scholarly journals Irrigation Scheduling Based on Wireless Sensors Output and Soil-Water Characteristic Curve in Two Soils

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1336 ◽  
Author(s):  
J.D. Jabro ◽  
W.B. Stevens ◽  
W.M. Iversen ◽  
B.L. Allen ◽  
U.M. Sainju
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Water ◽  
Root Zone ◽  
Sandy Loam ◽  
Characteristic Curve ◽  
Field Capacity ◽  
Irrigation Scheduling ◽  
Clay Loam ◽  
Soil Water Characteristic Curve

Data-driven irrigation planning can optimize crop yield and reduce adverse impacts on surface and ground water quality. We evaluated an irrigation scheduling strategy based on soil matric potentials recorded by wireless Watermark (WM) sensors installed in sandy loam and clay loam soils and soil-water characteristic curve data. Five wireless WM nodes (IRROmesh) were installed at each location, where each node consisted of three WM sensors that were installed at 15, 30, and 60 cm depths in the crop rows. Soil moisture contents, at field capacity and permanent wilting points, were determined from soil-water characteristic curves and were approximately 23% and 11% for a sandy loam, and 35% and 17% for a clay loam, respectively. The field capacity level which occurs shortly after an irrigation event was considered the upper point of soil moisture content, and the lower point was the maximum soil water depletion level at 50% of plant available water capacity in the root zone, depending on crop type, root depth, growth stage and soil type. The lower thresholds of soil moisture content to trigger an irrigation event were 17% and 26% in the sandy loam and clay loam soils, respectively. The corresponding soil water potential readings from the WM sensors to initiate irrigation events were approximately 60 kPa and 105 kPa for sandy loam, and clay loam soils, respectively. Watermark sensors can be successfully used for irrigation scheduling by simply setting two levels of moisture content using soil-water characteristic curve data. Further, the wireless system can help farmers and irrigators monitor real-time moisture content in the soil root zone of their crops and determine irrigation scheduling remotely without time consuming, manual data logging and frequent visits to the field.

Soil water content sensors from laboratory calibration to field monitoring: discrepancies and uncertainties

2021 ◽  
Author(s):  
Angela Gabriela Morales Santos ◽  
Reinhard Nolz
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Root Zone ◽  
Sandy Loam ◽  
Irrigation Scheduling ◽  
Water Monitoring ◽  
Rooting Depth ◽  
Water Fraction ◽  
Laboratory Calibration

<p>Monitoring soil water status is one key option to optimise water use in agriculture. Soil moisture sensors are widely used for investigating available soil water to optimally adapt irrigation scheduling to crop water requirements. Although reliable measurements are subject to proper soil-specific calibration of sensors, meaningful calibration functions are not always available. Another question is the plausibility of soil water monitoring under field conditions. The objective of this study was to calibrate four multi-sensor capacitance probes in the laboratory and  to evaluate the calibrated water content readings under natural conditions in an irrigated field by means of a modelling approach.</p><p>The multi-sensor capacitance probes (SM1 by ADCON Telemetry) were of 90 cm length and contained nine sensors (S1 to S9) at 10 cm spacing. The digital output values were given in scaled frequency units (SFU). The laboratory calibration was carried out on sandy loam and sand. Measurements were undertaken by placing the probes inside a PVC tube backfilled with soil at different water contents. Soil samples were collected using metallic cylinders of 250 cm<sup>3</sup>, from which volumetric water content (θ) was determined gravimetrically. The sensor readings in soil were normalised by using sensor readings in air and water as lower and upper limit, respectively. The pairs of measured θ and normalised SFU were related to each other by curve fitting. For each soil type, eight sensor-specific calibration functions were developed that allowed the calculation of θ in cm<sup>3</sup> cm<sup>−</sup><sup>3</sup> from SM1 readings.</p><p>After calibration, the SM1 probes were installed in a field in Obersiebenbrunn, Lower Austria, where sandy loam is the main soil. Three of the probes monitored irrigated plots and the fourth a rainfed plot. To obtain reference values, one HydraProbe soil moisture sensor (Stevens Water Monitoring Systems) was installed in 20 cm depth, near each SM1. The average daily θ-values from the S2 (20 cm depth) contained in each SM1 probe were compared to the water fraction collected with the corresponding HydraProbe. Moreover, the SM1 θ-values were used to determine the daily soil water depletion in the root zone (Dr) for a rooting depth of 1 m. The obtained Dr datasets were compared to Dr simulated using CROPWAT 8.0 by FAO.</p><p>The field results showed that the SM1 probes were able to reproduce the HydraProbe dynamics of wetting and drying periods during the crop season. Nevertheless, a considerable difference was noted between the sensor measurements. The SM1 overestimated θ in the irrigated plots, whereas it underestimated θ in the rainfed plot. The discrepancies can be attributed mainly to the different physical mechanisms behind the sensors and to the unfeasible reproduction of field bulk density and soil structure in the laboratory. Furthermore, the operational frequency and permittivity response of the SM1 probes should be revised for future versions. The simulation results showed that the observed Dr values were more consistent with CROPWAT Dr results at the end of the simulation period, suggesting that the SM1 required several weeks to consolidate and give representative θ-values for the soil profile.</p>

