共查询到20条相似文献，搜索用时 191 毫秒
1.
2.
秋季太湖悬浮物高光谱估算模型 总被引：10，自引：0，他引：10
2004年10月,在太湖设置67个采样点,现场测量了水体遥感反射比、后向散射系数和辅助参数,实验室分析了水体的悬浮物浓度和水色要素吸收系数.本文在对遥感反射比光谱分析的基础上,比较了几种水体遥感反射比光谱估算悬浮物浓度的方法,结果发现广泛应用的带比值项的算法,虽然可以应用于太湖总悬浮物浓度估算,但是普遍存在相对误差较高的弱点.通过对光谱的分析,确定了750hm单波段算法的参数,并提出了利用近红外812nm波峰高度来估算水体悬浮物的方法.文中还详细阐述了为什么比值算法等在太湖水体悬浮物浓度估算中相对误差比较高,并解释了利用近红外估算精度高的原因,并指明以上算法在遥感应用中的优点和不足,以及现实水体(水质)遥感对现有遥感器配置和遥感算法的需求. 相似文献
3.
基于半分析模型的波段最优化组合反演混浊太湖水体叶绿素a 总被引：5，自引：0，他引：5
内陆水体叶绿素a浓度定量反演是水质遥感的热点与难点.本文基于对内陆水体叶绿素a、悬浮物、溶解有机物与水分子的光谱特征分析,从半分析生物光学模型出发,利用太湖实测的水面 ASD 高光谱遥感数据三波段组合,进行迭代优化,得到与叶绿素浓度密切相关而受悬浮物与黄色物质影响小的最优波段组合模型,反演精度较高,其决定系数和均方根误差分别为 0.8358、3.816mg/m3,该方法可以有效地反演高浓度悬浮物主导光学特性的水体叶绿素a浓度. 相似文献
4.
风浪扰动下湖滨带悬浮物和营养盐响应特征 总被引：1，自引：0，他引：1
为研究风浪扰动下沉积物起悬过程中悬浮物浓度的分布特征和水体营养盐时空分布状况,以太湖西北湖滨带为例,选择代表4种不同生境的6个点位进行了连续12 d的野外观测.利用高精度分层同步采样装置,采用重量法计算悬浮量,并对悬浮过程中总磷(TP)、总氮(TN)、铵态氮(NH_4~+-N)和硝态氮(NO_3~--N)浓度进行分析.结果表明:风速是引起太湖西北湖滨带水体悬浮物增加的主要因素,沉积物悬浮的临界风速为3.6 m/s.各点位悬浮物浓度的均值差异明显,表现为:无植被区植被区河口区湖心区.太湖西北湖滨带水体氮、磷浓度日变化幅度较大,TN浓度为1.82~4.96 mg/L,TP浓度为0.10~1.47 mg/L.NH_4~+-N和NO_3~--N浓度分别在0.09~2.83和1.05~3.69 mg/L之间波动.近岸无植被区水柱的总悬浮量与风速的相关性最好,相关系数达到0.722;而远岸湖心区与风速的相关系数仅为0.039.悬浮物浓度除了受风情(风向和风速)的影响外,同样受水深、地形特征和水生植被的影响. 相似文献
5.
下行漫衰减系数(K_d)是描述水下光场的重要参数,决定水体真光层深度,影响着浮游藻类初级生产力及其分布特征.基于2008—2013年太湖4次大规模野外试验数据,分析太湖水体漫衰减系数特征及其影响因素,建立适用于多种卫星数据且较高精度的太湖水体490 nm处下行漫衰减系数估算模型.结果表明:无机悬浮物是太湖水体漫衰减系数的主要影响因素;红绿波段比值(674 nm/555 nm)最适合于太湖K_d(490)估算,模型反演精度较高(N=72,R~2=0.72,RMSE=0.89 m~(-1),MAPE=21.58%);利用实测光谱数据,模拟得到MODIS/EOS、OLCI/Sentinel-3、GOCI/COMS和MSI/Sentinel-2等主要传感器波段的信号,构建适用于多种卫星传感器K_d(490)估算的红绿波段模型,建模精度较高(N=72,R~20.7,RMSE0.9 m~(-1),MAPE22.0%),且进行了验证(N=37,R~20.7,RMSE0.9 m~(-1),MAPE22.0%). 相似文献
6.
