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Midwest Partnership Summer Meeting (July 6-8 2011). Bernie Engel, Youn Shik Park and Larry Theller [email protected] - [email protected] Purdue University. Discussion Outline. Case study: Fort McCoy and Low Impact Development L-THIA. Chris Urban

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Midwest partnership summer meeting july 6 8 2011

Midwest Partnership Summer Meeting (July 6-8 2011)

Bernie Engel, Youn Shik Park

and Larry Theller

[email protected] - [email protected]

Purdue University


Discussion outline
Discussion Outline

  • Case study: Fort McCoy and Low Impact Development L-THIA. Chris Urban

  • Case study: Desktop Arcview LTHIA in Korea, leads to desktop model for WI DNR. Larry Theller

  • L-THIA IDEM case study leads into Corps project with MSU – major upgrades to LTHIA OWLs. Larry Theller

  • LDC upgrades, LOADEST, etc . Youn Shik Park

  • WQX New Project ( LDC plugs in to WQX and is TMDL friendly, 6 FIFRA data sets uploaded. Larry Theller

  • Driftwatch update. Bernie Engel


Long term hydrologic impact model
Long Term Hydrologic Impact Model

  • As a quick and easy-to-use approach, L-THIA's results can be used to generate community awareness of potential long-term problems and to support planning aimed at minimizing disturbance of critical areas.

  • L-THIA is an ideal tool to assist in the evaluation of potential effects of planned or zoned land use change .

  • It can identify the best location of a particular land use so as to have minimum impact on a community's natural environment.



  • This study was particularly interested in the impact of N and P on algae growth.

  • Algae has been a problem occurrence on an annual average of 45 days in recent years (2005 – 2009.) The accumulation of N and P occurs through both dry and rainy seasons continuously.

  • To support management of the lake (created by a dam in 1980,) discharge and water quality data were collected from five sites including two streams and three sites close to the lake.

  • To estimate load under various conditions the research included simulation using the models Long-Term Hydrologic Impact Assessment (L-THIA) and Soil and Water Assessment Tool (SWAT).


Results
Results and P on algae growth.

  • For the analysis, Curve Number (CN) values were calculated based on growing season and dormant season and were used for the L-THIA simulation.

  • The L-THIA model was calibrated against observed data and produced a better fit than the SWAT model in the calibration.

  • The L-THIA results are used in the decision support process. Model results were produced to aid in the management of the watershed to control runoff.

  • Eutrophication is the major problem in this lake, and management measures are designed to control the addition of N and P in to the lake.


Desktop l thia calculator
Desktop L-THIA Calculator and P on algae growth.



Since 2002, there have been at least 17 watershed management plans (funded by IDEM's 319 or 205(j) program, or submitted to IDEM for review to be eligible for implementation funding) that have used L-THIA. Most commonly, L-THIA was used to estimate existing pollutant loads in a watershed. Sometimes L-THIA was used when there was no monitoring data available, and sometimes it was used to provide a comparison with loads calculated from monitoring data.

Watershed Management Case Study



Floating, semi-transparent toolbars, collapsible menus, open architecture for partners, improved editing perfrormance.

New Area of Interest tool : Polygon

“Select by Polygon” to use a single HUC 12 outline will work for off-site users, such as Michigan State.


Tool will now allow use of a polygon as an area of analysis.

This will improve ability to model zoning and LID BMP areas.


-Display of HIT target layers

-EPA Waters layers

-GIS layers



Load Duration Tool multiple pages.

with

LOADEST

https://engineering.purdue.edu/~ldc/new


To develop only multiple pages.FDC

To develop FDCand LDC,

To run “LOADEST”


FDC only multiple pages.

FDC and LDC with LOADEST execution

: by user’s flow and WQ data

: by USGS flow data and user’s WQ data

: by USGS flow data and user’s WQ data with drainage ratio

: by retrieving both data through the web


Flow multiple pages.data

- user’s data

- USGS flow data

Develop FDC and LDC

Execute LOADESTon background mode

WQdata

- user’s data

- USGS WQ data

Develop TMDLusing LOADEST result

FuturePlan

Estimate required reduction to meet goal


a multiple pages.

b

Select State (a). (Indiana and Wisconsin are available, so far.)

Three ways to find USGS gauging station :Type address or ZIP (b),Through Google Maps interface (c),Type Station Number (d).

c

d


The tool gives.. multiple pages.

.. Information of pre-selected 24 WQ data (a),

.. Information on Flow data (b),

.. Raw data file of flow and WQ data (c).

a

Select period to develop LDC(d),

and click this button.

