Field performance assessment and calibration of multi-depth AquaCheck capacitance-based soil moisture probes under permanent pasture for hill country soils

Hajdu, Istvan; Yule, Ian; Bretherton, Mike; Singh, Ranvir; Hedley, C. B.

doi:10.1016/j.agwat.2019.03.002

Cited by 23 publications

(25 citation statements)

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“…Soil water data were field calibrated as discussed by Hajdu, Yule, Bretherton, Singh, and Hedley (2019). In short, gravimetric soil samples were taken from each soil layer (0–10, 10–20, 20–40, 40–60, and 60–80 cm) using a hand‐auger (7‐cm diameter), while calibration readings were recorded simultaneously at the corresponding soil layers.…”

Section: Methodsmentioning

confidence: 99%

Narrow rows and high maize plant population improve water use and grain yield under conservation agriculture

Haarhoff

Swanepoel

2020

Agronomy Journal

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The relationship between maize (Zea mays L.) population density and grain yield is influenced by soil and crop management strategies, including Conservation Agriculture (CA). However, little is known about the response of maize grain yield to varying plant population and/or row spacing under CA. A 3-yr study was conducted under CA to evaluate the effects of plant population and row spacing on maize grain yield, plant available soil water, and soil temperature. Plant populations ranging from 40,000 to 80,000 plants ha −1 were evaluated at three row spacings (0.5, 0.76, and 1.0 m). The response of maize grain yield to plant population was highly variable between seasons: it was not affected by plant population in the season with the highest early season rainfall but increased with increasing plant population in the driest season and in the season with well-distributed, near average rainfall. Higher plant populations resulted in lower soil water levels, presumably due to greater water extraction. Plant population affected soil water availability in the 20-to 80-cm soil layer in Season 2, while plant population affected soil water availability at all soil layers except the 10-to 20-and 60-to 80-cm soil layers in Season 3. Rapid maize leaf-canopy closure provided by increased plant population and narrower row spacing is critical to adequately utilize the benefits associated with CA.Abbreviations: CA, conservation agriculture; DAE, days after emergence; FWC, field water capacity; PPAW, percent plant available water; PWP, permanent wilting point. How to cite this article:Haarhoff SJ, Swanepoel PA. Narrow rows and high maize plant population improve water use and grain yield under conservation agriculture. Agronomy Journal. 2020;112:921-931.

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Section: Methodsmentioning

confidence: 99%

Narrow rows and high maize plant population improve water use and grain yield under conservation agriculture

Haarhoff

Swanepoel

2020

Agronomy Journal

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“…PTSMN was deployed to capture spatiotemporal soil moisture trends on various topographical positions distributed over a 13.8 km2 area. The network is composed of twenty multi-sensor probes that were calibrated to the site-specific soils (Hajdu et al, 2019). The sensors provide readings at four consecutive depths down to 0.43 m.…”

Section: A42 Ptsmnmentioning

confidence: 99%

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Dorigo

2021

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In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort, funded by the European Space Agency, to serve as a centralised data hosting facility for globally available in situ soil moisture measurements (Dorigo et al., 2011b, a). The ISMN brings together in situ soil moisture measurements collected and freely shared by a multitude of organisations, harmonizes them in terms of units and sampling rates, applies advanced quality control, and stores them in a Ground-based soil moisture measurements of land surface variables are indispensable in the process of developing, validating, and advancing spatially contiguous data sets derived from satellites or models (Loew et al., 2017;Gruber et al., 2020). Although the first systematic measurements of soil moisture started well before the satellite era in the former Soviet Union to support agricultural decision making (Robock et al., 2000), it was not until the early 2000s that soil moisture monitoring networks started being widely established as part of hydrological and meteorological observing capacities. Particularly, the launch of the Soil Moisture Ocean Salinity (SMOS) mission of the European Space Agency (ESA) in 2009 (Kerr et al., 2016), and the launch of the Soil Moisture Active Passive (SMAP) mission of the National Aeronautics and Space Administration (NASA) in 2015 (Entekhabi et al., 2010), boosted the establishment of new research networks (Colliander et al., 2017).While all networks are a valuable asset for assessing the skill of soil moisture products under various conditions and scales, their usage is hampered by the diversity of sensors, data formats, quality control, and accessibility mechanisms. The need of bringing together and harmonising available soil moisture data was recognised by the international soil moisture community and expedited by the Global Energy and Water cycle Exchanges (GEWEX) project of the World Climate Research Programme (WCRP) with support of the Commission on Earth Observation Satellites (CEOS), the Global Climate Observing System (GCOS), and the Group on Earth Observation (GEO). In the advent of the SMOS mission, ESA decided to provide the financial impetus to establish a global reference database of in situ soil moisture measurements for the purpose of satellite product development and validation. As a result, the International Soil Moisture Network (ISMN) went online in 2010 (Dorigo et al., 2011b, a).The primary objective of the ISMN is to collect in situ soil moisture data sets shared by various data organisations on a voluntary basis and make them available in a harmonized format through a centralised free and open web portal (ismn.earth).While 10 years after its launch the core objective of the ISMN remains valid, its functionality has expanded since then. This new functionality includes the integration of advanced quality control methods (Dorigo et al., 2013), the provision of additional metadata and ancillary variables (e.g., precipitation, soil and air temperature), ongoing automation, the ...

