Forecasting monthly inflow with extreme seasonal variation using the hybrid SARIMA-ANN model

The optimal operation of dam reservoirs can be programmed and managed by predicting the inflow to these structures more accurately. To this end, there are various linear and nonlinear models. However, some hydrological problems like inflow with extreme seasonal variation are not purely linear or nonlinear. To improve the forecasting accuracy of this phenomenon, a linear Seasonal Auto Regressive Integrated Moving Average (SARIMA) model is combined with a nonlinear Artificial Neural Network (ANN) model. This new model is used to predict the monthly inflow to the Jamishan dam reservoir in West Iran. A comparison of the SARIMA and ANN models with the proposed hybrid model’s results is provided accordingly. More specifically, the models’ performance in forecasting base and flood flows is evaluated. The effect of changing the forecasting period length on the models’ accuracy is studied. The results of increasing the number of SARIMA model parameters up to five are investigated to achieve more accurate forecasting. The hybrid model predicts peak flood flows much better than the individual models, but SARIMA outperforms the other models in predicting base flow. The obtained results indicate that the hybrid model reduces the overall forecast error more than the ANN and SARIMA models. The coefficient of determination of the hybrid, ANN and SARIMA models were 0.72, 0.64 and 0.58, and the root mean squared error values were 1.02, 1.16 and 1.27 respectively, during the forecast period. Changing the forecasting length also indicated that these models can be used in the long term without increasing the forecast error.     

Improving at-site flood frequency analysis with additional spatial information: a probabilistic regional envelope curve approach

Extreme flood events have detrimental effects on society, the economy and the environment. Widespread flooding across South East Queensland in 2011 and 2013 resulted in the loss of lives and significant cost to the economy. In this region, flood risk planning and the use of traditional flood frequency analysis (FFA) to estimate both the magnitude and frequency of the 1-in-100 year flood is severely limited by short gauging station records. On average, these records are 42 years in Eastern Australia and many have a poor representation of extreme flood events. The major aim of this study is to test the application of an alternative method to estimate flood frequency in the form of the Probabilistic Regional Envelope Curve (PREC) approach which integrates additional spatial information of extreme flood events. In order to better define and constrain a working definition of an extreme flood, an Australian Envelope Curve is also produced from available gauging station data. Results indicate that the PREC method shows significant changes to the larger recurrence intervals (≥100 years) in gauges with either too few, or too many, extreme flood events. A decision making process is provided to ascertain when this method is preferable for FFA.     

A stochastic methodology for risk assessment of a large earthquake when a long time has elapsed

We propose a stochastic methodology for risk assessment of a large earthquake when a long time has elapsed from the last large seismic event. We state an approximate probability distribution for the occurrence time of the next large earthquake, by knowing that the last large seismic event occurred a long time ago. We prove that, under reasonable conditions, such a distribution is exponential with a rate depending on the asymptotic slope of the cumulative intensity function corresponding to a nonhomogeneous Poisson process. As it is not possible to obtain an empirical cumulative distribution function of the waiting time for the next large earthquake, an estimator of its cumulative distribution function based on existing data is derived. We conduct a simulation study for detecting scenario in which the proposed methodology would perform well. Finally, a real-world data analysis is carried out to illustrate its potential applications, including a homogeneity test for the times between earthquakes.     

Frequency based imputation of precipitation

Changing climate and precipitation patterns make the estimation of precipitation, which exhibits two-dimensional and sometimes chaotic behavior, more challenging. In recent decades, numerous data-driven methods have been developed and applied to estimate precipitation; however, these methods suffer from the use of one-dimensional approaches, lack generality, require the use of neighboring stations and have low sensitivity. This paper aims to implement the first generally applicable, highly sensitive two-dimensional data-driven model of precipitation. This model, named frequency based imputation (FBI), relies on non-continuous monthly precipitation time series data. It requires no determination of input parameters and no data preprocessing, and it provides multiple estimations (from the most to the least probable) of each missing data unit utilizing the series itself. A total of 34,330 monthly total precipitation observations from 70 stations in 21 basins within Turkey were used to assess the success of the method by removing and estimating observation series in annual increments. Comparisons with the expectation maximization and multiple linear regression models illustrate that the FBI method is superior in its estimation of monthly precipitation. This paper also provides a link to the software code for the FBI method.     

