scholarly journals Characterizing Spatial Variability in Soil Water Content for Precision Irrigation Management

Agronomy ◽  
2018 ◽  
Vol 8 (5) ◽  
pp. 59 ◽  
Author(s):  
Alfonso de Lara ◽  
Raj Khosla ◽  
Louis Longchamps
Keyword(s):  
Spatial Variability ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Irrigation Management ◽  
Precision Irrigation

Characterizing spatial variability in soil water content for precision irrigation management

2017 ◽  
Vol 8 (2) ◽  
pp. 418-422 ◽  
Author(s):  
A. de Lara ◽  
R. Khosla ◽  
L. Longchamps
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Irrigation Management ◽  
Soil Electrical Conductivity ◽  
Field Scale ◽  
Management Zones ◽  
Mean Differences ◽  
Precision Irrigation

One among many challenges in implementing precision irrigation is the reliable characterization of the soil water content (SWC) across spatially variable fields. For this purpose, commercial retailers are employing apparent soil electrical conductivity (ECa) to create irrigation prescription maps. The accuracy of this method at the field scale has received little attention from the scientific community. Hence, the objective of this study was to characterize spatial distribution of soil water content at the field scale for the purpose of precision irrigation management. Results showed mean SWC to be different across ECa derived management zones, indicating that soil ECa was able to characterize mean differences in SWC across management zones.

scholarly journals Temporal stability of electrical conductivity in a sandy soil

2016 ◽  
Vol 30 (3) ◽  
pp. 349-357 ◽  
Author(s):  
Aura Pedrera-Parrilla ◽  
Eric C. Brevik ◽  
Juan V. Giráldez ◽  
Karl Vanderlinden
Keyword(s):  
Electrical Conductivity ◽  
Spatial Variability ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Precision Agriculture ◽  
Temporal Stability ◽  
Principal Component ◽  
Model Parameters ◽  
Soil Spatial Variability

Abstract Understanding of soil spatial variability is needed to delimit areas for precision agriculture. Electromagnetic induction sensors which measure the soil apparent electrical conductivity reflect soil spatial variability. The objectives of this work were to see if a temporally stable component could be found in electrical conductivity, and to see if temporal stability information acquired from several electrical conductivity surveys could be used to better interpret the results of concurrent surveys of electrical conductivity and soil water content. The experimental work was performed in a commercial rainfed olive grove of 6.7 ha in the ‘La Manga’ catchment in SW Spain. Several soil surveys provided gravimetric soil water content and electrical conductivity data. Soil electrical conductivity values were used to spatially delimit three areas in the grove, based on the first principal component, which represented the time-stable dominant spatial electrical conductivity pattern and explained 86% of the total electrical conductivity variance. Significant differences in clay, stone and soil water contents were detected between the three areas. Relationships between electrical conductivity and soil water content were modelled with an exponential model. Parameters from the model showed a strong effect of the first principal component on the relationship between soil water content and electrical conductivity. Overall temporal stability of electrical conductivity reflects soil properties and manifests itself in spatial patterns of soil water content.

scholarly journals The spatial variability of soil water content in a potato field before and after spray irrigation in arid northwestern China

2020 ◽  
Vol 20 (3) ◽  
pp. 860-870 ◽  
Author(s):  
Tao Li ◽  
Jian-feng Zhang ◽  
Si-yuan Xiong ◽  
Rui-xi Zhang
Keyword(s):  
Spatial Variability ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Precision Agriculture ◽  
Field Experiments ◽  
Soil Layer ◽  
Northwestern China ◽  
Potato Field ◽  
Arid Northwestern China

Abstract Assessing the spatial variability of soil water content is important for precision agriculture. To measure the spatial variability of the soil water content and to determine the optimal number of sampling sites for predicting the mean soil water content at different stages of the irrigation cycle, field experiments were carried out in a potato field in northwestern China. The soil water content was measured in 2016 and 2017 at depths of 0–20 and 20–40 cm at 116 georeferenced locations. The average coefficient of variation of the soil water content was 20.79% before irrigation and was 16.44% after irrigation at a depth of 0–20 cm. The spatial structure of the soil water content at a depth of 20–40 cm was similar throughout the irrigation cycle, but at a depth of 0–20 cm a relatively greater portion of the variation in the soil water content was spatially structured before irrigation than after irrigation. The autocorrelation of soil water contents was influenced by irrigation only in the surface soil layer. To accurately predict mean soil moisture content, 40 and 20 random sampling sites should be chosen with errors of 5% and 10%, respectively.

