指标有显著影响。CCA的第一排序轴解释了景观指数与水质指标相关性的54.0%,前两排序轴累积能解释景观指数与水质指标相关性的87.6%,前两轴分别主要表达了城市化水平和景观破碎化水平的变化梯度。淡水河流域的景观格局特征从上游到下游呈现出城市—城乡交错—农村的景观梯度,水质变化也对应了这个梯度的变化,说明人类活动引起的流域土地覆盖及土地管理措施变化会对水质变化产生显著影响。     

太湖流域河流水质状况对景观背景的响应

为探索流域水质对景观背景的响应,以太湖流域为研究对象,在0.5—24 km共9个尺度上运用冗余分析研究了土地利用、河网密度、降水量、地形等景观背景因子与河流水化学指标的关系。结果表明:2006—2010年太湖流域河流水质状况总体较差,但整体有逐渐改善的趋势,超标水质指标主要包括总磷(TP)、氨氮(AN)、生化需氧量(BOD)、化学需氧量(COD)和溶解氧(DO),上游地区主要表现为林区和平原水网区的差异,下游地区主要表现为河段上下游间的差异。河流水质受到多种景观背景因子的综合影响,并表现出尺度依赖性和区位差异性。AN、TP、DO在流域上游与聚落用地正相关,在下游则与耕地、河网密度正相关。COD、BOD在流域上游主要与自然湿地负相关,与人工湿地正相关,在下游则与坡度负相关,与河网密度正相关。总方差贡献率在上下游表现出一致的尺度依赖特征,均在较小(0.5—1 km)和较大(16 km)两个尺度上具有较高的解释能力。自然湿地和坡度,河网密度和耕地分别为上游、下游地区在较小和较大尺度上解释能力最高的景观因子。     

厦门后溪水质与流域景观特征沿城乡梯度的变化分析

基于河流水质观测数据和Landsat 8影像数据,分析厦门后溪2013至2017年干季和湿季的水质时空变化特征,研究沿城乡梯度河流水质变化与流域景观特征的关系。结果表明:后溪上游(饮用水水源地水体)和下游(景观水体)溶解氧(DO)分别符合《地表水环境质量标准(GB3838—2002)》Ⅱ类标准和Ⅴ类标准,但是总氮(TN)和总磷(TP)有不同程度的超标,其中TN的超标比例较高。后溪上游土地利用类型中70%以上为林地,具有涵养水源、保护水质的作用;下游建设用地和耕地比重增加,TN、TP和叶绿素a (Chl a)显著高于上游。耕地和建设用地是提高TN、TP和Chl a等水质参数的主要土地利用类型,斑块密度、香农多样性指数和源汇景观指数与各水质指标也显著相关。冗余分析表明,流域景观特征可解释70%以上水质变化,对TN和TP的影响在湿季更大,而对Chl a的影响在干季较大。土地利用组成、配置、距离、高程和坡度对流域水质均有较大影响,其中土地利用组成对Chl a的影响较大,而景观指数则对TN和TP的影响较大。因此,在流域尺度加强土地利用的规划与综合管理,通过减少和控制地表径流面源污染的途径在一定程度上可降低人类活动对水质的不良影响。     

小流域土地利用景观格局对水质的影响

运用GIS技术及SPSS统计分析的方法, 探讨了芦山县清源河流域土地景观格局对河流水质的影响, 并分析了丰水期、平水期和枯水期土地景观格局与河流水质的关系。结果表明: (1)林地、湿地和草地与河流水质呈显著负相关; 耕地和建设用地以及LC与河流水质呈显著正相关; (2)景观格局指数PD、FN和SHDI与河流水质呈显著正相关; LPI和CONTAG与河流水质呈显著负相关; (3)总体分析看出枯水期土地景观格局对河流水质的影响较丰水期更为显著, 丰水期下游区域(4#、5#和6#区域)土地景观格局对河流水质影响比上游区域(1#、2#和3#区域)大。     

