Conceptually-based shot noise modeling of streamflows at short time interval

A conceptual-stochastic approach to short time runoff data modelling is proposed, according to the aim of reproducing the hydrological aspects of the streamflow process and of preserving as much as possible the dynamics of the process itself. This latter task implies preservation of streamflow characteristics at higher scales of aggregation and, within a conceptual framework, involves compatibility with models proposed for the runoff process at those scales. At a daily time scale the watershed response to the effective rainfall is considered as deriving from the response of three linear reservoirs, respectively representing contributions to streamflows of large deep aquifers, with over-year response lag, of aquifers which run dry by the end of the dry season and of subsurface runoff. The surface runoff component is regarded as an uncorrelated point process. Considering the occurrences of effective rainfall events as generated by an independent Poisson process, the output of the linear system represents a conceptually-based multiple shot noise process. Model identification and parameter estimation are supported by information related to the aggregated runoff process, in agreement to the conceptual framework proposed, and this allows parameter parsimony, efficient estimation and effectiveness of the streamflow reproduction. Good performances emerged from the model application and testing made with reference to some daily runoff series from Italian basins.     

Advances in shot noise modeling of daily streamflows

Univariate shot noise models for streamflow generation at short time scales are examined in detail, to reconsider the verification of the basic hypotheses behind the models, the problem of objectively evaluating their performances, and the importance of model parsimony. The classical approach to model estimation is shown to produce some inconsistencies in the inverse evaluation of the model input, in particular regarding the assumed independence and Poissonianity of the pulses; an alternative procedure for pulses identification is proposed, which enables the mentioned hypotheses to be respected. To evaluate model performances, two indices are proposed, respectively based on the comparison of real and generated flow duration curves (I₁) and annual maxima statistics (I₂). A method for explicitly accounting for the dependence of I₁ and I₂ on the number of model parameters is described. An application to seven daily streamflow time series in northern Italy demonstrates the validity of the proposed procedure for the identification of the input and the usefulness of the performance indices in discerning among competing models.     

A shot noise model for the generation of soil moisture data

An attempt is made to estimate the expected contribution of rainfall to soil moisture during the irrigation season. Effective rainfall and evapotranspiration are the parameters considered in the water balance carried out in the root zone. Rainfall occurrence is simulated by a Poisson process whereas evapotranspiration is described by a simple deterministic function of potential evapotranspiration and soil moisture in the root zone. Using the theory of shot noise models a closed form solution is derived from the expected soil moisture in the root zone at the end of the time interval (0,t]. For illustration purposes the proposed model is applied to a series of data from Mikra meteorological station in Greece.List of symbols x change in water storage in the root zone during the time interval t - X infiltrated rainfall of thei th storm event - ET actual evapotranspiration during thej th day - Poisson rate - number of storm events in (0,t] - t _r duration of rainfall - t _b interarrival time - h _i rainfall depth of thei th storm event - i _m mean rainfall intensity - i(t) instantaneous rainfall intensity - x(0),x(t) available soil moisture in the root zone at time 0 andt, respectively - PET potential evapotranspiration rate - x _F available soil moisture in the root zone at field capacity - soil moisture depletion rate (=PET/x _F ) - w impulse shape of filtered Poisson processes - E[·] mean value - S _i time of thei th rainfall event - N(t) time of storm events in (0,t] - estimated standard deviation The following symbols were used in this paper     

Matched block bootstrap for resampling multiseason hydrologic time series

A nonparametric method for resampling multiseason hydrologic time series is presented. It is based on the idea of rank matching, for simulating univariate time series with strong and/or long‐range dependence. The rank matching rule suggests concatenating with higher likelihood those blocks that match at their ends. In the proposed method, termed ‘multiseason matched block bootstrap’, nonoverlapping within‐year blocks of hydrologic data (formed from the observed time series) are conditionally resampled using the rank matching rule. The effectiveness of the method in recovering various statistical attributes, including the dependence structure from finite samples generated from a known population, is demonstrated through a two‐level hypothetical Monte Carlo simulation experiment. The method offers enough flexibility to the modeller and is shown to be appropriate for modelling hydrologic data that display strong dependence, nonlinearity and/or multimodality in the time series depicting the hydrologic process. The method is shown to be more efficient than the nonparametric ‘k‐nearest neighbor bootstrap’ method in simulating the monthly streamflows that exhibit a complex dependence structure and bimodal marginal probability density. Even with short block sizes, this bootstrap method is able to predict the drought characteristics reasonably accurately. Copyright © 2005 John Wiley & Sons, Ltd.     