水体Chl.a浓度是水质评价的一个重要指标,受悬浮物浓度季节性变化的影响,如何削弱悬浮物的光谱干扰,是实现内陆水体Chl.a浓度遥感高精度反演的难点之一.基于2011-2013年妫水河6次实测水体高光谱数据和水体Chl.a浓度数据,评价广泛应用的三波段模型和非线性拟合能力较好的支持向量机回归(SVR)模型的反演精度,使用基线校正和一阶微分方法来削弱实测高光谱中非Chl.a光谱信息.定义两种基线:750 nm的反射率值;500与750 nm的反射率值连线,基线校正为光谱反射率减去基线值.利用2013年7月的实测数据进行验证,结果表明,SVR模型比三波段模型更适合季节性浑浊水体的Chl.a浓度反演.通过基线校正筛选后的波段反射率组合作为输入变量能够提高SVR模型的反演精度,决定系数为0.68,均方根误差为3.38μg/L;线性基线校正提高三波段Chl.a估算模型的反演能力有限. 相似文献
7.
长江中下游浅水湖泊沉积物再悬浮对水下光场的影响研究--以龙感湖和太湖为例 总被引：6，自引：0，他引：6
基于2003年7月在龙感湖、太湖梅梁湾以及2004年7月在太湖站栈桥的连续不同风浪条件下水下光场原位观测资料,分析风浪作用引起的沉积物再悬浮对PAR衰减,吸收系数及真光层深度的影响.结果表明,在龙感湖,小风浪、中风浪和大风浪的PAR衰减系数分别是1.74,2.02,2.45 m-1,400～700 nm光谱衰减系数变化范围分别为0.98～2.97,1.34～3.95,1.82～5.40 m-1;在太湖梅梁湾,小风浪、中风浪和大风浪PAR衰减系数分别是2.63,3.72,4.37 m-1,从小风浪到、中风浪、大风浪衰减系数分别增加了41％,66％;太湖站栈桥边PAR波段积分CDOM吸收系数在中风浪和大风浪的值分别为0.26,0.28 m-1,浮游植物吸收系数从中风浪到大风浪反而由0.76降低到0.49m-1,沉积物再悬浮引起非藻类颗粒物的吸收则由0.94增加到1.73 m-1,增加了84％,总悬浮物颗粒物吸收由1.70增加到2.22 m-1,增加了30.6％.非藻类颗粒物吸收对总吸收系数贡献最大,中风浪、大风浪下贡献率分别达44.14％,65.05％.龙感湖,梅梁湾,栈桥边3站点从中风浪到大风浪,PAR真光层深度分别降低0.40,0.19,0.20 m.透明度、PAR衰减系数、真光层深度与悬浮物浓度、风速、波高等均存在显著性线性相关,并且与悬浮物中无机颗粒物相关性最好,而与叶绿素a、脱镁叶绿素及溶解性有机碳相关性很低.由此可见,在龙感湖和太湖等长江中下游浅水湖泊,风浪扰动引起悬浮物浓度的增加尤其是无机颗粒物的增加是影响水下光场的主导因素. 相似文献
8.
2008年11月、2009年4月,分别对太湖水体以及2009年6月对巢湖水体进行野外实验.对太湖水体遥感反射率进行因子分析,并利用遥感反射率的不同因子,对叶绿素和总悬浮物浓度进行反演,并对反演因子的普适性进行验证.利用第一因子反演太湖春季叶绿素浓度,平均相对误差为22.1%,均方根误差为3.48g/L,利用该方法反演巢湖、太湖秋季水体的叶绿素浓度没有取得较好的效果;利用第二因子反演太湖春季总悬浮物浓度,平均相对误差为13.9%,均方根误差为11.33mg/L,利用该因子反演巢湖、太湖秋季水体的总悬浮物浓度同样取得较好效果.结果表明:利用遥感反射率的第一因子对叶绿素浓度进行反演,该方法不具有普适性;利用遥感反射率的第二因子对总悬浮物浓度进行反演能取得较好的结果,此方法具有一定的普适性. 相似文献
9.