桂江流域附生硅藻群落特征及影响因素

研究了桂江流域水质、土地利用、地理因素对河流附生硅藻群落的影响。结果显示,桂江流域电导率(Conductivity,Cond.)由下游至源头呈降低趋势,其它水质参数变化趋势不明显。主成分分析(Principle Component Analysis,PCA)显示前两个主成分共解释了56.2%的水质特征,第一轴反映了氨氮(NH4-N)、硝氮(NO3-N)、总氮(Total Nitrogen,TN)的变化梯度,第二轴反映了水温(WT)、pH、Cond.、溶解氧(Dissolve Oxygen,DO)的变化梯度。桂江流域硅藻特定污染敏感指数(Specific PolluoSensitivity Index,IPS)和硅藻生物指数(Biological Diatom Index,IBD)下游低于源头,差异不显著,与多项水质、土地利用以及地理因子呈线性显著相关。24个样地共发现112种硅藻,丰富度大于5%的37种,丰富度最大的几个种类依次为Achnanthidium minutissimum,A.pusilla,A.tropica,Cymbella laevis。对应分析(Corresponding Analysis,CA)显示桂江流域存在3个差异较大的硅藻群落,流域下游以Nitzschia recta为优势种,A.lanceolata、Amphora montan、Planothidium frequentissimum在中下游丰度较高,上游区域种类较多。典型相关分析(Canonical Correspondence Analysis,CCA)排序前两轴解释了硅藻群落变异程度的28.60%,CCA排序轴1与水质(Cond.、WT、NH4-N、NO3-N、TN)和土地利用(城市面积、农田面积、植被覆盖)显著负相关,与地理因素(流域面积、海拔、坡度)显著正相关,第二轴与浊度(NTU)显著正相关(P<0.05)。偏典型相关分析(Partial CCAAnalyses)显示,土地利用、地理因子、水质分别解释了桂江流域硅藻群落变异的7.20%,17.50%,48.50%。结果表明,桂江流域附生硅藻群落结构是水质、地理因子和土地利用共同作用的结果,水质起决定性作用,电导和不同形态的氮是影响附生硅藻群落结构的主要水质因素。     

不同地貌条件下景观对河流水质的影响差异

景观对河流水质的影响在不同地区、不同空间尺度上存在差异。以赤水河流域为研究对象,根据地貌特征将研究区分为喀斯特地貌和非喀斯特地貌,在划分的29个子流域内采集测试水质数据,所选用的水质指标有溶解氧(DO)、电导率(EC)、总氮(TN)和总磷(TP),运用空间分析及数理统计方法,分析流域内不同地貌区景观之间的差异,探究不同空间尺度上景观与水质指标之间的关系。结果表明:(1)流域内景观组成以林地和灌草为主,建设用地和耕地次之,景观组成在不同地貌区各空间尺度上存在差异。建设用地和耕地对水质具有负面影响,且在碳酸盐岩地区更显著;林地对水质具有正面影响;灌草对水质的影响相对复杂。(2)流域内水质表现为碳酸盐岩地区优于碎屑岩地区。景观破碎化指数与总氮(TN)、总磷(TP)呈正相关,是水质变化的重要影响因素;景观聚集度指数与溶解氧(DO)呈正相关;景观破碎化指数和景观聚集度指数与电导率(EC)的关系在两个地区呈相反的结果。(3)不同地貌区景观对河流水质具有不同程度的影响。在两个地区,景观组成对河流水质解释能力最大空间尺度均为河岸带尺度,解释率分别为53.4%和59.1%;景观格局对河流水质解释能力最大的空间尺度在碳酸盐岩地区为河岸带尺度,解释率为62.9%,在碎屑岩地区为圆形缓冲区尺度,解释率为82.4%。因此,在不同地貌区应采取不同的景观优化措施以减少对流域水质的污染。     

城镇化流域“源-汇”景观格局对河流氮磷空间分异的影响——以天津于桥水库流域为例

随着流域城镇化的加速,流域城镇化景观格局对流域水质的影响逐渐加剧。以城镇化趋势明显的于桥水库流域为例,基于流域"源-汇"景观特征指数,并结合于桥水库流域2013、2014和2015年33个子流域的水质数据,采用空间分析、相关分析和冗余分析等方法,探讨了在城镇化影响下,于桥水库流域景观特征指数和水质指标的定量关系。结果表明:整个流域从上游到下游呈现"汇"景观面积减小,"源"景观面积增大的趋势,居民建设用地面积比在中下游子流域达34.6%,"汇"型景观中林地面积为33.5%;景观空间负荷对比指数(LWLI)全局Moran′s I的值为0.637,P0.01,在空间上存在趋于集群的现象,LWLI高-高聚集区与城镇化集中区域具有一致性。LWLI与流域氮、磷空间分布存在极显著的相关性,平水期TN与LWLI的复相关系数R_2为0.811,丰水期LWLI与TP的复相关系数R_2为0.741;子流域所有水质参数NH_4~+-N、TN、NO_3~--N、TP及LWLI均集中在同一象限,与其它景观特征指数相比,LWLI对河流中氮、磷的影响最大。城镇居民用地与水质指标存在极显著的相关性,是流域水质污染重要的贡献源。流域城镇化发展中,建议提高村镇的景观连通性,便于污染物集中处理,同时增加林地、草地面积,改善流域的生态水文功能。     

