CONTEMPORANEOUS AUTOREGRESSIVE-MOVING AVERAGE (CARMA) MODELING IN WATER RESOURCES1

ABSTRACT: The Contemporaneous Autoregressive-Moving Average (CARMA) model is a simple and efficient model that can be used to fit many multivariate hydrological time series. For certain types of multistation river flow systems, the CARMA model is naturally obtained when the physical restrictions of the system or the characteristics of the data are taken in consideration during the formulation of the model. It is shown how the CARMA model can optimally be used to handle multiple time series where the number of observations in each series may be different. Adequate model building techniques, as well as computational and statistical efficient algorithms to estimate the parameters of the model, are given. The methodologies and applications of the CARMA model are illustrated with three examples. It is also shown how the full multivariate ARMA model may lead to losses in efficient of the estimators when the CARMA model is adequate.     

A real-time simulating non-isothermal mathematical model for the passive feed direct methanol fuel cell

In order to understand the complex transport phenomena in a passive direct methanol fuel cell (DMFC), a theoretical model is essential. The analytical model provides a computationally efficient framework with a clear physical meaning. For this, a non-isothermal, analytical model for the passive DMFC has been developed in this study. The model considers the coupled heat and mass transport along with electrochemical reactions. The model is successfully validated with the experimental data. The model accurately describes the various species transport phenomena including methanol crossover and water crossover, heat transport phenomena, and efficiencies related to the passive DMFC. It suggests that the maximum real efficiency can be achieved by running the cell at low methanol feed concentration and moderate current density. The model also accurately predicts the effect of various operating and geometrical parameters on the cell performance such as methanol feed concentration, surrounding temperature, and polymer electrolyte membrane thickness. The model predictions are in accordance with the findings of the other researchers. The model is rapidly implementable and can be used in real-time simulation and control of the passive DMFC. This comprehensive model can be used for diagnostic purpose as well.     

Repeatability,Sensitivity, and Uncertainty Analyses of the BANCS Model Developed to Predict Annual Streambank Erosion Rates

Accelerated streambank erosion caused by channel instability can be the leading cause of sediment impairment of streams. Obtaining accurate streambank erosion rates for sediment budgeting and prioritizing mitigation efforts can be difficult and costly. One approach to quantifying streambank erosion rates is through the development and implementation of an empirically derived “Bank Assessment for Non‐point Source Consequences of Sediment” (BANCS) model. This study aims to improve the BANCS model application by evaluating repeatability between users and identifying sensitive and/or uncertain model inputs. Statistical analysis of streambank evaluations conducted by 10 different individuals suggests the implementation of the BANCS model may not be repeatable. This finding may be due to sensitive model inputs, such as streambank height and near‐bank stress level prediction method selection, and/or uncertain model inputs, such as bank material identification and the associated adjustment of erosion potential. Furthermore, it was found assessing streambanks as a group by obtaining a measure of central tendency from individual evaluations, as well as obtaining a higher level of training, may improve model implementation precision. Application of these suggestions may result in improved prediction of streambank erosion rates utilizing the BANCS model methodology.     

A Satellite Model of Forest Flammability

We describe a model of forest flammability, based on daily satellite observations, for national to regional applications. The model defines forest flammability as the percent moisture content of fuel, in the form of litter of varying sizes on the forest floor. The model uses formulas from the US Forest Service that describe moisture exchange between fuel and the surrounding air and precipitation. The model is driven by estimates of temperature, humidity, and precipitation from the moderate resolution imaging spectrometer and tropical rainfall measuring mission multi-satellite precipitation analysis. We provide model results for the southern Amazon and northern Chaco regions. We evaluate the model in a tropical forest-to-woodland gradient in lowland Bolivia. Results from the model are significantly correlated with those from the same model driven by field climate measurements. This model can be run in a near real-time mode, can be applied to other regions, and can be a cost-effective input to national fire management programs.     

Thomas Malthus,Ester Boserup,and Agricultural Development Models in the Age of Limits

Two competing models have served as the basis for agricultural development policies. One is based on observations and assumptions of The Reverend Thomas Malthus in late eighteenth century Britain, and the other from the Danish economist Ester Boserup in the mid-twentieth century. However, rational agricultural development decisions can only be made using a model that incorporates assumptions based on a technically appropriate model that takes into account the currently status of global systems. A new development model may incorporate elements of both Neo-Malthusian and Boserupian economic-demographic models, but because the world has changed substantially, it can be neither of them alone, nor a hybrid of the two models without significant expansion and refinement. The principles espoused by Malthus and Boserup can thus be used as the starting points in a dialectic argument to arrive at a new agricultural development paradigm.     

