极端天气下三峡库区土地利用对河流水质的多时空尺度影响

为探究极端天气下流域内水质对土地利用的响应关系,本研究基于不同空间尺度(1000 m河段缓冲区、500 m河岸带缓冲区及子流域)的土地利用指数以及旱季(2019年11月)、雨季-洪水期(2020年7月)和雨季-干旱期(2022年8月)的水质数据,探究流域内土地利用对水质的多时空尺度影响,从而得到保护流域水质和规划流域内土地利用格局的最佳时空尺度和对水质影响最显著的预测因子。研究表明:(1)流域水质受极端天气影响,降雨会增强水体的稀释能力,高温会加快水中微生物反应速率,具体表现为雨季-洪水期的水质较好,雨季-干旱期次之,旱季较差。(2)土地利用对水质指标的影响存在时空尺度效应,土地利用在子流域和旱季尺度下对河流水质影响最显著。(3)不同土地利用指数对流域水质影响存在差异,耕地、林地、斑块密度、最大斑块指数和边缘密度是影响水质指标最显著的解释变量。其中林地与多数水质指标具有负相关关系,建设用地、耕地、斑块密度与较多水质指标存在正相关关系。本研究结果为合理规划土地利用格局以及保护河流水质提供科学依据,对三峡库区环境可持续发展及生态保护具有一定意义。     

考虑空间尺度效应的云南异龙湖流域主要入湖河流污染源解析

定量解析污染源对水质影响的贡献是水环境精细化管理的重要基础。目前多通过水质和土地利用类型的关系以解析水体污染源的研究,忽略了空间尺度的差异性,引发景观配置不合理的后果。为此,本研究依据考虑空间尺度效应的污染源解析方法,基于异龙湖流域3条主要入湖河流的入湖口监测断面对雨季和旱季的水质数据进行研究。同时利用绝对主成分—多元线性回归模型(APCS-MLR)和bioenv分析揭示河道不同尺度缓冲区的土地利用变化对水质的影响并解析河流主要污染源。研究结果表明:(1)异龙湖主要入湖河流水质表现出季节性差异,旱季期间3条主要入湖河流的浊度、化学需氧量(COD_Cr)、氨氮(NH₃-N)、总磷(TP)和总氮(TN)浓度平均值相比于雨季减幅分别为39.53%、39.93%、94.48%、38.29%和1.72%。其中,入湖河流水体中的TN在旱季和雨季的超标率分别为58%和74%,成为首要污染物;(2)在旱季,20 m缓冲区尺度内河流水质受耕地和裸地占比影响较大,随着空间尺度的扩大,至50～300 m缓冲区尺度时建设用地、林地及水体占比对水质的影响增加;在雨季,C...     

城镇化下河流水质变化及其与景观格局关系分析——以太湖流域苏州市为例

以河流近域景观格局与水环境质量间的关系为研究对象,基于2001年及2010年两期土地利用类型以及7条典型河流的溶解氧、氨氮、高锰酸盐指数、总磷、总氮5项水质指标,分析城镇化下苏州市河流水质与景观格局之间的关系及其变化规律.结果表明:(1)苏州市河流水质状况总体较差,但呈现一定的好转趋势.(2)河流水质受到城镇用地、旱地及水田的综合影响,并表现出尺度效应.其中城镇用地与旱地对河流水质恶化具有明显的作用,水田则反之.2001-2010年城镇用地及水田对水质的影响程度有所减弱,旱地则增强.(3)蔓延度指数、最大面积斑块比例对河流水质呈现负相关,斑块数量、斑块密度、香农均匀度指数、香农多样性指数则与水质呈现正相关.景观格局对于水质的影响在大范围缓冲区更为显著.研究结果可为苏州水环境管理及太湖流域城市空间开发提供一定的参考依据.     

