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A review on the quantification of soil water balance components as a basis for agricultural water management with a focus on weighing lysimeters and soil water sensors / Ein Überblick über die Ermittlung von Wasserhaushaltsgrößen als Basis für die landeskulturelle Wasserwirtschaft mit Fokus auf Lysimeter und Bodenwassersensoren Cover

A review on the quantification of soil water balance components as a basis for agricultural water management with a focus on weighing lysimeters and soil water sensors / Ein Überblick über die Ermittlung von Wasserhaushaltsgrößen als Basis für die landeskulturelle Wasserwirtschaft mit Fokus auf Lysimeter und Bodenwassersensoren

By: Reinhard Nolz  
Open Access
|Dec 2016

Abstract

Knowing the components of a soil water balance—for example, evapotranspiration, soil water content, and precipitation—is the basis for agricultural water management. Weighing lysimeters and soil water sensors are commonly used to quantify these components. Data can be used to validate common models to estimate evapotranspiration based on meteorological data, for instance. As every measurement device has its own characteristics, it is helpful to assess and improve the performance of a system to obtain best possible data. Recent developments in the processing of lysimeter data allow determining both evapotranspiration and precipitation directly from lysimeter data. Resulting datasets are characterized by a proper accuracy, completeness, and a high temporal resolution. Soil water sensors usually measure a physical property that is related to soil water content or matric potential via a specific calibration function. Hence, measurement accuracy depends not only on this calibration but also on basic physical principles and material properties. Knowing the performance of a device is, therefore, essential for the selection of an adequate sensor arrangement and truthful data interpretation. Advanced soil water monitoring sites combine different sensor types that are integrated into a wireless network to enable real-time data availability and provide a basis for large-scale monitoring.

DOI: https://doi.org/10.1515/boku-2016-0012 | Journal eISSN: 2719-5430 | Journal ISSN: 0006-5471
Language: English
Page range: 133 - 144
Submitted on: Jun 6, 2016
Accepted on: Jul 28, 2016
Published on: Dec 2, 2016
Published by: Universität für Bodenkultur Wien
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2016 Reinhard Nolz, published by Universität für Bodenkultur Wien
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.