Conditioning mean steady state flow on hydraulic head and conductivity through geostatistical inversion

Nonlocal moment equations allow one to render deterministically optimum predictions of flow in randomly heterogeneous media and to assess predictive uncertainty conditional on measured values of medium properties. We present a geostatistical inverse algorithm for steady-state flow that makes it possible to further condition such predictions and assessments on measured values of hydraulic head (and/or flux). Our algorithm is based on recursive finite-element approximations of exact first and second conditional moment equations. Hydraulic conductivity is parameterized via universal kriging based on unknown values at pilot points and (optionally) measured values at other discrete locations. Optimum unbiased inverse estimates of natural log hydraulic conductivity, head and flux are obtained by minimizing a residual criterion using the Levenberg-Marquardt algorithm. We illustrate the method for superimposed mean uniform and convergent flows in a bounded two-dimensional domain. Our examples illustrate how conductivity and head data act separately or jointly to reduce parameter estimation errors and model predictive uncertainty.This work is supported in part by NSF/ITR Grant EAR-0110289. The first author was additionally supported by scholarships from CONACYT and Instituto de Investigaciones Electricas of Mexico. Additional support was provided by the European Commission under Contract EVK1-CT-1999-00041 (W-SAHaRA-Stochastic Analysis of Well Head Protection and Risk Assessment).     

基于抽水试验的土体渗透性耦合响应模型研究

土体中大量降排水的过程实际上是土体中有效应力增长的过程。通过对抽水试验中土体渗透系数的回归分析,建立了渗透系数与有效应力增量之间的耦合响应模型关系,说明降排水过程中土体渗透系数是呈非线性变化的。     

影响流域土壤流失的降水量的PPAR(K)预测模型

介绍了投影寻踪自回归（ＰＰＡＲ（Ｋ））的基本思想及其算法。用ＰＰＡＲ（Ｋ）和均生函数（ＭＧＦ）两种方法对泸州市和北碚市降水量的时间序列进行了建模预测。结果表明ＰＰＡＲ（Ｋ）模型具有较高的稳定性和预测精度。     

Biostratigraphy and depositional facies of the Cretaceous-Tertiary boundary strata in Amakusa-Shimojima,Kyushu, Western Japan

The Upper Himenoura Subgroup exposed in the island of Amakusa-Shimojima, Kyushu, Japan shows an example of the terminal Cretaceous stratigraphic record in the circum Pacific region. This sequence is a part of the Upper Cretaceous intra-arc basins of southwest Japan. Four cycles of upward coarse-graded facies are recognized. Each cycle consists of a basinal mud facies in the lower part and a tide-dominated shallow marine to brackish coarse clastic facies in the upper part. Biostratigraphic correlation chiefly based on ammonites, inocerami and trigoniids indicates that this sequence is Campanian to Maastrichtian in age. The occurrence of the above three fossils decreases upward and is terminated at the top of the sequence, being replaced by a molluscan assemblage similar to the Danian. This suggests that the sedimentation may have continued to the very end of the Cretaceous period and possibly to the beginning of the Tertiary.     

Cretaceous transgressions and regressions on the Russian Platform, in Crimea and Central Asia

This paper is a brief explanation of the diagrams of the Cretaceous transgressions and regressions on the Russian Platform, in the Crimea (Figures 1–3) and some regions of central Asia—the western flanks of the Tien Shan mountains, the Fergana basin, the Zeravshan-Gissar and Alaj mountains, and the Northern Pamirs (Figures 5–7).Internationally recognized stages are employed. They are interpreted by Sasonova (1967) for the Lower Cretaceous (K₁) of the Russian Platform, by Naidin (1977) for the Upper Cretaceous (K₂) of the Platform and the Crimea, by Djalilov (1971) and Pojarkova (1976) for the Upper Cretaceous of central Asia. General data on the stratigraphy of the Cretaceous of central Asia may be found in Anon 1977.     

