Using a H∞ filter assimilation procedure to estimate root zone soil water content

Root zone soil water content impacts plant water availability, land energy and water balances. Because of unknown hydrological model error, observation errors and the statistical characteristics of the errors, the widely used Kalman filter (KF) and its extensions are challenged to retrieve the root zone soil water content using the surface soil water content. If the soil hydraulic parameters are poorly estimated, the KF and its extensions fail to accurately estimate the root zone soil water. The H‐infinity filter (HF) represents a robust version of the KF. The HF is widely used in data assimilation and is superior to the KF, especially when the performance of the model is not well understood. The objective of this study is to study the impact of uncertain soil hydraulic parameters, initial soil moisture content and observation period on the ability of HF assimilation to predict in situ soil water content. In this article, we study seven cases. The results show that the soil hydraulic parameters hold a critical role in the course of assimilation. When the soil hydraulic parameters are poorly estimated, an accurate estimation of root soil water content cannot be retrieved by the HF assimilation approach. When the estimated soil hydraulic parameters are similar to actual values, the soil water content at various depths can be accurately retrieved by the HF assimilation. The HF assimilation is not very sensitive to the initial soil water content, and the impact of the initial soil water content on the assimilation scheme can be eliminated after about 5–7 days. The observation interval is important for soil water profile distribution retrieval with the HF, and the shorter the observation interval, the shorter the time required to achieve actual soil water content. However, the retrieval results are not very accurate at a depth of 100 cm. Also it is complex to determine the weighting coefficient and the error attenuation parameter in the HF assimilation. In this article, the trial‐and‐error method was used to determine the weighting coefficient and the error attenuation parameter. After the first establishment of limited range of the parameters, ‘the best parameter set’ was selected from the range of values. For the soil conditions investigated, the HF assimilation results are better than the open‐loop results. Copyright © 2010 John Wiley & Sons, Ltd.     

Towards a comprehensive approach to parameter estimation in land surface parameterization schemes

In climate models, the land–atmosphere interactions are described numerically by land surface parameterization (LSP) schemes. The continuing improvement in realism in these schemes comes at the expense of the need to specify a large number of parameters that are either directly measured or estimated. Also, an emerging problem is whether the relationships used in LSPs are universal and globally applicable. One plausible approach to evaluate this is to first minimize uncertainty in model parameters by calibration. In this paper, we conduct a comprehensive analysis of some model diagnostics using a slightly modified version of the Simple Biosphere 3 model for a variety of biomes located mainly in the Amazon. First, the degree of influence of each individual parameter in simulating surface fluxes is identified. Next, we estimate parameters using a multi‐operator genetic algorithm applied in a multi‐objective context and evaluate simulations of energy and carbon fluxes against observations. Compared with the default parameter sets, these parameter estimates improve the partitioning of energy fluxes in forest and cropland sites and provide better simulations of daytime increases in assimilation of net carbon during the dry season at forest sites. Finally, a detailed assessment of the parameter estimation problem was performed by accounting for the decomposition of the mean squared error to the total model uncertainty. Analysis of the total prediction uncertainty reveals that the parameter adjustments significantly improve reproduction of the mean and variability of the flux time series at all sites and generally remove seasonality of the errors but do not improve dynamical properties. Our results demonstrate that error decomposition provides a meaningful and intuitive way to understand differences in model performance. To make further advancements in the knowledge of these models, we encourage the LSP community to adopt similar approaches in the future. Copyright © 2012 John Wiley & Sons, Ltd.     

1993年7月湖北咸宁4.1级地震序列的活动特征

1993年 7月底至 8月中旬在咸宁发生的ML4 .1震群是一比较典型的有感震群 ,通过多种测震手段对该震群进行分析和处理 ,得到下列认识和结果 :1、该震群是一个非前兆震群。 2、此震群是一个主震型震群 ,地震主要发生在两个阶段 ,每个阶段均出现密集 -平静过程。 3、该震群可能与NE向潜山断裂的活动有关。 4、对咸宁震群的各种测震学参数计算表明 ,有一些参数在湖北省比较适用 (如b ,η ,U ,K ,ρ等 ) ,而有些则不适合 (如h ,F 等 )。     

A bimodal four‐parameter lognormal linear model of soil water repellency persistence

Soil water repellency may be characterized in terms of the delayed infiltration time of a water droplet resting on the soil surface, which is, water drop penetration time (WDPT), or repellency persistence. Such repellency persistence varies nonlinearly with soil water content (θ_g), although no models have been proposed to reproduce the variation of WDPT with θ_g in soils. Dynamic factor analysis (DFA) is used to identify two common patterns of unexplained variability in a scattered dataset of WDPT versus θ_g measurements. A four‐parameter lognormal distribution was fitted to both common patterns obtained by DFA, and these were combined additively in a weighted multiple linear bimodal model. We show how such an empirical model is capable of reproducing a large variety of WDPT versus θ_g curve shapes (N = 80) both within a wide range of measured WDPTs (0–17 000 s) and for samples with organic matter content ranging from 21·7 to 80·6 g (100 g)^?1. Copyright © 2009 John Wiley & Sons, Ltd.     

