Developing irrigation water conservation strategies for hybrid bermudagrass using an evapotranspiration-based smart irrigation controller in inland southern California
A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during...
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| Autor*in: |
Haghverdi, Amir [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Strain rate sensitivity of unequal grained nano-multilayers - 2011, an international journal, Amsterdam |
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| Übergeordnetes Werk: |
volume:245 ; year:2021 ; day:28 ; month:02 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.agwat.2020.106586 |
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ELV052632784 |
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| 245 | 1 | 0 | |a Developing irrigation water conservation strategies for hybrid bermudagrass using an evapotranspiration-based smart irrigation controller in inland southern California |
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| 520 | |a A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. | ||
| 520 | |a A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. | ||
| 650 | 7 | |a Urban irrigation |2 Elsevier | |
| 650 | 7 | |a Soil moisture sensor |2 Elsevier | |
| 650 | 7 | |a Evapotranspiration |2 Elsevier | |
| 650 | 7 | |a Water conservation |2 Elsevier | |
| 650 | 7 | |a Turfgrass water response function |2 Elsevier | |
| 650 | 7 | |a NDVI |2 Elsevier | |
| 650 | 7 | |a Weather-based irrigation controller |2 Elsevier | |
| 700 | 1 | |a Singh, Amninder |4 oth | |
| 700 | 1 | |a Sapkota, Anish |4 oth | |
| 700 | 1 | |a Reiter, Maggie |4 oth | |
| 700 | 1 | |a Ghodsi, Somayeh |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |t Strain rate sensitivity of unequal grained nano-multilayers |d 2011 |d an international journal |g Amsterdam |w (DE-627)ELV020959745 |
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10.1016/j.agwat.2020.106586 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001378.pica (DE-627)ELV052632784 (ELSEVIER)S0378-3774(20)32133-8 DE-627 ger DE-627 rakwb eng 600 VZ 670 VZ 530 VZ 570 VZ Haghverdi, Amir verfasserin aut Developing irrigation water conservation strategies for hybrid bermudagrass using an evapotranspiration-based smart irrigation controller in inland southern California 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. Urban irrigation Elsevier Soil moisture sensor Elsevier Evapotranspiration Elsevier Water conservation Elsevier Turfgrass water response function Elsevier NDVI Elsevier Weather-based irrigation controller Elsevier Singh, Amninder oth Sapkota, Anish oth Reiter, Maggie oth Ghodsi, Somayeh oth Enthalten in Elsevier Strain rate sensitivity of unequal grained nano-multilayers 2011 an international journal Amsterdam (DE-627)ELV020959745 volume:245 year:2021 day:28 month:02 pages:0 https://doi.org/10.1016/j.agwat.2020.106586 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_22 GBV_ILN_60 GBV_ILN_176 GBV_ILN_216 AR 245 2021 28 0228 0 |
| spelling |
10.1016/j.agwat.2020.106586 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001378.pica (DE-627)ELV052632784 (ELSEVIER)S0378-3774(20)32133-8 DE-627 ger DE-627 rakwb eng 600 VZ 670 VZ 530 VZ 570 VZ Haghverdi, Amir verfasserin aut Developing irrigation water conservation strategies for hybrid bermudagrass using an evapotranspiration-based smart irrigation controller in inland southern California 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. Urban irrigation Elsevier Soil moisture sensor Elsevier Evapotranspiration Elsevier Water conservation Elsevier Turfgrass water response function Elsevier NDVI Elsevier Weather-based irrigation controller Elsevier Singh, Amninder oth Sapkota, Anish oth Reiter, Maggie oth Ghodsi, Somayeh oth Enthalten in Elsevier Strain rate sensitivity of unequal grained nano-multilayers 2011 an international journal Amsterdam (DE-627)ELV020959745 volume:245 year:2021 day:28 month:02 pages:0 https://doi.org/10.1016/j.agwat.2020.106586 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_22 GBV_ILN_60 GBV_ILN_176 GBV_ILN_216 AR 245 2021 28 0228 0 |
| allfields_unstemmed |
10.1016/j.agwat.2020.106586 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001378.pica (DE-627)ELV052632784 (ELSEVIER)S0378-3774(20)32133-8 DE-627 ger DE-627 rakwb eng 600 VZ 670 VZ 530 VZ 570 VZ Haghverdi, Amir verfasserin aut Developing irrigation water conservation strategies for hybrid bermudagrass using an evapotranspiration-based smart irrigation controller in inland southern California 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. Urban irrigation Elsevier Soil moisture sensor Elsevier Evapotranspiration Elsevier Water conservation Elsevier Turfgrass water response function Elsevier NDVI Elsevier Weather-based irrigation controller Elsevier Singh, Amninder oth Sapkota, Anish oth Reiter, Maggie oth Ghodsi, Somayeh oth Enthalten in Elsevier Strain rate sensitivity of unequal grained nano-multilayers 2011 an international journal Amsterdam (DE-627)ELV020959745 volume:245 year:2021 day:28 month:02 pages:0 https://doi.org/10.1016/j.agwat.2020.106586 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_22 GBV_ILN_60 GBV_ILN_176 GBV_ILN_216 AR 245 2021 28 0228 0 |
| allfieldsGer |
10.1016/j.agwat.2020.106586 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001378.pica (DE-627)ELV052632784 (ELSEVIER)S0378-3774(20)32133-8 DE-627 ger DE-627 rakwb eng 600 VZ 670 VZ 530 VZ 570 VZ Haghverdi, Amir verfasserin aut Developing irrigation water conservation strategies for hybrid bermudagrass using an evapotranspiration-based smart irrigation controller in inland southern California 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. Urban irrigation Elsevier Soil moisture sensor Elsevier Evapotranspiration Elsevier Water conservation Elsevier Turfgrass water response function Elsevier NDVI Elsevier Weather-based irrigation controller Elsevier Singh, Amninder oth Sapkota, Anish oth Reiter, Maggie oth Ghodsi, Somayeh oth Enthalten in Elsevier Strain rate sensitivity of unequal grained nano-multilayers 2011 an international journal Amsterdam (DE-627)ELV020959745 volume:245 year:2021 day:28 month:02 pages:0 https://doi.org/10.1016/j.agwat.2020.106586 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_22 GBV_ILN_60 GBV_ILN_176 GBV_ILN_216 AR 245 2021 28 0228 0 |
