SEQUENTIAL GENERATION OF STREAMFLOW1

ABSTRACT: An auto-regressive model has been developed for hydrologic data simulation. The model is computationally easier, parsimonious in number of model parameters and more stable in statistical characteristics than the existing auto-regressive model. The proposed model was used for synthesizing 10 sequences, each of 100 year length, of monthly flows for the river Beas. The statistical parameters were calculated using 49-year historical record for the river. The data was also synthesized using existing auot-regressive model. The synthesized sequences have been compared. The results indicate that the proposed model is as good as the existing auto-regressive model in preserving the mean and standard deviation of historical record. It is further shown that the proposed model requires less parameters than the auto-regressive model for simulation of long-term dependence.     

AN ANALYTICAL FRAMEWORK FOR EVALUATING CHANNEL MAINTENANCE FLOWS IN COLORADO1

ABSTRACT: An accounting procedure is developed which determines a flow regime that is capable of transporting an amount of bedload sediment necessary to ensure channel stability downstream. The method allows for sediment buildup in the channel within geomorphic threshold limits during low flow periods. During periods of high runoff, enough water is bypassed to transport the stored sediment. The procedure utilizes only those flows of sufficient magnitude to maintain channel stability over the long run (25–50+ years). An example is presented which determines the volume of water and frequency of release for channel maintenance purposes downstream from a hypothetical water diversion project. Of some 1,200,000 acre feet generated during a 59-year period, 86,500 acre feet was required for channel maintenance flows. Bypass flows were not required each year, but only during those years when average daily flow reached bankfull or greater. Such releases were made on 202 of the 411 days when average flows either equalled or exceeded bankfull discharge.     

EVIDENCE OF CHAOTIC BEHAVIOR IN SINGAPORE RAINFALL1

ABSTRACT: This paper focuses on the investigation of the existence of chaotic behavior in the Singapore rainfall data. The procedure for the determination of the minimum number of variables essential and the number of variables sufficient to model the dynamics of the rainfall process was studied. An analysis of the rainfall behavior of different time periods was also conducted. The correlation dimension was used as a basis for discriminating stochastic and chaotic behaviors. Daily rainfall records for durations of 30, 20, 10, 5, 4, 3, 2, and 1 years from six stations were analyzed. The delay time for the phase-space reconstruction was computed using the autocorrelation function approach. The results provide positive evidence of the existence of chaotic behavior in the daily rainfall data. The minimum number of variables essential to model the dynamics of the rainfall process was identified to be 3 while the number of variables sufficient to model the dynamics of the rainfall process ranges from 11 to 18. The results also suggest that the attractor dimensions of rainfall data of longer time periods are higher than that of shorter time periods. The study suggests a minimum number of 1500 data points required for the computation of the correlation dimension of the rainfall data.     

Modeling human-induced climatic change: A summary for environmental managers

The rapid increase in atmospheric concentrations of greenhouse gases has caused concern because of their potential to alter the earth's radiation budget and disrupt current climate patterns While there are many uncertainties associated with use of general circulation models (GCMs), GCMs are currently the best available technology to project changes in climate associated with elevated gas concentrations. Results indicate increases in global temperature and changes in global precipitation patterns are likely as a result of doubled CO₂. GCMs are not reliable for use at the regional scale because local scale processes and geography are not taken into account. Comparison of results from five GCMs in three regions of the United States indicate high variability across regions and among models depending on season and climate variable. Statistical methods of scaling model output and nesting finer resolution models in global models are two techniques that may improve projections. Despite the many limitations in GCMs, they are useful tools to explore climate-earth system dynamics when used in conjunction with water resource and ecosystem models. A variety of water resource models showed significant alteration of regional hydrology when run with both GCM-generated and hypothetical climate scenarios, regardless of region or model complexity. Similarly, ecological models demonstrate the sensitivity of ecosystem production, nutrient dynamics, and distribution to changes in climate and CO₂ levels. We recommend the use of GCM-based scenarios in conjunction with water resource and ecosystem models to guide environmental management and policy in a “no-regrets” framework or as part of a precautionary approach to natural resource protection.     

