Study of polluted soil remediation based on freezing and thawing cycles   总被引：1，自引：0，他引：1  

DaHu Rui  BaiYang Song  Yuzuru Ito  Li Wang 《寒旱区科学》2014,6(4):0322-0330

It is generally known that soil pollution poses a terrible hazard to the environment, but the present techniques of contaminated soil remediation cannot control this growing threat. This paper compares the pollutant extraction efficiency of traditional pumping and treating, which is a typical washing technology for the remediation of contaminated soils, with methods that utilize freeze-thaw cycles. In the soil freezing process, water shifts from unfrozen soils to the freezing front, and the permeability of soil will be enhanced under certain temperature gradients and water conditions. Therefore, this paper discusses the purification of contaminated soil through freeze-thaw action. We conducted a cleansing experiment on clay and silica sand infused with NaCl（simulation of heavy metals） and found that the efficiency of purification was enhanced remarkably in the latter by the freeze-thaw action. To assess the effective extraction of DNAPLs in soil, we conducted an experiment on suction by freezing, predicated on the different freezing points of moisture and pollutants. We found that the permeability coefficient was significantly increased by the freezing-thawing action, enabling the DNAPL contaminants to be extracted selectively and effectively.  相似文献   

地表土壤水分与雷达后向散射系数及入射角之间关系研究   总被引：3，自引：0，他引：3  

刘伟  施建成  余琴  王建明  武胜利 《国土资源遥感》2004,15(3):14-17

应用雷达技术反演土壤水分较著名的经验模型有Oh模型[1]、Dubois模型[2]以及Shi模型[3]。本文在Shi模型的基础上,对土壤水分与雷达后向散射系数之间的关系进行探讨,反演出土壤水分与雷达后向散射系数及入射角之间的关系。  相似文献   

A REVIEW OF THE ANALYSIS OF MOISTURE VARIABLES AND THE APPLICATION IN NUMERICAL MODELS     

王在志  闫敬华 《热带气象学报(英文版)》2007,13(1):81-84

The application of the explicit microphysical process in the high-resolution mesoscale numerical models makes it necessary to analyze the moisture variables such as the cloud water, cloud ice and rain water to initialize the explicit predicted fields. While the inclusion of moisture variables in initial fields can influence the whole performance of the model significantly, it can also reduce the spin-up time and increase the short-term forecasting ability of the model since the dynamical fields become more accordant with the thermodynamic fields. Now the increase of the observing ability and the abundance of the data promote the development of ways to analyze the moisture variables. A review of some methods to analyze the moisture variables is presented, and the situation and problems of the application in the numerical models are also discussed in this paper.  相似文献   

2003年淮河流域持续性大暴雨的水汽输送分析   总被引：13，自引：4，他引：13       下载免费PDF全文

康志明 《气象》2004,30(2):20-24

利用NCEP资料对 2 0 0 3年淮河流域 6、7月间持续性强暴雨的水汽输送特征进行分析。结果表明 :持续性强暴雨发生在我国南方西南水汽输送异常偏强的背景下。水汽从南海北部经副热带高压西南侧向北及从孟加拉湾越过中南半岛到长江中下游两条通道向淮河流域输送。从整个梅汛期和暴雨个例的计算结果来看 ,暴雨区的各个层次上水汽收支有不同的特点 ,主要水汽辐合发生在 850hPa及其以下层。来自孟加拉湾和南海的水汽向暴雨区输送在不同层次上的比重有很大差异 ,在暴雨区水汽的主要辐合层上 ,南海是最重要的水汽源地  相似文献   

基于混合像元分解的南方地区植被覆盖度遥感监测——以广州市为例   总被引：3，自引：0，他引：3  

张志新  邓孺孺  李灏  陈蕾  陈启东  何颖清 《国土资源遥感》2011,(3):88-94

通过测量图像端元的地表反射率,对遥感图像进行精确大气校正;在对混合像元分解模型进行改进的基础上,建立了基于地表反射率的线性混合像元分解( Liner Spectral Unmixing,LSU)模型,有效地避免了因大气时间、空间差异所造成的多时相误差,实现了多时相对比;通过增加土壤湿度因子,消除了土壤湿度差异造成的误差...  相似文献   