太湖水体叶绿素浓度反演模型适宜性分析 总被引：2，自引：0，他引：2
为确定适合太湖水体叶绿素的反演算法,为同类卫星数据的建模和应用提供参考,本文根据太湖2007年11月、2009年4月和2011年8月实测水质参数以及同步光谱数据,结合水色遥感传感器MODIS、MERIS、GOCI及我国自主发射的HJ-1号卫星CCD传感器波段参数,基于差值模型、比值模型、三波段模型及APPEL模型,分别建立太湖水体叶绿素浓度反演模型,并分析模型的适宜性.结果显示,基于不同传感器数据APPEL模型的决定系数为0.7308~0.8107,模型相对误差为15%~24%,均方根误差为21%~32%;三波段模型基于不同传感器数据拟合的决定系数为0.6014~0.7610,相对误差为28%~36%,相对均方根误差为39%~46%;差值模型决定系数为0.4954~0.7244,相对误差为39%~53%,相对均方根误差为51%~72%;比值模型决定系数为0.4918~0.7098,相对误差为41%~55%,相对均方根误差为56%~75%.相比较而言,APPEL模型的稳定性较强,适合于不同传感器数据的太湖水体叶绿素浓度的反演.此外,相应不同传感器波段位置、波段宽度对模型反演的精度和稳定性的影响也不同,当波段位置接近叶绿素特征波长时,较窄的波宽有利于模型精度的提高,波段位置和叶绿素浓度特征波长相差较大时,合理增加波谱范围有利于叶绿素特征信息的获取. 相似文献
10.
基于叶绿素荧光峰特征的浑浊水体悬浮物浓度遥感反演 总被引：4，自引：0，他引：4
内陆水体光学特性复杂,其水质参数遥感反演是当前环境遥感研究的热点与难点.2004年10月在太湖实测了67个站点的遥感反射率与相应站点水质参数浓度,通过对水体反射率光谱的分析发现,秋季太湖悬浮物主导了水体光学特性,叶绿素荧光峰的特征主要体现为悬浮物浓度的变化.据此建立了基于水面实测岛光谱遥感反射率数据的叶绿素荧光峰特征与悬浮物浓度之间的拟合关系,发现二者具有很好的响应关系.具体分析了叶绿素荧光峰绝对高度、基线高度、归一化高度(分别归一化到560nm附近最大反射率波段与近红外810nm附近最大反射率波段)及荧光峰积分面积(包括积分总面积、基线以下面积与基线以上面积)等儿种光谱特征与悬浮物浓度之间的关系,其相关系数(R2)分别为0.8822、0.7483、0.8901、0.8547、0.8927、0.8877、0.8632,平均相对误差分别为27.25%、41.03%、27.11%、25.75%、24.91%、25.47%、27.54%.总体反演精度较高,其中总积分面积法效果最好,基线高度法效果最差,而叶绿索荧光峰波段的位移与悬浮物浓度之间不存在明显的相关性.研究结果表明叶绿素荧光峰特征在浑浊内陆水体悬浮物浓度信息提取中具有很好的应用前景,该方法可为浑浊的二类水体悬浮物遥感反演提供了一个新思路. 相似文献
11.
为明晰太湖风浪的空间分布及季节变化,在湖心区设立波浪观测站,利用其记录的波浪数据证明SWAN模型能够较好地模拟太湖风浪.基于所建模型,对2013年自然风场条件下太湖不同湖区风浪季节动态进行模拟分析,结果表明:受岸线、地形和岛屿等地理因素影响,大太湖的风浪总是最强,其有效波高均值为0.523 m;而东太湖风浪最小,有效波高均值为0.305 m.受盛行风场季节变化影响,太湖春、夏季有效波高均值明显大于秋、冬季.太湖波浪的能量主要来源于风场,其有效波高随风速增大而增大,两者呈极显著正相关.而风向则可以通过改变风区长度来影响风浪生消.在偏东风作用下,太湖湖西区的风浪大于东部湖区;而受盛行于冬季的偏北风影响,太湖南部水域风浪要大于北部.同时,太湖风浪的时空分布特征是造成太湖水质参数、沉积物和水生植物空间分布差异的重要原因之一. 相似文献
12.
太湖不同湖区底泥悬浮沉降规律研究及内源释放量估算 总被引：5，自引：1，他引：4
太湖是一个大型浅水湖泊,湖湾、沿岸及湖心等区域受地形影响,湖流结构及水土界面水力要素均有显著差异.针对目前对不同湖区底泥再悬浮规律差异性研究的缺失,本研究选取了3个具有代表性的点采集太湖底泥,采用矩形水槽开展底泥再悬浮模拟实验,并结合太湖二维水量水质模型及太湖全年实测数据,建立了不同湖区底泥再悬浮通量与风速之间的定量关系;通过室内静沉降实验,得到了静沉降通量与风速的相关关系;最后将底泥再悬浮实验结果参数化应用于太湖二维水量水质模型中,并对底泥悬浮沉降过程进行分解和概化,估算太湖全年内源释放量.结果表明:太湖每日的内源释放量受风速影响显著,和风速变化趋势较为接近,太湖全年进入水体的净底泥量有47.81×104t,夏季最大,冬季次之;就营养物质释放量而言,COD约为2.06×104t、总氮约为1149.05 t、总磷约为564.35 t,其中秋季营养物质释放量最小,夏季最大. 相似文献
13.