典型网状河网区域土地利用和景观格局对地表季节水质的影响——以江苏省溧阳市为例

地表水质受区域景观组成及其空间配置的影响较大,了解景观特征与水质之间的关系可以极大地提高潜在污染的可预测性和污染物输出的评估能力. 以典型网状河网区域(江苏省溧阳市)为例,研究了土地利用和景观格局特征对地表季节水质的影响. 本研究基于2017年每单月从12个监测断面收集的21个水质指标,首先分析了多尺度缓冲区(500、1000、1500、2000、2500和3000 m)内土地利用和景观格局特征,然后通过主成分分析选取12个指标作为主要水质因子,采用冗余分析确定景观因子对水质指标的最佳影响尺度,最后采用偏最小二乘回归(PLSR)探究了最佳影响尺度下景观因子对季节水质的影响. 结果表明,2500 m缓冲区是该区域景观因子对水质指标的最佳影响尺度,旱季大多数水质指标PLSR模型的显著性和预测能力比雨季强. 雨季大多数水质指标都受园地、林草地、散布与并列指数(IJI)和香农均匀度指数(SHEI)的重要影响,并且这些景观因子与除pH和溶解氧浓度之外的其他水质指标均呈负相关. 在旱季,溶解氧、石油类、化学需氧量、总氮和总磷浓度受土地利用的影响最大; 另外,IJI是电导率、硫酸盐和亚硝酸盐氮浓度的最重要影响因子,而SHEI对硫化物和总悬浮物浓度的影响最大. 此外,景观指数对雨季水质的影响更大. 本研究结果揭示了网状河网区域土地利用/景观格局与季节性水质的关系,为区域水环境管理和景观格局优化提供了科学依据.     

山地城市河流土地利用结构对水质的影响--以重庆市为例

以重庆主城区6条次级河流为研究区域,运用遥感和地理信息系统计算研究区土地利用构成,借助相关性分析和冗余分析等数理统计手段,分析监测断面汇水区内不同尺度土地利用结构与水质指标间的相关关系.结果表明:研究区土地利用结构以建设用地和林地为主,未利用地和农业用地所占面积比例较少;研究区土地利用结构对各水质指标有重要影响,其中建设用地和农业用地对河流水质恶化具有明显的作用,河流沿岸林地布局能显著改善水质,但随着雨季的到来林地将成为硝态氮的来源.冗余分析进一步证实土地利用类型对水环境有一定影响.研究成果对重庆市河流水环境管理具有重要的实际指导意义,并可为山地城市河流水环境研究提供借鉴.     

三峡库区土地利用对河流溶解性有机质的多时空尺度影响

三峡库区拥有目前世界上规模最大的水利枢纽工程,自投入使用以来,为长江流域提供了丰富的水源及电力,促进了经济的发展,但同时也对该区域的生态环境造成了严重的冲击。澎溪河流域作为三峡库区长江流域干流的典型回水区和消落带,是众多学者研究三峡库区生态环境变化的重点区域。为探究不同时空尺度下土地利用对河流溶解性有机质（DOM）的影响,以澎溪河流域为研究对象,基于紫外-可见光谱分析和三维荧光光谱矩阵-平行因子分析,结合河段缓冲区、河岸带缓冲区及子流域3种空间尺度的二级土地利用类型,解析了旱雨季水体DOM的组成及来源特征,并采用相关分析和冗余分析方法探讨了3种空间尺度下土地利用方式对旱雨季水体DOM的多时空尺度影响。结果表明：（1）旱季水体DOM荧光组分以陆源类腐殖质所占比例更大,雨季水体DOM荧光组分以富里酸贡献为主。（2）流域内陆源输入和内源产生对水体DOM丰度均有贡献,雨季较旱季水体DOM的陆源性更强,自生源特征较弱。（3）土地利用在雨季和子流域尺度下对水体DOM的影响更显著,其中,雨季子流域尺度下,土地利用指数对水体DOM参数的解释率为90.35%。（4）不同土地利用方式对水体DOM产生的影响...     

2010-2011水文年浙江省环太湖河道水质水量及污染物通量

根据2010-2011水文年浙江省环太湖河道水质水量同步监测资料,分析了进出太湖的水量、水质及污染物通量的时空变化.监测期内,浙江省入湖水量为22.890×108m3,出湖水量为31.576×108m3,环湖河道水质总体上保持稳定,主要污染物指标基本处于Ⅱ～Ⅲ类标准.污染物通量的估算结果表明,环湖河道的高锰酸盐指数、氨氮、总磷和总氮通量均以出湖为主,入湖污染物通量的减少主要源于入太湖河流倒流流量的增加.     

北方半干旱区土地利用/覆被变化对湖泊水质的影响:以岱海流域为例(2000-2018年)

土地利用/覆被变化对明晰气候变化和人类活动对湖泊水环境的影响有重要作用.以北方典型农牧交错的岱海流域为研究对象,基于遥感解译技术、马尔可夫转移矩阵、综合污染指数法等方法,对2000-2018年岱海流域土地利用/覆被和湖泊水质的变化进行分析,并结合冗余分析法和计量分析模型探究长时间序列尺度下土地利用/覆被变化对湖泊水质的...     

