1 / 26

Josh Woodbury Christine A. Shoemaker Dillon Cowan Zachary Easton

A Comparison of a SWAT model for the Cannonsville Watershed with and without Variable Source Area Hydrology. Josh Woodbury Christine A. Shoemaker Dillon Cowan Zachary Easton. Outline. SWAT2005 vs SWAT-VSA Calibration Corn analysis Conclusion Questions ?. SWAT2005 and SWAT-VSA.

quail-johns
Download Presentation

Josh Woodbury Christine A. Shoemaker Dillon Cowan Zachary Easton

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. A Comparison of a SWAT model for the Cannonsville Watershed with and without Variable Source Area Hydrology Josh Woodbury Christine A. Shoemaker Dillon Cowan Zachary Easton

  2. Outline • SWAT2005 vs SWAT-VSA • Calibration • Corn analysis • Conclusion • Questions ?

  3. SWAT2005 and SWAT-VSA • The current SWAT2005 version is a replication of the SWAT 2000 model developed by Bryan Tolson • Dillon Cowan replicated the SWAT 2000 files as closely as possible to create the current SWAT2005 version • This included creating the same number of subbasins with similar HRUs • Much time was spent insuring that the corn and pasture areas in each model are identical • Although corn is only a small percentage of the watershed, it accounts for a significant percentage of the phosphorous loading to the reservoir • Meticulous attention to corn area is important in order to create an accurate model replication • Very time consuming since the watershed delineation did not create the correct amount of corn area because of the small percentage

  4. SWAT2005 and SWAT-VSA • Source code changes done in the 2000 version (Tolson and Shoemaker, 2007, Jn of Hydrology) were also done in the 2005 source code • Includes modifications to manure spreading, plant growth, flow in/on frozen soils, and monthly subbasin temperatures • Tolson showed that these changes produce a better model

  5. SWAT-VSA model • The SWAT-VSA model incorporates the model and file changes in the SWAT2005 model, as well as Variable Source Area Hydrology • VSA hydrology is incorporated into the model using the same techniques used to create the Town Brook VSA model • Meticulously accounted for corn and pasture areas between the SWAT2005 and SWAT-VSA models • SWAT-VSA uses 10 different wetness classes

  6. Why bother with VSA hydrology? • The VSA model will make different predictions concerning the spatial distribution of the nutrient transport than a non-VSA model • If we know where the runoff is coming from, we can make judgments about the best nutrient placement • Apply management practices to the model and see how this changes future predictions • We can compare the future predictions of SWAT2005 and SWAT-VSA to see if careful placement of nutrients changes nutrient loading to the reservoir

  7. Outline SWAT2005 vs SWAT-VSA Calibration Corn analysis Conclusion Questions ?

  8. Calibration • Both of the models are calibrated first for flow, then sediment and finally phosphorous • The calibration period is from Jan. 1994 to Dec. 1999 • Auto-calibration and manual calibration techniques are used to get the best fit • Parameters used are based upon a sensitivity analysis done by Ryan Fleming

  9. Calibration Firstly the models are calibrated using an algorithm called DDS DDS is a simple stochastic single-solution based heuristic global search algorithm designed for automatic calibration of watershed models (Tolson and Shoemaker, WRR, 2007) DDS is used with a weighted Sum of Squared Error objective function

  10. Calibration Once flow and sediment are calibrated, Total Dissolved Phosphorous (TDP) and Particulate Phosphorous (PP) are calibrated using DDS • Manual calibration techniques are then used to slightly improve the models

  11. Calibration • Many different attempts where made in order to find the best way to calibrate for more than one output at a time • The problem is that the SSE values for each of the outputs vary by orders of magnitude • By simply summing all the outputs, some of the outputs are weighted more heavily than others • This problem has plagued users trying to auto-calibrate SWAT • Most papers addressing the subject suggest using some type of weighting scheme, either simple weighting factors, or complicated statistical weighting schemes