Nonpoint source pollution risk assessment in a watershed context

Nonpoint source pollution control requires assessment of the influence of dispersed runoff-contributing areas on downstream water quality. This evaluation must consider two separate phases: site-to-stream loading and downstream fluvial transport. Any model, combination of models, or procedure for making this assessment can be generalized to a simple spatial model or framework, which considers runoff or pollutant loading per unit area and down-stream attenuation, with drainage area as a scaling factor. This spatial model has a probabilistic interpretation and can be used in conjunction with a standard dilution model to give a probabilistic estimate of the impacts at the basin mouth of runoff from a specific upstream contributing area. It is illustrated by applying it to an assessment of the probability that various copper concentrations at the mouth of the urbanized South Platte River basin in Denver, Colorado, USA, will be exceeded as a result of runoff from a subbasin within the city. Determining the probability that a concentration of a pollutant at the basin mouth can be attributed to runoff from a discrete area within the basin is useful for targeting and risk assessment because it enables quantitative risk-based comparisons. The spatial framework is also useful for evaluating management and control options, since actions within the basin can be directly linked to water quality at a downstream point.     

Participatory Model Calibration for Improving Resource Management Systems: Case Study of Rainwater Harvesting in an Indian Village

While planning resource management systems in rural areas, it is important to consider criteria that are specific to the local social conditions. Such criteria might change from one region to another and are hence best identified using a participatory approach. In this work, we propose a participatory framework to identify such criteria and derive their weights. These identified criteria and their weights are used as parameters to develop a quantitative model for evaluating efficiency of each system. Such a model can serve as a support tool for stakeholders to simulate and analyze “what‐if” scenarios, evaluate alternatives, and select one which best satisfies their requirements. We use existing systems to test the model by comparing efficiencies evaluated by the model to efficiencies perceived by the stakeholders. The model is calibrated by repeating the process until statistically significant correlation is achieved between evaluated and perceived efficiencies. The novelty of the proposed framework lies in treating efficiencies perceived by the stakeholders as the ground truth since they know these systems well and are their ultimate users. The framework is successfully demonstrated using case study of rainwater harvesting (RWH) systems in an Indian village. The resulting calibrated model can be used to plan new RWH systems in this region and similar regions elsewhere. The framework can be used to plan other resource management systems in various regions.     

Environmental economic,political and ethical integration in a common decision-making framework

This article develops a decision-making framework for environmental management that integrates technical, economic, political and legal, and ethical decision levels. It attempts to show how these decision levels can be ordained, integrated and interconnected and postulates a hierarchic concentric sphere system that proposes an environmental management model for long-term solutions. This model can be used as a check list for environmental management decision-making and also as a guide for environmental conflict resolution where environmental problems necessitate several levels of decision making. It integrates various environmental ethical positions and evaluates political decisions into a comprehensive, broadly applicable multidisciplinary approach. The objective of this decision-making model is to interconnect into a simplified sequence different levels of environmental management processes in order to account for sustainability, efficacy, efficiency and the acceptability of environmental management processes in the long term. This is done by observing when an environmental problem needs to be solved within a certain sphere of solutions and when it requires wider frameworks, how these can be established and how this process proves that solidarity is the widest and most reasonable sphere.     

ASSESSMENT OF REMOTE SENSING INPUT TO HYDROLOGIC MODELS1

Remotely sensed variables such as land cover type and snow-cover extent can currently be used directly and effectively in a few specific hydrologic models. Regression models can also be developed using physiographic and snow-cover data to permit estimation of discharge characteristics over extended periods such as a season or year. Most models, however, are not of an appropriate design to readily accept as input the various types of remote sensing parameters that can be obtained now or in the future. Because this new technology has the potential for producing hydrologic data that has significant information content on an areal basis, both inexpensively and repetitively, effort should be devoted now to either modifying existing models or developing new models that can use these data. Minor modifications would at least allow the remote sensing data to be used in an ancillary way to update the model state variables, whereas major structural modifications or new models would permit direct input of the data through remote sensing compatible algorithms. Although current remote sensing inputs to hydrologic models employ only visible and near infrared data, model modification or development should accommodate microwave and thermal infrared data that will be more widely available in the future.     