THE VALUE OF STREAMFLOW FORECASTING IN RESERVOIR OPERATION1

ABSTRACT: The value of streamflow forecasts in reservoir operation depends on a number of factors and may vary considerably. Assessment of forecast benefits is presented here for three specific systems. Statistical streamflow models of increasing forecasting ability are coupled with a recently developed stochastic control method in extensive simulation experiments. The performance of the system is statisticafly evaluated with regard to energy generation and flood and drought prevention. The results indicate that forecast benefits are system specific and may range from quite substantial to fairly minimal.     

PAST AND FUTURE OF ANALYSIS OF WATER RESOURCES TIME SERIES1

ABSTRACT: water resources supply and demand time series consist of several or all of the four basic characteristics: tendency, intermittency, periodicity and stochasticity. Their importance changes from one type of variables to another. Historic developments of analysis of time series in hydrology have varied significantly over the past, from the stress on search for periodicities and persistence in annual series to the emphasis on the series stochastic properties. Supply and demand series are often highly interrelated, which fact is most often neglected in planning water resources systems in general, and water storage capacities in particular. The future of series analysis in water resources will likely be by a joint use of physically-based structural analysis and the use of advanced methods of treating data by stochastic processes, statistical estimation and inference techniques. The most intriguing challenge of the future of this analysis may be the treatment of nonnormal, nonlinear and in general nonstationary hydrologic and water use time series. The proper treatment of complex multivariate processes will also challenge the specialists, especially for the purposes of transfer of information between data on variables at given points, or between data at several points of a given variable, or both.     

A STOCHASTIC DYNAMIC PROGRAMMING BASED APPROACH TO THE OPERATION OF A MULTI-RESERVOIR SYSTEM1

ABSTRACT: An heuristic iterative technique based upon stochastic dynamic programming is presented for the analysis of the operation of a three reservoir ‘Y’ shaped hydroelectric system. The technique is initiated using historical inflow data for the downstream reservoir. At each iteration the optimal policies for the downstream hydroelectric generating unit are used to provide relative weightings or targets for operation of upstream reservoirs. New input inflows to the downstream reservoir are then obtained by running the historical streamflow record through the optimal policies for the upstream reservoirs. These flows are then used to develop a new operating policy for the downstream reservoir and hence new targets for the upstream reservoirs. The process is continued until the operating policies for each reservoir provide the same overall system benefit for two successive iterations. Results obtained from the procedure are compared to the results obtained by historical operation of the system. The procedure is shown to develop operating policies which give benefits which are as close to the historical benefits as can be expected given the choice of the number of storage state variables.     

A PROBABILISTIC BENEFIT-COST ANALYSIS OF A ZONING PROGRAM FOR FLOOD PLAINS1

ABSTRACT: Various techniques, one of which is zoning, are used to control the extent of flood damage. The benefit-cost analysis of zoning programs must take into account the random nature of flooding. This paper outlines a method for determining not only the expected value of the benefit-cost ratio, but also the probability of such a zoning program being profitable. It also presents an application of the method to the assessment of the Outaouais Regional Community zoning program.     

global climate change: processes and products – an overview

Our knowledge of global climate change has many uncertainties.Whether global air temperature will increase, by how much, and when,are subject to debate, but there is little doubt that troposphericconcentrations of several trace gases are increasing. While possibleincreases in the average air temperature is a product of these changes,the increases in the trace gases alone will have an effect on agriculture.Increases in the ambient concentrations of carbon dioxide are expectedto have a positive net effect on crop production. In contrast, anyincreases in the penetration of surface-level ultraviolet-B (280–320 nm)radiation, and known increases in surface ozone concentrations, areconsidered to have adverse effects on certain crops. Our presentknowledge of the joint effects on crops of elevated levels of carbondioxide, ultraviolet-B radiation and ozone, and possible alterations in airtemperature and precipitation patterns, is virtually zero. Therefore, anypredictions of the effects of global climate change on agriculture aresubject to significant uncertainties. In contrast, coupling of climatechange (only temperature and precipitation) models to crop productionhas led to a number of future scenarios. In spite of theirpresent limitations, results from these efforts can be useful in planningfor future agriculture.     

高级氧化技术处理垃圾渗滤液的研究进展

本文介绍了包括化学氧化法、电化学氧化法、光催化氧化法、超声氧化法、辐照氧化法和催化湿式氧化法等在内的高级氧化技术的机理和运用于垃圾渗滤液处理的研究进展,并提出高级氧化技术与生物处理联合运用和各种高级氧化工艺之间的优化组合将是实现高级氧化技术在垃圾渗滤液处理中工程化运用的发展方向.