A review of dissolved oxygen modelling techniques for lowland rivers

This review introduces the methods used to simulate the processes affecting dissolved oxygen (DO) in lowland rivers. The important processes are described and this provides a modelling framework to describe those processes in the context of a mass-balance model. The process equations that are introduced all require (reaction) rate parameters and a variety of common procedures for identifying those parameters are reviewed. This is important because there is a wide range of estimation techniques for many of the parameters. These different techniques elicit different estimates of the parameter value and so there is the potential for a significant uncertainty in the model's inputs and therefore in the output too. Finally, the data requirements for modelling DO in lowland rivers are summarised on the basis of modelling the processes described in this review using a mass-balance model. This is reviewed with regard to what data are available and from where they might be obtained. (C) 2003 Elsevier Science B.V. All rights reserved.

Modelling nitrogen fluxes from the land surface to the coastal zone in European systems: the perspective of the INCA project

This paper describes the results and conclusions of the INCA (Integrated Nitrogen Model for European CAtchments) project and sets the findings in the context of the ELOISE (European Land-Ocean Interaction Studies) programme. The INCA project was concerned with the development of a generic model of the major factors and processes controlling nitrogen dynamics in European river systems, thereby providing a tool (a) to aid the scientific understanding of nitrogen transport and retention in catchments and (b) for river-basin management and policy-making. The findings of the study highlight the heterogeneity of the factors and processes controlling nitrogen dynamics in freshwater systems. Nonetheless, the INCA model was able to simulate the in-stream nitrogen concentrations and fluxes observed at annual and seasonal timescales in Arctic, Continental and Maritime-Temperate regimes. This result suggests that the data requirements and structural complexity of the INCA model are appropriate to simulate nitrogen fluxes across a wide range of European freshwater environments. This is a major requirement for the production of coupled fiver-estuary-coastal shelf models for the management of our aquatic environment. With regard to river-basin management, to achieve an efficient reduction in nutrient fluxes from the land to the estuarine and coastal zone, the model simulations suggest that management options must be adaptable to the prevailing environmental and socio-economic factors in individual catchments: 'Blanket approaches' to environmental policy appear too simple. (c) 2004 Elsevier B.V. All rights reserved.

Integrating socio-economics and ecology: a taxonomy of quantitative methods and a review of their use in agro-ecology

Answering many of the critical questions in conservation, development and environmental management requires integrating the social and natural sciences. However, understanding the array of available quantitative methods and their associated terminology presents a major barrier to successful collaboration. We provide an overview of quantitative socio-economic methods that distils their complexity into a simple taxonomy. We outline how each has been used in conjunction with ecological models to address questions relating to the management of socio-ecological systems. We review the application of social and ecological quantitative concepts to agro-ecology and classify the approaches used to integrate the two disciplines. Our review included all published integrated models from 2003 to 2008 in 27 journals that publish agricultural modelling research. Although our focus is on agro-ecology, many of the results are broadly applicable to other fields involving an interaction between human activities and ecology. We found 36 papers that integrated social and ecological concepts in a quantitative model. Four different approaches to integration were used, depending on the scale at which human welfare was quantified. Most models viewed humans as pure profit maximizers, both when calculating welfare and predicting behaviour. Synthesis and applications. We reached two main conclusions based on our taxonomy and review. The first is that quantitative methods that extend predictions of behaviour and measurements of welfare beyond a simple market value basis are underutilized by integrated models. The second is that the accuracy of prediction for integrated models remains largely unquantified. Addressing both problems requires researchers to reach a common understanding of modelling goals and data requirements during the early stages of a project.

Optimal piecewise locally linear modeling

Associative memory networks such as Radial Basis Functions, Neurofuzzy and Fuzzy Logic used for modelling nonlinear processes suffer from the curse of dimensionality (COD), in that as the input dimension increases the parameterization, computation cost, training data requirements, etc. increase exponentially. Here a new algorithm is introduced for the construction of a Delaunay input space partitioned optimal piecewise locally linear models to overcome the COD as well as generate locally linear models directly amenable to linear control and estimation algorithms. The training of the model is configured as a new mixture of experts network with a new fast decision rule derived using convex set theory. A very fast simulated reannealing (VFSR) algorithm is utilized to search a global optimal solution of the Delaunay input space partition. A benchmark non-linear time series is used to demonstrate the new approach.

