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111.
Yongnian Ni Lin Wang Serge Kokot 《Journal of environmental science and health. Part. B》2013,48(4):328-335
A novel differential pulse voltammetry method (DPV) was researched and developed for the simultaneous determination of Pendimethalin, Dinoseb and sodium 5-nitroguaiacolate (5NG) with the aid of chemometrics. The voltammograms of these three compounds overlapped significantly, and to facilitate the simultaneous determination of the three analytes, chemometrics methods were applied. These included classical least squares (CLS), principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural networks (RBF-ANN). A separately prepared verification data set was used to confirm the calibrations, which were built from the original and first derivative data matrices of the voltammograms. On the basis relative prediction errors and recoveries of the analytes, the RBF-ANN and the DPLS (D – first derivative spectra) models performed best and are particularly recommended for application. The DPLS calibration model was applied satisfactorily for the prediction of the three analytes from market vegetables and lake water samples. 相似文献
112.
D. L. DeAngelis P. J. Mulholland J. W. Elwood A. V. Palumbo A. D. Steinman 《Environmental management》1990,14(5):685-697
In systems where production is limited by the availability of a nutrient, nutrient input to and recycling within the system
is related to the resilience, or speed of recovery, of a system to its steady state following a disturbance. In particular,
it is shown that the return timeT
s
of the system to steady state, or the inverse of the resilience, is approximately equal to the mean turnover time of the
limiting nutrient in the system. From this relationship, it is possible to understand and predict how various properties of
food webs and their environments affect resilience. These properties include nutrient input rate, loss rate, size of the detritus
compartment, and trophic structure. The effects of these properties on resilience are described by using simple mathematical
models.
To test model predictions, experimental studies of the response of periphyton-dominated stream ecosystems to disturbance are
being conducted on a set of laboratory streams in which nutrient inputs and grazing intensity are regulated at different levels.
In streams without snail grazers (low-grazed streams), 90% recirculation of stream water to reduce nutrient inputs resulted
in longer turnover times (T
r
) of phosphorus within the stream compared with once-through flow. However, in streams with snail grazers (high-grazed streams),
there were no differences in phosphorus turnover time between once-through and partially recirculated treatments. Results
on the rate of recovery of periphyton from a flood/scour disturbance to each stream partially support the model prediction
of a positive relationship between ecosystem return time (T
s
) and nutrient turnover time (T
r
) within the streams. 相似文献
113.
Richard A. Herbert Darrell D. Carlson Gregg J. Wiche 《Journal of the American Water Resources Association》1985,21(6):953-965
The crest-stage gage program in Louisiana was evaluated to determine if the data were adequate for use in developing regional flood-frequency equations and to determine if any crest-stage gage stations could be discontinued. An abundance of data at many crest-stage gage stations and a lack of data for urban areas and flat-slope areas indicated a need for a shift in the number, type, and locations of gages. Correlations and comparisons of annual peak discharges and watershed characteristics of 96 existing stations resulted in the elimination of 72 stations and the addition of one new station, reducing the total network to 25 stations that could be used for future flood-frequency analyses. The adequacy of the reduced network for development and verification of regional flood-frequency equations was tested by comparing a set of regional flood-frequency equations developed using data from the full network with a set developed using data from the reduced network. The results indicate that the crest-stage gage network can be reduced to 25 stations and still provide adequate information for future flood-frequency analyses. 相似文献
114.
Large-scale constructed wetlands for nutrient removal from stormwater runoff: An everglades restoration project 总被引:14,自引:0,他引:14
Mariano Guardo Larry Fink Thomas D. Fontaine Susan Newman Michael Chimney Ronald Bearzotti Gary Goforth 《Environmental management》1995,19(6):879-889
The South Florida Water Management District (SFWMD) constructed a wetland south of Lake Okeechobee to begin the process of
removing nutrients (especially phosphorus) from agricultural stormwater runoff entering the Everglades. The project, called
the Everglades Nutrient Removal (ENR) project, is a prototype for larger, similarly constructed wetlands that the SFWMD will
build as part of the Everglades restoration program. This innovative project is believed to be one of the largest agricultural
stormwater cleanup projects in the United States, if not in the world. This publication describes the ENR project's design,
construction, and proposed operation, as well as the proposed research program to be implemented over the next few years. 相似文献
115.
