Fox River Watershed investigation : Stratton Dam to the Illinois River, phase II : hydrologic and water quality simulation models, part 1, methodology and procedure for development of HSPF models /

"May 2007"--T.p.

Water resource data and preliminary trend analysis for the Blue Creek Watershed Project, Pike County, Illinois : Phase I /

"IEPA/WPC/82-001".

Alternative harvest strategies to alleviate predation bottlenecks: a bioeconomic modeling approach to inform adaptive management

Thesis (Ph.D.)--University of Washington, 2016-06

An advanced regularization methodology for use in watershed model calibration

A calibration methodology based on an efficient and stable mathematical regularization scheme is described. This scheme is a variant of so-called Tikhonov regularization in which the parameter estimation process is formulated as a constrained minimization problem. Use of the methodology eliminates the need for a modeler to formulate a parsimonious inverse problem in which a handful of parameters are designated for estimation prior to initiating the calibration process. Instead, the level of parameter parsimony required to achieve a stable solution to the inverse problem is determined by the inversion algorithm itself. Where parameters, or combinations of parameters, cannot be uniquely estimated, they are provided with values, or assigned relationships with other parameters, that are decreed to be realistic by the modeler. Conversely, where the information content of a calibration dataset is sufficient to allow estimates to be made of the values of many parameters, the making of such estimates is not precluded by preemptive parsimonizing ahead of the calibration process. White Tikhonov schemes are very attractive and hence widely used, problems with numerical stability can sometimes arise because the strength with which regularization constraints are applied throughout the regularized inversion process cannot be guaranteed to exactly complement inadequacies in the information content of a given calibration dataset. A new technique overcomes this problem by allowing relative regularization weights to be estimated as parameters through the calibration process itself. The technique is applied to the simultaneous calibration of five subwatershed models, and it is demonstrated that the new scheme results in a more efficient inversion, and better enforcement of regularization constraints than traditional Tikhonov regularization methodologies. Moreover, it is argued that a joint calibration exercise of this type results in a more meaningful set of parameters than can be achieved by individual subwatershed model calibration. (c) 2005 Elsevier B.V. All rights reserved.

Efficient accommodation of local minima in watershed model calibration

The Gauss-Marquardt-Levenberg (GML) method of computer-based parameter estimation, in common with other gradient-based approaches, suffers from the drawback that it may become trapped in local objective function minima, and thus report optimized parameter values that are not, in fact, optimized at all. This can seriously degrade its utility in the calibration of watershed models where local optima abound. Nevertheless, the method also has advantages, chief among these being its model-run efficiency, and its ability to report useful information on parameter sensitivities and covariances as a by-product of its use. It is also easily adapted to maintain this efficiency in the face of potential numerical problems (that adversely affect all parameter estimation methodologies) caused by parameter insensitivity and/or parameter correlation. The present paper presents two algorithmic enhancements to the GML method that retain its strengths, but which overcome its weaknesses in the face of local optima. Using the first of these methods an intelligent search for better parameter sets is conducted in parameter subspaces of decreasing dimensionality when progress of the parameter estimation process is slowed either by numerical instability incurred through problem ill-posedness, or when a local objective function minimum is encountered. The second methodology minimizes the chance of successive GML parameter estimation runs finding the same objective function minimum by starting successive runs at points that are maximally removed from previous parameter trajectories. As well as enhancing the ability of a GML-based method to find the global objective function minimum, the latter technique can also be used to find the locations of many non-global optima (should they exist) in parameter space. This can provide a useful means of inquiring into the well-posedness of a parameter estimation problem, and for detecting the presence of bimodal parameter and predictive probability distributions. The new methodologies are demonstrated by calibrating a Hydrological Simulation Program-FORTRAN (HSPF) model against a time series of daily flows. Comparison with the SCE-UA method in this calibration context demonstrates a high level of comparative model run efficiency for the new method. (c) 2006 Elsevier B.V. All rights reserved.