太湖流域河流与湖泊间主要水质指标的空间关联特征

基于2006—2012年太湖流域主要观测断面水质监测资料,应用冗余分析法,研究分析了流域上游入湖河流、下游出湖河流与太湖湖体间水质在5、10、20、40和80 km等不同观测尺度上的关联性。研究表明,2006—2012年,太湖流域水质总体较差,但不同观测尺度内主要水质指标超标率存在较大差异,太湖湖体水质好于上游入湖河流,上游入湖河流水质总体好于下游出湖河流;上游入湖河流是太湖湖体营养盐输入的主要来源,其溶解氧、总磷和氨氮对太湖湖体相应指标超标率的累计方差贡献率均超过50%,分别达到75.9%、67.4%和57.4%;在单尺度上,太湖湖体水质主要对上游0~5 km内环湖河流水质变化的响应较显著,而对其他尺度河流水质无明显响应。在下游出流区,太湖湖体主要水质指标对出湖河流相应水质指标超标率的累计尺度和单尺度方差贡献率均低于7%,河流水质受太湖湖体水质的影响总体较小,且尺度效应不明显,下游出流区河流主要水质指标的高超标率更多受陆源污染的影响。     

不同空间尺度景观特征对南流江水质的影响差异

流域景观特征决定了非点源污染物来源与地表景观削减消纳能力,但尚缺乏全流域不同空间尺度对二者关联性的认识。以广西北部湾南流江为例,分别在子流域、河岸缓冲带以及监测点圆形缓冲区三种尺度上,基于2020年Landsat 8 OLI遥感影像解译的土地利用类型特征,结合水质监测数据,运用数理统计和GIS空间分析方法,探讨了流域景观特征在不同空间尺度上对河流水质的影响。结果表明：(1)在子流域尺度,土地利用类型以林地为主,而在河岸缓冲带与监测点圆形缓冲区均以耕地为主;(2)水质指标高锰酸盐指数、生化需氧量与景观特征相关性最为显著,耕地、建设用地、其他用地和园地与其呈正相关,是南流江水质污染负荷的重要来源区;景观格局指数中,斑块密度、蔓延度指数、多样性指数、均匀度指数是引起河流水质指标变化的主要景观因子;(3)受流域内或不同子流域间景观特征差异,景观组成面积占比和景观格局指数均在河岸缓冲带尺度对水质状况影响最大,分别可解释57.0%和64.7%的水质指标变化;子流域尺度次之,圆形缓冲区尺度最小,且景观格局指数对水质状况的影响大于景观组成面积占比。建议在河岸带50 m范围内严格控制耕地面积,建设河岸缓...     

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。     

流域尺度上河流水质与土地利用的关系

以苏子河流域内54个水质采样点为基点,生成6种尺度的河岸带缓冲区,并借助FRAGSTATS软件计算景观水平和类型水平上的8种景观指数.分别从景观空间格局与景观类型组成两方面,对景观指数与水质进行相关分析.结果表明:区域景观格局在不同缓冲区内对流域水质具有不同的效应.当缓冲区距离≤300 m时,旱地、建筑用地、水田为主要的景观类型组成,其面积比例、斑块数量、斑块密度、最大斑块指数、最大形状指数、景观斑块聚集度指数均较高,农田的连通性较高,对水质的影响较大.在距离河流较远的区域(缓冲区距离＞300 m),林地面积比例较高,林地聚集连通程度较好,对水质改善具有一定作用,但不明显.该流域耕地、建设用地等对水质有着关键的影响作用.     

Land use disturbance indicators and water quality variability in the Biscayne Bay Watershed,Florida