Time series outlier and intervention analysis: Irrigation management influences on soil water content in silty loam soil

2012 ◽  
Vol 111 ◽  
pp. 105-114 ◽  
Author(s):  
Basem Aljoumani ◽  
Jose A. Sànchez-Espigares ◽  
Nuria Cañameras ◽  
Ramon Josa ◽  
Joaquim Monserrat
Keyword(s):  
Time Series ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Irrigation Management ◽  
Intervention Analysis ◽  
Silty Loam ◽  
Loam Soil

scholarly journals Evaluation of Improved Model to Accurately Monitor Soil Water Content

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3441
Author(s):  
Jingyu Ji ◽  
Junzeng Xu ◽  
Yixin Xiao ◽  
Yajun Luan
Keyword(s):  
Organic Matter ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Texture ◽  
Irrigation Management ◽  
Clay Fraction ◽  
Organic Matter Content ◽  
Matter Content ◽  
Improved Model

The accurate monitoring of soil water content during the growth of crops is of great importance to improve agricultural water use efficiency. The Campbell model is one of the most widely used models for monitoring soil moisture content from soil thermal conductivities in farmland, which always needs to be calibrated due to the lack of adequate original data and the limitation of measurement methods. To precisely predict the water content of complex soils using the Campbell model, this model was evaluated by investigating several factors, including soil texture, bulk density and organic matter. The comparison of the R2 and the reduced Chi-Sqr values, which were calculated by Origin, was conducted to calibrate the Campbell model calculated. In addition, combining factors of parameters, a new parameter named m related to soil texture and the organic matter was firstly introduced and the original fitting parameter, E, was improved to an expression related to clay fraction and the organic matter content in the improved model. The soil data collected from both the laboratory and the previous literature were used to assess the revised model. The results show that most of the R2 values of the improved model are >0.95, and the reduced Chi-Sqr values are <0.01, which presents a better matching performance compared to the original. It is concluded that the improved model provides more accurate monitoring of soil water content for water irrigation management.

Mesoscale spatial variability of soil‐water content in an alpine meadow on the northern Tibetan Plateau

2019 ◽  
Vol 33 (19) ◽  
pp. 2523-2534 ◽  
Author(s):  
Xuchao Zhu ◽  
Mingan Shao ◽  
Yin Liang ◽  
Zhiyuan Tian ◽  
Xin Wang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Spatial Variability ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Alpine Meadow ◽  
Northern Tibetan Plateau

scholarly journals Soil water potential during different phenological phases of coffee irrigated by center pivot

2013 ◽  
Vol 33 (2) ◽  
pp. 269-278 ◽  
Author(s):  
Adão W. P. Evangelista ◽  
Luiz A. Lima ◽  
Antônio C. da Silva ◽  
Carla de P. Martins ◽  
Moisés S. Ribeiro
Keyword(s):  
Water Potential ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Irrigation Management ◽  
Soil Water Potential ◽  
Field Capacity ◽  
Limiting Factor ◽  
Center Pivot ◽  
Phenological Phases

Irrigation management can be established, considering the soil water potential, as the limiting factor for plant growth, assuming the soil water content between the field capacity and the permanent wilting point as available water for crops. Thus, the aim of this study was to establish the soil water potential interval during four different phenological phases of coffee irrigated by center pivot. The experiment was set at the experimental area of the Engineering Department at the Federal University of Lavras, in Brazil. The coffee variety planted is designated as Rubi, planted 0.8 meters apart, with rows spaced 3.5 meters apart. The treatments corresponded to the water depths applied based on different percentages of Kc and reference evapotranspiration (ET0) values. Sensors were used to measure the soil water potential interval, installed 25 centimeters depth. In order to compare the results, it was considered as the best matric potential the one that was balanced with the soil water content that resulted in the largest coffee productivity. Based on the obtained results, we verified that in the phases of fruit expansion and ripening, the best results were obtained, before the irrigations, when the soil water potential values reached -35 and -38 kPa, respectively. And in the flowering, small green and fruit expansion phases, when the values reached -31 and -32 kPa, respectively.