徐州市土壤水分与降雨的时空相关性分析     

赵洁  奚砚涛  崔夺  赵冉 《测绘与空间地理信息》2011,34(3):40-43

以徐州市为例,以TM影像为主要信息源,利用ERDAS IMAGINE遥感图像处理软件,将1987年,1995年及2000年徐州市的遥感图像进行一系列的校正与降噪处理,SAVI植被指数的提取,波段的合成与非监督分类,最后与降雨数据相结合,对徐州市的土壤水分与降雨的时空相关性进行分析。这种土壤水分与降雨的时空相关性分析,可以通过降雨数据,预测一段时期内的土壤中水分的变化,有利于对城市小气候的变化、泥石流灾害的预测,也有利于城市的生态建设。  相似文献   

A Multimodel Ensemble-based Kalman Filter for the Retrieval of Soil Moisture Profiles   总被引：1，自引：0，他引：1  

ZHANG Shuwen  LI Deqin  QIU Chongjian 《大气科学进展》2011,28(1):195-206

With the combination of three land surface models (LSMs) and the ensemble Kalman filter (EnKF), a multimodel EnKF is proposed in which the multimodel background superensemble error covariance matrix is estimated by two different algorithms: the Simple Model Average (SMA) and the Weighted Average Method (WAM). The two algorithms are tested and compared in terms of their abilities to retrieve the true soil moisture profile by respectively assimilating both synthetically-generated and actual near-surface soil moisture measurements. The results from the synthetic experiment show that the performances of the SMA and WAM algorithms were quite different. The SMA algorithm did not help to improve the estimates of soil moisture at the deep layers, although its performance was not the worst when compared with the results from the single-model EnKF. On the contrary, the results from the WAM algorithm were better than those from any single-model EnKF. The tested results from assimilating the field measurements show that the performance of the two multimodel EnKF algorithms was very stable compared with the single-model EnKF. Although comparisons could only be made at three shallow layers, on average, the performance of the WAM algorithm was still slightly better than that of the SMA algorithm. As a result, the WAM algorithm should be adopted to approximate the multimodel background superensemble error covariance and hence used to estimate soil moisture states at the relatively deep layers.  相似文献   

Dual state-parameter estimation of root zone soil moisture by optimal parameter estimation and extended Kalman filter data assimilation   总被引：1，自引：0，他引：1  

Haishen Lü  Zhongbo Yu  Yonghua ZhuSam Drake  Zhenchun HaoEdward A. Sudicky 《Advances in water resources》2011,34(3):395-406

With well-determined hydraulic parameters in a hydrologic model, a traditional data assimilation method (such as the Kalman filter and its extensions) can be used to retrieve root zone soil moisture under uncertain initial state variables (e.g., initial soil moisture content) and good simulated results can be achieved. However, when the key soil hydraulic parameters are incorrect, the error is non-Gaussian, as the Kalman filter will produce a persistent bias in its predictions. In this paper, we propose a method coupling optimal parameters and extended Kalman filter data assimilation (OP-EKF) by combining optimal parameter estimation, the extended Kalman filter (EKF) assimilation method, a particle swarm optimization (PSO) algorithm, and Richards’ equation. We examine the accuracy of estimating root zone soil moisture through the optimal parameters and extended Kalman filter data assimilation method by using observed in situ data at the Meiling experimental station, China. Results indicate that merely using EKF for assimilating surface soil moisture content to obtain soil moisture content in the root zone will produce a persistent bias between simulated and observed values. Using the OP-EKF assimilation method, estimates were clearly improved. If the soil profile is heterogeneous, soil moisture retrieval is accurate in the 0-50 cm soil profile and is inaccurate at 100 cm depth. Results indicate that the method is useful for retrieving root zone soil moisture over large areas and long timescales even when available soil moisture data are limited to the surface layer, and soil moisture content are uncertain and soil hydraulic parameters are incorrect.  相似文献   