基于“水文频率-水质”拟合曲线的河流水质变异与等级特征值分析方法

时空特征分析对全面掌握水质变异规律具有重要意义,但现有的水质时空特征分析方法仍存在水质变异次序不分、水质变幅极值不清、水质评价特征值不明等不足。为更加清晰地探析水质时空特征信息,以秦淮河为研究对象,参考工程水文学经验频率法,建立“水文频率-水质”拟合曲线用于探索流域内高/低活动区不同时间段和丰/枯水期不同河段水质变异特征,并与传统的箱线图法进行对比。结果表明:与箱线图相比,“水文频率-水质”拟合曲线可量化关键水质评判点与特征值信息,使水质时空变异过程更为清晰。在时间上“水文频率-水质”拟合曲线的最佳形式为线性曲线,水质浓度一般不会发生突变;在空间上“水文频率-水质”拟合曲线的最佳形式为指数曲线,水质浓度有较大可能发生突增。各时间段高活动区氮磷浓度大于低活动区,各水体断面丰水期氮磷浓度低于枯水期。该方法分析过程简单方便,结果直观有序,能将水质信息以统计规律自动反映出来,在水质采样点、采样时间和采样频率典型时可作为优选方法用于河流水质时空特征研究。     

梯级筑坝对黑河水质时空分布特征的影响

为探究梯级大坝建设对河流水质变化规律的影响,将黑河上中游划分为坝上河段、坝下河段及自然河段,于2017年12月-2018年8月选取了24个主要控制断面进行水质调查,并采用多元统计的方法对比分析了不同时空尺度上的水质分布特征.结果表明:黑河上中游水质时空变化的主要影响因子为水温(WT)、pH值、溶解氧(DO)、电导率(EC)、总氮(TN)、总磷(TP)和五日生化需氧量(BOD_5).空间尺度上,WT、EC、BOD_5、高锰酸盐指数(CODMn)、TN等指标具有显著性差异,其中坝上河段受BOD_5、CODMn影响较大,自然河段WT、EC和TN为关键指标,而各个因子对坝下河段水质影响较小.时间尺度上,WT、EC、BOD_5、氨氮与季节变化存在明显相关性,是不同河段水质时间变化的控制因子,且大多数水质因子在非汛期变化最明显.降水、温度、水文条件等季节性影响因素和梯级水库联合运用模式是该区域水质时间差异的主要原因;空间差异主要受祁连、张掖地区外源性污染物排放以及筑坝环境下水动力条件改变而产生的沉积滞留效应和沿程累积效应影响.研究表明,外源性污染源依然是导致水质变差的主要因素,梯级筑坝则是导致水质变差的间接因素.因此控制该区域人类活动所造成的外源性污染源,并针对不同种类污染物的季节变化特征实施合理的水库运行方式是改善水电梯级开发河段水质状况的关键.     

土地利用结构与景观格局对鄱阳湖流域赣江水质的影响

于2015年1月和7月采集赣江干流及支流34个采样点水样,测定电导率、水化学离子、无机氮等水质指标.利用赣江流域2014年30 m分辨率的土地利用数据,以流域景观类型占比表征土地利用结构,景观指数表征景观格局;采用Pearson相关分析、Bioenv分析、Mantle检验与方差分解等方法分析流域土地利用结构与景观格局对赣江水质的影响.结果表明:上游Cl^-、Na⁺浓度最高,中游电导率、Cl^-、Na⁺、K⁺、Ca²⁺等水质指标最低,下游电导率、HCO₃^-、SO₄^2-、Mg²⁺、Ca²⁺、NO₃^--N等水质指标最高.居民建设用地是对水质影响最显著的单一土地利用类型.林地、水田与居民建设用地是对水质影响最显著的土地利用类型组合.平均最近邻体指数是对水质影响最显著的单一景观指数,斑块个数、斑块...     

Impact of environmental factors on water quality at multiple spatial scales and its spatial variation in Huai River Basin,China

Quantitative assessment of water quality and its spatial variation identification, as well as the discernment of primary factors affecting water quality are in its urgent in water environment management. In this study, four key water quality indicators,namely, ammonia nitrogen(NH_4~+-N), permanganate index(COD_(Mn)), total phosphorus(TP) and total nitrogen(TN) at 71 sampling sites were selected to evaluate water quality and its spatial variation identification. More concerns were emphasized on the anthropogenic factors(land use pattern) and natural factors(river density, elevation and precipitation) to quantify the overall water quality variations at different spatial scales. Results showed that the Yi-Shu-Si River sub-basin had a better water quality status than the Huai River sub-basin. The moderate polluted area nearly distributed in the upper and middle reaches of the Shaying River and Guo River. The high cluster centers which were surrounded with COD_(Mn), NH_4~+-N, TN and TP mainly also distributed in the upper and middle reaches of the Shaying River and Guo River. Redundancy analysis showed that the 200 m buffer area acted as the most sensitive area, which was easily subjected to pollution. The precipitation was identified as the most important variables among all the studied hydrological units, followed by farmland, urban land or elevation. The point source pollution was still existed although the non-point source pollution was also identified. The urban surface runoff pollution was severer than farmland fertilizer loss at the sub-basin scale in flood season, while the farmland showed "small-scale" effects for explaining overall water quality variations. This research is helpful for identifying the overall water quality variations from the scale-process interactions and providing a scientific basis for pollution control and decision making for the Huai River Basin.     