Model for predicting resilient modulus of unsaturated subgrade soil using soil-water characteristic curve

2015 ◽  
Vol 52 (10) ◽  
pp. 1605-1619 ◽  
Author(s):  
Zhong Han ◽  
Sai K. Vanapalli
Keyword(s):  
Moisture Content ◽  
Soil Water ◽  
Resilient Modulus ◽  
Characteristic Curve ◽  
Optimum Moisture Content ◽  
Model Parameters ◽  
Soil Water Characteristic Curve ◽  
Subgrade Soils ◽  
Fine Grained ◽  
Proposed Model

Soil suction (ψ) is one of the key factors that influence the resilient modulus (MR) of pavement subgrade soils. There are several models available in the literature for predicting the MR–ψ correlations. However, the various model parameters required in the existing models are generally determined by performing regression analysis on extensive experimental data of the MR–ψ relationships, which are cumbersome, expensive, and time-consuming to obtain. In this paper, a model is proposed to predict the variation of the MR with respect to the ψ for compacted fine-grained subgrade soils. The information of (i) the MR values at optimum moisture content condition (MROPT) and saturation condition (MRSAT), which are typically determined for use in pavement design practice; (ii) the ψ values at optimum moisture content condition (ψOPT); and (iii) the soil-water characteristic curve (SWCC) is required for using this model. The proposed model is validated by providing comparisons between the measured and predicted MR–ψ relationships for 11 different compacted fine-grained subgrade soils that were tested following various protocols (a total of 16 sets of data, including 210 testing results). The proposed model was found to be suitable for predicting the variation of the MR with respect to the ψ for all the subgrade soils using a single-valued model parameter ξ, which was found to be equal to 2.0. The proposed model is promising for use in practice, as it only requires conventional soil properties and alleviates the need for experimental determination of the MR–ψ relationships.

Area-representative validation of remotely sensed high resolution soil moisture using a cosmic-ray neutron sensor

2020 ◽  
Author(s):  
Dragana Panic ◽  
Isabella Pfeil ◽  
Andreas Salentinig ◽  
Mariette Vreugdenhil ◽  
Wolfgang Wagner ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Root Zone ◽  
Spatial Scales ◽  
Temporal Frequency ◽  
Cosmic Ray ◽  
Irrigation Scheduling ◽  
Water Index ◽  
The Impact