Assimilation of streamflow and in situ soil moisture data into operational distributed hydrologic models: Effects of uncertainties in the data and initial model soil moisture states   总被引：1，自引：0，他引：1  

Haksu Lee  Dong-Jun Seo  Victor Koren 《Advances in water resources》2011,34(12):1597-1615

We assess the potential of updating soil moisture states of a distributed hydrologic model by assimilating streamflow and in situ soil moisture data for high-resolution analysis and prediction of streamflow and soil moisture. The model used is the gridded Sacramento (SAC) and kinematic-wave routing models of the National Weather Service (NWS) Hydrology Laboratory’s Research Distributed Hydrologic Model (HL-RDHM) operating at an hourly time step. The data assimilation (DA) technique used is variational assimilation (VAR). Assimilating streamflow and soil moisture data into distributed hydrologic models is new and particularly challenging due to the large degrees of freedom associated with the inverse problem. This paper reports findings from the first phase of the research in which we assume, among others, perfectly known hydrometeorological forcing. The motivation for the simplification is to reduce the complexity of the problem in favour of improved understanding and easier interpretation even if it may compromise the goodness of the results. To assess the potential, two types of experiments, synthetic and real-world, were carried out for Eldon (ELDO2), a 795-km² headwater catchment located near the Oklahoma (OK) and Arkansas (AR) border in the U.S. The synthetic experiment assesses the upper bound of the performance of the assimilation procedure under the idealized conditions of no structural or parametric errors in the models, a full dynamic range and no microscale variability in the in situ observations of soil moisture, and perfectly known univariate statistics of the observational errors. The results show that assimilating in situ soil moisture data in addition to streamflow data significantly improves analysis and prediction of soil moisture and streamflow, and that assimilating streamflow observations at interior locations in addition to those at the outlet improves analysis and prediction of soil moisture within the drainage areas of the interior stream gauges and of streamflow at downstream cells along the channel network. To assess performance under more realistic conditions, but still under the assumption of perfectly known hydrometeorological forcing to allow comparisons with the synthetic experiment, an exploratory real-world experiment was carried out in which all other assumptions were lifted. The results show that, expectedly, assimilating interior flows in addition to outlet flow improves analysis as well as prediction of streamflow at stream gauge locations, but that assimilating in situ soil moisture data in addition to streamflow data provides little improvement in streamflow analysis and prediction though it reduces systematic biases in soil moisture simulation.  相似文献   

Improving hydrologic predictions of a catchment model via assimilation of surface soil moisture   总被引：2，自引：0，他引：2  

Fan ChenWade T. Crow  Patrick J. StarksDaniel N. Moriasi 《Advances in water resources》2011,34(4):526-536

This paper examines the potential for improving Soil and Water Assessment Tool (SWAT) hydrologic predictions of root-zone soil moisture, evapotranspiration, and stream flow within the 341 km² Cobb Creek Watershed in southwestern Oklahoma through the assimilation of surface soil moisture observations using an Ensemble Kalman filter (EnKF). In a series of synthetic twin experiments assimilating surface soil moisture is shown to effectively update SWAT upper-layer soil moisture predictions and provide moderate improvement to lower layer soil moisture and evapotranspiration estimates. However, insufficient SWAT-predicted vertical coupling results in limited updating of deep soil moisture, regardless of the SWAT parameterization chosen for root-water extraction. Likewise, a real data assimilation experiment using ground-based soil moisture observations has only limited success in updating upper-layer soil moisture and is generally unsuccessful in enhancing SWAT stream flow predictions. Comparisons against ground-based observations suggest that SWAT significantly under-predicts the magnitude of vertical soil water coupling at the site, and this lack of coupling impedes the ability of the EnKF to effectively update deep soil moisture, groundwater flow and surface runoff. The failed attempt to improve stream flow prediction is also attributed to the inability of the EnKF to correct for existing biases in SWAT-predicted stream flow components.  相似文献