顾及有色噪声的GNSS时间序列时域信号提取

随着大型地震的发生,GNSS时间序列中除线性趋势和周期信号外,还存在大量震后瞬态,准确地提取各项时域信号是运用GNSS时间序列进行地学研究的关键.为此,本文提出了顾及有色噪声的GNSS时间序列时域信号提取法.该方法首先基于白噪声（White Noise,WN）+闪烁噪声（Flicker Noise,FN）模型,使用最大似然估计（Maximum Likelihood Estimation,MLE）对震前GNSS时间序列进行参数估计,并根据参数估值来去除震后时间序列中的震前信号,以此获取残差序列;然后将残差序列作为求解特征时间尺度的观测量,WN+FN模型作为观测量的随机模型,并采取非线性最小二乘法（Non-linear Least Squares,NLS）法估计特征时间尺度;最后利用估计的特征时间尺度构建GNSS时间序列函数模型,并采用MLE估计其未知参数,进而实现时域信号的提取.经模拟数据分析,考虑有色噪声时,特征时间尺度估计算法的收敛性提高了25%,各项未知参数的标准差（Standard Deviation,STD）显著下降.最后,将该算法应用于日本区域实测数据,并与传统方法进行了对比分析.

     

金属矿山地地区地震勘探随机噪声的波动方程模拟

消减随机噪声是目前陆地地震勘探数据处理的关键问题之一,分析随机噪声的产生机制及特征是对其进行有效压制的先决条件.本文针对中国南方山地金属矿区的勘探环境,根据随机噪声中包含的自然噪声和人文噪声的发声机理分别确定其噪声源函数,以波动方程作为噪声传播模型对山地地区随机噪声进行建模,将随机噪声作为一个综合波场,并且与实际噪声记录进行比较.随机噪声记录作为时空域的二维随机过程,分别对模拟噪声和实际噪声记录的时间域波形(振动图)特征包括频谱、功率谱密度,相空间轨迹图,统计量特征(能量分布,累积分布,均值,方差,峰度,偏度),和空间域波形(波剖面)特征包括波数谱和统计量特征进行比较,对比结果显示在时空域模拟噪声和实际噪声都有基本相同的性质,证明了本文对随机噪声模拟方法的可行性,为进一步研究随机噪声时空域传播特性以及噪声消除奠定理论基础.     

沙漠地区地震勘探随机噪声建模及其在噪声压制中的应用

随机噪声是影响地震勘探有效信号的主要因素,其存在大大降低了地震记录的信噪比.在噪声压制方法不断被改进的同时,对随机噪声特性进行研究,了解噪声的产生机制是对其进行压制的先决条件,目前对噪声的研究主要是特性研究以寻找规律性,对其进行定性定量的分析还比较少.本文根据塔里木沙漠地区实际采集环境,考虑到噪声的连续性给计算带来的不便,假设各类噪声源以点源的形式分布在检波器周围,依据相应理论确定各类噪声源的源函数,其激发的噪声经由波动方程传播,将随机噪声作为各类噪声源共同作用的综合波场,建立随机噪声的理论模型.通过分析不同种噪声对地震记录的影响,选取合适的滤波方法对其进行压制,实验结果表明,通过建立沙漠地区随机噪声的理论模型,为选择有效的滤波方法,提高地震记录信噪比起到理论指导作用.     