Sediment resuspension under action of wind in Taihu Lake,China 总被引：2，自引：0，他引：2
A field study was undertaken to investigate the changes of the current speed, wave parameters and sediment resuspension under different wind speeds in the Taihu Lake. The Acoustic Doppler Current Profi... 相似文献
14.
太湖波浪数值模拟 总被引：8，自引：7，他引：1
在太湖实际波浪观测的基础上,采用率定验证后的第三代动谱平衡方程,考虑实际水底地形、波浪折射、浅化、反射、破碎、湖流等条件下,对太湖波浪进行数值模拟,研究太湖波浪的主要影响因素.结果表明:SWAN模型可以较好地模拟风作用下太湖风浪的生成和传播过程,模型在太湖应用是合适的;波高、波长、波周期等波浪参数在太湖的分布与风速、风向、水深等因素密切相关;在相同风向、不同风速情况下,太湖波浪发展至稳定状态的时间不一样;在不同风向,相同风速持续作用下,有效波高达到稳定的时间差不多,变化趋势也比较相同.说明波浪的发展不光取决于风速的大小,还同风的持续吹的时间和风区长度有关. 相似文献
15.
Study on the simulation of transparency of Lake Taihu under different hydrodynamic conditions 总被引：2，自引：0，他引：2
It was indicated in this study that there were negative relations between the concentrations of suspended solid (SS) and transparency according to the analysis of measured data of Lake Taihu. Their relations in pervious studies were reviewed, which showed that the changes of transparency in Lake Taihu could be reflected by simulating suspended solid concentration (SSC). Measured data showed that the changes of SSC with wind speed were similar at different water depths. SSC increased with the increasing of wind speed. Both wave and lake current of Lake Taihu had positive relations with SSC. However, wave was the main factor affecting sediment suspension, while flow took the second place. In this study, a numerical model coupling lake current, wave and SSC of Lake Taihu was developed. In the SS model, the combined effects of wave and current were included. The amounts of suspended and deposited sediments near the lake bed surface layer were treated separately. The stochastic characteristics of turbulent flow pulsation near lake beds were also considered, and the start-up conditions of sediment suspension were introduced to the model. The model elucidated the mutual exchange processes between sediment particles in SS and active sediments within and on the bed surface layer. Simulated results showed that lake current had relatively significant effects on the SSC at littoral areas of Lake Taihu, while SSC at the central area of the lake was mainly influenced by wave. The changes of transparency with SSC were simulated for Lake Taihu using this model. Calculated results were validated by measured data with good fitness, which indicated that the model is basically suitable for the simulation and prediction of transparency of Lake Taihu. 相似文献
16.
It was indicated in this study that there were negative relations between the concentrations of suspended solid (SS) and transparency according to the analysis of measured data of Lake Taihu. Their relations in pervious studies were reviewed, which showed that the changes of transparency in Lake Taihu could be reflected by simulating suspended solid concentration (SSC). Measured data showed that the changes of SSC with wind speed were similar at different water depths. SSC increased with the increasing of wind speed. Both wave and lake current of Lake Taihu had positive relations with SSC. However, wave was the main factor affecting sediment suspension, while flow took the second place. In this study, a numerical model coupling lake current, wave and SSC of Lake Taihu was developed. In the SS model, the combined effects of wave and current were included. The amounts of suspended and deposited sediments near the lake bed surface layer were treated separately. The stochastic characteristics of turbulent flow pulsation near lake beds were also considered, and the start-up conditions of sediment suspension were introduced to the model. The model elucidated the mutual exchange processes between sediment particles in SS and active sediments within and on the bed surface layer. Simulated results showed that lake current had relatively significant effects on the SSC at littoral areas of Lake Taihu, while SSC at the central area of the lake was mainly influenced by wave. The changes of transparency with SSC were simulated for Lake Taihu using this model. Calculated results were validated by measured data with good fitness, which indicated that the model is basically suitable for the simulation and prediction of transparency of Lake Taihu. 相似文献
17.
18.