(period : Jan/1/2008 – Nov/8/2010, WQ : 00530)

b

c

d


a multiple pages.

b

A simple module works to combine flowand WQdata.

Set Water Quality Standard (a).

Also combined data file is downloadable to use in other models (b).



a multiple pages.

FDC

LDC

Time Series Plot

LOADEST can be run with background mode on this page (a).

It provides Mean Daily Load estimated by measured data (b).

Concentration Plot

b


Changed by multiple pages.

LOADEST result

During processing, the figures on the page will be replaced by LOADEST results.

LOADEST Inputs and Outputs are downloadable (a).

a


Changed by multiple pages.

LOADEST result

During processing, the figures will be replaced by LOADEST result.

Estimated Annual Load File is downloadable (a).

Mean Daily Load by LOADEST result will be displayed (b).

a

b


LOADEST multiple pages. results,

Estimated Mean Daily Load compared to

Mean Daily Load from observed data.


Mi hoon jeong june 20 2011

Spatial Optimization for Managing Surface Runoff from Urbanization- Parameterization and Application of a Spatial Runoff Minimization Model

Mi HoonJeong

June 20, 2011


Multiple objective spatial optimization for new urban development

3 Urbanizationrd Objective – Results

Multiple-Objective Spatial Optimization for New Urban Development

The ROMIN model was adjusted to identify optimal regions in terms of hydrologic management and socioeconomic consideration

The LTM (Land Transformation Model) was chosen as a way to adjust the ROMIN model by providing socioeconomic preference for urban development


Summary and implications

Overall Summary Urbanization

Summary and Implications

Hydrologic management can be supported by better decisions regarding urban development scale and location

The proposed approach identifies optimal locations based on multiple objectives and the solutions are considered more practical than those based on only consideration of hydrologic impact management

The ROMIN model has potential for solving other multiple objective problems


Appendix Urbanization

(a)

(b)

(c)

Muskegon Watershed

Southfork Wildcat Creek-Cary

Watershed

(c) Little Eagle Creek Watershed


2 Urbanizationnd Objective –Results

  • The relationship between urban development scale and hydrologic impact is a characteristic specific to a watershed

Southfork Wildcat

Creek-Cary

Southfork Wildcat

Creek-Cary

Little Eagle Creek


2 Urbanizationnd Objective –Results

Optimal locations depend on development scale

40 ha development

(23% urbanized)

120 ha development

(29% urbanized)

200 ha development

(34% urbanized)

360 ha development

(46% urbanized)

280 ha development

(40% urbanized)

320 ha development

(43% urbanized)


2 Urbanizationnd Objective –Results

Optimal Location Change

As the required area is increased, the current optimal location isn’t able to satisfy the required shape or area, or minimize runoff increase at the same location; therefore, it is necessary to re-compute the optimal location of development

Critical Points & Slope Changes

- a change in optimal development location or

- Running out of least cost neighbor areas around the current location and inclusion of higher cost areas for development.


The ltm socioeconomic preference

3 Urbanizationrd Objective - Results

The LTM-socioeconomic preference

Likelihood of urbanization

for each cell

-> a substitute for

socioeconomic preference

Likelihood

  • 0 : no likelihood

  • Higher: higher likelihood of urbanization


1 Urbanizationst Objective - Results

ROMIN solutions are better than suitability solutions in terms of contiguousness and area requirement.

The ROMIN Model Solution

(c) Runoff Increase≤0.99cm (d) Runoff Increase ≤ 1.09cm

Suitability Map Solutions

(a) Runoff Increase≤0.1cm (b) Runoff Increase ≤ 0.76cm

Suitability Map Solutions


Future possibilities

Overall Summary Urbanization

Future Possibilities

Potential for a variety of applications by defining the objective function cost such as:

  • Identification of management zones for precision agriculture applications.

  • an optimal site selection whose objective is to minimize NPS pollution or erosion instead of runoff increase.

  • determination of land prioritization for water supply protection.


DriftWatch Urbanization Overview

Pesticide Sensitive Crops and Habitats Registry

Bernie Engel and Larry Theller

[email protected] and [email protected]

Purdue University

Leighanne Hahn

[email protected]

Office of Indiana State Chemist

www.driftwatch.org


Illinois sensitive crops and habitats registry Urbanization

[email protected]




Additional “sensitive areas or habitats” layers are streamed over the Google Maps™ display.

This example contains nearby commercial wind turbines.

[email protected]


Driftwatch national expansion
Driftwatch National Expansion. streamed over the Google Maps™ display.

Join in 2012

Active in 2011


Questions
Questions streamed over the Google Maps™ display.


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