A database for integrated assessment of European agricultural systems

A major bottleneck for data-based policy making is that data sources are collected, managed, and distributed by different institutions, residing in different locations, resulting in conceptual and practical problems. The use of dispersed data for agricultural systems research requires the integration of data sources, which means to ensure consistency in data interpretations, units, spatial and temporal scales, to respect legal regulations of privacy, ownership and copyright, and to enable easy dissemination of data. This paper describes the SEAMLESS integrated database on European agricultural systems. It contains data on cropping patterns, production, farm structural data, soil and climate conditions, current agricultural management and policy information. To arrive at one integrated database, a shared ontology was developed according to a collaborative process, which facilitates interdisciplinary research. The paper details this process, which can be re-used in other research projects for integrating data sources.     

Estimating marine biogeochemical rates of the carbonate pH system—A Kalman filter tested

Oxygen (O₂), nitrate (NO₃), dissolved inorganic carbon (DIC) or pCO₂, and pH or total alkalinity (TA), are useful indices of marine chemical, physical and biological processes operating on varying time-scales. Although these properties are increasingly being monitored at high frequency, they have not been extensively used for studying ecosystem dynamics. We test whether we can estimate time-evolving biogeochemical rates (e.g. primary production, respiration, calcification and carbonate dissolution, and nitrification) from synthetic high frequency time-series of O₂, NO₃, DIC, pCO₂, TA or pH. More specifically, a Kalman filter has been implemented in a very simplified biogeochemical model describing the dynamics of O₂, NO₃, DIC and TA and linking the concentration data to biogeochemical fluxes. Different sets of concentration data are assimilated and biogeochemical rates are estimated. The frequency of assimilation required to get acceptable results is investigated and is compared with the frequency of sampling in the field or in controlled experimental settings.Smoothing of the data to remove data noise before assimilation improves the estimation of the biogeochemical rates. The best estimated rates are obtained when assimilating O₂, NO₃ and TA although the assimilation of DIC instead of TA also gives satisfactory results. In case pH or pCO₂ is assimilated rather than DIC or TA, the linearization of the (now nonlinear) observation equation introduces perturbations and the Kalman filter behaves suboptimal. We conclude that, given the resolution of data required, the tool has potential to estimate biogeochemical rates of the carbonate system under controlled settings.     

The AVI project: A bibliographical and archive inventory of landslides and floods in Italy

The AVI project was commissioned by the Minister of Civil Protection to the National Group for Prevention of Hydrogeologic Hazards to complete an inventory of areas historically affected by landslides and floods in Italy. More than 300 people, divided into 15 research teams and two support groups, worked for one year on the project. Twenty-two journals were systematically searched for the period 1918–1990, 350,000 newspaper issues were screened, and 39,953 articles were collected. About 150 experts on mass movement and floods were interviewed and 1482 published and unpublished technical and scientific reports were reviewed. The results of the AVI project, in spite of the limitations, represent the most comprehensive archiving of mass movement and floods ever prepared in Italy. The type and quality of the information collected and the methodologies and techniques used to make the inventory are discussed. Possible applications and future developments are also presented.     

Groundwater mapping: An analysis of the United States Hydrological Investigation Atlas Series

Groundwater mapping is a critical component of efficient water resource management today. Difficulties arise when highly specialized and complex groundwater data are collected and presented in map form. This is an analysis of the map content and its presentation in the USGS Hydrological Investigation Atlas Series. This analysis reveals the problems to be surmounted in mapping groundwater information. The technical nature of the groundwater data requires special design considerations.     

Information Management System for Site Remediation Efforts

/ Environmental regulatory agencies are responsible for protecting human health and the environment in their constituencies. Their responsibilities include the identification, evaluation, and cleanup of contaminated sites. Leaking underground storage tanks (USTs) constitute a major source of subsurface and groundwater contamination. A significant portion of a regulatory body's efforts may be directed toward the management of UST-contaminated sites. In order to manage remedial sites effectively, vast quantities of information must be maintained, including analytical dataon chemical contaminants, remedial design features, and performance details. Currently, most regulatory agencies maintain such information manually. This makes it difficult to manage the data effectively. Some agencies have introduced automated record-keeping systems. However, the ad hoc approach in these endeavors makes it difficult to efficiently analyze, disseminate, and utilize the data. This paper identifies the information requirements for UST-contaminated site management at the Waste Cleanup Section of the Department of Environmental Resources Management in Dade County, Florida. It presents a viable design for an information management system to meet these requirements. The proposed solution is based on a back-end relational database management system with relevant tools for sophisticated data analysis and data mining. The database is designed with all tables in the third normal form to ensure data integrity, flexible access, and efficient query processing. In addition to all standard reports required by the agency, the system provides answers to ad hoc queries that are typically difficult to answer under the existing system. The database also serves as a repository of information for a decision support system to aid engineering design and risk analysis. The system may be integrated with a geographic information system for effective presentation and dissemination of spatial data.     

