Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management
Irrigated turfgrass is a major crop in urban areas of the drought-stricken Western United States. A considerable proportion of irrigation water is wasted through the use of conventional sprinkler systems. While smart sprinkler systems have made progress in reducing temporal mis-applications, more re...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Agronomy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4395/13/5/1267 |
| _version_ | 1797601499235221504 |
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| author | Ruth Kerry Ben Ingram Keegan Hammond Samantha R. Shumate David Gunther Ryan R. Jensen Steve Schill Neil C. Hansen Bryan G. Hopkins |
| author_facet | Ruth Kerry Ben Ingram Keegan Hammond Samantha R. Shumate David Gunther Ryan R. Jensen Steve Schill Neil C. Hansen Bryan G. Hopkins |
| author_sort | Ruth Kerry |
| collection | DOAJ |
| description | Irrigated turfgrass is a major crop in urban areas of the drought-stricken Western United States. A considerable proportion of irrigation water is wasted through the use of conventional sprinkler systems. While smart sprinkler systems have made progress in reducing temporal mis-applications, more research is needed to determine the most appropriate variables for accurately and cost-effectively determining spatial zones for irrigation application. This research uses data from ground and drone surveys of two large sports fields. Surveys were conducted pre-, within and towards the end of the irrigation season to determine spatial irrigation zones. Principal components analysis and k-means classification were used to develop zones using several variables individually and combined. The errors associated with uniform irrigation and different configurations of spatial zones are assessed to determine comparative improvements in irrigation efficiency afforded by spatial irrigation zones. A determination is also made as to whether the spatial zones can be temporally static or need to be re-determined periodically. Results suggest that zones based on spatial soil moisture surveys and simple observations of whether the grass felt wet or dry are better than those based on NDVI, other variables and several variables in combination. In addition, due to the temporal variations observed in spatial patterns, ideally zones should be re-evaluated periodically. However, a less labor-intensive solution is to determine temporally static zones based on patterns in soil moisture averaged from several surveys. Of particular importance are the spatial patterns observed prior to the start of the irrigation season as they reflect more temporally stable variation that relates to soil texture and topography rather than irrigation management. |
| first_indexed | 2024-03-11T04:01:35Z |
| format | Article |
| id | doaj.art-710851e628bf44d2b22f5046db8d07bf |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-11T04:01:35Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-710851e628bf44d2b22f5046db8d07bf2023-11-18T00:05:36ZengMDPI AGAgronomy2073-43952023-04-01135126710.3390/agronomy13051267Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation ManagementRuth Kerry0Ben Ingram1Keegan Hammond2Samantha R. Shumate3David Gunther4Ryan R. Jensen5Steve Schill6Neil C. Hansen7Bryan G. Hopkins8Department of Geography, Brigham Young University, Provo, UT 84602, USASchool of Water, Energy and Environment, Cranfield University, Cranfield, Bedfordshire MK43 0AL, UKDepartment of Plant and Wildlife Sciences, Brigham Young University, Provo, UT 84602, USADepartment of Plant and Wildlife Sciences, Brigham Young University, Provo, UT 84602, USADepartment of Geography, Brigham Young University, Provo, UT 84602, USADepartment of Geography, Brigham Young University, Provo, UT 84602, USADepartment of Geography, Brigham Young University, Provo, UT 84602, USADepartment of Plant and Wildlife Sciences, Brigham Young University, Provo, UT 84602, USADepartment of Plant and Wildlife Sciences, Brigham Young University, Provo, UT 84602, USAIrrigated turfgrass is a major crop in urban areas of the drought-stricken Western United States. A considerable proportion of irrigation water is wasted through the use of conventional sprinkler systems. While smart sprinkler systems have made progress in reducing temporal mis-applications, more research is needed to determine the most appropriate variables for accurately and cost-effectively determining spatial zones for irrigation application. This research uses data from ground and drone surveys of two large sports fields. Surveys were conducted pre-, within and towards the end of the irrigation season to determine spatial irrigation zones. Principal components analysis and k-means classification were used to develop zones using several variables individually and combined. The errors associated with uniform irrigation and different configurations of spatial zones are assessed to determine comparative improvements in irrigation efficiency afforded by spatial irrigation zones. A determination is also made as to whether the spatial zones can be temporally static or need to be re-determined periodically. Results suggest that zones based on spatial soil moisture surveys and simple observations of whether the grass felt wet or dry are better than those based on NDVI, other variables and several variables in combination. In addition, due to the temporal variations observed in spatial patterns, ideally zones should be re-evaluated periodically. However, a less labor-intensive solution is to determine temporally static zones based on patterns in soil moisture averaged from several surveys. Of particular importance are the spatial patterns observed prior to the start of the irrigation season as they reflect more temporally stable variation that relates to soil texture and topography rather than irrigation management.https://www.mdpi.com/2073-4395/13/5/1267turfgrassirrigationmanagement zonessoil moistureNDVI |
| spellingShingle | Ruth Kerry Ben Ingram Keegan Hammond Samantha R. Shumate David Gunther Ryan R. Jensen Steve Schill Neil C. Hansen Bryan G. Hopkins Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management Agronomy turfgrass irrigation management zones soil moisture NDVI |
| title | Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management |
| title_full | Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management |
| title_fullStr | Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management |
| title_full_unstemmed | Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management |
| title_short | Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management |
| title_sort | spatial analysis of soil moisture and turfgrass health to determine zones for spatially variable irrigation management |
| topic | turfgrass irrigation management zones soil moisture NDVI |
| url | https://www.mdpi.com/2073-4395/13/5/1267 |
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