内陆水体后向散射系数模拟研究

在利用半分析方法结合光学闭合原理模拟水体后向散射系数的过程中,参考波长的选择对最终结果有较大影响.为了得出最佳参考波长的影响因子,利用太湖、巢湖和滇池的野外实测数据,对后向散射系数进行模拟,进而分析水体的最佳参考波长与其对应的水质参数浓度之间的变化规律.同时,建立了太湖、巢湖和滇池水体的后向散射系数曲线的幂函数光谱模型,获得的光谱指数分别为2.643±0.317、 2.719±0.242、 1.638±0.534.结果表明：①以整个湖泊为研究对象时,最佳参考波长随着湖泊水体中总颗粒物浓度c_SPM、有机颗粒物浓度c_SPOM和叶绿素浓度c_CHL平均值的增大而向长波方向移动,太湖、巢湖和滇池水体的最佳参考波长分别为695、 720和730 nm;②以单个湖泊的各个样点为研究对象时,由于内陆湖泊光学特性的复杂性,最佳参考波长的影响因子存在一定差异,但c_SPM是一个共同的影响因子.此外,过高的c_CHL将削弱水质参数浓度与最佳参考波长间的规律性;③在以无机颗粒物为主的水体中,后向散射系数与总颗粒物浓度之间存在更好的相关性,如在太湖水体中,R²达到0.852.     

富营养水体中常绿水生植被组建及净化效果研究

1992～1993年在富营养湖泊五里湖中开展了常绿型人工水生植被组建实验,在面积为2000m²的半封闭式围隔实验区中,选用耐寒植物伊乐藻和喜温植物菱及风眼莲,组建成了常绿型人工水生植被。这种常绿型人工水生植被不仅使实验区内常年保持较好的水质,而且对外来污染冲击有很强的缓冲能力。它可用于水源保护、局部性水质控制、污水净化生态工程、小型富营养水体的生态恢复等。如能解决耐寒型沉水植物伊乐藻与喜温型沉水植物种类间的衔接过渡,这种常绿型人工水生植被技术还可望用于富营养水体中天然水生植被的恢复。     

RESPONSE OF NORTH AMERICAN FRESHWATER LAKES TO SIMULATED FUTURE CLIMATES1

ABSTRACT: We apply a physically based lake model to assess the response of North American lakes to future climate conditions as portrayed by the transient trace-gas simulations conducted with the Max Planck Institute (ECHAM4) and the Canadian Climate Center (CGCM1) atmosphere-ocean general circulation models (A/OGCMs). To quantify spatial patterns of lake responses (temperature, mixing, ice cover, evaporation) we ran the lake model for theoretical lakes of specified area, depth, and transparency over a uniformly spaced (50 km) grid. The simulations were conducted for two 10-year periods that represent present climatic conditions and those around the time of CO₂ doubling. Although the climate model output produces simulated lake responses that differ in specific regional details, there is broad agreement with regard to the direction and area of change. In particular, lake temperatures are generally warmer in the future as a result of warmer climatic conditions and a substantial loss (> 100 days/yr) of winter ice cover. Simulated summer lake temperatures are higher than 30°C over the Midwest and south, suggesting the potential for future disturbance of existing aquatic ecosystems. Overall increases in lake evaporation combine with disparate changes in A/OGCM precipitation to produce future changes in net moisture (precipitation minus evaporation) that are of less fidelity than those of lake temperature.     

A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.     

Enhancing perspectives on lake impairments using satellite observations: A case study on High Rock Lake,North Carolina

Stakeholders developing water quality improvement plans for lakes and reservoirs are challenged by the sparsity of in-situ data and the uncertainty ingrained in management decisions. This study explores how satellite images can fill gaps in water quality databases and provide more holistic assessments of impairments. The study site is an impaired water body that is serving as a pilot for improving state-wide nutrient management planning processes. An existing in-situ database was used to calibrate semi-analytical models that relate satellite reflectance values to turbidity and total suspended solids (TSS). Landsat-7 images from 1999 to 2020 that overpass High Rock Lake, North Carolina were downloaded and processed, providing 42 turbidity and 39 TSS satellite and in-situ match-ups for model calibration and validation. Model r-squared values for the fitted turbidity and TSS models are 0.72 and 0.74, and the mean absolute errors are 14.6 NTU and 3.2 mg/L. The satellite estimates were compared to the in-situ data and simulated TSS values produced by a calibrated hydrologic-hydrodynamic model. The process-based model is considered less accurate than the satellite model based on statistical performance metrics. Comparisons between data sources are illustrated with time series plots, frequency curves, and aggregate decision metrics to highlight the dependence of lake impairment assessments on the spatial and temporal frequency of available data and model accuracy.     

青海省东部农业区参考作物蒸散量的变化及对气象因子的敏感性分析

使用FAO推荐的Penman-Monteith公式计算了青海省东部农业区7个气象代表站的逐日参考作物蒸散量(ET₀),运用多窗谱方法(MTM)对青海省东部代表站的ET₀的变化周期进行了分析,同时,分析了影响ET₀的主要气象要素的变化趋势,运用基于偏导数的敏感系数法分析了生长季ET₀对气温、日照时数、相对湿度、风速的敏感性,结果表明,青海省东部农业区的7个站点有比较一致的19.23~22.22 a的周期;整个东部农业区的气温(最高温度、最低温度、平均温度)呈明显的上升趋势,日照时数、风速、相对湿度则随纬度的变化而趋势不同,北纬36°以南的两个站日照时数、风速均有增加的趋势,相对湿度则减小,以北的5个站则呈相反的变化;ET₀对日照时数最为敏感,其次是气温、相对湿度和风速;敏感系数在整个生长季随气象因子的变化而变化,日照时数敏感系数呈波动状,最大值出现在4月,最小值出现在9月,气温敏感系数呈现单峰型变化,最大值出现在7月,风速敏感系数则呈单谷型变化,最小值出现在7月。     