Modelling of urban sensible heat flux at multiple spatial scales : a demonstration using airborne hyperspectral imagery of Shanghai and a temperature–emissivity separation approach

Urbanization related alterations to the surface energy balance impact urban warming (‘heat islands’), the growth of the boundary layer, and many other biophysical processes. Traditionally, in situ heat flux measures have been used to quantify such processes, but these typically represent only a small local-scale area within the heterogeneous urban environment. For this reason, remote sensing approaches are very attractive for elucidating more spatially representative information. Here we use hyperspectral imagery from a new airborne sensor, the Operative Modular Imaging Spectrometer (OMIS), along with a survey map and meteorological data, to derive the land cover information and surface parameters required to map spatial variations in turbulent sensible heat flux (QH). The results from two spatially-explicit flux retrieval methods which use contrasting approaches and, to a large degree, different input data are compared for a central urban area of Shanghai, China: (1) the Local-scale Urban Meteorological Parameterization Scheme (LUMPS) and (2) an Aerodynamic Resistance Method (ARM). Sensible heat fluxes are determined at the full 6 m spatial resolution of the OMIS sensor, and at lower resolutions via pixel aggregation and spatial averaging. At the 6 m spatial resolution, the sensible heat flux of rooftop dominated pixels exceeds that of roads, water and vegetated areas, with values peaking at ∼ 350 W m− 2, whilst the storage heat flux is greatest for road dominated pixels (peaking at around 420 W m− 2). We investigate the use of both OMIS-derived land surface temperatures made using a Temperature–Emissivity Separation (TES) approach, and land surface temperatures estimated from air temperature measures. Sensible heat flux differences from the two approaches over the entire 2 × 2 km study area are less than 30 W m− 2, suggesting that methods employing either strategy maybe practica1 when operated using low spatial resolution (e.g. 1 km) data. Due to the differing methodologies, direct comparisons between results obtained with the LUMPS and ARM methods are most sensibly made at reduced spatial scales. At 30 m spatial resolution, both approaches produce similar results, with the smallest difference being less than 15 W m− 2 in mean QH averaged over the entire study area. This is encouraging given the differing architecture and data requirements of the LUMPS and ARM methods. Furthermore, in terms of mean study QH, the results obtained by averaging the original 6 m spatial resolution LUMPS-derived QH values to 30 and 90 m spatial resolution are within ∼ 5 W m− 2 of those derived from averaging the original surface parameter maps prior to input into LUMPS, suggesting that that use of much lower spatial resolution spaceborne imagery data, for example from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is likely to be a practical solution for heat flux determination in urban areas.

PERSiST: a flexible rainfall-runoff modelling toolkit for use with the INCA family of models

Runoff generation processes and pathways vary widely between catchments. Credible simulations of solute and pollutant transport in surface waters are dependent on models which facilitate appropriate, catchment-specific representations of perceptual models of the runoff generation process. Here, we present a flexible, semi-distributed landscape-scale rainfall-runoff modelling toolkit suitable for simulating a broad range of user-specified perceptual models of runoff generation and stream flow occurring in different climatic regions and landscape types. PERSiST (the Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport) is designed for simulating present-day hydrology; projecting possible future effects of climate or land use change on runoff and catchment water storage; and generating hydrologic inputs for the Integrated Catchments (INCA) family of models. PERSiST has limited data requirements and is calibrated using observed time series of precipitation, air temperature and runoff at one or more points in a river network. Here, we apply PERSiST to the river Thames in the UK and describe a Monte Carlo tool for model calibration, sensitivity and uncertainty analysis

A toxicokinetic model for thiamethoxam in rats: implications for higher-tier risk assessment

Risk assessment for mammals is currently based on external exposure measurements, but effects of toxicants are better correlated with the systemically available dose than with the external administered dose. So for risk assessment of pesticides, toxicokinetics should be interpreted in the context of potential exposure in the field taking account of the timescale of exposure and individual patterns of feeding. Internal concentration is the net result of absorption, distribution, metabolism and excretion (ADME). We present a case study for thiamethoxam to show how data from ADME study on rats can be used to parameterize a body burden model which predicts body residue levels after exposures to LD50 dose either as a bolus or eaten at different feeding rates. Kinetic parameters were determined in male and female rats after an intravenous and oral administration of 14C labelled by fitting one-compartment models to measured pesticide concentrations in blood for each individual separately. The concentration of thiamethoxam in blood over time correlated closely with concentrations in other tissues and so was considered representative of pesticide concentration in the whole body. Body burden model simulations showed that maximum body weight-normalized doses of thiamethoxam were lower if the same external dose was ingested normally than if it was force fed in a single bolus dose. This indicates lower risk to rats through dietary exposure than would be estimated from the bolus LD50. The importance of key questions that should be answered before using the body burden approach in risk assessment, data requirements and assumptions made in this study are discussed in detail.