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10.1016/j.agwat.2020.106586 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001378.pica (DE-627)ELV052632784 (ELSEVIER)S0378-3774(20)32133-8 DE-627 ger DE-627 rakwb eng 600 VZ 670 VZ 530 VZ 570 VZ Haghverdi, Amir verfasserin aut Developing irrigation water conservation strategies for hybrid bermudagrass using an evapotranspiration-based smart irrigation controller in inland southern California 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. 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A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. |
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A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand. |
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10.1016/j.agwat.2020.106586 |
| up_date |
2024-07-06T16:42:20.481Z |
| _version_ |
1803848662891102208 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV052632784</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626033529.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">210910s2021 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.agwat.2020.106586</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001378.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV052632784</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0378-3774(20)32133-8</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">600</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">670</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">530</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Haghverdi, Amir</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Developing irrigation water conservation strategies for hybrid bermudagrass using an evapotranspiration-based smart irrigation controller in inland southern California</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021transfer abstract</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">A three-year (2017–2019) irrigation research trial was conducted to evaluate the response of hybrid bermudagrass to a wide range of irrigation scenarios and assess the efficacy of Weathermatic Evapotranspiration-based (ET-based) smart controller for autonomous landscape irrigation management during dry seasons in inland southern California. The irrigation levels applied throughout the experiment ranged between 39% and 103% reference ET (ETo) and the irrigation frequency restrictions imposed were 3, 5 and 7 d/wk. Normalized difference vegetation index (NDVI) data were continuously collected to evaluate the response of hybrid bermudagrass [‘Tifgreen’ Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] to irrigation treatments. Plots were also visually assessed and scaled from 1 (dead plot) to 9 (ideal turfgrass) following the National Turfgrass Evaluation Program (NTEP) standards. Turfgrass water response function (TWRF) was introduced as a statistical regression model to estimate hybrid bermudagrass quality response (NDVI values) to irrigation levels over time. In the years 2018 (p < 0.01) and 2019 (p < 0.001), the irrigation levels showed a significant effect on NDVI values. The irrigation frequency restrictions showed no significant impact on NDVI in any of the years. We observed a high correlation (r = 0.84) between visual rating (VR) and NDVI data. The TWRF shows a high accuracy (RMSE = 0.047, no units), and estimated NDVI values were highly correlated (r = 0.89) with measured NDVI values. A comparison between the California irrigation management information system (CIMIS) reference evapotranspiration (ETo) versus temperature-based ETo estimations by the controller revealed the smart controller on average over-irrigated by 12%, 2% and 3% throughout the experimental periods in 2017, 2018 and 2019, respectively. A long term (34 years) analysis using CIMIS ETo data and TWRF model revealed 75% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in the inland southern California semiarid climate for months with high irrigation demand (i.e., May to November). The results also showed that hybrid bermudagrass could withstand more severe deficit irrigation treatments for shorter periods depending on ETo demand.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Urban irrigation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Soil moisture sensor</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Evapotranspiration</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Water conservation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Turfgrass water response function</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">NDVI</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Weather-based irrigation controller</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Singh, Amninder</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Sapkota, Anish</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Reiter, Maggie</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ghodsi, Somayeh</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="t">Strain rate sensitivity of unequal grained nano-multilayers</subfield><subfield code="d">2011</subfield><subfield code="d">an international journal</subfield><subfield code="g">Amsterdam</subfield><subfield code="w">(DE-627)ELV020959745</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:245</subfield><subfield code="g">year:2021</subfield><subfield code="g">day:28</subfield><subfield code="g">month:02</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.agwat.2020.106586</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_176</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_216</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">245</subfield><subfield code="j">2021</subfield><subfield code="b">28</subfield><subfield code="c">0228</subfield><subfield code="h">0</subfield></datafield></record></collection>
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| score |
7.400262 |