ALTERNATIVE FUTURES USING THE WOLLMAN-BONEM MODELS1

Alternative futures are defined to be mutually consistent alternative combinations of assumed sets of future conditions. Alternative futures are employed in conjunction with the Wollman-Bonem model to project future water use. The model solutions under different alternative futures provide an indication of the direction and relative magnitude of changes in water use, both in quantity and quality, that may result from changes in policy-influenced variables, technology, and other data. The Wollman-Bonem model is employed in this paper as a tool to illustrate the alternative futures concept. The model can best be cast as an economic model. The model solutions are not given as a set of formal projections, but as various possible water-use-over-time curves. This should aid in disspelling the erroneous idea that it is possible to make distant projections of water use as a single curve. Multiple curves suggest that water use is really a function of many variables.     

Carbon dynamics and land-use choices: building a regional-scale multidisciplinary model

Policy enabling tropical forests to approach their potential contribution to global-climate-change mitigation requires forecasts of land use and carbon storage on a large scale over long periods. In this paper, we present an integrated modeling methodology that addresses these needs. We model the dynamics of the human land-use system and of C pools contained in each ecosystem, as well as their interactions. The model is national scale, and is currently applied in a preliminary way to Costa Rica using data spanning a period of over 50 years. It combines an ecological process model, parameterized using field and other data, with an economic model, estimated using historical data to ensure a close link to actual behavior. These two models are linked so that ecological conditions affect land-use choices and vice versa. The integrated model predicts land use and its consequences for C storage for policy scenarios. These predictions can be used to create baselines, reward sequestration, and estimate the value in both environmental and economic terms of including C sequestration in tropical forests as part of the efforts to mitigate global climate change. The model can also be used to assess the benefits from costly activities to increase accuracy and thus reduce errors and their societal costs.     

A DYNAMIC SYSTEM MODEL FOR SIMULATING SEDIMENT DISCHARGE1

ABSTRACT: A dynamic sediment discharge model was developed and proposed for the simulation of watershed systems. It war developed from an expansion of splash and flow erosion relationships under steady state conditions. It was described as a general erosion model that can be reduced to forms comparable to many conceptual soil erosion and sediment yield models. The model incorporates eight parameters such as rainfall intensities, runoff rates, and previous sediment discharges. The model was tested with two small watersheds with simulation results which were very satisfactory compared to the data.     

An approach to optimise nutrient management in environmental sanitation systems despite limited data

The material flow analysis method can be used to assess the impact of environmental sanitation systems on resource consumption and environmental pollution. However, given the limited access to reliable data, application of this data-intensive method in developing countries may be difficult. This paper presents an approach allowing to develop material flow models despite limited data availability. Application of an iterative procedure is of key importance: model parameter values should first be assessed on the basis of a literature review and by eliciting expert judgement. If model outputs are not plausible, sensitive input parameters should be reassessed more accurately. Moreover, model parameters can be expressed as probability distributions and variable uncertainty estimated by using Monte Carlo simulation. The impact of environmental sanitation systems on the phosphorus load discharged into surface water in Hanoi, Vietnam, is simulated by applying the proposed approach.     

Market efficiency,filter rules and buffer stock profitability

This paper uses a model of the optimum buffer stock as a ‘filter rule’ together with a financial model that can be used to assess the efficiency of international commodity markets. The approach is simpler to apply than many other methods which have hitherto been used and yields an economy in theoretical and computational effort. The arguments are applied as a case study to the international copper market. The main conclusion is that private storage is not under-provided for and that a public buffer stock agency would be unlikely to be self-financing.     