Challenges in quantifying wind generation's contribution to securing peak demand

Wind generation's contribution to supporting peak electricity demand is one of the key questions in wind integration studies. Differently from conventional units, the available outputs of different wind farms cannot be approximated as being statistically independent, and hence near-zero wind output is possible across an entire power system. This paper will review the risk model structures currently used to assess wind's capacity value, along with discussion of the resulting data requirements. A central theme is the benefits from performing statistical estimation of the joint distribution for demand and available wind capacity, focusing attention on uncertainties due to limited histories of wind and demand data; examination of Great Britain data from the last 25 years shows that the data requirements are greater than generally thought. A discussion is therefore presented into how analysis of the types of weather system which have historically driven extreme electricity demands can help to deliver robust insights into wind's contribution to supporting demand, even in the face of such data limitations. The role of the form of the probability distribution for available conventional capacity in driving wind capacity credit results is also discussed.

Greenhouse gas emissions from waste management—assessment of quantification methods

Of the many sources of urban greenhouse gas (GHG) emissions, solid waste is the only one for which management decisions are undertaken primarily by municipal governments themselves and is hence often the largest component of cities’ corporate inventories. It is essential that decision-makers select an appropriate quantification methodology and have an appreciation of methodological strengths and shortcomings. This work compares four different waste emissions quantification methods, including Intergovernmental Panel on Climate Change (IPCC) 1996 guidelines, IPCC 2006 guidelines, U.S. Environmental Protection Agency (EPA) Waste Reduction Model (WARM), and the Federation of Canadian Municipalities- Partners for Climate Protection (FCM-PCP) quantification tool. Waste disposal data for the greater Toronto area (GTA) in 2005 are used for all methodologies; treatment options (including landfill, incineration, compost, and anaerobic digestion) are examined where available in methodologies. Landfill was shown to be the greatest source of GHG emissions, contributing more than three-quarters of total emissions associated with waste management. Results from the different landfill gas (LFG) quantification approaches ranged from an emissions source of 557 kt carbon dioxide equivalents (CO2e) (FCM-PCP) to a carbon sink of −53 kt CO2e (EPA WARM). Similar values were obtained between IPCC approaches. The IPCC 2006 method was found to be more appropriate for inventorying applications because it uses a waste-in-place (WIP) approach, rather than a methane commitment (MC) approach, despite perceived onerous data requirements for WIP. MC approaches were found to be useful from a planning standpoint; however, uncertainty associated with their projections of future parameter values limits their applicability for GHG inventorying. MC and WIP methods provided similar results in this case study; however, this is case specific because of similarity in assumptions of present and future landfill parameters and quantities of annual waste deposited in recent years being relatively consistent.

Simulating human and environmental exposure from hand-held knapsack pesticide application: Be-WetSpa-Pest, an integrative, spatially explicit modeling approach

This paper presents an integrative and spatially explicit modeling approach for analyzing human and environmental exposure from pesticide application of smallholders in the potato producing Andean region in Colombia. The modeling approach fulfills the following criteria: (i) it includes environmental and human compartments; (ii) it contains a behavioral decision-making model for estimating the effect of policies on pesticide flows to humans and the environment; (iii) it is spatially explicit; and (iv) it is modular and easily expandable to include additional modules, crops or technologies. The model was calibrated and validated for the Vereda La Hoya and was used to explore the effect of different policy measures in the region. The model has moderate data requirements and can be adapted relatively easy to other regions in developing countries with similar conditions.

Are CGE Models still useful in economic policy making?

This paper develops background considerations to help better framing the results of a CGE exercise. Three main criticisms are usually addressed to CGE efforts. First, they are too aggregate, their conclusions failing to shed light on relevant sectors or issues. Second, they imply huge data requirements. Timeliness is frequently jeopardised by out-dated sources, benchmarks referring to realities gone by. Finally, results are meaningless, as they answer wrong or ill-posed questions. Modelling demands end up by creating a rather artificial context, where the original questions lose content. In spite of a positive outlook on the first two, crucial questions lie in the third point. After elaborating such questions, and trying to answer some, the text argues that CGE models can come closer to reality. If their use is still scarce to give way to a fruitful symbiosis between negotiations and simulation results, they remain the only available technique providing a global, inter-related way of capturing economy-wide effects of several different policies. International organisations can play a major role supporting and encouraging improvements. They are also uniquely positioned to enhance information and data sharing, as well as putting people from various origins together, to share their experiences. A serious and complex homework is however required, to correct, at least, the most dangerous present shortcomings of the technique.