Calibration and evaluation of a capacitance probe in agricultural soils in northeast Brazil

2020 ◽  
Author(s):  
Ceres Duarte Guedes Cabral de Almeida ◽  
Lais Barreto Franco ◽  
José Ediclécio Barbosa dos Santos ◽  
Brivaldo Gomes de Almeida ◽  
Giuseppe Provenzano
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Agricultural Soils ◽  
Irrigation Management ◽  
Clay Loam ◽  
Sandy Clay Loam ◽  
Sandy Clay ◽  
Disturbed Soil ◽  
Capacitance Probe

&lt;p&gt;Soil water content is an important parameter for irrigation management. Among the indirect methods to determine soil water content (SWC), there are electronic sensors, that need site-specific calibration to increase the accuracy of the measurements. In this research, a capacitance probe (Diviner 2000&amp;#174;, Sentek Pty Ltda., Australia) was calibrated for two agricultural soils. The experiment was carried out in a protected environment at the Federal Rural University of Pernambuco (UFRPE), Brazil. The textural classes of soils were sandy clay loam (66% sand) and sandy (95% sand). Undisturbed and disturbed soil samples were collected in the soil top layer (0-30 cm). The disturbed soil samples were initially air-dried, passed through a 4.75 mm mesh sieve, and then introduced to fill eight vessels (four replications for each soil). These vessels, equipped with drainage holes, have lower and upper diameters of 15 cm and 25 cm, respectively, and height of 22.5 cm (4.66 L). In each pot, a 5 cm layer of gravel with an average diameter of 2 cm covered with bidim&amp;#174; geotextile was disposed before introducing the soil. During filling, the soil was compacted to reach the same bulk density measured on the undisturbed samples (sandy clay loam: 1.54 g cm&lt;sup&gt;-3&lt;/sup&gt; and sandy: 1.50 g cm&lt;sup&gt;-3&lt;/sup&gt;). In the center of each pot, a PVC access tube was installed. According to the manufacturer's recommendation, during calibration, the probe normalization was performed. The pots were wetted by capillary rise and, once saturated, they were placed on a bench for drainage. After this process stopped each pot was daily weighed at a fixed time (8 a.m.), and the sensor reading was acquired until when the daily mass variations became negligible. Data were used for regression analysis to fit the site-specific calibration equation and to evaluate the mean error. Linear calibration equations, characterized by R&lt;sup&gt;2&lt;/sup&gt;=0.931 and 0.986, were obtained for the sandy clay loam and the sandy soil, respectively. The mean errors (ME) associated with the manufacturer&amp;#8217;s equation resulted in -0.05 and -0.01 for sandy clay loam and for sandy soil and decreased after calibration. The results confirmed the suitability of the manufacturer's equation in sandy soils. On the other hand, the manufacture&amp;#8217;s equation slightly underestimated SWC, in sandy clay loam soil, especially in the range above 0.26 m&lt;sup&gt;3&lt;/sup&gt; m&lt;sup&gt;-3&lt;/sup&gt;. The Diviner 2000 probe can be therefore successfully used to support irrigation management in irrigated areas with soils similar to those investigated because it is easy to operate and allows fairly accurate estimations of soil water content.&lt;/p&gt;

scholarly journals Spatial variability of soil water content and related factors across the Hexi Corridor of China

2018 ◽  
Vol 11 (1) ◽  
pp. 123-134 ◽  
Author(s):  
Xiangdong Li ◽  
Ming’an Shao ◽  
Chunlei Zhao ◽  
Xiaoxu Jia
Keyword(s):  
Spatial Variability ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Hexi Corridor ◽  
Related Factors
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