Estimation of ravine sediment production and sediment dynamics in the lower Le Sueur River watershed, Minnesota

This study focuses on quantifying explicitly the sediment budget of deeply incised ravines in the lower Le Sueur River watershed, in southern Minnesota. High-rate-gully-erosion equations along with the Universal Soil Loss Equation (USLE) were implemented in a numerical modeling approach that is based on a time-integration of the sediment balance equations. The model estimates the rates of ravine width and depth change and the amount of sediment periodically flushing from the ravines. Components of the sediment budget of the ravines were simulated with the model and results suggest that the ravine walls are the major sediment source in the ravines. A sensitivity analysis revealed that the erodibility coefficients of the gully bed and wall, the local slope angle and the Manning’s coefficient are the key parameters controlling the rate of sediment production. Recommendations to guide further monitoring efforts in the watershed and increased detail modeling approaches are highlighted as a result of this modeling effort.

An integrated flow and transport model to study the impact of mercury remediation strategies for East Fork Poplar Creek watershed, Oak Ridge, Tennessee

An integrated flow and transport model using MIKE SHE/MIKE 11 software was developed to predict the flow and transport of mercury, Hg(II), under varying environmental conditions. The model analyzed the impact of remediation scenarios within the East Fork Poplar Creek watershed of the Oak Ridge Reservation with respect to downstream concentration of mercury. The numerical simulations included the entire hydrological cycle: flow in rivers, overland flow, groundwater flow in the saturated and unsaturated zones, and evapotranspiration and precipitation time series. Stochastic parameters and hydrologic conditions over a five year period of historical hydrological data were used to analyze the hydrological cycle and to determine the prevailing mercury transport mechanism within the watershed. Simulations of remediation scenarios revealed that reduction of the highly contaminated point sources, rather than general remediation of the contaminant plume, has a more direct impact on downstream mercury concentrations.

Distribution of Diatoms Along Environmental Gradients in the Charlotte Harbor, Florida (USA), Estuary and Its Watershed: Implications for Bioassessment of Salinity and Nutrient Concentrations

The relative abundance of diatom species in different habitats can be used as a tool to infer prior environmental conditions and evaluate management decisions that influence habitat quality. Diatom distribution patterns were examined to characterize relationships between assemblage composition and environmental gradients in a subtropical estuarine watershed. We identified environmental correlates of diatom distribution patterns across the Charlotte Harbor, Florida, watershed; evaluated differences among three major river drainages; and determined how accurately local environmental conditions can be predicted using inference models based on diatom assemblages. Sampling locations ranged from freshwater to marine (0.1–37.2 ppt salinity) and spanned broad nutrient concentration gradients. Salinity was the predominant driver of difference among diatom assemblages across the watershed, but other environmental variables had stronger correlations with assemblages within the subregions of the three rivers and harbor. Eighteen indicator taxa were significantly affiliated with subregions. Relationships between diatom taxon distributions and salinity, distance from the harbor, total phosphorus (TP), and total nitrogen (TN) were evaluated to determine the utility of diatom assemblages to predict environmental values using a weighted averaging-regression approach. Diatom-based inferences of these variables were strong (salinity R 2 = 0.96; distance R 2 = 0.93; TN R 2 = 0.83; TP R 2 = 0.83). Diatom assemblages provide reliable estimates of environmental parameters on different spatial scales across the watershed. Because many coastal diatom taxa are ubiquitous, the diatom training sets provided here should enable diatom-based environmental reconstructions in subtropical estuaries that are being rapidly altered by land and water use changes and sea level rise.