实地测试太湖水体的反射光谱,实验室分析水样,运用相关分析法探求叶绿素、悬浮物的光谱特征波段,估测叶绿素和悬浮物含量;对比LandsatETM波段,运用不同的函数曲线对相应的波段组合进行回归拟合,建立相应的估测模型,选取精度最好的两个分别对太湖的叶绿素和悬浮物含量进行估测.结果表明:(1)对多光谱遥感而言,LandsatTM/ETM是定量获取叶绿素和悬浮物的较好的数据源,但不是最适合的数据源;(2)通过ETM3与叶绿素建立一定的函数关系来估测叶绿素含量具有较高的精度,其中利用算术组合ETM3/ETM1估测叶绿素的精度最高;(3)ETM4与悬浮物具有较高的相关度,其中利用算术组合ETM4/ETM1估测悬浮物含量的精度最高;(4)LandsatETM卫星影像中,不同尺寸的像元窗口影响水质参数的估测精度;对叶绿素估测而青,7×7或者5×5窗口比较适合,对悬浮物估测而言,一般不超过3×3. 相似文献
19.
由于风浪对浅水湖泊底泥的强烈扰动作用,底泥再悬浮的生态效应研究成为目前国际研究热点之一.但方法的缺乏极大地限制了有关底泥再悬浮环境效应的深入研究.本研究应用一种新的沉积物再悬浮装置,模拟了太湖南部长兜港水域不同风浪影响下悬浮物的垂向分布,获得水柱总悬浮物量(T)与扰动频率(n)的定量关系:T=19.77×exp(n/2.61)-71.7.结合现场实测风情下的水柱总悬浮物量,建立了室内水动力条件、水柱总悬浮物量和现场风情的定量关系.研究2004年10月至2005年10月太湖全年代表性小风、中风及大风与再悬浮装置的扰动频率对应关系,估算了小风、中风和大风常规风情引起的总悬浮物量分别为159、230、425 g/m2.结果表明,模拟获得的太湖悬浮物垂向分布规律与现场状况较为接近,是目前较为适用的浅水水体沉积物再悬浮模拟方法. 相似文献
20.
Based on field investigation of wave, sediment suspension and the changes in nutrient concentration of the water column in Lake Taihu, China, we proposed two release models to quantify nutrient release under static and dynamic conditions, respectively. Under static conditions, nutrient release from sediments to the overlying water mainly depends on chemical diffusion induced by concentration gradient, in which the nutrient release is controlled by the temperature, dissolved oxygen concentration in the sediment-water interface, oxidation-reduction potential and the concentration difference between porewater and overlying water. Under dynamic condition (or disturbed condition), both dissolved and particulate nutrients in sediments are released into the water column because of wind-induced sediment suspension. The amount of nutrient release under dynamic conditions is larger than that under the static condition. The release of dissolved nutrients, however, does not increase because the wind induced turbulence made oxidation of metallic elements such as Fe (ferric iron), Mn which are capable of precipitating soluble reactive phosphate (SRP). Under dynamic conditions, therefore, the release of total phosphorus (TP) increases dramatically but the release of SRP is close to those under static conditions. In sediments of Lake Taihu, high Fe content leads to a high ratio of Fe to P contents in sediments (Fe:P ratio). Under dynamic conditions, therefore, nutrient release is controlled by the intensity of disturbance, sediment consolidation and nutrient content in sediments. As for dissolved nutrients, especially SRP, the release is also controlled by the intensity of dynamic re-oxidation, Fe content in sediments and nutrient concentration gradient between porewater and overlying water. Based on these two release modes, the release flux in Lake Taihu has been estimated. In the static condition (i.e. laboratory experimental condition), total release of NH4 +-N for whole lake is ca. 10,000 ton/a, and PO4 3?-P is ca. 900 ton/a. In the dynamic condition, nutrient release following sediment suspension was estimated according to three different intensities of wind forcing which were defined as “calm” (wind speed is less than 2 m/s), “gentle” (wind speed is greater than 2 m/s and less than 6 m/s) and “gust” (wind speed is greater than 6 m/s). The release rate in the condition of “calm” was estimated in terms of the nutrient release in the laboratory experimental static condition; whereas the release rate in conditions of “gentle” and “gust” was estimated in terms of measurement during sediment resuspension conducted in flume experiments. With the observation of wind velocity and frequency in 2001, each type of wind forcing took the frequency of 12%, 82% and 6% for “calm”, “gentle” and “gust”, respectively. The yearly release of nitrogen was 81,000 ton and phosphorus was 21,000 ton, which is about 2–6 folds of annual external loading, respectively. 相似文献