Moon Seong Rang Min Goo Kang Seung Woo Park Jeong Jae Lee Ryung Hak Yoo 《Journal of the American Water Resources Association》2006,42(2):473-486
The main focus of this study was to compare the Grey model and several artificial neural network (ANN) models for real time flood forecasting, including a comparison of the models for various lead times (ranging from one to six hours). For hydrological applications, the Grey model has the advantage that it can easily be used in forecasting without assuming that forecast storm events exhibit the same stochastic characteristics as the storm events themselves. The major advantage of an ANN in rainfall‐runoff modeling is that there is no requirement for any prior assumptions regarding the processes involved. The Grey model and three ANN models were applied to a 2,509 km2 watershed in the Republic of Korea to compare the results for real time flood forecasting with from one to six hours of lead time. The fifth‐order Grey model and the ANN models with the optimal network architectures, represented by ANN1004 (34 input nodes, 21 hidden nodes, and 1 output node), ANN1010 (40 input nodes, 25 hidden nodes, and 1 output node), and ANN1004T (14 input nodes, 21 hidden nodes, and 1 output node), were adopted to evaluate the effects of time lags and differences between area mean and point rainfall. The Grey model and the ANN models, which provided reliable forecasts with one to six hours of lead time, were calibrated and their datasets validated. The results showed that the Grey model and the ANN1010 model achieved the highest level of performance in forecasting runoff for one to six lead hours. The ANN model architectures (ANN1004 and ANN1010) that used point rainfall data performed better than the model that used mean rainfall data (ANN1004T) in the real time forecasting. The selected models thus appear to be a useful tool for flood forecasting in Korea. 相似文献
116.
随着计算机的普及 ,局域网络越来越广为利用 ,但也出现了相应的失密问题。本文从信息及实体两个方面 ,论述了局域网络的保密措施。 相似文献
117.
118.
R. M. Patel S. O. Prasher P. K. God R. Bassi 《Journal of the American Water Resources Association》2002,38(1):91-100
ABSTRACT: This study explores the applicability of Artificial Neural Networks (ANNs) for predicting salt build‐up in the crop root zone. ANN models were developed with salinity data from field lysimeters subirrigated with brackish water. Different ANN architectures were explored by varying the number of processing elements (PEs) (from 1 to 30) for replicate data from a 0.4 m water table, 0.8 m water table, and both 0.4 and 0.8 m water table lysimeters. Different ANN models were developed by using individual replicate treatment values as well as the mean value for each treatment. For replicate data, the models with twenty, seven, and six PEs were found to be the best for the water tables at 0.4 m, 0.8 m and both water tables combined, respectively. The correlation coefficients between observed salinity and ANN predicted salinity of the test data with these models were 0.89, 0.91, and 0.89, respectively. The performance of the ANNs developed using mean salinity values of the replicates was found to be similar to those with replicate data. Not only was there agreement between observed and ANN predicted salinity values, the results clearly indicated the potential use of ANN models for predicting salt build‐up in soil profile at a specific site. 相似文献
119.
Shie‐Yui Liong Chandrasekaran Sivapragasam 《Journal of the American Water Resources Association》2002,38(1):173-186
ABSTRACT: Machine learning techniques are finding more and more applications in the field of forecasting. A novel regression technique, called Support Vector Machine (SVM), based on the statistical learning theory is explored in this study. SVM is based on the principle of Structural Risk Minimization as opposed to the principle of Empirical Risk Minimization espoused by conventional regression techniques. The flood data at Dhaka, Bangladesh, are used in this study to demonstrate the forecasting capabilities of SVM. The result is compared with that of Artificial Neural Network (ANN) based model for one‐lead day to seven‐lead day forecasting. The improvements in maximum predicted water level errors by SVM over ANN for four‐lead day to seven‐lead day are 9.6 cm, 22.6 cm, 4.9 cm and 15.7 cm, respectively. The result shows that the prediction accuracy of SVM is at least as good as and in some cases (particularly at higher lead days) actually better than that of ANN, yet it offers advantages over many of the limitations of ANN, for example in arriving at ANN's optimal network architecture and choosing useful training set. Thus, SVM appears to be a very promising prediction tool. 相似文献
120.
Jurgen Garbrecht Lawrence W. Martz 《Journal of the American Water Resources Association》1993,29(6):909-916
ABSTRACT: An automated extraction of channel network and sub-watershed characteristics from digital elevation models (DEM) is performed by model DEDNM. This model can process DEM data of limited vertical resolution representing low relief terrain. Such representations often include ill-defined drainage boundaries and indeterminate flow paths. The application watershed is an 84 km2 low relief watershed in southwestern Oklahoma. The standard for validation is the network and subwatershed parameters defined by the blue line method on USGS 7.5–minute topographic maps. Evaluation of the generated and validation networks by visual comparisons shows a high degree of correlation. Comparison of selected network parameters (channel length, slope, drainage density, etc.) and of drainage network composition (bifurcation, length, slope, and area ratios) shows that, on the average, the generated parameters are within 5 percent of those derived from the validation network. The largest discrepancies were found for the channel slope values. The results of this application demonstrate that DEDNM effectively addresses network definition problems often encountered in low relief terrain and that it can generate accurate network and subwatershed parameters under those conditions. 相似文献