Evaluation of the Hurricane Weather Research and Forecasting (HWRF) model for tropical cyclone forecasts over the North Indian Ocean (NIO)

Natural Hazards - The Hurricane Weather Research and Forecast (HWRF) model, which was operational at the US National Centers for Environmental Prediction, was ported in India Meteorological...     

咸阳地热田钻孔温度测量及水动力系统

地热田温度场分析, 不仅为地热田类型划分和热源机理研究提供科学根据, 而且可以为确定地热田有利开采区域和深度提供直接依据。本文报道了咸阳地热田13口钻孔的系统(准)稳态测温数据, 对研究区温度的垂向分布特征做了初步分析, 并据此划分了地热田水动力系统。结果表明, 咸阳地热田属于以传导为主的沉积盆地型地热田, 地温梯度为26.2~40.1 ℃/km, 平均为32.4 ℃/km。然而, 与典型的传导型地热田相比, 咸阳地热田的地温场特征又存在特殊性, 表现为钻孔温度-深度曲线分段性明显: 浅部受地表水流动对温度场的影响, 地温曲线呈现出锯齿形波动; 钻孔中上部受地表水和深部水热活动影响较小, 温度曲线为传导性地热特征; 井孔中下部测温曲线明显"下凹", 揭示了地下水沿渭河断裂侧向补给的同时使地层温度降低; 井孔下部温度随深度异常增大, 表明存在异常压力流体封存箱。测温资料揭示了咸阳地热田水动力系统在垂向上存在多层结构: 浅部为垂向重力驱动型, 中上部为正常压实型, 中下部为侧向重力驱动型, 下部为封闭型。基于咸阳地热田水动力系统的多层结构, 建议将各系统赋存的地热资源分别进行规划和开发。     

Dynamic soil–structure interaction analysis using Lanczos vectors with adaptive time integration technique

An analytical procedure to obtain the response of soil–structure interaction problems, time domain is described. The procedure makes use of large domain for descritization along with co-ordinate transformation using Lanczos vectors. The responses are obtained in time domain using an adaptive direct integration method. The scheme has the ability to estimate errors due to temporal discretization as well as co-ordinate transformation. The procedure has been applied to half-space problems and non-convex domains for validation of the scheme, and the scheme obeys causality condition in both the situations. The present method has all the advantages of time domain scheme which is local both in space and time with small computational effort. Copyright © 1999 John Wiley & Sons, Ltd.     

Groundwater modelling to quantify the effect of water harvesting structures in Wagarwadi watershed,Parbhani district,Maharashtra, India

Marathwada Agricultural University, Pharbani, has developed about 560 hectares of Wagarwadi watershed in Pharbani district since 1987. Groundwater monitoring on 16 observations wells at weekly intervals commenced in January 1992, and rainfall and pan evaporation has been measured daily at a hydrometeorological station situated in the nearby university campus. Aquifer parameters, namely, transmissivity and specific yield, have been estimated by carrying out a pumping test on a large diameter well. Groundwater recharge resulting from rainfall has been estimated using a water balance model of the soil moisture zone considering soil zone thickness and crops grown. The SCS (Soil Conservation Service) curve number method was used for surface runoff estimation. The groundwater flow model has been constructed using the nested squares, finite difference method. Nested square meshes of sizes 160 m×160 m and 80 m×80 m have been used and the steady-state condition of aquifer system was simulated in the model assuming the June 1992 water level configuration under equilibrium conditions. The model has been calibrated for transient conditions incorporating additional seepage from the water harvesting structures and their contribution to the groundwater regime has been assessed. © 1998 John Wiley & Sons, Ltd.     

基于正交多项式变换的CMP动校正道集随机噪声压制

本文提出了一种新的基于正交多项式变换来压制动校正后CMP道集上随机噪声的方法,将地震资料经过正交多项式变换,建立正交多项式系数谱,该谱描述了地震资料在正交多项式域的能量分布,可以较好地分离有效波和随机噪声,相对于固定阶次的基于正交多项式变换压制噪声的方法,所提出的方法根据能量随阶次变化的规律,自适应确定表达有效信号的正交多项式阶次,既提高了信号和噪声的分离效果,又有效地保护了地震信号中的AVO信息,对人工合成数据和实际资料的处理结果表明了所提出方法的有效性.     

Modelling groundwater levels in an urban coastal aquifer using artificial neural networks

The prediction of groundwater levels in a basin is of immense importance for the management of groundwater resources, especially in coastal regions where the water table fluctuations are to be limited to avoid seawater intrusion. In this paper, an Artificial Neural Network (ANN) methodology is presented to predict groundwater levels in individual wells with one month lead. Groundwater levels were also predicted in neighboring wells using model parameters from the best network of a well. This methodology is applied to an urban coastal aquifer in Andhra Pradesh state, India. The results suggest that the feed forward neural network with Levenberg Marquardt (LM) algorithm is a good choice for predicting groundwater levels in individual wells. Bayesian Regularization (BR) model parameters of Balaji Nagar well are also used successfully to predict groundwater levels in the study area. It was observed that the ANN‐based algorithms were a better choice for the prediction of groundwater levels with limited hydrological parameters. Copyright © 2007 John Wiley & Sons, Ltd.     

Non-linear analysis of undrained cyclic strength of soft marine clay

Iwan models are used to simulate the non-linear and hysteretic behaviour of soils under cyclic loading conditions. However, the model in its original form cannot take into account the stiffness degradation which is observed during cyclic loading of soft clays. Studies show that the stiffness reduction (expressed as degradation index) can be represented as a function of the number of cycles and of a degradation parameter depending on the strain amplitude in the case of strain controlled cyclic loading tests. This degradation index has been incorporated into Iwan's series–parallel model as a single fatigue parameter to account for the degradation during cyclic loading. The comparisons made with the existing results of two marine clays tested under undrained cyclic triaxial and simple shear conditions provided an opportunity to understand the capability of the one dimensional model.     

Role of reservoirs in sustained seismicity of Koyna-Warna region—a statistical analysis

Koyna-Warna region in western India is a globally recognized site of reservoir-triggered seismicity near the Koyna and Warna reservoirs. The region has been reported with several M?>?5 earthquakes in the last five decades including M6.3 Koyna earthquake which is considered as the largest triggered earthquake worldwide. In the present study, a detailed statistical analysis has been done for long period earthquake catalogues during 1968–2004 of MERI and 2005–2012 of CSIR-NGRI to find out the spatio-temporal influence of the Koyna and Warna reservoirs impoundment on the seismicity of the region. Depending upon the earthquake clusters, we divided the region into three different zones and performed power spectrum and singular spectrum analysis (SSA) on them. For the time period 1983–1995, the earthquake zone near the Warna reservoir; for 1996–2004, the earthquake zone near the Koyna reservoir; and for 2005–2012, the earthquake zone near the Warna reservoir found to be influenced by the annual water level variations in the reservoirs that confirm the continuous role of both the reservoirs in the seismicity of the Koyna-Warna region.