A watershed scale lumped parameter hydrology and water quality model that includes an uncertainty analysis component was developed and tested on a lower coastal plain watershed in North Carolina. Uncertainty analysis was used to determine the impacts of uncertainty in field and network parameters of the model on the predicted outflows and nitrate-nitrogen loads at the outlet of the watershed. T...

The morphological approach to image segmentation is based on the watershed transform. It is a very powerful tool which presents many advantages: it is not parametric, computationally efficient... However, in comparison with energy-based methods as active contours, it does not allow to control the smoothness of the result. In order to introduce geometrical regularization constraints in the morph...

The ability of a watershed model to mimic specified watershed processes is assessed through the calibration and validation process. The Soil and Water Assessment Tool (SWAT) watershed model was implemented in the Beaver Reservoir Watershed of Northwest Arkansas. The objectives were to: (1) provide detailed information on calibrating and applying a multisite and multivariable SWAT model; (2) con...

Historical and recent remote sensing data can be used to address temporal and spatial relationships between upland land cover and downstream vegetation response at the watershed scale. This is demonstrated for sub-watersheds draining into Elkhorn Slough, California, where salt marsh habitat has diminished because of the formation of sediment fans that support woody riparian vegetation. Multiple...

Urban activities and related infrastructure alter the natural patterns of stream physical and chemical conditions. According to the Urban Stream Syndrome, streams draining urban landscapes are characterized by high concentrations of nutrients and ions, and might have elevated water temperatures and variable oxygen concentrations. Here, we report temporal and spatial variability in stream physic...

This paper proposes, a method modified Gradient image as input to the watershed transform algorithm this is compared with Fast Level Set method. The method is feasible in medical imaging and deserves. It could be used to segment the white matter, brain tumor and other small and simple structured organs in CT and MR images. In this paper used Gradient watershed transform and Fast Level Set metho...

The watershed algorithm from mathematical morphology is powerful for segmentation. However, it does not allow incorporation of a priori information as segmentation methods that are based on energy minimization. In particular, there is no control of the smoothness of the segmentation result. In this paper we show how to represent watershed segmentation as an energy minimization problem, using th...

This paper presents a solution to a major drawback of watershed transformation: over segmentation. The solution utilizes one of its main advantages – very good edge extraction. It is a method that simulates pouring water onto a landscape created on a basis of a digital image. Unfortunately transformation produces a region for each local minimum so, usually, the number of watersheds (catchment b...

Incorporation of Geographic Information Systems (GIS) into Unsupervised-Supervised Artificial Neural Networks (ANNs) was applied to quantify the similarity of watershed characteristics. The goal of this approach is to find the best match watershed from a large knowledge base of over one thousand quantifying watersheds and to determine the reliability of “transplant” watershed information during...

The Maumee River watershed is the largest drainage basin that discharges into the Great Lakes. Although the watershed is largely a rural landscape, several major urban-industrial cities, including Fort Wayne and Toledo are located along the river. Many water quality concerns are present, especially nonpoint rural runoff that contributes significant amounts of sediment into the Maumee River. The...