Simultaneous identification of parameter,initial condition,and boundary condition in groundwater modelling

In this paper, we perform an inverse method to simultaneously estimate aquifer parameters, initial condition, and boundary conditions in groundwater modelling. The parameter estimation is extended to a complete inverse problem that makes the calibrated groundwater flow model more realistic. The adjoint state method, the gradient search method, and the least square error algorithm are combined to build the optimization procedure. Horizontal two‐dimensional groundwater flow in a confined aquifer is exemplified to demonstrate the correlation between unknowns, the contribution of observation, as well as the suitability of applying the inverse method. The correlation analysis shows the connection between storage coefficient and initial condition. Besides, transmissivity and boundary conditions are also highly correlated. More observations at different location and time are necessary to provide sufficient information. A time series of unsteady head is requested for estimation of storage coefficient and initial condition. Observation near boundary is very effective for boundary condition estimation. The observation at pumping well mostly contributes to the estimation of transmissivity. According to all observations, it is possible to identify parameters, initial condition, and boundary condition simultaneously. Furthermore, the results not only illustrate the traditional assumption of known boundary condition but also initial condition, which may cause an incorrect estimation. Copyright © 2009 John Wiley & Sons, Ltd.     

顾及多尺度分割参数的FNEA面向对象分类

首先对分形网络演化（FNEA）算法做了介绍,通过试验对比4种分割方法棋盘分割、四叉树分割、多尺度分割、光谱差异分割的效果。此外,通过eCognition Developer 8.7分析软件对影像进行多尺度分割预处理,从5开始,以5为单位向上递增,共选取12组参数进行分割试验,采用面向对象CART分类器对分割后影像分类。对比分类效果图可知,小尺度分割参数对分类效果能有较好的提升;对比总体精度及Kappa系数可知,小尺度分割参数分类精度优于大尺度分割参数,且当分割参数Scale为10时,分类精度达到最好的级别。     

页岩储层物性参数对CO2不同封存机制及封存量的影响

CO₂增强页岩气开采技术(CO₂-ESGR)一方面可提高CH4产量,另一方面又可实现CO₂地质封存。为了分析页岩储层物性参数对CO₂封存机制的影响,文章以鄂尔多斯盆地延长组页岩为研究对象,采用CMG-GEM软件建立双孔双渗均质模型,分析了CO₂-ESGR中页岩储层垂直渗透率与水平渗透率之比(Kv/Kh)、含水饱和度和孔隙度对不同CO₂封存机制封存量的影响;并设计了27组正交试验采用极差分析法比较了三种因素的影响程度。研究表明,Kv/Kh在0.1～1范围增大会增加不同CO₂封存机制的封存量,封存总量最大可增加69.96%,其中吸附封存量最大可增加97.96%,受到影响最大;含水饱和度在0～0.9范围增大引起CO₂封存总量先增加后减小,封存总量最大可减少67.12%,其中溶解封存量最大可减少83.35%,范围波动最大;页岩储层孔隙度在0.1～0.99范围增大会导致CO₂封存总量减少,封存总量最大...     

水文模型参数区域化研究进展

参数区域化方法是解决资料缺乏地区水文模拟和预报的有效手段,主要包括回归法、空间邻近法和属性相似法三类方法,可将有资料流域的水文模型参数移用到资料缺乏流域。首先回顾了区域化方法的基本原理和应用方法,并分析了三类主要区域化方法的适用性。从流域特征因子、水文模型及参数、不确定性探讨三个方面综述了区域化方法的研究进展。分析发现,当前区域化方法缺乏完善的理论基础,流域特征因子选择存在主观性,水文模型及参数的适用性方面研究不足。最后展望了未来的研究重点：（1）多维度适用性比较;（2）水文过程和参数的空间分布规律;（3）参数的尺度问题;（4）参数区域化的不确定性问题。     

Physical parameters identification for full-scale ten-story reinforced concrete building with degrading tri-linear model by modal iterative error correction method

To assess the post-earthquake seismic safety of buildings, it is crucial to predict seismic response, and it is necessary to set the appropriate physical parameters of the response analysis model. Numerous methods have been proposed to identify physical parameters. However, most of them are limited to linear systems, and previous researches on nonlinear systems have difficulties in practical applications. In this paper, a nonlinear response analysis model is identified for a full-scale ten-story reinforced concrete building with the degrading tri-linear stiffness model by the modal iterative error correction (MIEC) method, and the accuracy of this technique is discussed by comparing with the shaking table test.