OPTIMAL RESERVOIR MANAGEMENT AND CROP PLANNING UNDER DETERMINISTIC AND STOCHASTIC INFLOWS1

ABSTRACT: This study analyzes planning under deterministic and stochastic inflows for the Mayurakshi project in India. Models are developed to indicate the optimal storage of reservoir water, the transfer of water to the producing regions, and the spillage of water from the reservoir, if needed. A deterministic programming model was first formulated to represent the existing situation. A chance-constrained model then was constructed to evaluate potential violations of the deterministic model. Both models were quantified for the command area. Data were collected from surveys of the area and from government agencies. Both the deterministic and change-constrained models suggest a more intensive cropping program in the region. Both emphasize more dependence on rabi and less on kharif crops. The chance-constrained especially suggests use of more water in the rabi season. Important chances in cropping programs and labor use take place under the chance-constrained model.     

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.     

STOCHASTIC MODELING OF MONTHLY AND DAILY RAINFALL SEQUENCES1

ABSTRACT: A monthly model and two daily models (I and II) are presented for the purpose of generating monthly and daily rainfall sequences in the Quae Yai river basin in Thailand. Performance of the models are evaluated by comparing the statistical parameters of the generated sequences with those from historical data. For monthly generation, Thomas-Fiering model worked satisfactorily in spite of the monthly correlations being weak, if any. Daily Model I, which assumes no persistence between daily rainfall amounts within the wet spells, could not preserve some important parameters regardless of the simplicity in model construction. Application of multi-state transition probability matrix model gave good results, although the user has to modify some parameters looking at the performance of the model for each historical record.     

Energy analysis and the coupling of man and estuaries

New concepts and insights concerning human and natural systems in the coastal zone are emerging from recent energy analysis and synthesis studies. By using new concepts for measuring the quality of energy, one can express the work of ecosystems and human economies in equivalent terms. From energy models and new energy quality evaluations, one can learn what kinds of coastal systems maximize power, are competitive, economically vital, and likely to have a survival advantage.Energy analysis and synthesis is aided by energy circuit diagrams. Models of the coastal zone that emphasize the change in external driving functions related to world energy sources provide insights and some predictive abilities that are not found in economic studies, since money flows alone do not evaluate external driving energies.This paper suggests four procedures for coastal planning: 1) calculation of investment ratio in units of equal quality to determine which projects are economic in a broad sense, 2) development of energy signatures for coastal ecosystems, 3) determination of which interface ecosystems develop the best energy flows, and 4) development of regional models that include the main features of human and natural ecosystems.     

Natural control mechanisms in models of aquatic ecosystems

Based on cybernetic categories of natural control mechanisms, four generations of ecosystem models are distinguished: feed-forward, feedback, self-adaptation and self-organization models. The analysis of the natural control mechanisms in aquatic ecosystems suggests that different processes are controlled in different ways, and, although the four mechanisms were identified in historical sequence, they all operate simultaneously. The concept of self-organization of an ecosystem is introduced and specified for a model of an aquatic pelagic ecosystem. The concept of the ecosystem as a multilayer, multigoal and multiechelon hierarchical system with hierarchy of the levels of biological organization is also introduced.     

A New Approach to Plant Diversity Assessment Combining HPLC Data, Simplex Mixture Design and Discriminant Analysis

The quantitative assessment of plant diversity and its monitoring with time represent a key environmental issue for management and conservation of natural resources. Assessment of plant diversity could be based on chemical analyses of secondary metabolites (e.g. flavonoids, terpenoids), because of the substantial quantitative and qualitative between-individual variability in such compounds. At a geographical scale, the plant populations become widely dispersed, and their monitoring from numerous routine individual analyses could become restricting. To overcome such constraint, this study develops a multivariate calibration model giving the relative frequency of a particular taxon from a simple high-performance liquid chromatography (HPLC) analysis of a plant mixture. The model was built from a complete set of mixtures combining different taxons, according to an experimental design (Scheffé’s matrix). For each mixture, a reference HPLC pattern was simulated by averaging the individual HPLC profiles of the constitutive taxons. The calibration models, based on Bayesian discriminant analysis (BDA), gave statistical relationships between the contributions of each taxon in mixtures and reference HPLC patterns of these mixtures. Finally, these models were validated on new mixtures by using outside plants. This new biodiversity survey approach is illustrated on four chemical taxons (four chemotypes) of Astragalus caprinus (Fabaceae). The more differentiated the taxon, the better predicted its contributions (in mixtures) were by BDA calibration model. This new approach could be very useful for a global routine survey of plant diversity.     

A MANGANESE OXIDATION MODEL FOR RIVERS1

ABSTRACT: The presence of manganese in natural waters (>0.05 mg/L) degrades water-supply quality. A model was devised to predict the variation of manganese concentrations in river water released from an impoundment with the distance downstream. The model is one-dimensional and was calibrated using dissolved oxygen, biochemical oxygen demand, pH, manganese, and hydraulic data collected in the Duck River, Tennessee. The results indicated that the model can predict manganese levels under various conditions. The model was then applied to the Chattahoochee River, Georgia. Discrepancies between observed and predicted may be due to inadequate pH data, precipitation of sediment particles, unsteady flow conditions in the Chattahoochee River, inaccurate rate expressions for the low pH conditions, or their combinations.     

Calculating losses of crops in Denmark caused by high ozone levels

In order to help guide air pollution legislation at the European level, harmful air pollution effects on agriculture crops and the consequent economic implications for policy have been studied for more than a decade. Ozone has been labeled as the most serious of the damaging air pollutants to agriculture, where growth rates and consequently yields are dramatically reduced. Quantifying the effects has formed a key factor in policymaking. Based on the widely held view that AOT40 (Accumulated exposure Over Threshold of 40 ppb) is a good indicator of ozone-induced damage, the Danish Eulerian Model (DEM) was used to compute reduced agriculture yields on a 50 km×50 km grid over Europe. In one set of scenarios, a ten year meteorological time series was combined with realistic emission inventories. In another, various idealized emission reduction scenarios are applied to the same meteorological time series. The results show substantial inter-annual variability in economic losses, due in most part to meteorological conditions which varied much more substantially than the emissions during the same period. It is further shown that, taking all uncertainties into account, estimates of ozone-induced economic losses require that a long meteorological record is included in the analysis, for statistical significance to be improved to acceptable levels for use in policy analysis. In this study, calculations were made for Europe as a whole, though this paper presents results relevant for Denmark.     

Evaluating the impacts of global environmental assessments

There are currently no widely accepted procedures for comparing the performance of global environmental assessments (GEAs) and this may be a barrier to improving their methodology. To encourage greater self-reflection within the GEA community, it is proposed to introduce consistent evaluation approaches. Two elements from current evaluation practice are reviewed here that could be particularly useful for evaluating GEAs. The first are logic models which provide a transparent visual mapping of how activities in a GEA are intended to have impacts on policies. The second are performance metrics. It is proposed that GEAs adopt two kinds of metrics: (i) A common generic set for use in all GEAs to provide a basis for comparing the performance of GEAs, and (ii) a specific set of measureable metrics for each particular GEA derived from/linked to the generic set. Although many issues arise in applying these and other elements from evaluation theory and practice to GEAs, the potential benefits are greater comparability of GEA performance and new knowledge about how to improve them. This Short Communication is part of a Special Issue on solution-oriented GEAs.