强随机噪声条件下时窗类型局部线性化对TFPF技术的影响

为了更广泛地应用时频峰值滤波方法消减地震勘探记录中强随机噪声,本文比较详细地探讨了该方法在应用时需要处理的时窗选取、一个时窗内局部线性化等主要基础技术问题.经过时变时窗的仿真计算,运用多项指标比较,包括整体背景强弱、振幅谱、信噪比、均方误差、有效子波波峰波谷幅值、畸变程度,综合评价出（L0+Lx）时窗滤波的效果较理想.对于三角波这类简单类型的周期波,其时频峰值滤波效果与边线段平均曲率变化、时窗长度等条件有关,即三角波边线段平均曲率越大,滤波结果的均方误差越大;另外,边线段平均曲率增大时,选取的时窗长度有变小的趋势.总之,在地震勘探中应用时频峰值滤波方法消减强随机噪声时,一方面要合理地选取时窗参数,另一方面时窗参数又不能变化过大,以避免对有效子波波形产生畸变影响.     

连云港地震台台基噪声与干扰源分析

通过对连云港地震台台基背景噪声进行计算和分析,得出该台台基背景噪声属于Ⅰ类噪声水平。分析该台6—7月观测数据,得出日夜噪声差值约3 dB。分析发现,该台人为干扰为基础建设的工程车干扰、景区人员聚集和车辆干扰;自然环境干扰主要来自大风干扰。     

龙门山断裂带中上地壳速度结构的短周期环境噪声成像

本文利用在龙门山断裂带周边布设的57个台站自2008年11月至2009年11月为期一年的垂直分量连续地震环境噪声数据,通过短周期地震环境噪声成像方法,获得了龙门山断裂带中北段地壳25 km深度范围的S波精细速度结构.结果表明: (1)龙门山断裂带周边区域10 km以上的速度结构与地表断裂的分布形态具有良好的一致性,速度结构控制了龙门山主要断层的深部延展特征;在15 km及以下深度,S波速度结构呈现沿龙门山和沿岷山隆起走向的交叉构造格局,由此造成的速度结构差异可能影响了汶川地震的破裂过程; (2)速度结构随深度的分布特征为龙门山断裂带主要断层的深部延伸形态给出了良好的约束,结果进一步确认了龙门山断裂中段的高角度铲型断裂构造特征; (3)研究区的南端发现了龙门山断裂下方20 km以下深度具有与松潘地块中地壳低速层相关的低速结构的迹象,这可能是汶川地震破裂带南段22 km左右深度存在脆韧转换带的一个证据.研究结果显示出密集台阵和短周期环境噪声成像方法在地壳浅部精细结构和断层探测研究中具有巨大潜力.     

前兆定点形变观测数据噪声分析

地球物理研究表明,可以构造或选择合适的统计模型模拟观测噪声,从而了解噪声特性,获得噪声谱及其含量.对吉林省5个台站的倾斜观测共18个测项产出的时间序列进行噪声分析,结果表明,长期观测噪声可用带通噪声和随机游走噪声的组合模型模拟,短时间观测噪声可用谱指数介于-1至-2的幂律噪声模型模拟.该结论对定点形变观测噪声的认识、噪声源的研究以及地壳构造信息的提取具有参考意义.     

用时频峰值滤波方法消减地震勘探资料中随机噪声的初步研究

时频峰值滤波算法是一种新颖的基于时频分析的信号增强算法,能够有效地消除随机噪声,恢复有效波信息.本文将这种时频分析算法用于消除地震勘探资料中的随机噪声,对淹没于随机噪声下的40道共炮点记录进行时频峰值滤波,恢复出来的共炮点记录可以清楚地表现原始记录同相轴的位置.经过对40道中任选两道（即第21道和第7道）滤波前后的子波形态Wigner\|Ville分布、傅立叶振幅谱等的比较,可知仅在谷值和峰值点误差较大,子波带宽相对误差小于25％.仿真试验表明信噪比可达－7dB,说明该方法可以有效地消减地震资料中的随机噪声.     