Administração ativa de portfólio de crédito: uma revisão dos principais conceitos para uma implementação efetiva em bancos comerciais

Trata dos principais aspectos da administração ativa de portfólio de crédito a pessoa jurídica por bancos comerciais, que vem tomando o lugar do modo tradicional de administrar crédito. Inicialmente, apresenta a definição de administração ativa de portfólio de crédito, compara com a abordagem tradicional e aponta as motivações para o surgimento desta nova abordagem. Segue demonstrando as adaptações dos conceitos da Teoria Moderna de Portfólios aos portfólios de crédito e apresenta alguns modelos para a determinação de variáveis importantes para a mensuração do risco de crédito, tais como probabilidades de inadimplência, correlações entre ativos de crédito e risco de crédito de portfólio. Apresenta, ainda, o conceito de capital econômico e o Risk-Adjusted Return on Capital (RAROC) relativamente ao risco de crédito. Discute as responsabilidades e funções a serem desempenhadas pela administração ativa de portfólio de crédito e, como contribuição, apresenta, à luz das considerações deste trabalho, uma estrutura hipotética de um banco comercial que adota a administração ativa de portfólio de crédito.

Uso da krigagem indicatriz na avaliação de indicadores de fertilidade do solo

Este trabalho teve como objetivo identificar zonas diferenciadas de manejo por meio de indicadores de fertilidade em Latossolos cultivados com cana-de-açúcar, utilizando-se a técnica de krigagem indicatriz, com vistas em buscar um aprimoramento na utilização de técnicas de agricultura de precisão. O estudo foi realizado em uma área de 90 ha pertencente a uma área maior de 1.900 ha, localizada em Jaboticabal, Estado de São Paulo, Brasil (21 ° 15 ' S e 48 ° 18 ' W). Na área experimental, foi estabelecida uma malha de amostragem regular de 50 m, com 420 pontos. em cada ponto, coletou-se uma amostra de solo, na qual foram determinados os teores de matéria orgânica, P, K disponíveis e o valor de V. Os dados obtidos para estas características do solo, assim como as combinações entre elas, foram codificados em valores indicadores 0 ou 1, conforme as variáveis apresentassem valores acima ou abaixo do valor de corte estabelecido, escolhido para cada variável, respectivamente. Os resultados propiciaram a confecção de mapas de probabilidade de cada variável (individual e combinada), o que possibilitou identificar regiões com diferentes níveis de fertilidade do solo na área experimental.

Estudo da decomposição de plantas aquáticas em função das quantidades depositadas, da umidade e do tipo de disposição no solo

Um estudo foi realizado com a finalidade de avaliar a decomposição da biomassa de plantas aquáticas, incorporadas ou não ao solo, provenientes do controle mecânico, no reservatório da UHE Americana. O ensaio foi realizado em casa de vegetação, localizada no Núcleo de Pesquisas Avançadas em Matologia (NUPAM) da FCA/Unesp-Botucatu. A avaliação foi conduzida em vasos contendo 14 kg de solo, simulando descartes de 50, 100, 150 e 200 t MF de plantas ha-1 e avaliando o processo de decomposição através da liberação de CO2, divididos em duas etapas: a primeira em solo seco e, a segunda, na seqüência, com o solo úmido. A quantificação do CO2 liberado foi realizada através de titulação de solução adicionada ao processo de incubação de 24 horas dos vasos. Os dados foram interpolados e analisados seguindo modelo de Mitscherlich, com algumas modificações. Na primeira etapa, foi observada uma rápida liberação de CO2 até o décimo dia, seguida de estabilização. O maior teor de CO2 liberado foi observado no tratamento com descarte de 200 t MF ha-1 incorporado ao solo. Os dados avaliados durante a segunda fase do ensaio representaram uma maior linearidade no processo de liberação de CO2, indicando um período mais longo do processo de degradação da biomassa descartada.

Variabilidade espacial de atributos de um solo sob videira em Vitória Brasil (SP)

Foi pesquisada a variabilidade espacial de alguns atributos físicos e químicos de uma associação de solos cultivada sob videira (Vitis vinifera-L), do município de Vitória Brasil, estado de São Paulo, Brasil. O objetivo foi estudar a dependência espacial de tais atributos, assim como caracterizar as respectivas variabilidades, distribuições de freqüência e números mínimos de subamostras do solo para a cultura da videira. Para isso, coletaram-se dados do solo, dispostos segundo uma malha com 156 pontos amostrais, sendo analisados por meio da geoestatística. As maiores variabilidades foram verificadas para a macroporosidade (MA), P, K, Ca, Mg, SB e CTC, ao passo que as menores foram para a densidade do solo (DS), pH e V. O número mínimo de subamostras, necessário para formar uma amostra composta e representativa, variou de 1 (pH e V) a 241 (Mg), tendo seu valor médio de 64 subamostras. Quanto à dependência espacial, o P e o V apresentaram, respectivamente, forte e fraca dependência, enquanto o restante dos atributos apresentou moderada dependência. Desta forma, o alcance dos atributos físicos variou de 2,56 a 4,32 m, enquanto o dos químicos variou de 1,82 a 5,64 m.