Simulation modeling and resource management

Simulation models are becoming increasingly important as tools for synthesizing and applying information in almost all aspects of land management. They are particulary valuable for predicting and comparing outcomes of alternative decisions and assumptions. Models also permit managers to consider and integrate the potential influences of a large number of variables.     

Modelling and Prediction of Diesel Engine Performance using Relevance Vector Machine

Diesel engines are being increasingly adopted by many car manufacturers today, yet no exact mathematical diesel engine model exists due to its highly nonlinear nature. In the current literature, black-box identification has been widely used for diesel engine modelling and many artificial neural network (ANN) based models have been developed. However, ANN has many drawbacks such as multiple local minima, user burden on selection of optimal network structure, large training data size, and over-fitting risk. To overcome these drawbacks, this article proposes to apply an emerging machine learning technique, relevance vector machine (RVM), to model and predict the diesel engine performance. The property of global optimal solution of RVM allows the model to be trained using only a few experimental data sets. In this study, the inputs of the model are engine speed, load, and cooling water temperature, while the output parameters are the brake-specific fuel consumption and the amount of exhaust emissions like nitrogen oxides and carbon dioxide. Experimental results show that the model accuracy is satisfactory even the training data is scarce. Moreover, the model accuracy is compared with that using typical ANN. Evaluation results also show that RVM is superior to typical ANN approach.     

It’s All in the Numbers: Acreage Tallies and Environmental Program Evaluation

Increasingly, performance measurement is being used to hold federal agencies accountable, represent environmental progress, and evaluate the effectiveness of environmental programs. The need to track measurable outputs has created a tendency to present programmatic progress solely by quantifiable data, despite the inherent complexity of natural resource management. Wetlands and fire management programs are two specific environmental arenas that have come to overemphasize the tracking of acreage numbers to validate existing policy direction. In both of these arenas, we find the definition and categorization of "countable" acres to be inconsistent and unreliable. We explore this systemic flaw for both wetlands and fire programs and describe its implications for environmental policy and natural resource management more broadly. We conclude with recommendations for improved performance measurement in these arenas.     

Studying crop sequences with CarrotAge,a HMM-based data mining software

We have developed a knowledge discovery system based on high-order hidden Markov models for analyzing spatio-temporal data bases. This system, named CarrotAge , takes as input an array of discrete data – the rows represent the spatial sites and the columns the time slots – and builds a partition together with its a posteriori probability. CarrotAge has been developed for studying the cropping patterns of a territory. It uses therefore an agricultural drench database, named Ter-Uti , which records every year the land-use category of a set of sites regularly spaced. The results of CarrotAge are interpreted by agronomists and used in research works linking agricultural land use and water management. Moreover, CarrotAge can be used to find out and study crop sequences in large territories, that is a main question for agricultural and environmental research, as discussed in this paper.     

PAH deposition to snow surface

The urban snowpack effectively acts as a collection device for atmospheric-deposited PAHs. When these PAHs are flushed out in a short time interval along with springtime snowmelt, these cause shockloading to receiving waters. In order to assess the PAH deposition and accumulation in urban snowpacks, a deposition survey of PAH for the winter months of 1991-92 from the city of Sault Ste. Marie, Ontario, Canada was undertaken. The results of the survey are interpreted in view of prevailing meteorology and various emission sources in the study area. The relative PAH deposition levels (to BaP) are compared with relative source emission fingerprints to examine consistency in sampling and analysis. While analyzing the PAH samples using the ASTM (1987) method, the problem of concentration levels being below the detection level was encountered. The ASTM method for PAH analysis was modified to enhance the detection limit of the PAHs by concentrating the PAH extract to very low volumes, on the order of 200-300 microL.