Stage level,volume and time‐frequency information content of Lake Tana using stochastic and wavelet analysis methods     

Y. Chebud  A. Melesse 《水文研究》2013,27(10):1475-1483

Lake Tana is the largest fresh water body situated in the north‐western highlands of Ethiopia. In addition to its ecological services, it serves for local transport, electric power generation, fishing, recreational purposes, and source of dry season irrigation water supply. Evidence shows that the lake has dried at least once at about 15,000–17,000 before present owing to a combination of high evaporation and low precipitation events. Past attempts to understand and simulate historical fluctuation of Lake Tana based on simplistic water balance approach of inflow, outflow, and storage have failed to capture well‐known events of drawdown and rise of the lake that have happened in the last 44 years. This study tested different stochastic methods of lake level and volume simulation for supporting Lake Tana operational planning decision support. Three stochastic methods (perturbations approach, Monte Carlo methods, and wavelet analysis) were employed for lake level and volume simulation, and the results were compared with the stage level measurements. Forty‐four years of daily, monthly, and mean annual lake level data have shown a Gaussian variation with goodness of fit at 0.01 significant levels of the Kolmogorov–Smirnov test. The stochastic simulations predicted the lake stage level of the 1972, 1984, and 2002/2003 historical droughts 99% of the time. The information content (frequency) of fluctuation of Lake Tana for various periods was resolved using Wigner's Time‐Frequency Decomposition method. The wavelet analysis agreed with the perturbations and Monte Carlo simulations resolving the time (1970s, 1980s, and 2000s) in which low frequency and high spectral power fluctuation has occurred. The Monte Carlo method has shown its superiority for risk analysis over perturbation and deterministic method whereas wavelet analysis reconstructed historical record of lake stage level at daily and monthly time scales. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

航空重力数据谐波小波滤波中卷积运算的处理          下载免费PDF全文

田颜锋  李姗姗  吴星  叶修松 《海洋测绘》2010,30(2):4-6

数据的滤波提取是航空重力测量数据处理的一个重要环节。谐波小波滤波器在频域具有良好的盒形谱特征,可以较好地实现信号的滤波。但谐波小波滤波器是一个连续函数,航空重力测量采集的信号是离散的,无法直接进行卷积运算。讨论了谐波小波用于航空重力数据滤波处理时的卷积运算处理方法,给出了谐波小波频域卷积的算法实现过程和仿真算例。  相似文献   

一种新的基于PCA变换多源遥感影像像素级融合方法          下载免费PDF全文

王冬梅  李雪萍  袁建东 《海洋测绘》2010,30(1):44-46

在多源遥感影像融合中，基于传统PCA变换的多源遥感影像融合的光谱分辨率受到较大影响。提出了一种新的基于PCA变换的多源遥感影像像素级融合方法，通过在传统PCA变换融合算法基础上引入小波变换融合，保留了多波段遥感图像光谱特性的有用信息，进一步提高融合后遥感影像的效果。给出实验的融合结果，并与传统PCA变换方法进行对比，证明了该方法的有效性。  相似文献   

Discrete wavelet‐based trend identification in hydrologic time series     

Yan‐Fang Sang  Zhonggen Wang  Changming Liu 《水文研究》2013,27(14):2021-2031

Trend identification is a substantial issue in hydrologic series analysis, but it is also a difficult task in practice due to the confusing concept of trend and disadvantages of methods. In this article, an improved definition of trend was given as follows: ‘a trend is the deterministic component in the analysed data and corresponds to the biggest temporal scale on the condition of giving the concerned temporal scale’. It emphasizes the intrinsic and deterministic properties of trend, can clearly distinguish trend from periodicities and points out the prerequisite of the concerned temporal scale only by giving which the trend has its specific meaning. Correspondingly, the discrete wavelet‐based method for trend identification was improved. Differing from those methods used presently, the improved method is to identify trend by comparing the energy difference between hydrologic data and noise, and it can simultaneously separate periodicities and noise. Furthermore, the improved method can quantitatively estimate the statistical significance of the identified trend by using proper confidence interval. Analyses of both synthetic and observed series indicated the identical power of the improved method as the Mann–Kendall test in assessing the statistical significance of the trend in hydrologic data, and by using the former, the identified trend can adaptively reflect the nonlinear and nonstationary variability of hydrologic data. Besides, the results also showed the influences of three key factors (wavelet choice, decomposition level choice and noise content) on discrete wavelet‐based trend identification; hence, they should be carefully considered in practice. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers     

