Borehole and surface-based hydrogeophysics     

Roger Guérin 《Hydrogeology Journal》2005,13(1):251-254

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Stochastic Modelling of the Impact of Flood Protection Measures Along the River Waal in the Netherlands     

Saskia Van Vuren  Huib J. De. Vriend  Sonja Ouwerkerk  Matthijs Kok 《Natural Hazards》2005,36(1-2):81-102

River flooding is a problem of international interest. In the past few years many countries suffered from severe floods. A large part of the Netherlands is below sea level and river levels. The Dutch flood defences along the river Rhine are designed for water levels with a probability of exceedance of 1/1250 per year. These water levels are computed with a hydrodynamic model using a deterministic bed level and a deterministic design discharge. Traditionally, the safety against flooding in the Netherlands is obtained by building and reinforcing dikes. Recently, a new policy was proposed to cope with increasing design discharges in the Rhine and Meuse rivers. This policy is known as the Room for the River (RfR) policy, in which a reduction of flood levels is achieved by measures creating space for the river, such as dike replacement, side channels and floodplain lowering. As compared with dike reinforcement, these measures may have a stronger impact on flow and sediment transport fields, probably leading to stronger morphological effects. As a result of the latter the flood conveyance capacity may decrease over time. An a priori judgement of safety against flooding on the basis of an increased conveyance capacity of the river can be quite misleading. Therefore, the determination of design water levels using a fixed-bed hydrodynamic model may not be justified and the use of a mobile-bed approach may be more appropriate. This problem is addressed in this paper, using a case study of the river Waal (one of the Rhine branches in the Netherlands). The morphological response of the river Waal to a flood protection measure (floodplain lowering in combination with summer levee removal) is analysed. The effect of this measure is subject to various sources of uncertainty. Monte Carlo simulations are applied to calculate the impact of uncertainties in the river discharge on the bed levels. The impact of the “uncertain” morphological response on design flood level predictions is analysed for three phenomena, viz. the impact of the spatial morphological variation over years, the impact of the seasonal morphological variation and the impact of the morphological variability around bifurcation points. The impact of seasonal morphological variations turns out to be negligible, but the other two phenomena appear to have each an appreciable impact (order of magnitude 0.05–0.1 m) on the computed design water levels. We have to note however, that other sources of uncertainty (e.g. uncertainty in hydraulic roughness predictor), which may be of influence, are not taken into consideration. In fact, the present investigation is limited to the sensitivity of the design water levels to uncertainties in the predicted bed level.  相似文献   

成熟勘探矿集区新一轮找矿：勘查战略创新及铜陵矿集区找矿实例   总被引：7，自引：0，他引：7       下载免费PDF全文

刘亮明吕俊武  彭省临王国平方维萱  邵拥军 《地质论评》2005,51(3):325-333

成熟勘探的矿集区非常有必要开展新一轮的找矿，但矿床模式的局限和大埋藏深度等困难制约了这些地区的预测性找矿发现。促进其预测性找矿发现的关键战略包括：勘查模型的创新、勘查技术的创新和各种信息的综合集成预测。勘查模型的创新必须包含基于地球动力学剖析的新成矿概念，动力学数值模拟是有效的创新手段之一；勘查技术创新的主要目的是加大探测深度和提高探测与解释的准确性，必须以详细可靠的地质资料为基础；综合信息集成是利用GIS和知识驱动及数据驱动的方法充分提取各种数据中的有用信息，集成为更加可靠的预测图。在这种思想的指导下，我们在铜陵凤凰山矿田进行了预测和勘查，并成功地发现了深部的隐伏矿床。  相似文献   

Low-order stabilized finite element for the full Biot formulation in soil mechanics at finite strain     

Lluís Monforte  Pedro Navas  Josep Maria Carbonell  Marcos Arroyo  Antonio Gens 《国际地质力学数值与分析法杂志》2019,43(7):1488-1515

This article presents a novel finite element formulation for the Biot equation using low-order elements. Additionally, an extra degree of freedom is introduced to treat the volumetric locking steaming from the effective response of the medium; its balance equation is also stabilized. The accuracy of the proposed formulation is demonstrated by means of numerical analyses.  相似文献   

