This 4-day applied groundwater modeling course is designed to present the theory behind MODFLOW (MODFLOW-2005, MODFLOW-NWT, MODFLOW-USG), MODPATH, ZoneBudget, MT3D/RT3D, SEAWAT, PEST, and to illustrate the practical development of groundwater flow and transport models using Visual MODFLOW Premium (Flex and Classic interfaces). This course introduces the modeling process including conceptual model development, numerical model implementation and model calibration. It alternates between lectures and exercises to illustrate the ease of using Visual MODFLOW Premium. Course participants will work individually on their own computers (provided), allowing to perform the Visual MODFLOW Premium exercises at their own pace.
It has become obvious by now that, as compared to traditional approaches such as collecting occasional grab samples and analyzing them under laboratory conditions, or performing measurements using hand-held instrumentation, much trusted monitoring data may be obtained by permanent deployment of water quality probes in either surface or groundwater monitoring locations. Of course, the traditional approaches have their undisputed technical and economical benefits as well.
In-Situ water quality sensors (optical and ion selective) become increasingly accessible, and the number of measured parameters is growing as well. By taking in consideration that datalogging techniques and data analysis procedures are readily available for a long while, it becomes clear that we have at hand excellent and completely new possibilities for monitoring and collecting high density groundwater quality data.
Nitrogen (nitrate and ammonium) is an important nutrient for plants living in aquatic ecosystems. Its sources can be wastewater treatment plants, runoff from cities, agricultural lands and farms, but it can also originate from the decomposition of organic matter, or manure leaching. Nitrate is water soluble, and the amount that is not used up can infiltrate into the soil and underlying aquifers, causing potential contamination.