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Investigating Crop Yield and Water Quality Benefits of Drainage Water Recycling.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Investigating Crop Yield and Water Quality Benefits of Drainage Water Recycling./
作者:	Moursi, Hossam Abdelghani Abdelhalim.
面頁冊數:	1 online resource (209 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-02, Section: B.
Contained By:	Dissertations Abstracts International84-02B.
標題:	Reservoirs. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29228767click for full text (PQDT)
ISBN:	9798841528180

Investigating Crop Yield and Water Quality Benefits of Drainage Water Recycling.
Moursi, Hossam Abdelghani Abdelhalim.

Investigating Crop Yield and Water Quality Benefits of Drainage Water Recycling. - 1 online resource (209 pages)

Source: Dissertations Abstracts International, Volume: 84-02, Section: B.

Thesis (Ph.D.)--North Carolina State University, 2022.

Includes bibliographical references

Drainage water recycling (DWR) has been proposed to improve crop production by providing supplemental irrigation during the dry periods of growing season, and improve water quality by reducing downstream nutrient and sediment losses. Limited number of studies were conducted to investigate the performance of DWR. The objectives of this study were to: 1) experimentally evaluate the effect of DWR on reducing the export of nitrogen (N), phosphorous (P), and sediment loadings from agricultural fields to downstream surface water bodies; 2) experimentally quantify the effect of DWR on corn and soybean yields during 4 growing seasons with varying weather conditions; 3) enhance DRAINMOD model to simulate the hydrology and crop yield of DWR systems. Water quality and hydrology data were collected for two years (May 2019-April 2021) at a research site in eastern North Carolina. On average, the DWR reservoir retained 14% of received inflow. The reservoir significantly reduced nitrate-N(NO3-N), ammonium-N (NH4-N), and total N (TN) concentrations by 53%, 51%, and 40%, respectively. The mass loadings of NO3-N, NH4-N, and TN were also reduced by 59%, 56%, and 47%, respectively. Orthophosphate (OP) concentration was significantly reduced by 46%, while Total P (TP) concentration reduction was not statistically significant. The mass loadings of OP and TP were reduced by 52% and 30%, respectively, while particulate P load was not significantly different. Sediment concentration was significantly reduced by 86% and the sediment loading was also reduced by 87%. Two treatments were monitored at the same study site for 4 growing seasons (2018- 2021): DWR and control treatment (CT). The CT treatment was a non-irrigated field that was primarily drained by a surface drainage system. The DWR treatment had a subsurface drainage system that was used to drain the field during the wet periods of the growing season and subirrigated it during dry periods. DWR increased corn yields by 0.39 and 0.90 Mg ha-1 and soybean yields by 0.40 and 0.66 Mg ha-1 . DWR mainly increased crop yield by reducing drought stress during the critical crop growth stages through providing irrigation (5 to 73 mm). In addition, the smart drainage water management system implemented at the DWR treatment helped to store more water in the soil profile and reduce water outflow from the field. The amount of N and P recycled back to the DWR treatment through irrigation was not large enough to recommend reducing fertilizer application rates. DRAINMOD was enhanced to simulate the hydrology and crop yield of DWR systems as affected by weather conditions, soil type, crop rotation, reservoir size, and irrigation and drainage management. The expanded model; named DRAINMOD-DWR, has a new module that conducts a water balance of the storage reservoir and simulates the interaction between the reservoir and the field, irrigated from and/or draining into the reservoir. Three performance metrics were defined based on model predictions to quantify irrigation, crop yield, and water capture benefits of DWR. To demonstrate the new features of the model, DRAINMOD-DWR was applied to a hypothetical DWR system with continuous corn using a 50-year weather record in Eastern North Carolina, U.S.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798841528180Subjects--Topical Terms:

671697
Reservoirs.
Index Terms--Genre/Form:

542853
Electronic books.

Investigating Crop Yield and Water Quality Benefits of Drainage Water Recycling.
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245 1 0 $a Investigating Crop Yield and Water Quality Benefits of Drainage Water Recycling.
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300 $a 1 online resource (209 pages)
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500 $a Source: Dissertations Abstracts International, Volume: 84-02, Section: B.
500 $a Advisor: Poole, Chad; Richardson, Robert; Castro-Bolinaga, Celso; Chescheir, George; Youssef, Mohamed.
502 $a Thesis (Ph.D.)--North Carolina State University, 2022.
504 $a Includes bibliographical references
520 $a Drainage water recycling (DWR) has been proposed to improve crop production by providing supplemental irrigation during the dry periods of growing season, and improve water quality by reducing downstream nutrient and sediment losses. Limited number of studies were conducted to investigate the performance of DWR. The objectives of this study were to: 1) experimentally evaluate the effect of DWR on reducing the export of nitrogen (N), phosphorous (P), and sediment loadings from agricultural fields to downstream surface water bodies; 2) experimentally quantify the effect of DWR on corn and soybean yields during 4 growing seasons with varying weather conditions; 3) enhance DRAINMOD model to simulate the hydrology and crop yield of DWR systems. Water quality and hydrology data were collected for two years (May 2019-April 2021) at a research site in eastern North Carolina. On average, the DWR reservoir retained 14% of received inflow. The reservoir significantly reduced nitrate-N(NO3-N), ammonium-N (NH4-N), and total N (TN) concentrations by 53%, 51%, and 40%, respectively. The mass loadings of NO3-N, NH4-N, and TN were also reduced by 59%, 56%, and 47%, respectively. Orthophosphate (OP) concentration was significantly reduced by 46%, while Total P (TP) concentration reduction was not statistically significant. The mass loadings of OP and TP were reduced by 52% and 30%, respectively, while particulate P load was not significantly different. Sediment concentration was significantly reduced by 86% and the sediment loading was also reduced by 87%. Two treatments were monitored at the same study site for 4 growing seasons (2018- 2021): DWR and control treatment (CT). The CT treatment was a non-irrigated field that was primarily drained by a surface drainage system. The DWR treatment had a subsurface drainage system that was used to drain the field during the wet periods of the growing season and subirrigated it during dry periods. DWR increased corn yields by 0.39 and 0.90 Mg ha-1 and soybean yields by 0.40 and 0.66 Mg ha-1 . DWR mainly increased crop yield by reducing drought stress during the critical crop growth stages through providing irrigation (5 to 73 mm). In addition, the smart drainage water management system implemented at the DWR treatment helped to store more water in the soil profile and reduce water outflow from the field. The amount of N and P recycled back to the DWR treatment through irrigation was not large enough to recommend reducing fertilizer application rates. DRAINMOD was enhanced to simulate the hydrology and crop yield of DWR systems as affected by weather conditions, soil type, crop rotation, reservoir size, and irrigation and drainage management. The expanded model; named DRAINMOD-DWR, has a new module that conducts a water balance of the storage reservoir and simulates the interaction between the reservoir and the field, irrigated from and/or draining into the reservoir. Three performance metrics were defined based on model predictions to quantify irrigation, crop yield, and water capture benefits of DWR. To demonstrate the new features of the model, DRAINMOD-DWR was applied to a hypothetical DWR system with continuous corn using a 50-year weather record in Eastern North Carolina, U.S.
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650 4 $a Climate change. $2 bicssc $3 2079509
650 4 $a Agriculture. $3 518588
650 4 $a Water resources management. $3 794747
655 7 $a Electronic books. $2 lcsh $3 542853
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710 2 $a North Carolina State University. $3 1018772
773 0 $t Dissertations Abstracts International $g 84-02B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29228767 $z click for full text (PQDT)