Evolution of the variability of surface temperature and vegetation density in the great plains

This study focuses on how the variability of land surface temperature and vegetation density at the SGP ARM-CART site changes over episodic (day to day) and seasonal time scales using AVHRR satellite data. Four drying periods throughout the year are analyzed. Land surface temperature had an erratic relationship with time exhibiting no deterministic pattern from day-to-day or season-to-season. Furthermore, it did not exhibit spatial pattern persistence. On the other hand, vegetation density had a consistent spatial pattern and temporal decay during average length drying periods (less than 7 days) as well as within a season. However, there were distinct differences in the seasonal pattern of variation between winter and growing seasons. In addition, the paper highlights a methodology to quantify the relationships that exist at the land surface between the primary parameter of interest and the controlling variables.     

The influence of land use patterns on water quality at multiple spatial scales in a river system

The influence of land use patterns on water quality in a river system is scale‐dependent. In this study, a four‐order hierarchical arrangement method was used to select water sampling sites and to delineate sub‐basins in the Daliao River Basin, China. The 20 sub‐basins were classified into four spatial scales that represented four different stream orders. Pearson correlation analysis was used to quantify relationships between land use composition and the river's physical‐chemical variables for all samples collected. This analysis showed that the presence of forest cover was associated with higher water quality at the scale of the whole basin. The scale effects of land use patterns on water quality were then examined using stepwise multiple regression analysis that compared different land use types with water quality variables. The results from this analysis showed that urban areas, as opposed to forest areas, became the most significant contributors of water pollutants when scale effects were considered. The influence of urban land cover on water pollution was significantly higher at larger scales. The lack of a significant regression correlation for the forest land use type at smaller scales revealed that forest located upstream of the Daliao River Basin did not provide a buffer for improved water quality. Further analysis showed that this result could be because of disproportionate spatial distributions for forest and urban land use types. The topographic characteristics of sub‐basins, such as average slope (S) and size (A), were determined to be secondary explanatory variables that affected land use impacts on stream water quality. Areas with steep slopes were associated with increased water oxygenation, whereas areas with flatter slopes were associated with higher concentrations of pollutants. These results are significant because they can provide a better understanding of the appropriate spatial scale required for effective river basin management in the future. Copyright © 2013 John Wiley & Sons, Ltd.     

Statistical characterization of impact of system variables on temporal dynamics of groundwater in highly weathered regoliths

In situations where the water table fluctuates during the rainy season the characterization of the impact of system variables on the temporal dynamics of the groundwater (GW) is essential to improve the understanding at catchment or regional scale behaviour of GW. In this study the appropriateness of the statistical parameters; mean, median, the 80^th percentile (PC80), coefficient of variation (CV), correlation coefficient (r), and multiple regression models were assessed to characterize the impact of system variables on the temporal dynamics of hydraulic head relative to ground surface (HH) during rainy seasons. The study was conducted from 1999 to 2003 in the wet tropical Johnstone River catchment (JRC) in north‐east Queensland, Australia. Piezometer wells were installed at 32 sites under cropping to 5–90 m depth on different soil types, landscape positions, and varying proximity to surface water bodies (i.e. four system variables). The HH was measured, at least at 10–15 day intervals during 1–5 consecutive rainy seasons. The HH in the 32 wells fluctuated throughout each of the five rainy seasons. The mean HH averaged over the seasons ranged from 1·1 to 17·2 m across the wells, the median from 0·9 to 17·3 m, and the PC80 from 0·3 to 16·1 m. The temporal behaviour of HH characterization by mean of means of HH, the mean of medians of HH, and the mean of PC80 of HH, indicated the HH can be classified to belong to three different groups for each one of these parameters. The impact of the system variables on temporal dynamics, explored using multiple regression procedure, indicated that the model for median was marginally better than mean. The CV was found to be most appropriate parameter to characterize the impact of GW system variable (aquifer type), a component of the system variables, on temporal dynamics. The interactions of GW (i) belonging to different GW system and (ii) at shoulder with footslope in a landscape were best characterized by simple linear correlations. Copyright © 2007 John Wiley & Sons, Ltd.