阿拉善地区土壤盐渍化的遥感反演及分布特征

土壤盐渍化是威胁干旱区土地的重要环境问题。利用遥感技术对土壤盐渍化进行动态监测,分析土壤盐度水平与空间分布,有利于掌握土壤盐渍化现状,为土地资源可持续利用提供理论依据。现有研究多在田间尺度,随着土壤环境问题涉及的范围越来越大,区域斑块信息的提取已无法满足宏观地模拟和展示整体土壤环境的空间分布。以阿拉善地区为例,结合遥感光谱指数与实测土壤盐分数据,运用偏最小二乘回归（PLSR）方法,构建区域尺度范围的土壤盐渍化反演模型,实现大面积地区土壤盐度的精准模拟和定量监测。结果表明,构建的模型验证精度达到0.8788,达到极显著水平,预测结果与实际情况相符,可以较准确地模拟研究区土壤盐渍化状况。受地形、气候、景观类型、农业活动以及土地管理等因素的综合影响,阿拉善地区约20%的区域土壤呈现出不同程度的盐渍化,其中黑河下游河岸带、雅布赖山西侧及贺兰山西侧冲积扇土壤盐渍化程度最为严重。本研究可为大面积区域土壤盐分状况的快速监测及遥感定量反演提供可行的方法,同时为该区域不同程度盐渍化土壤的治理和土地利用管理提供依据。     

基于GWR模型的道路网络对森林碳密度干扰的地理变异

以闽江上游地区为例,在分析三明市2007—2016年森林碳密度时空动态的基础上,采用常规的以及改进后的道路网络测度指标,应用缓冲区分析方法和地理加权回归（Geographically Weighted Regression,GWR）模型,从线上和面上分别探讨道路网络对森林碳密度干扰的地理变异规律。结果表明：① 碳密度受到道路网络的较大影响,路网影响域内外碳密度的大小排序为：路网影响域内＜整个研究区＜路网影响域外;多条道路影响域重叠区的碳密度(26.330 Mg/hm²)明显低于单条道路影响域的碳密度(37.406 Mg/hm²);不同等级道路影响域的碳密度由大到小依次为县道＞高速＞省道＞其它道路＞国道＞乡道。道路网络对2007—2016年碳密度的降低也有明显影响。② GWR模型的分析结果表明,路网对碳密度的影响程度随着样点的变化而变化,具有“空间非平稳性”。碳密度随着路网密度的增加而降低,而随着离道路距离的增加而增加。③ 研究区西北部和中部,GWR的回归系数及相关系数均较大,表明这2个区域道路对碳密度影响大且解释力皆较强。     

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.     

Response of runoff to climate change in the area of runoff yield in upstream Shiyang River Basin,Northwest China: A case study of the Xiying River

The objective of this study was to analyze the response of runoff in the area of runoff yield of the upstream Shiyang River basin to climate change and to promote sustainable development of regional water resources and ecological environment. As the biggest tributary of the Shiyang River, Xiying River is the only hydrological station (Jiutiaoling) that has provincial natural river and can achieve long time series monitoring data in the basin. The data obtained from this station is representative of natural conditions because it has little human activites. This study built a regression model through identifying the characteristics of runoff and climate change by using Mann-Kendall nonparametric statistical test, cumulative anomaly, and correlation analysis. The results show that the average annual runoff is 320.6 million m³/a with the coefficient of variation of 0.18 and shows slightly decrease during 1956–2020. It has a significant positive correlation the average annual precipitation (P<0.01). Runoff is sensitive to climate change, and the climate has becoming warm and wet and annual runoff has entering wet period from 2003. Compared to the earlier period (1955–2000), the increases of average annual temperature, precipitation and runoff in recent two decades were 15%, 9.3%, and 7.8%, respectively. Runoff in the Shiyang River is affected by temperature and precipitation among climate factors, and the simulation results of the runoff-climate response model (R = 0.0052P ? 0.1589T + 2.373) indicate that higher temperature leads to a weakening of the ecological regulation of surface runoff in the flow-producing area.