基于Stacking集成学习的恒星/星系分类研究          下载免费PDF全文

李超  张文辉  李然  王俊义  林基明 《天文学报》2020,61(2):21-111

机器学习在当今诸多领域已经取得了巨大的成功,但是机器学习的预测效果往往依赖于具体问题.集成学习通过综合多个基分类器来预测结果,因此,其适应各种场景的能力较强,分类准确率较高.基于斯隆数字巡天(Sloan Digital Sky Survey,SDSS)计划恒星/星系中最暗源星等集分类正确率低的问题,提出一种基于Stacking集成学习的恒星/星系分类算法.从SDSS-DR7(SDSS Data Release 7)中获取完整的测光数据集,并根据星等值划分为亮源星等集、暗源星等集和最暗源星等集.仅针对分类较为复杂且困难的最暗源星等集展开分类研究.首先,对最暗源星等集使用10折嵌套交叉验证,然后使用支持向量机(Support Vector Machine,SVM)、随机森林(Random Forest,RF)、XGBoost(eXtreme Gradient Boosting)等算法建立基分类器模型;使用梯度提升树(Gradient Boosting Decision Tree,GBDT)作为元分类器模型.最后,使用基于星系的分类正确率等指标,与功能树(Function Tree,FT)、SVM、RF、GBDT、XGBoost、堆叠降噪自编码(Stacked Denoising AutoEncoders,SDAE)、深度置信网络(Deep Belief Network,DBN)、深度感知决策树(Deep Perception Decision Tree,DPDT)等模型进行分类结果对比分析.实验结果表明,Stacking集成学习模型在最暗源星等集分类中要比FT算法的星系分类正确率提高了将近10%.同其他传统的机器学习算法、较强的提升算法、深度学习算法相比,Stacking集成学习模型也有较大的提升.  相似文献   

徐州市水土流失时空变化研究     

陈报章  渠俊峰  葛梦玉  沈艳文  王安妮  王国斌 《地球信息科学学报》2018,20(11):1622-1630

本文以3S技术为支撑,在修正水土流失方程（RUSLE）的基础上,针对徐州黄泛平原-丘陵地带的特殊地形地貌、对2000年以来徐州市水土流失时空变化特征进行了分析。结果表明：2000-2014年徐州市土壤侵蚀等级以微度为主,微度侵蚀面积占总侵蚀面积多年平均达到76.34%;中度侵蚀次之,所占比例在10%~17%间;剧烈侵蚀所占比例最少。轻度及以上土壤侵蚀等级主要发生在中部微山湖下游、京杭大运河一带的丘陵岗地地区、主城区与故黄河北岸的黄泛平原地区,以及丰县、新沂、邳州的局部区域;土壤侵蚀存在一定程度年际变化特征,睢宁、丰县、邳州的部分地区侵蚀面积年际变化较为明显,土壤侵蚀总面积整体上呈现下降趋势。  相似文献   

Ocean current estimation using a Multi-Model Ensemble Kalman Filter during the Grand Lagrangian Deployment experiment (GLAD)     

《Ocean Modelling》2015

In the summer and fall of 2012, during the GLAD experiment in the Gulf of Mexico, the Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) used several ocean models to assist the deployment of more than 300 surface drifters. The Navy Coastal Ocean Model (NCOM) at 1 km and 3 km resolutions, the US Navy operational NCOM at 3 km resolution (AMSEAS), and two versions of the Hybrid Coordinates Ocean Model (HYCOM) set at 4 km were running daily and delivering 72-h range forecasts. They all assimilated remote sensing and local profile data but they were not assimilating the drifter’s observations. This work presents a non-intrusive methodology named Multi-Model Ensemble Kalman Filter that allows assimilating the local drifter data into such a set of models, to produce improved ocean currents forecasts. The filter is to be used when several modeling systems or ensembles are available and/or observations are not entirely handled by the operational data assimilation process. It allows using generic in situ measurements over short time windows to improve the predictability of local ocean dynamics and associated high-resolution parameters of interest for which a forward model exists (e.g. oil spill plumes). Results can be used for operational applications or to derive enhanced background fields for other data assimilation systems, thus providing an expedite method to non-intrusively assimilate local observations of variables with complex operators. Results for the GLAD experiment show the method can improve water velocity predictions along the observed drifter trajectories, hence enhancing the skills of the models to predict individual trajectories.  相似文献   