<p>Reliable measurements of soil moisture (SM) are required for many applications worldwide, e.g., for flood and drought forecasting, and for improving the agricultural water use efficiency (e.g., irrigation scheduling). For the retrieval of large-scale SM datasets with a high temporal frequency, remote sensing methods have proven to be a valuable data source. (Sub-)daily SM is derived, for example, from observations of the Advanced Scatterometer (ASCAT) since 2007. These measurements are available on spatial scales of several square kilometers and are in particular useful for applications that do not require fine spatial resolutions but long and continuous time series. Since the launch of the first Sentinel-1 satellite in 2015, the derivation of SM at a spatial scale of 1 km has become possible for every 1.5-4 days over Europe (SSM1km) [1]. Recently, efforts have been made to combine ASCAT and Sentinel-1 to a Soil Water Index (SWI) product, in order to obtain a SM dataset with daily 1 km resolution (SWI1km) [2]. Both datasets are available over Europe from the Copernicus Global Land Service (CGLS, https://land.copernicus.eu/global/). As the quality of such a dataset is typically best over grassland and agricultural areas, and degrades with increasing vegetation density, validation is of high importance for the further development of the dataset and for its subsequent use by stakeholders.</p><p>Traditionally, validation studies have been carried out using in situ SM sensors from ground networks. Those are however often not representative of the area-wide satellite footprints. In this context, cosmic-ray neutron sensors (CRNS) have been found to be valuable, as they provide integrated SM estimates over a much larger area (about 20 hectares), which comes close to the spatial support area of the satellite SM product. In a previous study, we used CRNS measurements to validate ASCAT and S1 SM over an agricultural catchment, the Hydrological Open Air Laboratory (HOAL), in Petzenkirchen, Austria. The datasets were found to agree, but uncertainties regarding the impact of vegetation were identified.</p><p>In this study, we validated the SSM1km, SWI1km and a new S1-ASCAT SM product, which is currently developed at TU Wien, using CRNS. The new S1-ASCAT-combined dataset includes an improved vegetation parameterization, trend correction and snow masking. The validation has been carried out in the HOAL and on a second site in Marchfeld, Austria’s main crop producing area. As microwaves only penetrate the upper few centimeters of the soil, we applied the soil water index concept [3] to obtain soil moisture estimates of the root zone (approximately 0-40 cm) and thus roughly corresponding to the depth of the CRNS measurements. In the HOAL, we also incorporated in-situ SM from a network of point-scale time-domain-transmissivity sensors distributed within the CRNS footprint. The datasets were compared to each other by calculating correlation metrics. Furthermore, we investigated the effect of vegetation on both the satellite and the CRNS data by analyzing detailed information on crop type distribution and crop water content.</p><p>[1] Bauer-Marschallinger et al., 2018a: https://doi.org/10.1109/TGRS.2018.2858004<br>[2] Bauer-Marschallinger et al., 2018b: https://doi.org/10.3390/rs10071030<br>[3] Wagner et al., 1999: https://doi.org/10.1016/S0034-4257(99)00036-X</p>

EFFECTS OF IRRIGATION AND NITROGEN ON A NATURAL PASTURE SWARD

1978 ◽  
Vol 58 (2) ◽  
pp. 347-356
Author(s):  
W. N. BLACK
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Sandy Loam ◽  
Field Capacity ◽  
Early Spring ◽  
Naturally Occurring ◽  
Natural Pasture ◽  
Loam Soil ◽  
Grazing Period

Irrigation and nitrogen (N) requirements of a natural pasture sward were studied on a Charlottetown sandy loam soil over a 5-yr period. The soil moisture content at the 0-to 15- and 15- to 30-cm depths was determined at from 7- to 10-day intervals, while irrometer soil moisture readings at 15-, 30-, and 45-cm depths were recorded more frequently during the grazing seasons. Soil moisture content in irrigated plots averaged 92 and 94% of field capacity, respectively, at 0- to 15- and 15- to 30-cm sampling depths. In non-irrigated plots, corresponding values were 77 and 82%. N treatments resulted in significant dry matter (DM) increases over untreated plots. Yield differences among plots receiving 56, 84, and 112 kg of N/ha in mid-June and again in mid-August were not significant. Early spring and September applications of N at 56 kg/ha, combined with mid-June and early August supplements of N at 84 kg/ha were superior to all other treatments in prolonging the grazing period. Neither irrigation nor N affected the characteristic yield decline of naturally occurring forage species in mid- and late-season. Mean DM production for the 5-yr period, and for years, showed no significant N treatment × moisture level interaction. While irrigation failed to increase yields significantly, livestock preferred to graze the irrigated plots. As a result of less competition from grasses, volunteer white clover became better established, and constituted a larger percentage of the sward than on non-irrigated plots.