Rapid land use transformations due to extensive agricultural and urban development in south Florida (USA) threaten water resources such as Biscayne Bay, an oligotrophic estuary draining the Miami metropolitan complex and South Dade Agricultural Area. Biscayne Bay is sensitive to nutrient inputs and this study evaluated watershed land use-water quality relationships from 1995 to 2004. Using eight monitoring sites, three spatial extents were considered: sub-basins, canal buffers, and site buffers. Selected sites represented agricultural, urban, and mixed land use classes. Disturbance indicators (landscape metrics; Landscape Development Intensity (LDI) index; percent imperviousness), nutrient loads (nitrate/nitrite-nitrogen (NO_X-N); total ammonia nitrogen (NH₃-N); total phosphorus (TP)), and multivariate regression models were used to determine land use factors influencing water quality variability. The sub-basin regression model was the best predictor of annual NO_X-N loads in the watershed. Both LDI and largest patch index variables were included in this model, indicating that the relative distribution of dominant land use classes influences NO_X-N loads. There were no significant regression models for total inorganic nitrogen (NO_X-N plus NH₃-N) loads. Total phosphorus loads were more closely related to disturbance indicators at a smaller spatial extent (1000 m canal buffer), which is a function of watershed nutrient transport processes. The relative proportion of directly connected impervious areas (DCIA) was not identified as a significant land use variable for regression models. Positive correlations between LDI and DCIA values suggested both indicators provided similar information regarding the intensity of human disturbance. However, the LDI index incorporates anthropogenic intensity associated with a broad range of land uses while DCIA primarily reflects the impact of watershed urbanization. Watershed managers can use the LDI index with landscape metrics that evaluate spatial patterns to link land use development to water quality parameters.     

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浓度在枯水期为显著负向相关,相关系数为-0.653,SHAPE_AM与NH₄⁺-N、TP呈显著正向相关,表明随人类活动强度的增大,水质恶化;FRAC_AM与水质的关系无法得到合理的解释。通过多角度分析,在一定程度揭示了青弋江流域的生态水文过程,有利于土地利用管理和水质保护,进而促进资源的可持续利用。研究结果可为政府相关职能部门进行决策时提供参考。     

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。     

Modeling the effects of riparian buffer zone and contour strips on stream water quality

The use of contour and riparian buffer strips planted with perennial vegetation has been found to improve surface water quality by reducing NO₃-N and sediment outflow from cropland to a river. Modeling such a system to compare alternative layout and different strip sizes often faces challenges in flow routing scheme. The hillslope scheme in the Soil and Water Assessment Tool (SWAT) offers the flexibility of allowing the flow from a crop area to be routed through a buffer and/or contour strip, in which a thin sheet flow represents more closely the natural condition of a watershed. In this study, the SWAT model was applied to the Walnut Creek watershed and the hillslope option was used to examine the effectiveness of contour and riparian buffer strips in reducing NO₃-N outflows from crop fields to the river. Numerical experiments were conducted to identify potential subbasins in the watershed that have high water quality impact, and to examine the effects of strip size and location on NO₃-N reduction in the subbasins under various meteorological conditions (dry, average and wet). Variable sizes of contour and riparian buffer strips (10%, 20%, 30% and 50%, respectively, of a subbasin area) planted with perennial switchgrass were used to simulate the effects of strip size on stream water quality. Simulation results showed that a filter strip having 10–50% of the subbasin area could lead to 55–90% NO₃-N reduction in the subbasin during an average rainfall year. Strips occupying 10–20% of the subbasin area were found to be more efficient in reducing NO₃-N when placed along the contour than that when placed along the river. Varying the area and location of the contour and buffer strip affects NO₃-N outflow and crop yields as well since it takes the land out of production. The size of the filter strip has economic implications in deciding how much land area to dedicate to prevent NO₃-N loss to a desired limit or vice versa. The results of this study can assist in cost-benefit analysis and decision-making in best management practices for environmental protection.     

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.     

Impacts of land use patterns on river water quality: the case of Dongjiang Lake Basin,China

Landscape pattern can regulate water quality, but determining the thresholds at which landscape metrics impact water quality remains a key issue. Thus, in this study, we investigated landscape metrics that affect the water quality of the rivers flowing into Dongjiang Lake, China, and their spatial and seasonal differences, were investigated using redundancy and partial redundancy analyses. Further, a raw water quality parameter-landscape metric data set was constructed. Threshold values of landscape metrics that induced sudden changes in water quality were analyzed using the bootstrap method applied to 1000 random samples extracted from data set. Finally, mechanisms of landscape patterns that affected river water quality were quantitively explored. The following results were obtained: (1) The key area of landscape that impacted water quality in the Dongjiang Lake Basin was the 400 m buffer zone; (2) Seasonal differences were observed in water quality changes, which better explained by landscape metrics in the dry season than in the wet season. Moreover, water quality was most influenced by landscape configuration metrics. The influence of landscape topographic metrics was greater than that of composition metrics in the dry season, whereas the opposite was true in the wet season; and (3) In this watershed, the largest patch index of grassland and landscape shape index of built-up land were the key metrics at the sub-basin and 400 m buffer zone, respectively. If the largest patch index of grassland was below 8.5% or the landscape shape index of built-up land exceeded 1.5, the water quality of the rivers flowing into the lake was prone to a risk of significant decline, which has an important guiding significance to the optimization of land use pattern.