Nebraska Agricultural Water Management Demonstration Network (NAWMDN): Integrating Research and Extension/Outreach

Irmak, Suat; Rees, Jennifer; Zoubek, Gary L.; DeWalle, B. S. van; Rathje, William R.; DeBuhr, R.; Leininger, D.; Siekman, Darrel D.; Schneider, J.; Christiansen, Ashley

doi:10.13031/2013.32066

Cited by 39 publications

(17 citation statements)

References 10 publications

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“…However, a significant gap still exists in fully reconciling differences between point observations with remote sensing [12] given the natural heterogeneity [13] and spatial organization SWC fields exhibit [14]. With the unresolved issues between point sensors and remote sensing, and critical spatiotemporal gaps from remote sensing observations, production agriculture has typically relied on direct insertion point based SWC monitoring technologies to aid in decision-making [15,16], albeit with recent acceptance of indirect sensors [17]. A key weakness of direct insertion point sensors in production agriculture is often logistical, as routine management practices of planting, soil cultivation, and harvest make installation and maintenance of point sensor networks costly and time consuming to continuously manage.…”

Section: Introductionmentioning

confidence: 99%

Using Cosmic-Ray Neutron Probes to Monitor Landscape Scale Soil Water Content in Mixed Land Use Agricultural Systems

Franz

Wahbi

Vreugdenhil

et al. 2016

Applied and Environmental Soil Science

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With an ever-increasing demand for natural resources and the societal need to understand and predict natural disasters, soil water content (SWC) observations remain a critical variable to monitor in order to optimally allocate resources, establish early warning systems, and improve weather forecasts. However, routine agricultural production practices of soil cultivation, planting, and harvest make the operation and maintenance of direct contact point sensors for long-term monitoring challenging. In this work, we explore the use of the newly established Cosmic-Ray Neutron Probe (CRNP) and method to monitor landscape average SWC in a mixed agricultural land use system in northeast Austria. The calibrated CRNP landscape SWC values compare well against an independent in situ SWC probe network (MAE = 0.0286 m 3 /m 3 ) given the challenge of continuous in situ monitoring from probes across a heterogeneous agricultural landscape. The ability of the CRNP to provide real-time and accurate landscape SWC measurements makes it an ideal method for establishing long-term monitoring sites in agricultural ecosystems to aid in agricultural water and nutrient management decisions at the small tract of land scale as well as aiding in management decisions at larger scales.

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Section: Introductionmentioning

confidence: 99%

Using Cosmic-Ray Neutron Probes to Monitor Landscape Scale Soil Water Content in Mixed Land Use Agricultural Systems

Franz

Wahbi

Vreugdenhil

et al. 2016

Applied and Environmental Soil Science

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“…A similar conclusion was reached in Oklahoma where farmers and ranchers did not want to pay significant fees to have access to weather information beyond raw data [44]. Nevertheless, technology transfer of agricultural water management programs from weather networks via extension and outreach activities remains a high priority in Nebraska [45] and elsewhere. The occurrence of drought events remains a driver for the use and adoption of "smart" irrigation controllers based on ET [46] and in the adoption of information generated from weather networks.…”

Section: Introductionmentioning

confidence: 71%

“…While our research approach is specific to our location, climate and crop, we believe that our method has general applications to other regions and crops. Our goal was to identify options to improve the successful adoption of ET-based irrigation as a management tool [45,48]. Our purpose is not to evaluate specific advantages or disadvantages of any particular irrigation system for cotton production in the THP.…”

Section: Introductionmentioning

confidence: 99%

Irrigation Analysis Based on Long-Term Weather Data

Mahan

Lascano

2016

Agriculture

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Irrigation management is based upon delivery of water to a crop in the correct amount and time, and the crop's water need is determined by calculating evapotranspiration (ET) using weather data. In 1994, an ET-network was established in the Texas High Plains to manage irrigation on a regional scale. Though producers used the ET-network, by 2010 public access was discontinued. Why did producers allow a valuable irrigation-management tool to be eliminated? Our objective was to analyze the effect of declining well capacities on the usefulness of cotton ET (ET c ) for irrigation. Thirty years of daily ET c data were used to compare irrigation demand vs. irrigation responses at four locations, analyzed for multiple years and range of well capacities for three irrigation-intervals. Results indicated that when well capacities declined to the point that over-irrigation was not possible, the lower well capacities reduced the value of ET c in terms of the number of irrigations and total amount of water applied. At well capacities <1514 L·min −1 the fraction of irrigations for which ET c information was used to determine the irrigation amount was <35% across years and irrigation intervals. The value of an ET c -based irrigation may fall into disuse when irrigation-water supplies decline.

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“…This WD-3-WET-5Y TDR type soil water potential sensor can simultaneously measure volumetric water content (VWM), electric conductivity (EC) and temperature of the soil. Furthermore, this sensor is rated IP68; this rating means protection from contact with harmful dust and immersion in water with a depth of more than 1 m. Currently for the WSN, the soil water potential seems to be the most suitable measurement item whose aim is irrigation control [10]. For measuring the water potential in soil, it is necessary to measure it at different points in a field, because soil moisture varies even within the same field.…”

Section: Object Fields and Methodsmentioning

confidence: 99%

A Wireless Sensor Network for Growth Environment Measurement and Multi-Band Optical Sensing to Diagnose Tree Vigor

Kameoka

Isoda

Hashimoto

et al. 2017

Sensors

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We have tried to develop the guidance system for farmers to cultivate using various phenological indices. As the sensing part of this system, we deployed a new Wireless Sensor Network (WSN). This system uses the 920 MHz radio wave based on the Wireless Smart Utility Network that enables long-range wireless communication. In addition, the data acquired by the WSN were standardized for the advanced web service interoperability. By using these standardized data, we can create a web service that offers various kinds of phenological indices as secondary information to the farmers in the field. We have also established the field management system using thermal image, fluorescent and X-ray fluorescent methods, which enable the nondestructive, chemical-free, simple, and rapid measurement of fruits or trees. We can get the information about the transpiration of plants through a thermal image. The fluorescence sensor gives us information, such as nitrate balance index (NBI), that shows the nitrate balance inside the leaf, chlorophyll content, flavonol content and anthocyanin content. These methods allow one to quickly check the health of trees and find ways to improve the tree vigor of weak ones. Furthermore, the fluorescent x-ray sensor has the possibility to quantify the loss of minerals necessary for fruit growth.

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Nebraska Agricultural Water Management Demonstration Network (NAWMDN): Integrating Research and Extension/Outreach

Cited by 39 publications

References 10 publications

Using Cosmic-Ray Neutron Probes to Monitor Landscape Scale Soil Water Content in Mixed Land Use Agricultural Systems

Using Cosmic-Ray Neutron Probes to Monitor Landscape Scale Soil Water Content in Mixed Land Use Agricultural Systems

Irrigation Analysis Based on Long-Term Weather Data

A Wireless Sensor Network for Growth Environment Measurement and Multi-Band Optical Sensing to Diagnose Tree Vigor

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