Soil Water Measurement as Basis to Optimize Irrigation Scheduling: A Review

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 553f-554
Author(s):  
A.K. Alva ◽  
A. Fares
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Real Time ◽  
Soil Water Content ◽  
Root Zone ◽  
Soil Water Potential ◽  
Irrigation Scheduling ◽  
Rooting Depth ◽  
The Impact

Supplemental irrigation is often necessary for high economic returns for most cropping conditions even in humid areas. As irrigation costs continue to increase more efforts should be exerted to minimize these costs. Real time estimation and/or measurement of available soil water content in the crop root zone is one of the several methods used to help growers in making the right decision regarding timing and quantity of irrigation. The gravimetric method of soil water content determination is laborious and doesn't suite for frequent sampling from the same location because it requires destructive soil sampling. Tensiometers, which measure soil water potential that can be converted into soil water content using soil moisture release curves, have been used for irrigation scheduling. However, in extreme sandy soils the working interval of tensiometer is reduced, hence it may be difficult to detect small changes in soil moisture content. Capacitance probes which operate on the principle of apparent dielectric constant of the soil-water-air mixture are extremely sensitive to small changes in the soil water content at short time intervals. These probes can be placed at various depths within and below the effective rooting depth for a real time monitoring of the water content. Based on this continuous monitoring of the soil water content, irrigation is scheduled to replenish the water deficit within the rooting depth while leaching below the root zone is minimized. These are important management practices aimed to increase irrigation efficiency, and nutrient uptake efficiency for optimal crop production, while minimizing the impact of agricultural non-point source pollutants on the groundwater quality.

scholarly journals An Optimal Irrigation Scheduling for Drip Irrigated Onion in A- Semi-Arid Region Using the Computer Program CROPWAT 8.0

2020 ◽  
pp. 96-105
Author(s):  
P. R. Anjitha Krishna ◽  
B. Maheshwara Babu ◽  
A. T. Dandekar ◽  
R. H. Rajkumar ◽  
G. Ramesh ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Arid Region ◽  
Root Zone ◽  
Management Strategies ◽  
Field Capacity ◽  
Irrigation Scheduling ◽  
Water Requirement ◽  
Estimation Model ◽  
Semi Arid Region ◽  
Semi Arid

Efficient utilization of available water resources requires appropriate management strategies considering the changing environmental conditions. The present study used a widely adopted crop water requirement estimation model-CROPWAT 8.0 for estimation and scheduling of irrigation requirement for onion crop grown under Vertisol in the Rabi season in the semi-arid region of Raichur district. The soil moisture at the root zone was not allowed to fall below 50% depletion. The irrigation events brought the soil moisture back to the field capacity level. The total water requirement for the 1st and 2nd seasons was 428.77 mm and 399.98 mm respectively at 90% irrigation efficiency. CROPWAT based two days irrigation scheduling scenario was found to be appropriate to maintain optimal soil moisture range within the crop root zone at different crop stages.

Study on Unsaturated Mechanism of Loess Compaction

2011 ◽  
Vol 368-373 ◽  
pp. 2960-2965
Author(s):  
Qing Feng Lv ◽  
Jing Wen Zhao ◽  
Sheng Xin Wang ◽  
Yan Xu Zhao
Keyword(s):  
Moisture Content ◽  
Soil Water ◽  
Unsaturated Soils ◽  
Pore Space ◽  
Characteristic Curve ◽  
Dry Density ◽  
Physical Factors ◽  
Mineral Component ◽  
Space Topology ◽  
Soil Water Characteristic Curve

The soil-water characteristic curve is an important constitutive feature of unsaturated soils, defining the relationship between the soil suction and moisture content. Mineral component and pore space topology are the most important physical factors affecting the soil-water characteristic, and that dry density synthetically reflects the mineral component and pore space topology. Compaction is a classical application involving unsaturated soil, and dry density represents the pore structure at special moisture content. Soil water characteristic curve for compacted loess is studied by test, and the effect of dry density on soil water characteristic curve is discussed. Based the soil-water characteristic curve and compaction curve, mechanism of compaction is explained. Research results show that the soil-water characteristic curves for all dry density soil intersect at the point, which is optimize moisture content, and suction is the most important factor affecting the compaction.