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“…Suponen una herramienta importante que facilita la toma de decisiones en la programación del riego, tales como determinar la cantidad de agua y el momento de aplicarla. Así, se evitan pérdidas excesivas por percolación profunda o por escorrentía para reducir los impactos ambientales o bien evitar aplicar una cantidad insuficiente y optimizar la producción [4].…”

Section: Congreso Ibérico De Agroingeniería X Congresso Ibérico De unclassified

Determinación del consumo de agua en lechuga (Lactuca Sativa L CV Neruda) mediante lisimetría de pesada compacta y sondas de humedad

López¹,

Méndez²,

Oates³

et al. 2019

Congreso Ibérico De Agroingeniería

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Resumen: Se desarrollaron los ensayos en una parcela experimental de la Escuela Politécnica Superior de Orihuela (EPSO) de la Universidad Miguel Hernández de Elche (UMH). En la citada parcela se instaló un sistema de riego localizado con cuatro sectores para aplicar cuatro tratamientos diferenciales de fertilización. Se escogió como cultivo de control la lechuga (Lactuca Sativa L Neruda). Se evaluaron las estrategias culturales más adecuadas en el manejo del cultivo en la parcela experimental a partir de los datos periódicos proporcionados por una estación meteorológica próxima y los datos de sensores de humedad del suelo. En uno de los tratamientos se hizo el seguimiento del riego mediante la instalación de un lisímetro de pesada compacto enterrado. La metodología utilizada para la medida simultánea del balance hídrico se ha contrastado y es válida. Es necesario contrastar con más campañas.Palabras clave: sostenibilidad, ahorro de agua, sensores de bajo coste, programación de riego, horticultura IntroducciónEl uso eficiente del agua de riego disponible es fundamental para conseguir la mejora de la gestión de los recursos hídricos en agricultura [1]. El conocimiento del consumo de agua por los cultivos y el manejo adecuado del riego son factores determinantes. El agua aplicada en exceso o en momentos inadecuados puede provocar efectos no deseados. Un manejo eficiente del agua empleada en riego se fundamenta en la elección del sistema de riego adecuado, la modernización de los regadíos, el ajuste de la dosis de riego a las necesidades reales del cultivo en cada momento y evitar las pérdidas de agua por escorrentía e infiltración fuera del alcance de las raíces. Las mejoras en las técnicas de programación de riego no sólo producen un ahorro del agua, sino que también reduce el riesgo del lavado de nutrientes y minimiza el impacto de la agricultura en las aguas subterráneas. Adicionalmente se asegura el correcto desarrollo del cultivo [2].La programación del riego se basa principalmente en la determinación de las necesidades hídricas de los cultivos, el conocimiento del estado hídrico de las plantas y la determinación del agua del suelo disponible para el cultivo. El nivel de agua en suelo se puede medir mediante el uso de sensores de humedad instalados de forma apropiada en zonas representativas del cultivo permitiendo observar y estimar la distribución de la humedad y determinar si el riego es excesivo o deficitario [3].

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Field performance assessment and calibration of multi-depth AquaCheck capacitance-based soil moisture probes under permanent pasture for hill country soils

Cited by 23 publications

References 54 publications

Narrow rows and high maize plant population improve water use and grain yield under conservation agriculture

Narrow rows and high maize plant population improve water use and grain yield under conservation agriculture

Reply on RC1

Determinación del consumo de agua en lechuga (Lactuca Sativa L CV Neruda) mediante lisimetría de pesada compacta y sondas de humedad

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