Assessment of earthquake hazard for the northwestern Vietnam from geological and geophysical data using an original program package

The highest seismic activity in Vietnam is observed in the northwest of the country, hence the practical significance of more accurate assessment of the earthquake hazard for the area. The worldwide experience of seismicity, in particular, the recent Tohoku mega-earthquake (March 11, 2011, M _w = 9.0, Japan) shows that instrumental and historical data alone are insufficient to reliably estimate earthquake hazard. This is all the more relevant in relation to Vietnam where the period of instrumental observation is short and historical evidence is nearly lacking. In this connection we made an attempt to construct maps of earthquake hazard based on known seismicity data using the available geological and geophysical data and the method of G.I. Reisner and his associates for classification of areas by seismic potential. Since the question of what geological and geophysical parameters are to be used and with what weights remains unresolved, we developed a program package to estimate Mmax based on different options in the use of geological and geophysical data. In this paper we discuss the first results and the promise held by this program package.     

汶川8.0级地震前地震空间相关长度变化特征

分析了汶川8.0级地震前的地震空间长度的时空演变。在计算空间相关长度过程中采用长轴与孕震区主要断裂走向一致的椭圆型空间窗,并设计了优化程序。在本次特大地震前观测到了增长的地震空间相关长度。利用合成地震目录对结果进行了显著性检验,结果否定了零假设,表明观察到的模型不是由随机数据干扰造成的,这一观点的置信水平被证实为93.9%。     

A simplified methd of evaluating the seismic performance of buildings

This paper presents a simplified method of evaluating the seismic performance of buildings. The proposed method is based on the transformation of a multiple degree of freedom (MDOF) system to an equivalent single degree of freedom (SDOF) system using a simple and intuitive process. The proposed method is intended for evaluating the seismic performance of the buildings at the intermediate stages in design, while a rigorous method would be applied to the final design. The performance of the method is evaluated using a series of buildings which are assumed to be located in Victoria in western Canada, and designed based on the upcoming version of the National Building Code of Canada which is due to be published in 2005. To resist lateral loads, some of these buildings contain reinforced concrete moment resisting frames,while others contain reinforced concrete shear walls. Each building model has been subjected to a set of site-specific seismic spectrum compatible ground motion records, and the response has been determined using the proposed method and the general method for MDOF systems. The results from the study indicate that the proposed method can serve as a useful tool for evaluation of seismic performance of buildings, and carrying out performance based design.     

Summary of recent volcanic activity

Information included in this summary is based on more detailed reports published in the Bulletin of the Global Volcanism Network, v. 29, no. 4, April 2004 (on the Internet at ). Edited by scientists at the Smithsonian, this Bulletin includes reports provided by a worldwide network of correspondents. The reports contain the names and contact information for all sources. Please note that these reports are preliminary and subject to change as events are studied in more detail. The Global Volcanism Program welcomes further reports of current volcanism, seismic unrest, monitoring data, and field observations.     

Smithsonian Institution’s Global Volcanism Network

Information included in this summary is based on more detailed reports published in the Bulletin of the Global Volcanism Network, vol. 28, No. 9, September 2003 (on the Internet at ). Edited by scientists at the Smithsonian, this bulletin includes reports provided by a worldwide network of correspondents. The reports contain the names and contact information for all sources. Please note that these reports are preliminary and subject to change as events are studied in more detail. The Global Volcanism Program welcomes further reports of current volcanism, seismic unrest, monitoring data, and field observations.