A NEW METHOD FOR ESTIMATING FUTURE RESERVOIR STORAGE CAPACITIES1

ABSTRACT: A new method has been developed for estimating future reservoir storage capacities, allowing for sediment deposition and compaction. Reservoir sedimentation surveys for 117 reservoirs, conducted by the Illinois State Water Survey over the past 60 years, were used to determine regional constants K to represent the severity of sediment deposition in the reservoirs. More than half of the 82 water supply reservoirs investigated had records of reservoir sedimentation surveys, and their K values were calculated by using data from those sediment surveys. The average K values of the remaining non-surveyed water supply reservoirs were estimated from the regional distribution of the K values. Other important factors considered in the estimation of future reservoir storage capacities are the trap efficiency of the reservoirs and the variation of density of sediment deposits due to compaction. The model can also be used for analyzing the economics of alternative sites and of design features that can be incorporated in dams for reducing reservoir sedimentation.     

MODELING RAINFALL-RUNOFF PROCESS INCLUDING LOSSES1

ABSTRACT: Existing discrete, linear rainfall-runoff models generally require the effective rainfall of a given storm as the input for computing the runoff hydrograph. This paper proposes a method for estimating, simultaneously, the optimal values of model parameters and the rainfall losses frem the measured rainfall hyetograph and the runoff hydrograph. The method involves an ARMA model for the rainfall-runoff process and a nonlinear iterative technique. The number of model parameters to be estimated for the ARMA model is much less than the unit hydrograph model. Applications of the model to three different watersheds show that the computed runoff hydrographs agree well with the measurements.     

CATCHMENT RESPONSE TIME AS A PREDICTOR OF FLOOD QUANTILES1

ABSTRACT: A regression analysis using a generalized least squares approach on flow data from the driftless area of Wisconsin indicates that the ratio of drainage area to time-to-peak is a good predictor of flood quantiles. The estimation of time-to-peak (or some other measure of basin response time) requires direct measurement of river stage and possibly rainfall at the site of which the quantiles are to be estimated. The cost-effectiveness of such an approach must yet be determined.     

A COMPARATIVE ANALYSIS OF TECHNIQUES FOR SPATIAL INTERPOLATION OF PRECIPITATION1

One of the problems which often arises in engineering hydrology is to estimate data at a given site because either the data are missing or the site is ungaged. Such estimates can be made by spatial interpolation of data available at other sites. A number of spatial interpolation techniques are available today with varying degrees of complexity. It is the intent of this paper to compare the applicability of various proposed interpolation techniques for estimating annual precipitation at selected sites. The interpolation techniques analyzed include the commonly used Thiessen polygon, the classical polynomial interpolation by least-squares or Lagrange approach, the inverse distance technique, the multiquadric interpolation, the optimal interpolation and the Kriging technique. Thirty years of annual precipitation data at 29 stations located in the Region II of the North Central continental United States have been used for this study. The comparison is based on the error of estimates obtained at five selected sites. Results indicate that the Kriging and optimal interpolation techniques are superior to the other techniques. However, the multiquadric technique is almost as good as those two. The inverse distance interpolation and the Thiessen polygon gave fairly satisfactory results while the polynomial interpolation did not produce good results.     

PERIODIC AUTOREGRESSIVE-MOVING AVERAGE (PARMA) MODELING WITH APPLICATIONS TO WATER RESOURCES1

Results involving correlation properties and parameter estimation for autoregressive-moving average models with periodic parameters are presented. A multivariate representation of the PARMA model is used to derive parameter space restrictions and difference equations for the periodic autocorrelations. Close approximation to the likelihood function for Gaussian PARMA processes results in efficient maximum-likelihood estimation procedures. Terms in the Fourier expansion of the parameters are sequentially included, and a selection criterion is given for determining the optimal number of harmonics to be included. Application of the techniques is demonstrated through analysis of a monthly streamflow time series.     

Subsampling program for the estimation of fish impingement

Federal regulations require operators of nuclear and coal-fired power-generating stations to estimate the number of fish impinged on intake screens. During winter months, impingement may range into the hundreds of thousands for certain species, making it impossible to count all intake screens completely. We present graphs for determinig the appropriateoptimal subsample that must be obtained to estimate the total number impinged. Since the number of fish impinged tends to change drastically within a short time period, the subsample size is determined based on the most recent data. This allows for the changing nature of the species-age composition of the impinged fish. These graphs can also be used for subsampling fish catches in an aquatic system when the size of the catch is too large to sample completely.     

Modeling Afforestation and the Underlying Uncertainties

A dynamic model of the carbon budget of an oak forest ecosystem that takes into account forest stand age was developed. A numerical experiment was designed to simulate the afforestation process, and a Monte Carlo simulation was performed to determine how parameter uncertainties and environmental variability influence the result. It was found that while the total amount of carbon stored in the ecosystem increases from 1.9 kg C/m² to 4.4 kg C/m² over the following 20 years, the relative standard deviation increases from 9 to 21%. The contribution of varying climate and carbon dioxide parameters to total uncertainty is substantial; for example, the standard deviation at the 10th modeling year for phytomass doubles and the uncertainties of the soil pool and total accumulated carbon increase by a factor of nearly 1.4, while the uncertainty of the litter pool stays almost at the same level.     

基于GIS的2.5维场地地震液化势概率评价

用具有概率意义的饱和砂土抗液化强度经验公式对2.5维工程场地进行了地震液化势概率评价,通过Kriging法对目标场地区域进行空间插值,可以对大区域工程场地的液化深度和液化范围进行分析评价;采用不规则三角网表面和四面体综合法共同描述地质体模型,在GIS的3维分析模块支持下建立了液化势可视化模型。研究表明:Kriging法通过已勘测点的土层地震液化势来估计未勘测点的土层地震液化势,能够较好地区划出场地地震液化势的空间分布特征,并对待估点进行预测;利用GIS的3维分析模块,实现2.5维场地地震液化势可视化模型的建立是一条有效的技术路线。     

非线性时序法在城市大气污染预测中的应用

建立城市大气污染预测模型是治理城市大气污染的重要工作。在简述时间序列方法基本原理的基础上，分析了系数为变量的自回归滑动平均（ARMA）模型、截断ARMA模型，和残差为自回归综合滑动平均（ARIMA）的半参数方法等城市大气污染预测模型。以法国某城市为例，分别采用AR模型和系数为变量的AR模型对大气污染进行了预测。通过比较预测结果可知，基于非线性时间序列方法的城市大气污染预测模型可以提高预测精度，降低预测误差。     

基于多元线性回归的宗地地价评估--以东营市为例

基准地价系数修正法作为大量评估宗地地价的一种方法，得到了广泛的应用，但是由于修正体系因素的权重确定多是通过特尔斐法来确定，主观性比较强。以东营市为例，探讨了用多元线性回归模型的方法进行修正因素影响的计算，并对宗地地价进行了评估。