Cost-Efficient Spatial Placement of Water Retention Sites (WRS) to Reduce Sediment in Le Sueur River Watershed,MN

Thesis (Master's)--University of Washington, 2016-06

Rathbun Lake Special Project: BMPs for priority land in Targeted Sub-Watershed 2012 1221-010, Final Report 2013-2061,

The Rathbun Land and Water Alliance and partners have undertaken a highly effective approach to water quality protection through the Rathbun Lake Special Project. This approach is achieving a significant reduction in the sediment and phosphorus that impair water quality in Rathbun Lake and its tributaries as a result of the targeted application of best management practices (BMPs) for priority land in the watershed. This project application proposes to assist landowners to apply BMPs that will reduce sediment and phosphorus delivery from priority land in three targeted sub-watersheds as part of the Rathbun Lake Special Project. Features of this project are: (1) use of geographic information system (GIS) analysis to identify priority land that requires BMPs; (2) assistance for landowners to apply BMPs for 1,200 acres that will reduce the annual delivery of sediment by 1,800 tons and phosphorus by 6,000 pounds; (3) evaluation of the benefits from BMP application using GIS analysis and water quality monitoring; and (4) watershed outreach activities that encourage landowners to apply BMPs for priority land to protect water quality.

Dry Run Creek Watershed Improvement Project 1248-023: Final Project Report: July 2013-December 2015, October 11, 2016

In 2010 a group of farmers in the Dry Run Creek watershed, an Iowa High Quality Water Resource, formed the Dry Run Creek Watershed Improvement Association to learn more about and implement solutions to remedy a bacteria impairment in their stream. Through a partnership with Luther College, Iowa DNR Watershed Monitoring and Assessment and Iowa State University Extension the farmers were able to conduct an assessment of their stream and watershed. The assessment showed multiple potential sources of bacteria, dependent on whether water samples were collected following rain events or during dry conditions. This project will allow watershed farmers to implement solutions to reduce bacteria delivery during both wet and dry weather. Funding will be targeted to feedlot runoff control improvements, cover crops and vegetative filters, manure management strategies and livestock stream access. The council intends to continue intensive water monitoring to determine whether the strategies are successful. Research shows the bacteria reduction in water bodies can be seen relatively quickly, within 1-2 years, compared to other types of impairments.

Dry Run Creek Watershed Improvement Project 1248-023, Final Project Report: July 2013-December 2015, March 26, 2015

In 2010 a group of farmers in the Dry Run Creek watershed, an Iowa High Quality Water Resource, formed the Dry Run Creek Watershed Improvement Association to learn more about and implement solutions to remedy a bacteria impairment in their stream. Through a partnership with Luther College, Iowa DNR Watershed Monitoring and Assessment and Iowa State University Extension the farmers were able to conduct an assessment of their stream and watershed. The assessment showed multiple potential sources of bacteria, dependent on whether water samples were collected following rain events or during dry conditions. This project will allow watershed farmers to implement solutions to reduce bacteria delivery during both wet and dry weather. Funding will be targeted to feedlot runoff control improvements, cover crops and vegetative filters, manure management strategies and livestock stream access. The council intends to continue intensive water monitoring to determine whether the strategies are successful. Research shows the bacteria reduction in water bodies can be seen relatively quickly, within 1-2 years, compared to other types of impairments.

Using landscape metrics to predict hydrologic connectivity patterns between forested wetlands and streams in a coastal plain watershed

Geographically isolated wetlands, those entirely surrounded by uplands, provide numerous ecological functions, some of which are dependent on the degree to which they are hydrologically connected to nearby waters. There is a growing need for field-validated, landscape-scale approaches for classifying wetlands based on their expected degree of connectivity with stream networks. During the 2015 water year, flow duration was recorded in non-perennial streams (n = 23) connecting forested wetlands and nearby perennial streams on the Delmarva Peninsula (Maryland, USA). Field and GIS-derived landscape metrics (indicators of catchment, wetland, non-perennial stream, and soil characteristics) were assessed as predictors of wetland-stream connectivity (duration, seasonal onset and offset dates). Connection duration was most strongly correlated with non-perennial stream geomorphology and wetland characteristics. A final GIS-based stepwise regression model (adj-R2 = 0.74, p < 0.0001) described wetland-stream connection duration as a function of catchment area, wetland area and number, and soil available water storage.