THE SENSITWITY OF NORTHERN SIERRA NEVADA STREAMFLOW TO CLIMATE CHANGE1

ABSTRACT: The sensitivity of streamflow to climate change was investigated in the American, Carson, and Truckee River Basins, California and Nevada. Nine gaging stations were used to represent streamflow in the basins. Annual models were developed by regressing 1961–1991 streamflow data on temperature and precipitation. Climate-change scenarios were used as inputs to the models to determine streamflow sensitivities. Climate-change scenarios were generated from historical time series by modifying mean temperatures by a range of +4°C to—4°C and total precipitation by a range of +25 percent to -25 percent. Results show that streamflow on the warmer, lower west side of the Sierra Nevada generally is more sensitive to temperature and precipitation changes than is streamflow on the colder, higher east side. A 2°C rise in temperature and a 25-percent decrease in precipitation results in stream-flow decreases of 56 percent on the American River and 25 percent on the Carson River. A 2°C decline in temperature and a 25-percent increase in precipitation results in streamflow increases of 102 percent on the American River and 22 percent on the Carson River.     

EMPIRICAL MODELS FOR TROPHIC STATE IN SOUTHEASTERN U.S. LAKES AND RESERVOIRS1

ABSTRACT: A cross-sectional data set of 80 lakes and reservoirs in nine southeastern states was examined to specify and parameterize trophic state relationships. The relationships fitted are based on measurements of several limnological variables taken over the course of a growing season or year in each of the lakes. The trophic state models relate phosphorus and nitrogen loading to inlake phosphorus and nitrogen concentrations, which in turn are related to maximum chlorophyll level, Secchi disk depth, dominant algal species, and hypolimnetic dissolved oxygen status. Due to the empirical nature of the study, causal conclusions are limited; rather, the models are most useful for prediction of average growing season conditions related to trophic state.     

ANALYTICAL REGRESSION STAGE ANALYSIS FOR DEVILS HOLE,DEATH VALLEY NATIONAL PARK,NEVADA1

ABSTRACT: Devils Hole is a collapse depression connected to the regional carbonate aquifer of the Death Valley ground water flow system. Devils Hole pool is home to an endangered pupfish that was threatened when irrigation pumping in nearby Ash Meadows lowered the pool stage in the 1960s. Pumping at Ash Meadows ultimately ceased, and the stage recovered until 1988, when it began to decline, a trend that continued until at least 2004. Regional ground water pumping and changes in recharge are considered the principal potential stresses causing long term stage changes. A regression was found between pumpage and Devils Hole water levels. Though precipitation in distant mountain ranges is the source of recharge to the flow system, the stage of Devils Hole shows small change in stage from 1937 to 1963, a period during which ground water withdrawals were small and the major stress on stage would have been recharge. Multiple regression analyses, made by including the cumulative departure from normal precipitation with pumpage as independent variables, did not improve the regression. Drawdown at Devils Hole was calculated by the Theis Equation for nearby pumping centers to incorporate time delay and drawdown attenuation. The Theis drawdowns were used as surrogates for pumpage in multiple regression analyses. The model coefficient for the regression, R²= 0.982, indicated that changes in Devils Hole were largely due to effects of pumping at Ash Meadows, Amargosa Desert, and Army 1.     

DETERMINING SIGNIFICANCE AND PRECISION OF ESTIMATED PARAMETERS FOR RUNOFF FROM SEMIARID WATERSHEDS1

ABSTRACT Significant parameters for predicting thunderstorm runoff from small semiarid watersheds are determined using data from the Walnut Gulch watershed in southern Arizona. Based on these data, thunderstorm rainfall is dominant over watershed parameters for predicting runoff from multiple linear regression equations. In some cases antecedent moisture added significantly to the models. A technique is developed for estimating precision of predicted values from multiple linear regression equations. The technique involves matrix methods in estimating the variance of mean predicted values from a regression equation. The estimated variance of the mean predicted value is then used to estimate the variance of an individual predicted value. A computer program is developed to implement these matrix methods and to form confidence limits on predicted values based on both a normality assumption and the Chebyshev inequality.     

对华北GPS监测区近期地壳应变连续分布的估计

直接利用华北ＧＰＳ监测网各个测点的位移观测值,借助高斯型位移协方差函数通过最小二乘配置建立连续分布的位移函数,并根据应变与位移的偏导关系,对华北ＧＰＳ监测区１９９２～１９９５年、１９９５～１９９６年最大剪应变及面膨胀连续分布进行估算,得到其应变场动态图像。     

The hybrid model of empirical wavelet transform and relevance vector regression for monthly wind speed prediction

ABSTRACT

In order to improve the prediction ability for the monthly wind speed of RVR, the hybrid model of empirical wavelet transform and relevance vector regression (EWT-RVR) is proposed for monthly wind speed prediction in this study. Compared with empirical mode decomposition (EMD), empirical wavelet transform (EWT) can obtain a more consistent decomposition and have a mathematical theory. In order to testify the superiority of EWT-RVR, several traditional RVR models are used to compare with the proposed EWT-RVR method under the situation of the same embedding dimensions. The experimental results show that the proposed EWT-RVR method has a better prediction ability for monthly wind speed than RVR. It can be concluded that the proposed EWT-RVR method for monthly wind speed is effective.     

Predicting mass rapid transit noise levels on an elevated station

This study developed a noise prediction model for elevated mass rapid transit (MRT) platforms. Relevant physical and operational parameters (e.g. cruise speed, acceleration and deceleration rates for trains, building fa?ade setbacks and so on) were collected from the Bangkok mass transit system (BTS), the first elevated MRT system operated in Bangkok, Thailand. The equivalent continuous sound pressure levels (L(Aeq)) were collected from both sides of the MRT stations at the center of each platform. The relevant parameters were collected on both platforms and ground level, on both sides of MRT stations. These parameters were statistically tested to determine their correlation with MRT noise. The final model was built from highly correlated parameters using multiple regression analysis with a stepwise regression technique. Statistical evaluation showed a high degree of goodness-of-fit test for the model to the observed data. Therefore, it can be efficiently used for the projection of MRT noise in the affected areas.     

安全投入与事故直接经济损失的问题研究

通过对安全投入及事故直接经济损失的分析研究,利用最小二乘法对安全投入比例(安全投入占GDP的比例)与事故直接经济损失之间的关系进行了回归分析,确定了其对应的函数关系.结果表明,安全投入比例与事故直接经济损失之间呈较明显的负指数关系.探讨了安全投入存在的主要问题,提出了几点关于加强安全投入的建议及措施.     

基于优势隐含周期分析的气象灾害预报

建立了优势因子和优势隐含周期的概念,并提出了多因子逐步回归周期分析的新方法。该方法既能增长预报期,又能充分利用物理因子的重要信息,同时在计算过程中还能挑选出起显著作用的优势因子和优势隐含周期,对预报气象要素的变化趋势效果较好,有一定的实用价值,是气象灾害预报的一条比较有效的途径。     

数字隐写技术及发展趋势

笔者通过强调数字隐写算法和隐写分析算法间的矛盾统一,介绍数字隐写算法的发展历程和趋势以及国内外的研究现状。重点介绍具有代表性的空域LSB隐写算法和频域JPEG图像隐写算法。通过基本算法、对基本算法的分析方法、基本算法改进措施的顺序,介绍算法的发展历程,分析算法的性能。对当前实验研究的进展和数字隐写技术存在的问题进行说明,并提出一些建设性意见,对隐写技术的发展前景和方向进行展望,指出数字隐写技术会成为密码术的重要补充,在信息安全传输方面发挥巨大的作用。