鹤岗地震台背景噪声分析

选取2015年和2019年在1月1日00时、06时、12时3个时段的数字地震资料,对鹤岗地震台进行台基地动噪声分析,确定台站的观测动态范围、地噪声功率谱密度及地动噪声RMS值,分析台站观测能力,找出影响观测的各种干扰因素。通过对该台站背景噪声的分析,有利于提高地震台站观测质量,为研究区域地震背景噪声积累数据。     

Amplitude-compensated Laplacian filtering of reverse time migration and its application

Reverse time migration is an advanced seismic migration imaging method. When the source wavefield and the receiver wavefield are cross-correlated, the cross-correlations of direct arrivals, backscattered waves and overturned waves will produce a lot of low-frequency noise, which will mask the final imaging results. Laplacian filtering, as a common method to suppress low-frequency noise, can adapt to any complex media, just adding a little computational cost. However, simple direct Laplacian filtering will destroy the characteristics of the useful signals. Therefore, the amplitude needs to be compensated before filtering when using the Laplacian filtering method. Zhang and Sun proposed an improved Laplacian filtering method and gave a simple calculation formula and explanation. This method can effectively suppress the low-frequency noise in reverse time migration while retaining the useful signal characteristics, but lacks detailed and strict mathematical derivation. Therefore, this paper gives a detailed and rigorous mathematical derivation of the amplitude-compensated Laplace filtering method from the point of view of amplitude-preserved filtering. The source wavelet is used instead of the source wavefield to compensate amplitude, just adding a little calculation cost. Finally, the amplitude-compensated Laplace filtering method is verified by two theoretical models and compared with the direct Laplacian filtering method.     

环境变化对信阳测震台背景噪声水平的影响

利用均方根速度值计算方法及背景噪声功率谱概率密度函数方法,对信阳测震台20082013年数据进行计算,得到不同时期背景噪声水平,分析环境变化对背景噪声的影响.     

Suitability of satellite-based hydro-climate variables and machine learning for streamflow modeling at various scale watersheds

ABSTRACT

Streamflow modeling is essential to investigate processes in the hydrologic cycle and important for water resource management application. However, in-situ hydrologic data paucity, because of various factors such as economic, political, instrument malfunctioning, and poor spatial distribution, makes the modeling process challenging. To overcome this limitation, we introduced a satellite remote sensing-based machine learning approach – boosted regression tree (BRT) – that integrates spatial land surface and climate variables that describe the sub-units, and applied it in three variable size watersheds in the Upper Mississippi River Basin (UMRB), USA. The model simulation results were tested using an independent dataset and showed Nash–Sutcliffe efficiency values of 0.80, 0.76, and 0.69 for the UMRB, Illinois River Watershed, and Raccoon River Watershed, respectively. In addition, we compared the performance of the machine learning models with existing process-based modeling results. Overall performance is comparable with the process-based approaches, but with significantly less modeling effort and resources.     

浙江省地震台网台站地动噪声分析

介绍浙江省数字地震台网基本情况,阐述功率谱分析的计算方法,并对各台站地动噪声计算分析。结果表明,各台站的台址环境和观测仪器的性能基本优良,能够适应宽频带地震观测要求。部分台址观测条件由于受到人为因素的影响,可以有针对性地对部分台站进行环境改造,为地震监测预报创造条件。     

佘山地磁信号的小波消噪处理

上海地铁9号线开通后,佘山地震基准台地磁观测受到严重影响,本文运用小波分析的方法,对被地铁9号线干扰的余山地磁数据进行消噪处理,并将变换后得到的结果和没有地铁干扰的崇明地震台同一仪器观测的地磁数据进行时序变化和相关系数比较,消噪处理效果较明显。     

国家数字地震台网台站地动噪声功率谱分析

介绍了国家数字地震台站仪器的配置,通过对37个新建数字地震台站自2002年8月至2003年7月台基噪声功率谱的计算和分析,把37个国家数字地震台站的台基分为3类。为了得到台站地动噪声的变化情况,我们已经把计算地动噪声功率谱作为国家数字地震台网资料分析处理的一项日常工作进行。