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Impact of turfgrass systems on the n...

Zwierschke, Kerry Hughes.

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Impact of turfgrass systems on the nutrient status of surface water, and ground water.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Impact of turfgrass systems on the nutrient status of surface water, and ground water./
作者:	Zwierschke, Kerry Hughes.
面頁冊數:	387 p.
附註:	Source: Dissertation Abstracts International, Volume: 70-09, Section: B, page: 5645.
Contained By:	Dissertation Abstracts International70-09B.
標題:	Agriculture, Horticulture. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3376073
ISBN:	9781109388374

Impact of turfgrass systems on the nutrient status of surface water, and ground water.
Zwierschke, Kerry Hughes.

Impact of turfgrass systems on the nutrient status of surface water, and ground water. - 387 p.

Source: Dissertation Abstracts International, Volume: 70-09, Section: B, page: 5645.

Thesis (Ph.D.)--The Ohio State University, 2009.

Turfgrass systems require large inputs of fertilizers and pesticides that can impact surface water, ground water, and soil quality. Water quality and hydrologic data were collected at Morris Williams Municipal Golf Course in Austin, Texas, between 1998 and 2003. The data were analyzed, illustrating the application of time series analysis to hydrological data sets. Time series analyses were used to assess the dependence of nutrient concentrations in drainage and surface water on climate and management factors.

ISBN: 9781109388374Subjects--Topical Terms:

1017832
Agriculture, Horticulture.

Impact of turfgrass systems on the nutrient status of surface water, and ground water.
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245 1 0 $a Impact of turfgrass systems on the nutrient status of surface water, and ground water.
300 $a 387 p.
500 $a Source: Dissertation Abstracts International, Volume: 70-09, Section: B, page: 5645.
500 $a Adviser: Ann D. Christy.
502 $a Thesis (Ph.D.)--The Ohio State University, 2009.
520 $a Turfgrass systems require large inputs of fertilizers and pesticides that can impact surface water, ground water, and soil quality. Water quality and hydrologic data were collected at Morris Williams Municipal Golf Course in Austin, Texas, between 1998 and 2003. The data were analyzed, illustrating the application of time series analysis to hydrological data sets. Time series analyses were used to assess the dependence of nutrient concentrations in drainage and surface water on climate and management factors.
520 $a The analysis of nutrient loads in drainage water and runoff from the site indicated that nitrate-N posed no significant threat to ground or surface water. Dissolved reactive phosphorus (DRP) concentrations in ground water were higher than values recorded for locations planted with agricultural crops. In-stream attenuation of DRP occurred, but there was still a net contribution of DRP to surface water. Management strategies to reduce DRP concentrations may be needed to protect surface and ground waters from the intensive application of fertilizers in turfgrass systems.
520 $a Calibration and validation of a modified SWAT model (SWAT-TGER) was conducted using runoff data collected from the study site. The model generally underestimated the volume of runoff for most rainfall events, especially small volume events. The SWAT-TGER predictions were not significantly different (p=0.05) from measured values when fewer than 5 days had elapsed between rain events and either the intensity was greater than 5 mm in 15 minutes or the rainfall event was greater than 30mm. It also overestimated the concentrations of nitrate-N in the runoff from the site. Runoff estimation efficiency (E = 0.65 to 0.73) and nitrate-N estimation efficiencies were, however, within values reported in the literature for similar studies.
520 $a SWAT currently incorporates the curve number method in its simulation of runoff. The data from this site demonstrate that for some watersheds, the curve number's traditional definition of the initial abstraction value (0.2S) may not be appropriate. After testing a range of values, it was found that using an initial abstraction of 0.05S resulted in more accurate runoff predictions. Incorporating this method into SWAT may allow better simulation of runoff without the necessity of elevating curve numbers.
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