Approaches to Evaluate Water Quality Model Parameter Uncertainty for Adaptive TMDL Implementation1

Abstract: The National Research Council recommended Adaptive Total Maximum Daily Load implementation with the recognition that the predictive uncertainty of water quality models can be high. Quantifying predictive uncertainty provides important information for model selection and decision‐making. We review five methods that have been used with water quality models to evaluate model parameter and predictive uncertainty. These methods (1) Regionalized Sensitivity Analysis, (2) Generalized Likelihood Uncertainty Estimation, (3) Bayesian Monte Carlo, (4) Importance Sampling, and (5) Markov Chain Monte Carlo (MCMC) are based on similar concepts; their development over time was facilitated by the increasing availability of fast, cheap computers. Using a Streeter‐Phelps model as an example we show that, applied consistently, these methods give compatible results. Thus, all of these methods can, in principle, provide useful sets of parameter values that can be used to evaluate model predictive uncertainty, though, in practice, some are quickly limited by the “curse of dimensionality” or may have difficulty evaluating irregularly shaped parameter spaces. Adaptive implementation invites model updating, as new data become available reflecting water‐body responses to pollutant load reductions, and a Bayesian approach using MCMC is particularly handy for that task.     

A comprehensive waste collection cost model applied to post-consumer plastic packaging waste

Post-consumer plastic packaging waste (PPW) can be collected for recycling via source separation or post-separation. In source separation, households separate plastics from other waste before collection, whereas in post-separation waste is separated at a treatment centre after collection. There are also two collection schemes, either curb side or via drop-off locations. These different schemes have impact on total costs of collection at the municipal level. It can also influence the facility choices and network design. Therefore, a method which can compare costs of various collection schemes is needed.A comprehensive cost model was developed to compare costs of municipal collection schemes of PPW. The ‘municipal waste collection cost model’ is based on variables including fixed and variable costs per vehicle, personnel cost, container or bag costs as well as on emission costs (using imaginary carbon taxes). The model can be used for decision support when strategic changes to the collection scheme of municipalities are considered. The model takes into account the characteristics of municipalities, including urbanization degree and taxation schemes for household waste management.The model was applied to the Dutch case of post-consumer plastic packaging waste. Results showed that that in general post-separation collection has the lowest costs and curb side collection in urban municipalities without residual waste collection taxing schemes the highest. These results were supported by the conducted sensitivity analysis, which showed that higher source separation responses are negatively related to curb side collection costs. Greenhouse gas emission costs are a significant part of the total costs when collecting post-consumer plastic packaging waste due to the low density to weight ratio of the materials collect. These costs can amount to 15% of the total collection costs.     

System dynamics model for analyzing effects of eco-design policy on packaging waste management system

EU's long-term objective is to become a recycling and resource effective society, where waste is utilized as a resource and waste generation is prevented. A system dynamics model was developed to analyze the policy mechanisms that promote packaging material efficiency in products through increased recycling rates. The model includes economic incentives such as packaging and landfill taxes combined with market mechanisms, behavioral aspects and ecological considerations in terms of material efficiency (the packaging material per product unit, recycled fraction in products). The paper presents the results of application of various policy instruments for increasing packaging material efficiency and recovery rate and reducing landfilled fraction. The results show that a packaging tax is an effective policy instrument for increasing the material efficiency. It ensures the decrease of the total consumption of materials and subsequent waste generation. The tax helps to counteract a rebound effect, which, as identified by the analysis, can be caused by reduced material costs due to eco-design. The model is applied to the case of Latvia. Yet, the elements and structure of the model developed are similar to waste management systems in many countries. By changing numeric values of certain parameters, the model can be applied to analyze policy mechanisms in other countries.     

ARCGIS‐SWAT: A GEODATA MODEL AND GIS INTERFACE FOR SWAT1

This paper presents ArcGIS‐SWAT, a geodata model and geographic information system (GIS) interface for the Soil and Water Assessment Tool (SWAT). The ArcGIS‐SWAT data model is a system of geodatabases that store SWAT geographic, numeric, and text input data and results in an organized fashion. Thus, it is proposed that a single and comprehensive geodatabase be used as the repository of a SWAT simulation. The ArcGIS‐SWAT interface uses programming objects that conform to the Component Object Model (COM) design standard, which facilitate the use of functionality of other Windows‐based applications within ArcGIS‐SWAT. In particular, the use of MS Excel and MATLAB functionality for data analysis and visualization of results is demonstrated. Likewise, it is proposed to conduct hydrologic model integration through the sharing of information with a not‐model‐specific hub data model where information common to different models can be stored and from which it can be retrieved. As an example, it is demonstrated how the Hydrologic Modeling System (HMS) ‐ a computer application for flood analysis ‐ can use information originally developed by ArcGIS‐SWAT for SWAT. The application of ArcGIS‐SWAT to the Seco Creek watershed in Texas is presented.