SIMULATION AND DECISIONMAKING: THE PLATTE RIVER BASIN IN NEBRASKA1

Substantial conflict exists over water management and allocation in the Platte River Basin of Nebraska. An interdisciplinary computer simulation model, representing the water quantity, water quality, environmental, and economic dimensions of the conflict, was developed in order to analyze the tradeoffs among allocation scenarios. Most importantly, decisionmakers and interest groups were involved in model development. Simulation results for a base case and two scenarios are presented. One scenario favors protection of instream flow for wildlife; the other favors water diversions for agriculture. Impacts of the instream flow scenario, as measured by the amount of land irrigated, groundwater levels, the amount of wildlife habitat for cranes and catfish, and net agricultural benefits did not differ greatly from those of the base case. However, impacts of the diversion scenario were substantial. On the negative side, instream flows and wildlife habitat declined an average of 39 percent; while, on the positive side, groundwater levels and net agricultural benefits each increased 6 percent. The modeling process was successful insofar as it promoted an understanding among the highly diverse interest groups of the systems nature of the Basin. One agreement on a water diversion schedule among three of the parties has been reached, partly as a result of this process. More comprehensive compromises have not yet been forged. Our experience, however, indicates that modeling success at the policymaking level depends more on the extent to which the policymakers understand the model than it does on model sophistication.     

EFFECTS OF NO-FLOW RIVER CONDITIONS ON THE PLATTE RIVER WELL FIELD1

ABSTRACT: Effects of no-flow river conditions on the quantity and quality of water in the Platte River well field of the City of Grand Island, Nebraska, were examined utilizing a finite-difference computer simulation model specifically developed for this well field. Results suggest that the effects of these no-flow periods on water quality may be most important. In particular, the no-flow periods eliminate the hydraulic barrier between the well field and an area north of the River that is contaminated with nitrate (concentrations in the 20 to 40 mg/1 NO₃-N range). They also change the direction and velocity of movement of the contaminated ground water. Simulation results indicate that contaminated ground water moves toward the well field with a velocity of 0.42 ft/d after 30 days of no-flow and 1.43 ft/d after 180 days of no-flow. Limiting no-flow conditions to 10 consecutive days would protect the well field.     

Comprehensive temperature monitoring in an in-vessel forced-aeration static-bed composting process

Comprehensive temperature monitoring was done in an in-vessel forced-aeration static-bed composting process using sewage sludge. The three layers that divided the compost pile horizontally showed different temperature distributions. The temperature of the top layer appeared not to be influenced by the ambient temperature. The temperature of the center area of the top layer was taken to be the representative temperature for evaluating composting start-up performance. The temperature of the bottom layer was strongly influenced by the ambient temperature, and the temperature of the center area of the bottom layer was taken to be the representative temperature for pathogen control as it was the minimum temperature in the reactor. Composting start-up performance was influenced by several factors when the ambient temperature was either below or above 20°C. When the ambient temperature was below 20°C, the time taken to reach 65°C (T ₆₅) was influenced by the temperature of inflowing air, but when the temperature was higher than 20°C, it was influenced by the ratio of sewage sludge to seed compost (F/S). T ₆₅ was least when F/S was 1–2. Received: January 9, 2001 / Accepted: October 10, 2001     

Estimation of internal radiation dose to the adult Asian population from the dietary intakes of two long-lived radionuclides

Daily dietary intakes of two naturally occurring long-lived radionuclides, 232Th and 238U, were estimated for the adult population living in a number of Asian countries, using highly sensitive analytical methods such as instrumental and radiochemical neutron activation analysis (INAA and RNAA), and inductively coupled plasma mass spectrometry (ICP-MS). The Asian countries that participated in the study were Bangladesh (BGD), China (CPR), India (IND), Japan (JPN), Pakistan (PAK), Philippines (PHI), Republic of Korea (ROK) and Vietnam (VIE). Altogether, these countries represent more than 50% of the world population. The median daily intakes of 232Th ranged between 0.6 and 14.4 mBq, the lowest being for Philippines and the highest for Bangladesh, and daily intakes of 238U ranged between 6.7 and 62.5 mBq, lowest and the highest being for India and China, respectively. The Asian median intakes were obtained as 4.2 mBq for 232Th and 12.7 mBq for 238U. Although the Asian intakes were lower than intakes of 12.3 mBq (3.0 ug) 232Th and 23.6 mBq (1.9 ug) 238U proposed by the International Commission on Radiological Protection (ICRP) for the ICRP Reference Man, they were comparable to the global intake values of 4.6 mBq 232Th and 15.6 mBq 238U proposed by the United Nation Scientific Commission on Effects of Radiation (UNSCEAR). The annual committed effective doses to Asian population from the dietary intake of 232Th and 238U were calculated to be 0.34 and 0.20 microSv, respectively, which are three orders of magnitude lower than the global average annual radiation dose of 2400 microSv to man from the natural radiation sources as proposed by UNSCEAR.     

An algorithm for assessing the risk of traffic accident

INTRODUCTION: This study is aimed at developing an algorithm to estimate the number of traffic accidents and assess the risk of traffic accidents in a study area. METHOD: The algorithm involves a combination of mapping technique (Geographical Information System (GIS) techniques) and statistical methods (cluster analysis and regression analysis). Geographical Information System is used to locate accidents on a digital map and realize their distribution. Cluster analysis is used to group the homogeneous data together. Regression analysis is performed to realize the relation between the number of accident events and the potential causal factors. Negative binomial regression model is found to be an appropriate mathematical form to mimic this relation. Accident risk of the area, derived from historical accident records and causal factors, is also determined in the algorithm. The risk is computed using the Empirical Bayes (EB) approach. A case study of Hong Kong is presented to illustrate the effectiveness of the proposed algorithm. RESULTS: The results show that the algorithm improves accident risk estimation when comparing to the estimated risk based on only the historical accident records. The algorithm is found to be more efficient, especially in the case of fatality and pedestrian-related accident analysis. IMPACT ON INDUSTRY: The output of the proposed algorithm can help authorities effectively identify areas with high accident risk. In addition, it can serve as a reference for town planners considering road safety.     

A COMPARISON OF STATISTICAL TESTS ON THE EXTREME-VALUE TYPE-1 DISTRIBUTION1

ABSTRACT: The effects of the selections of plotting position formulae and class division schemes on goodness of fit tests are investigated for the extreme-value type-1 distribution using annual flood and annual maximum daily rainfall data. It was found that the plotting position formulae have a minor influence on the tests which involve their use, while the class division schemes may have a pronounced effect on the X²-test. The study also recommended the maximum likelihood method for fitting purposes and a new test which is independent of the afore-mentioned selections for judging the goodness of fit.     

COMPARISON OF TWO AUTOREGRESSIVE MODELS FOR MONTHLY STREAM FLOW GENERATION1

ABSTRACT: Two autoregressive models for monthly stream flow generation are compared based on the reproduction of the historical record in terms of several important statistics such as the mean, standard deviation, skewness coefficient, correlation coefficient, and the reservoir storage components. In the comparison, both theoretical considerations and practical applications are employed to evaluate the performance of each model.     

Normality of Hydrological Data1

ABSTRACT: Assessment of normality of hydrological data has been based upon subjective judgments. This paper aims to provide an objective method for such an assessment by introducing three computationally simple statistical tests. Application to some stream flow data indicates that (1) for annual values, at least one of the three sequences- original, square root, and logarithmic - can be considered to be normally distributed; and (2) most monthly stream flows are skew and neither the square root nor the logarithmic transformation is able to render their sequences in all the 12 months normal.