Efficient estimation of flood forecast prediction intervals via single‐ and multi‐objective versions of the LUBE method          下载免费PDF全文

Lei Ye  Jianzhong Zhou  Hoshin V. Gupta  Hairong Zhang  Xiaofan Zeng  Lu Chen 《水文研究》2016,30(15):2703-2716

Prediction intervals (PIs) are commonly used to quantify the accuracy and precision of a forecast. However, traditional ways to construct PIs typically require strong assumptions about data distribution and involve a large computational burden. Here, we improve upon the recent proposed Lower Upper Bound Estimation method and extend it to a multi‐objective framework. The proposed methods are demonstrated using a real‐world flood forecasting case study for the upper Yangtze River Watershed. Results indicate that the proposed methods are able to efficiently construct appropriate PIs, while outperforming other methods including the widely used Generalized Likelihood Uncertainty Estimation approach. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

Analytical solutions for advective–dispersive solute transport in double‐layered finite porous media     

Peter John Cleall 《国际地质力学数值与分析法杂志》2011,35(4):438-460

Analytical solutions for advection and dispersion of a conservative solute in a one‐dimensional double‐layered finite porous media are presented. The solutions are applicable to five scenarios that have various combinations of fixed concentration, fixed flux and zero concentration gradient conditions at the inlet and outlet boundaries that provide a wide number of options. Arbitrary initial solute concentration distributions throughout the media can be considered via explicit formulations or numerical integration. The analytical solutions presented have been verified against numerical solutions from a finite‐element‐based approach and an existing closed‐form solution for double‐layered media with an excellent correlation being found in both cases. A practical application pertaining to advective transport induced by consolidation of underlying sediment layers on contaminant movement within a capped contaminated sediment system is presented. Comparison of the calculated concentrations and fluxes with alternative approaches clearly illustrates the need to consider advection processes. Consideration of the different features of contaminant transport due to varying pore‐water velocity fields in primary consolidation and secondary consolidation stages is achieved via the use of non‐uniform initial concentration distributions within the proposed analytical solutions. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

The data‐driven approach as an operational real‐time flood forecasting model     

Phuoc Khac‐Tien Nguyen  Lloyd Hock‐Chye Chua 《水文研究》2012,26(19):2878-2893

Accurate water level forecasts are essential for flood warning. This study adopts a data‐driven approach based on the adaptive network–based fuzzy inference system (ANFIS) to forecast the daily water levels of the Lower Mekong River at Pakse, Lao People's Democratic Republic. ANFIS is a hybrid system combining fuzzy inference system and artificial neural networks. Five ANFIS models were developed to provide water level forecasts from 1 to 5 days ahead, respectively. The results show that although ANFIS forecasts of water levels up to three lead days satisfied the benchmark, four‐ and five‐lead‐day forecasts were only slightly better in performance compared with the currently adopted operational model. This limitation is imposed by the auto‐ and cross‐correlations of the water level time series. Output updating procedures based on the autoregressive (AR) and recursive AR (RAR) models were used to enhance ANFIS model outputs. The RAR model performed better than the AR model. In addition, a partial recursive procedure that reduced the number of recursive steps when applying the AR or the RAR model for multi‐step‐ahead error prediction was superior to the fully recursive procedure. The RAR‐based partial recursive updating procedure significantly improved three‐, four‐ and five‐lead‐day forecasts. Our study further shows that for long lead times, ANFIS model errors are dominated by lag time errors. Although the ANFIS model with the RAR‐based partial recursive updating procedure provided the best results, this method was able to reduce the lag time errors significantly for the falling limbs only. Improvements for the rising limbs were modest. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献