UNCERTAINTY BASED OPERATION OF LARGE SCALE RESERVOIR SYSTEMS: DEZ AND KAROON EXPERIENCE1

ABSTRACT: Reservoir operation involves a complex set of human decisions depending upon hydrologic conditions in the supply network including watersheds, lakes, transfer tunnels, and rivers. Water releases from reservoirs are adjusted in an attempt to provide a balanced response to different demands. When a system involves more than one reservoir, computational burdens have been a major obstacle in incorporating uncertainties and variations in supply and demand. A new generation of stochastic dynamic programming was developed in the 1980s and 1990s to incorporate the forecast and demand uncertainties. The Bayesian Stochastic Dynamic Programming (BSDP) model and its extension, Demand Driven Stochastic Dynamic Programming (DDSP) model, are among those models. Recently, a Fuzzy Stochastic Dynamic Programming model (FSDP) also was developed for a single reservoir to model the errors associated with discretizing the variables using fuzzy set theory. In this study the DDSP and the FSDP models were extended and simplified for a complex system of Dez and Karoon reservoirs in the southwestern part of Iran. The simplified models are called Condensed Demand Driven Stochastic Programming (CDDSP) and Condensed Fuzzy Stochastic Dynamic Programming (CFSDP). The optimal operating policies developed by the CDDSP and the CFSDP models were simulated in a classical model and a fuzzy simulation model, respectively. The case study was used to demonstrate the advantages of implementing the proposed algorithm, and the results show the significant value of the proposed fuzzy based algorithm.     

REGIONAL FREQUENCY ANALYSIS OF HYDROLOGIC MULTIYEAR DROUGHTS1

This paper is concerned with regional frequency analysis of hydrologic multiyear droughts. A drought event is defined by three parameters: severity, duration, and magnitude. A method is proposed here to standardize drought severities with a duration adjustment to enable comparison among drought events. For purposes of a regional study, the index drought method is selected and applied to standardized droughts to give a regional frequency curve. However, the recurrence intervals of the drought events obtained from index drought method are limited to the historic period of record. Therefore, by taking advantage of random variations of droughts in both time and space, a multivariate simulation model is used to estimate exceedence probabilities associated with regional drought maxima. This method, named the regional extreme drought method, is capable of generating a series of drought events which, although they have not occurred historically, are more severe than historic events. By combining the results of the index drought method and regional extreme drought analysis, a regional drought probability graph is constructed which ranges from severe droughts to more frequent droughts. This procedure is applied to the mean annual flow records of streams located in the San Joaquin Valley of California, and drought-severity-frequency plots are prepared for 1-year, 2-year, and 3-year durations.     

Developments in remote sensing, dynamic modelling and GIS applications for integrated coastal zone management

The International Institute for Aerospace Survey and Earth Sciences (ITC) has a research programme that should result in an integrated environmental coastal zone management system through three subprojects. The programme aims to develop methodologies and tools for assessing coastal zone changes, and for the evaluation of scenarios for coastal zone management, based on a spatio-temporal Geographical Information System (GIS) working platform which integrates remote sensing data, physical-morphodynamic and eco-hydrologic modelling, and a decision support system. The first subproject develops methodologies for the generation of optimum Remote Sensing (RS) data sets, leading to better interpretation and complementary use of conventional and new remote sensing imagery. It also integrates RS, GIS, and modelling through hypothesis generation, parameter estimation, evaluation and validation. The second subproject facilitates qualitative and quantitative analysis and prediction of the physical aspects of coastal landscape development under the influence of natural processes and human impacts. This subproject is based on the application of remote sensing and dynamic modelling. The third subproject leads to a spatio-temporal working platform which supports data integration of RS and in-situ measurements, and qualitative and quantitative analysis for the prediction of coastal landscape development. Both support decision making in Integrated Coastal Zone Management.     

Application of ANN and ANFIS models for reconstructing missing flow data

Hydrological yearbooks, especially in developing countries, are full of gaps in flow data series. Filling missing records is needed to make feasibility studies, potential assessment, and real-time decision making. In this research project, it was tried to predict the missing data of gauging stations using data from neighboring sites and a relevant architecture of artificial neural networks (ANN) as well as adaptive neuro-fuzzy inference system (ANFIS). To be able to evaluate the results produced by these new techniques, two traditionally used methods including the normal ratio method and the correlation method were also employed. According to the results, although in some cases all four methods presented acceptable predictions, the ANFIS technique presented a superior ability to predict missing flow data especially in arid land stations with variable and heterogeneous data. Comparing the results, ANN was also found as an efficient method to predict the missing data in comparison to the traditional approaches.     

Impacts of home shopping on vehicle operations and greenhouse gas emissions: multi-year regional study

As a shopping behavior trend, home shopping has become more popular. This shopping method seems to decrease shopping trips, yet more delivery trucks are required to be on the roads. In addition, even more personal trips may occur because saving time on shopping might allow more time for alternate activities. A study investigated the effects of home shopping on vehicle operations and greenhouse gas emissions. The purpose of that study was to identify the home-shopping impacts on transportation system, its net effects on traffic volume of the transportation network, its effects associated with environmental sustainability and then to provide some projections for future condition. Simulation results showed that home shopping will put additional burden on Newark transportation network, as identified through four measures of effectiveness (MOEs) which were travel time, delay, average speed and greenhouse gas (GHG) emissions.     

Effect of application rate and irrigation on the movement and dissipation of indaziflam

Indaziflam is a new preemergence herbicide for the control of annual grass and broadleaf weeds in various cropping systems including pecan orchards. The objectives of this study were to (1) determine the mobility and dissipation of indaziflam and (2) evaluate herbicide efficacy in a flood-irrigated pecan orchard in southern New Mexico, USA. Indaziflam was applied at 0, 36.5, and 73.1 g/ha in areas with (impacted) and without (unimpacted) tree injury symptoms. Soil samples were collected at 0–15, 15–30, and 30–46 cm depths 26, 63, 90, and 126 days after the first herbicide application. Additional soil samples were collected 4, 30, and 56 days after the second application. Indaziflam was detected in soil samples collected at each depth, suggesting movement with irrigation water. Indaziflam concentrations decreased with increasing soil depth and time. Indaziflam mass recoveries were greater in the unimpacted area than in the impacted area after the first and second applications. Dissipation half-lives of indaziflam in the soil ranged from 30 to 86 days for total indaziflam recovered from the entire soil profile after the first and second applications in both areas. The percent weed control was similar in the impacted and unimpacted areas for both rates of indaziflam on 26 and 63 days after application; however, on 90 days after the application, percent weed control was lower in the impacted than unimpacted area.