  12. Calibration • Initially tried to calibrate for Flow, Sediment, PP and TDP at once • Tried using weighting values, taking the natural log of the data, and weighting the natural logs of the data in order to decrease the differences in magnitude • Eventually gave up on calibrating all four outputs at once and adopted the calibration method previously presented • This is still not the best way to auto-calibrate, as it still requires some manual calibration at the end

  13. Results – Calibration Period • Calibration period: January 1994 to December 1999 • Both models do well simulating the measured data • Discrepancy in PP phosphorous results • SWAT model does better although both models do well with sediment

  14. Results – Flow and Sediment • Flow • Calibrations are quite good, both models capture trends • Models tend to over predict high flows and under predict low flows Flow • Sediment • Models do well with average loads, but tend to under predict high loadings • Some of this error can be attributed to flow error Sediment

  15. Results – Phosphorous • TDP • Both models do well with average loads, but tend to under predict high loads • Part of this error can be attributed to flow under prediction TDP • PP • SWAT2005 model does better than SWAT-VSA model • Interesting since PP is largely impacted by sediment, which is captured well by both models PP

  16. Outline SWAT2005 vs SWAT-VSA Calibration Corn analysis Conclusion Questions ?

  17. Land Use Management Analysis • Since SWAT-VSA uses a combination of land use and wetness class to determine HRUs, we can look into the impact of moving different land uses • In this analysis, we looked at the impact of moving corn to low runoff generating areas, i.e. low wetness classes

  18. Corn Analysis - Setup • SWAT-VSA • All corn HRUs are changed to either wetness class 1 or 2 • Turned corn wetness classes of 3 – 10 into hay or pasture • In order to keep total corn area constant, some hay and pasture wetness classes 1 and 2 were turned into corn • Meticulously kept track of each wetness class area as well as land use area • SWAT2005 • All corn was turned into either hay or pasture of the same soil type • Only thing that can really be done with SWAT in terms of land use

  19. SWAT2005 Model without Corn • Flow • % Difference = 0.23 • There is no difference because overall CN did not change • Sediment • % Difference = -33.5 • Peak sediment loads are nearly cut in half, shows the impact of corn on the sediment loading

  20. SWAT2005 Model without Corn • TDP • % Difference = -38.4 • Shows the large impact that corn has on TDP loading • PP • % Difference = -71 • large impact on PP is due to removal of corn as a direct source as well as the decrease in sediment loading

  21. SWAT-VSA Model Corn Analysis • Flow • % Difference = -0.07 • Does not change because overall wetness class areas do not change • Sediment • % Difference = -0.23 • Does not change because decrease in sediment loading from corn is balanced by the increase in sediment loading from hay and pasture

  22. SWAT-VSA Model Corn Analysis • TDP • % Difference = -27.5 • substantial decrease in peak loadings shows the impact of moving corn to areas of lower runoff • PP • % Difference = -49 • Since the overall sediment loadings do not change, this change in PP is directly due to moving corn areas

  23. Corn Analysis - conclusion • From the previous analysis, it is apparent that the location of corn areas has a significant impact on Phosphorous runoff • Analysis results make physical sense • This type of nutrient reduction would occur in the watershed if all corn is moved to low-runoff areas • Although this is a best case scenario in terms of nutrient reduction, it may not be entirely practical • Moving corn to low-runoff areas may also reduce corn yeild • Need to find some trade-off point

  24. Outline SWAT vs SWAT-VSA Calibration Corn analysis Conclusion Questions ?

  25. Conclusion • SWAT-VSA and SWAT 2005 Models produce similar results based on available calibration data for the large 1200 km2 Cannonsville watershed. • Flow distributions can have important implications for nutrient management • Management scenarios in SWAT-VSA can include specific nutrient placement based on flow distributions • SWAT-VSA will predict decreases in phosphorous transport when corn is placed mostly in dry areas.

  26. Outline SWAT vs SWAT-VSA Calibration Corn analysis Conclusion Questions ?

More Related