Wisconsin Water Science Center
In addition to conducting innovative science investigations, the Wisconsin Water Science Center also evaluates, expands, and creates environmental software, modeling, and statistical packages. We also provide data for software and model calibration. (Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.)
The SLAMM model is used to identify sources of pollutants in urban stormwater runoff and to evaluate management alternatives for reduce pollutants. These files provide stormwater flow and pollutant-concentration data for calibrating and verifying SLAMM for use in Wisconsin (WinSLAMM).
The Soil-Water-Balance (SWB) model has been developed to allow estimates of potential recharge to be made quickly and easily. The code calculates components of the water balance at a daily time-step by means of a modified version of the Thornthwaite-Mather soil-moisture-balance approach.
The PEST++ software suite is object-oriented universal computer code written in C++ that expands on and extends the algorithms included in PEST, a widely used parameter estimation code written in Fortran. PEST++ is designed to lower the barriers of entry for users and developers while providing efficient algorithms that can accommodate large, highly parameterized problems.
PESTCommander is an object-oriented Graphical User Interface (GUI) written in Python® that facilitates the management of model files ("file management") and remote launching and termination of slave computers across a distributed network of computers ("run management").
GENIE Version 2 is a model-independent suite of programs that can be used to generally distribute, manage, and execute multiple model runs via a TCP/IP network. The suite consists of a file distribution interface, a run manager, a run executer, and a routine that can be compiled as part of a program and used to exchange model runs with the run manager.
TSPROC (Time Series PROCessor) is a software package designed to assist in the calibration of models by editing and distilling time series datasets into more meaningful observations to be used in the optimization objective function. TSPROC uses a simple scripting language to process and analyze time series.