东湖、汤逊湖和梁子湖沉积物磷形态及pH对磷释放的影响

文章采用淡水沉积物中磷形态标准测试程序(SMT)研究了东湖、汤逊湖和梁子湖沉积物中磷的形态分布,并比较了不同pH条件下沉积物磷释放特征的差异性。结果表明:东湖沉积物总磷质量分数最高,平均值1.232 mg.g-1,其次为汤逊湖(0.762mg.g-1),梁子湖沉积物总磷质量分数最低(0.572 mg.g-1);3个湖泊上覆水总磷质量浓度也表现出类似的变化规律,线性相关性分析显示上覆水中总磷质量浓度与沉积物总磷质量分数显著正相关。东湖和梁子湖沉积物总磷中无机磷和有机磷所占比例较接近,汤逊湖无机磷所占比例远低于有机磷。不同湖泊之间磷形态的分布并没有一定的规律性,湖泊的地理分布以及人为因素可能是造成磷形态差异的主要因素。当pH为2.0~7.0时,3个湖泊沉积物中溶解性活性磷(SRP)释放量均呈先增加后减小的趋势;当pH为7.0~12.0时,SRP释放量呈增加趋势。相关分析结果表明,SRP的释放与有机质的质量分数无显著相关性。方差分析结果显示3个湖泊沉积物在黏粒和粉粒组成上均没有显著差异(P>0.1),表明实验样品的粒径组成不是造成各个湖泊间磷释放差异的原因。不同pH条件下,SRP释放量与沉积物总磷质量分数显著正相关;酸性环境下,SRP释放量与酸式磷(HCl-P)的相关性优于碱式磷(NaOH-P),碱性环境下则刚好相反。     

再生水补给城市河湖水生态系统构建及管护技术体系研究应用—以圆明园为例

提出了"再生水水源补给城市河湖水生态系统构建及管护技术体系",并在圆明园开展了推广应用,设计建设了近70 hm2再生水水源补给城市河湖水生态系统构建及管护示范区.结果表明,该技术可有效改善水体景观、水质及水生态状况:浊度明显降低,示范区浊度大多小于3NTU(饮用水浊度国家标准1NTU),感官效果明显优于修复前;总磷平均...     

南水北调东线山东境内调蓄湖库蓝藻种群分布特征及环境驱动因子

为掌握南水北调东线山东境内调蓄湖库在工程运行前后蓝藻种群的分布情况及其环境驱动因子,于2010～2019年的5～11月对南四湖、东平湖、大屯水库、东湖水库和双王城水库进行藻类和水环境调查.共检出浮游蓝藻44种,其中丝状蓝藻23种.湖泊假鱼腥藻、拉氏拟柱孢藻、铜绿微囊藻和惠氏微囊藻在各调蓄湖库的检出频次和密度均较高,是主要有害蓝藻种.通过分析各调蓄湖库蓝藻种群的分布特征,发现丝状蓝藻在水力扰动较大水体中的生长优势较为明显,应成为日后调蓄湖库蓝藻风险防控的重点.Pearson相关性分析和广义线性拟合曲线结果显示,总氮、总磷、水温和水深是影响调蓄湖库主要有害蓝藻种生长的主要环境驱动因子.氮磷营养盐对于有害蓝藻种的生长具有显著的促进作用.湖泊假鱼腥藻具有良好的温度适应性,在夏初秋末仍能成为优势种,而当水温大于25℃时,拉氏拟柱孢藻、铜绿微囊藻和惠氏微囊藻具明显的生长优势.此外,较小的水深更利于拉氏拟柱孢藻的生长.建议在加强控制湖库氮磷营养盐输入的基础上,在夏初和秋末对湖泊假鱼腥藻进行重点监控,并在高温时期密切关注浅水区拉氏拟柱孢藻的生长情况,保障水质安全.     

Bioremediation of Acidic and Metalliferous Drainage (AMD) through organic carbon amendment by municipal sewage and green waste

Pit lakes (abandoned flooded mine pits) represent a potentially valuable water resource in hot arid regions. However, pit lake water is often characterised by low pH with high dissolved metal concentrations resulting from Acidic and Metalliferous Drainage (AMD). Addition of organic matter to pit lakes to enhance microbial sulphate reduction is a potential cost effective remediation strategy. However, cost and availability of suitable organic substrates are often limiting. Nevertheless, large quantities of sewage and green waste (organic garden waste) are often available at mine sites from nearby service towns. We treated AMD pit lake water (pH 2.4) from tropical, North Queensland, Australia, with primary-treated sewage sludge, green waste, and a mixture of sewage and green waste (1:1) in a controlled microcosm experiment (4.5 L). Treatments were assessed at two different rates of organic loading of 16:1 and 32:1 pit water:organic matter by mass. Combined green waste and sewage treatment was the optimal treatment with water pH increased to 5.5 in only 145 days with decreases of dissolved metal concentrations. Results indicated that green waste was a key component in the pH increase and concomitant heavy metal removal. Water quality remediation was primarily due to microbially-mediated sulphate reduction. The net result of this process was removal of sulphate and metal solutes to sediment mainly as monosulfides. During the treatment process NH(3) and H(2)S gases were produced, albeit at below concentrations of concern. Total coliforms were abundant in all green waste-treatments, however, faecal coliforms were absent from all treatments. This study demonstrates addition of low-grade organic materials has promise for bioremediation of acidic waters and warrants further experimental investigation into feasibility at higher scales of application such as pit lakes.