Seyed Ahmad Mirbagheri  Taher Rajaee  Amir Alikhani 《水文科学杂志》2013,58(7):1175-1189

Abstract

The study of sediment load is important for its implications to the environment and water resources engineering. Four models were considered in the study of suspended sediment concentration prediction: artificial neural networks (ANNs), neuro-fuzzy model (NF), conjunction of wavelet analysis and neuro-fuzzy (WNF) model, and the conventional sediment rating curve (SRC) method. Using data from a US Geological Survey gauging station, the suspended sediment concentration predicted by the WNF model was in satisfactory agreement with the measured data. Also the proposed WNF model generated reasonable predictions for the extreme values. The cumulative suspended sediment load estimated by this model was much higher than that predicted by the other models, and is close to the observed data. However, in the current modelling, the ANN, NF and SRC models underestimated sediment load. The WNF model was successful in reproducing the hysteresis phenomenon, but the SRC method was not able to model this behaviour. In general, the results showed that the NF model performed better than the ANN and SRC models.

Citation Mirbagheri, S. A., Nourani, V., Rajaee, T. & Alikhani, A. (2010) Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers. Hydrol. Sci. J. 55(7), 1175–1189.  相似文献   

A physically constrained wavelet-aided statistical model for multi-decadal groundwater dynamics predictions     

Fatih Gordu  Mahmood H. Nachabe 《水文研究》2021,35(8):e14308

A physically constrained wavelet-aided statistical model (PCWASM) is presented to analyse and predict monthly groundwater dynamics on multi-decadal or longer time scales. The approach retains the simplicity of regression modelling but is constrained by temporal scales of processes responsible for groundwater level variation, including aquifer recharge and pumping. The methodology integrates statistical correlations enhanced with wavelet analysis into established principles of groundwater hydraulics including convolution, superposition and the Cooper–Jacob solution. The systematic approach includes (1) identification of hydrologic trends and correlations using cross-correlation and multi-time scale wavelet analyses; (2) integrating temperature-based evapotranspiration and groundwater pumping stresses and (3) assessing model prediction performances using fixed-block k-fold cross-validation and split calibration-validation methods. The approach is applied at three hydrogeologicaly distinct sites in North Florida in the United States using over 40 years of monthly groundwater levels. The systematic approach identifies two patterns of cross-correlations between groundwater levels and historical rainfall, indicating low-frequency variabilities are critical for long-term predictions. The models performed well for predicting monthly groundwater levels from 7 to 22 years with less than 2.1 ft (0.7 m) errors. Further evaluation by the moving-block bootstrap regression indicates the PCWASM can be a reliable tool for long-term groundwater level predictions. This study provides a parsimonious approach to predict multi-decadal groundwater dynamics with the ability to discern impacts of pumping and climate change on aquifer levels. The PCWASM is computationally efficient and can be implemented using publicly available datasets. Thus, it should provide a versatile tool for managers and researchers for predicting multi-decadal monthly groundwater levels under changing climatic and pumping impacts over a long time period.  相似文献   

