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Introduction

SEEM (Simple Estuarine Eutrophication Model) is a software toolkit which provides the user with a basic capability to model nitrogen cycling and algal biomass in estuaries in response to nitrogen loads. The toolkit is designed to make model implementation, analysis and calibration as simple as possible. SEEM is intended to provide synthesis and interpretation of field data for scientists, and as a decision support tool for environmental managers. A detailed explanation of the principles underlying SEEM, and example applications to three test cases, are given in Parslow et al (1999).

The toolkit consists of two principal modules and some auxiliary tools.

• The biogeochemical model (SEEM.BAT) is implemented in JAVA and integrated within a graphical user interface which provides run management, and graphical display of output.
• The physical exchanges to drive the model are estimated from observed salinity fields, using an inverse package implemented in FORTRAN, and supplied as a WIN-32 executable (INVERSE.EXE) which can be run from a command prompt INVERSE.BAT.
• The state variable input and output files are written as random-access binary files, to allow for hot starts from previous runs. These can be converted to and from ASCII files, to make the data easily accessible by text editors or other analysis packages, using STATEGEN.BAT (ASCII to binary) and STATEDUMP.BAT (binary to ASCII).

Seem Users Manual

• If you wish to download this software manual then you should first obtain a copy of Estuarine Eutrophication Models Final Report Project E6 National River Health Program. The Estuarine Eutrophication Models report is published in HTML in full on au.riversinfo.org.
• To obtain further information or a copy of the software please contact Dr John Parslow at the address shown in the report.
• There is no charge for the software.
• This document is password modify protected. You cannot modify it without copying it to a new document.
• Original File Statistics seem.doc:
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  • Size 0.251 megabytes.

SEEM Figure 1: Exchanges in n-layer hybrid model

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