scholarly journals Irrigation Scheduling Using Soil Moisture Sensors

2017 ◽  
Vol 10 (1) ◽  
pp. 1 ◽  
Author(s):  
Ruixiu Sui
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Management Practices ◽  
Root Zone ◽  
Weighted Average ◽  
Irrigation Scheduling ◽  
Time Interval ◽  
Soil Moisture Sensors

Irrigation is required to ensure crop production. Practical methods of use sensors to determine soil water status are needed in irrigation scheduling. Soil moisture sensors were evaluated and used for irrigation scheduling in humid region of the Mid-South US. Soil moisture sensors were installed in soil at depths of 15 cm, 30 cm, and 61 cm belowground. Soil volumetric water content was automatically measured by the sensors in a time interval of an hour during the crop growing season. Soil moisture data were wirelessly transferred onto internet through a wireless sensor network (WSN) so that the data could be remotely accessed online. Soil water content measured at the three depths were interpreted using a weighted average method to reflect the status of soil water in plant root zone. A threshold to trigger an irrigation event was determined with sensor-measured soil water content. An antenna mounting device was developed for operation of the WSN. Using the antenna mounting device, the soil moisture measurement was not be interrupted by crop field management practices.

Influence of Soil Texture on Soil-Water Characteristic Curves of Different Sandy Loam Layers

2014 ◽  
Vol 955-959 ◽  
pp. 3607-3610
Author(s):  
Li Zhu Hou ◽  
Jochen Wenninger ◽  
Xu Jie Li
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Water ◽  
Soil Moisture Content ◽  
Sandy Loam ◽  
Soil Water Storage ◽  
Characteristic Curves ◽  
Van Genuchten Model ◽  
Soil Water Characteristic Curves ◽  
Matrix Suction

Characteristic curves of soil moisture, between water content and matrix suction, are the basis for solving the problems of water flow and solute movement in soils. The soil–water characteristics of five layers of depths, 0–12 cm, 12–24 cm, 24–36 cm, 36–48 cm, and 48–60 cm, were measured for a sandy loam soil from Daxing District of Beijing in the northern part of the North China Plain by a pressure membrane apparatus. Curves were fitted using the Van Genuchten model. The fit between measured data and modeled results was excellent. The soil-water characteristic curves showed the typical Sshape of the Van Genuchten model. Matrix suction decreased with an increase in soil moisture; at low suctions, soil moisture content changed to a greater extent with suction, but at high suction, changes in soil moisture content with changes in suction were small. Clay content was proportional to soil water storage capacity and was inversely related to the speed of dehydration.

Experimental Study on Gravel Soils of Matrix Suction

2013 ◽  
Vol 275-277 ◽  
pp. 310-315 ◽  
Author(s):  
Hong Mei Tang ◽  
Pei Wei Liao ◽  
Lin Feng Wang ◽  
Hong Kai Chen
Keyword(s):  
Moisture Content ◽  
Water Content ◽  
Soil Water ◽  
Characteristic Curve ◽  
Curved Surface ◽  
Soil Water Characteristic Curve ◽  
Content Change ◽  
Two Factors ◽  
The Matrix ◽  
Matrix Suction

Soil-water characteristic curve（SWCC）is closely relevant to two main factors which are structure and moisture content. According to the two factors the values of matrix suction of 45 groups experimental specimens within different moisture content and soil -stone ratio of unsaturated soil are get through filter paper method. Date analysis shows that relation between matrix suction and soil-stone ratio at different moisture states is of different characteristics. Relation between matrix suction and water content is notably nonlinear. Distribution of matrix suction is curved surface in the moisture and soil-stone ration state space which is the function of water content and soil-stone ratio, in which the axial plan is parallel to the axis of soil-stone ratio.At low water content,the matrix suction on the moisture content change is very sensitive, at high moisture content and closed to saturation stage matrix suction hardly changes along with water content and soil-stone ratio change. The curved surface which Located in the middle section ,the matrix suction on the change of water content are more sensitive, reduced with water content increasing; and in this phase the matrix suction is insensitive to the variation of soil-stone ratio. Finally, it is concluded that the saturation to describe the soil water characteristic curve is a bad choice, with moisture to depict the so. In contrast, directly using the water content to describe the soil water characteristic curve is better.

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