基于解析信号重构的同步挤压小波变换的时频谱影响因素分析          下载免费PDF全文

游龙庭  宋建国  于会臻  王月蕾 《CT理论与应用研究》2017,26(3):267-278

受测不准原理的制约,小波变换、S变换等时频分析算法无法同时获得高时间分辨率和高频率分辨率。为了满足更高的要求,出现了一种联合小波变换和时频谱重组的新方法—同步挤压小波变换。本文从同步挤压小波变换和基于解析信号重构的同步挤压小波变换的原理出发,通过模型分析算法中参数设置对时频分析结果的影响,包括小波母函数、小波母函数的参数选择和小波阈值等,分析瞬时频率变化率不为零的信号所存在的时频谱模糊现象,并通过控制小波母函数、小波母函数参数以及小波阈值有效地减轻瞬时频率变化率不为零的信号所存在的时频谱模糊现象,时频谱的质量得到一定程度的提高。研究结果对获取高分辨率地震时频谱具有一定的指导意义。   相似文献   

工业部门污染物治理协同控制温室气体效应评价——基于重庆市的实证分析     

王敏  冯相昭  杜晓林  吴莉萍  赵梦雪  王鹏  安祺 《气候变化研究进展》2021,17(3):296-304

以高能耗为主要特征的工业部门是大气污染物和温室气体的重要排放源。为推动协同管控,文中结合生态环境部在重庆市组织开展的试点工作,对工业企业NOx污染治理协同控制温室气体的效应进行了量化分析。结果表明,以末端治理为手段的NOx治理措施协同控制温室气体的效果为负,即工业企业去除1 t NOx会直接或间接增加CO₂排放1.811 t,采用SNCR技术且选择氨水等非尿素类脱硝剂有助于减少工艺过程和电力间接CO₂排放。2017年工业企业NOx减排导致CO₂排放增加52.57万t,占重庆市能源活动CO₂排放总量的0.3%。电力碳排放因子降低1%和降低5%情景下,NOx减排的总协同度将分别提高0.9%和4.3%,尤以水泥制造业的协同效果改善最明显。减少尿素使用和提高电力低碳化程度有助于降低工业领域NOx减排对CO₂排放的负协同效果。  相似文献   

中国长三角地区PM2.5时空分布数值模拟研究     

许敏 《气象与环境学报》2021,37(4):33-39

利用第三代空气质量预报模式LOTOS-EUROS(Long Term Ozone Simulation-European Operational Smog)对2018年中国长三角地区细颗粒物(PM_2.5)浓度的时空分布进行数值模拟,通过对比模拟结果与地面观测值,验证模式对PM_2.5长期特征模拟的合理性并探讨长三角地区PM_2.5的时空分布特征。结果表明：LOTOS-EUROS模式可以较好地再现中国长三角地区PM_2.5浓度的时空分布特征,监测站点观测值和模拟值的整体相关系数达到0.64,可以用于长三角地区细颗粒物的模拟。长三角地区PM_2.5浓度呈冬高夏低,西北高东南低的特征。冬季PM_2.5浓度高值出现在长三角地区的西北部,安徽省等地区的浓度水平最大值可达到160 μg·m^-3;春季和秋季PM_2.5浓度的高值集中在30°N以北、120°E以西地区,浓度为40-80 μg·m^-3;而夏季PM_2.5浓度水平大幅度降低,大部分地区维持在20-40 μg·m^-3,低值中心出现在长三角地区东南部沿海城市,低于10 μg·m^-3,最低值可达5 μg·m^-3。  相似文献   

COVID-19疫情期间全球空气质量变化:臭氧响应的区域间差异          下载免费PDF全文

Rong Tang  Xin Huang  Derong Zhou  Haikun Wang  Jiawei Xu  Aijun Ding 《大气和海洋科学快报》2021,14(4):45-51

疫情期间全球各地一次排放大幅削减,而臭氧等二次污染的响应则存在着区域间差异.结合地面和卫星观测发现,同在氮氧化物大幅下降的情况下,臭氧在东亚和欧洲呈现出可达14ppb的上升信号,而北美则下降为主(约2-4ppb).我们结合气象分析和臭氧敏感性进一步讨论了臭氧响应差异性的原因,一方面受臭氧与前体物间关系的影响;另一方面来自于气象,尤其是温度.研究明晰了人为排放,化学和气象三者的内在关联,强调了在臭氧控制过程中考虑前体物削减和气象条件协同的重要性.  相似文献