HR: 0800h
AN: H41D-0447    [Abstracts]
TI: Hydrologic Impact Of Subsurface Drainage Of Agricultural Fields
AU: * Naz, B S
EM: bnaz@purdue.edu
AF: Department of Agronomy, 915 W. State Street Purdue University , West Lafayette, IN 47907-2054 United States
AU: Johannsen, C J
EM: johan@purdue.edu
AF: Department of Agronomy, 915 W. State Street Purdue University , West Lafayette, IN 47907-2054 United States
AU: Bowling, L C
EM: bowling@purdue.edu
AF: Department of Agronomy, 915 W. State Street Purdue University , West Lafayette, IN 47907-2054 United States
AB: Although subsurface drainage has benefited agricultural productions in many regions of the U.S., there are also concerns about the potential impacts of these systems on watershed hydrology and water quality. This study was focused on tile lines identification and hydrologic response of subsurface drainage systems for the Agronomy Center for Research and Education (ACRE), West Lafayette, Indiana and the Southeastern Purdue Agriculture Center (SEPAC) in southeastern, Indiana. The purpose of the study was to develop and evaluate a remote sensing methodology for automatic detection of tile lines from aerial photographs and to evaluate the Distributed Hydrology Soil-Vegetation Model (DHSVM) to analyze the hydrologic response of tile drained fields. A step-wise approach was developed to first use different image enhancement techniques to increase the visual distinction of tile lines from other details in the image. A new classification model was developed to identify locations of subsurface tiles using a decision tree classifier which compares the multiple data sets such as enhanced image data, land use class, soil drainage class, hydrologic group and surface slope. Accuracy assessment of the predicted tile map was done by comparing the locations of tile drains with existing historic maps and ground-truth data. The overall performance of decision tree classifier model coupled with other pre- and post- classification methods shows that this model can be a very effective tool in identifying tile lines from aerial photographs over large areas of land. Once the tile map was created, the DHSVM was applied to ACRE and SEPAC respectively to see the hydrological impact of the subsurface drainage network. Observed data for 3-years (1998-2000) at ACRE and for 6-years (1993-1998) at SEPAC were used to calibrate and validate the model. The model was simulated for three scenarios: 1) baseline scenario (no tiles), 2) with known tile lines and 3) with tile lines created through automatic detection techniques using meteorological data for 14-years (1990-2004) and 15-years (1985-2000) at both sites respectively. In general, hydrologic outputs predicted by the model were acceptable. In addition to hydrologic response of subsurface drainage network, the model simulation can also be helpful to determine the required accuracy of predicted tile location maps for analyzing hydrologic responses of agricultural fields.
DE: 1218 Mass balance (0762, 1223, 1631, 1836, 1843, 3010, 3322, 4532)
DE: 1631 Land/atmosphere interactions (1218, 1843, 3322)
DE: 1800 HYDROLOGY
DE: 3322 Land/atmosphere interactions (1218, 1631, 1843)
SC: Hydrology [H]
MN: Fall Meeting 2005