Predictive Uncertainty in Water-Quality Modeling

A general and integrated approach to parameter identification, model calibration, and estimation of predictive uncertainty in water-quality models is proposed and validated. The proposed approach determines the maximal conditional likelihood functions of each of the model parameters using a transformation that forces the model errors to be normally distributed, with predictive uncertainty characterized by random normally distributed and homoscedastic model errors in the transform space. The proposed approach is demonstrated using a watershed-scale model to predict the fecal coliform levels in a third-order stream within the Little River Experimental Watershed in Georgia. Maximal conditional likelihood functions were identified for all parameters in the log, square root, and no-transformation cases. The key results are: (1) the number of sensitive parameters and the optimal parameter values can depend on the transformation; (2) only in the case of the log-transformation are the errors normally distributed and consistent with the assumed Gaussian likelihood function; (3) the standard error in the model is least for the no-transform case and highest for the log-transform case; and (4) the observed model errors are most predictable using the log-transform and least predictable using the no-transform approach.     

图像的区域描述方法及运动估计

文中提出一种任意形状区域的图像描述方法进行图像序列的运动估计。首先,对初始帧图像采用保边界平滑,然后,对平滑帧进行分水岭分割。根据标记图像,将图像以区域邻接图的方式进行存储。为解决过度分割的问题,给出了区域的灰度特性和边界强度及区域尺寸相结合的融合准则。最后,每个区域采用仿射运动模型及非线性最小均方法进行参数优化。得到的运动矢量场同基于像素点的估计方法相比具有更高的一致性和抗干扰性,运动补偿差图像的峰值信噪比得以提高。     

Reference and Crop Evapotranspiration in South Central Nebraska. I: Comparison and Analysis of Grass and Alfalfa-Reference Evapotranspiration

In Nebraska, historically, there have been differences among the water regulatory agencies in terms of the methods used to compute reference evapotranspiration (ETref) to determine actual crop water requirements and hydrologic balances of watersheds. Because simplified and/or empirical temperature or radiation-based methods lack some of the major weather parameters that can significantly affect grass and alfalfa-reference ET (ETo and ETr) the performance of these methods needs to be investigated to help decision makers to determine the potential differences associated with using various ETref equations relative to the standardized ASCE Penman–Monteith (ASCE-PM) equations. The performance of 12 ETo and five ETr equations were analyzed on a daily basis for south central Nebraska from 1983 to 2004. The standardized ASCE-PM ETo and ETr values were used as the basis for comparisons. The maximum ASCE-PM ETo value was estimated as 12.6?mm?d?1, and the highest ETr value was estimated as 19?mm?d?1 on June 21, 1988. On this day, the atmospheric demand for evaporation was extremely high and the vapor pressure deficit (VPD) reached a remarkably high value of 4.05?kPa. The combination-based equations exhibited significant differences in performance. The 1963 Penman method resulted in the lowest RMSD of 0.30?mm?d?1 (r2 = 0.98) and its estimates were within 2% of the ASCE-PM ETo estimates. The 1948 Penman estimates were similar to the 1963 Penman (r2 = 0.98, RMSD = 0.39?mm?d?1). Kimberly forms of alfalfa-reference Penman equations performed well with RMSD of 0.48?mm?d?1 for the 1972 Kimberly–Penman and 0.67?mm?d?1 for the 1982 Kimberly–Penman. The locally-calibrated High Plains Regional Climate Center (HPRCC) Penman method, ranked 6th, performed well and underestimated the ASCE-PM ET by 5% (RMSD = 0.56?mm?d?1). Most of the underestimations occurred at the high ET range (>11?mm) and this was attributed to the upper limits applied by the HPRCC on VPD, (2.3?kPa) and wind speed (5.1?m?s?1). The lack of ability of the radiation methods in accounting for the wind speed and relative humidity hindered the performance of these methods in the windy and rapidly changing VPD conditions of south central Nebraska. The 1977 FAO24 Blaney–Criddle method was the highest ranked (seventh) noncombination method (RMSD = 0.64?mm?d?1, r2 = 0.94). The FAO24 Penman estimates were within 4% of the ASCE-PM ETo. Overall, there were large differences between the ASCE-PM ETo and ETr versus other ETref equations that need to be considered when other forms of the combination or radiation and temperature-based equations are used to compute ETref. We recommend that the ASCE-PM ETo or ETr equations be used for estimating ETref when necessary weather variables are available and have good quality. The results of this study can be used as a reference tool to provide practical information, for Nebraska and similar climates, on the potential differences between the ASCE-PM ETo and ETr and other ETref equations. Results can aid in selection of the alternative method(s) for reasonable ETref estimations when all the necessary weather inputs are not available to solve the ASCE-PM equation.