A Study on the Application Design of Soil Moisture Diffusion and Crop Roots According to Subsurface Irrigation Method

2021 ◽  
Author(s):  
Jin Hyun Kim ◽  
Tae Wook Kim ◽  
Seol Ha Kim ◽  
Hwang Gyu Lee ◽  
Duk Ho Eum ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Moisture Diffusion ◽  
Irrigation Method ◽  
Application Design

Prediction of Trifluralin Diffusion Coefficients

Weed Science ◽  
1973 ◽  
Vol 21 (5) ◽  
pp. 485-489 ◽  
Author(s):  
L. E. Bode ◽  
C. L. Day ◽  
M. R. Gebhardt ◽  
C. E. Goering
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Diffusion Coefficients ◽  
Moisture Diffusion ◽  
Soil Parameters ◽  
Void Space ◽  
Exponential Relationship ◽  
Maximum Value ◽  
Soil Temperatures ◽  
Dry Soil

In the range of 4.4 to 49 C, there is an exponential relationship between temperature and trifluralin (α,α,α-trifluoro-2,6-dinitro-N,N-dipropyl-p-toluidine) diffusion coefficients. Diffusion is low in air-dry soil for all temperatures. It increases to a maximum value when the soil has between 8 and 15% w/w soil moisture content and then decreases steadily as moisture content increases. When the air-filled fraction of soil void space is reduced below approximately 40% v/v by either compression or addition of moisture, diffusion begins to decrease. An equation was developed to predict trifluralin diffusion coefficients from a factorial experiment with seven soil moisture contents, five soil temperatures, and two bulk densities. Diffusion coefficients range from 3.8 X 10-11 cm2/sec to 2.8 X 10-6 cm2/sec. Fifteen terms are required in the prediction model to describe accurately the response surface of trifluralin diffusion coefficients. With the equation it is possible to predict trifluralin diffusion coefficients for any combination of measured soil parameters as long as they are represented by the range of the variables used in the experiment.

scholarly journals Testing water fluxes and storage from two hydrology configurations within the ORCHIDEE land surface model across US semi-arid sites

2020 ◽  
Vol 24 (11) ◽  
pp. 5203-5230
Author(s):  
Natasha MacBean ◽  
Russell L. Scott ◽  
Joel A. Biederman ◽  
Catherine Ottlé ◽  
Nicolas Vuichard ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Moisture Diffusion ◽  
Bare Soil ◽  
Soil Evaporation ◽  
Arid Ecosystems ◽  
Layer Model ◽  
Soil Fraction ◽  
Bare Soil Evaporation ◽  
Semi Arid

Abstract. Plant activity in semi-arid ecosystems is largely controlled by pulses of precipitation, making them particularly vulnerable to increased aridity that is expected with climate change. Simple bucket-model hydrology schemes in land surface models (LSMs) have had limited ability in accurately capturing semi-arid water stores and fluxes. Recent, more complex, LSM hydrology models have not been widely evaluated against semi-arid ecosystem in situ data. We hypothesize that the failure of older LSM versions to represent evapotranspiration, ET, in arid lands is because simple bucket models do not capture realistic fluctuations in upper-layer soil moisture. We therefore predict that including a discretized soil hydrology scheme based on a mechanistic description of moisture diffusion will result in an improvement in model ET when compared to data because the temporal variability of upper-layer soil moisture content better corresponds to that of precipitation inputs. To test this prediction, we compared ORCHIDEE LSM simulations from (1) a simple conceptual 2-layer bucket scheme with fixed hydraulic parameters and (2) an 11-layer discretized mechanistic scheme of moisture diffusion in unsaturated soil based on Richards equations, against daily and monthly soil moisture and ET observations, together with data-derived estimates of transpiration / evapotranspiration, T∕ET, ratios, from six semi-arid grass, shrub, and forest sites in the south-western USA. The 11-layer scheme also has modified calculations of surface runoff, water limitation, and resistance to bare soil evaporation, E, to be compatible with the more complex hydrology configuration. To diagnose remaining discrepancies in the 11-layer model, we tested two further configurations: (i) the addition of a term that captures bare soil evaporation resistance to dry soil; and (ii) reduced bare soil fractional vegetation cover. We found that the more mechanistic 11-layer model results in a better representation of the daily and monthly ET observations. We show that, as predicted, this is because of improved simulation of soil moisture in the upper layers of soil (top ∼ 10 cm). Some discrepancies between observed and modelled soil moisture and ET may allow us to prioritize future model development and the collection of additional data. Biases in winter and spring soil moisture at the forest sites could be explained by inaccurate soil moisture data during periods of soil freezing and/or underestimated snow forcing data. Although ET is generally well captured by the 11-layer model, modelled T∕ET ratios were generally lower than estimated values across all sites, particularly during the monsoon season. Adding a soil resistance term generally decreased simulated bare soil evaporation, E, and increased soil moisture content, thus increasing transpiration, T, and reducing the negative bias between modelled and estimated monsoon T∕ET ratios. This negative bias could also be accounted for at the low-elevation sites by decreasing the model bare soil fraction, thus increasing the amount of transpiring leaf area. However, adding the bare soil resistance term and decreasing the bare soil fraction both degraded the model fit to ET observations. Furthermore, remaining discrepancies in the timing of the transition from minimum T∕ET ratios during the hot, dry May–June period to high values at the start of the monsoon in July–August may also point towards incorrect modelling of leaf phenology and vegetation growth in response to monsoon rains. We conclude that a discretized soil hydrology scheme and associated developments improve estimates of ET by allowing the modelled upper-layer soil moisture to more closely match the pulse precipitation dynamics of these semi-arid ecosystems; however, the partitioning of T from E is not solved by this modification alone.

Simplified Analysis of Unsteady Moisture Flow Through Unsaturated Soil

2003 ◽  
Vol 1821 (1) ◽  
pp. 75-82 ◽  
Author(s):  
Charles Aubeny ◽  
Robert Lytton ◽  
Dina Tang
Keyword(s):  
Soil Moisture ◽  
Unsaturated Soils ◽  
Moisture Diffusion ◽  
Soil Mass ◽  
Practical Significance ◽  
Restrictive Assumption ◽  
Diffusion Characteristics ◽  
Highly Nonlinear ◽  
Flow Through ◽  
Diffusion Properties

The moisture diffusion properties of unsaturated soils control the rate of infiltration of surface moisture into the soil mass and hence are critical to a wide variety of civil structures, including pavements, structures, retaining walls, and slopes. Because of the dependence of permeability on suction and the nonlinearity of the suction–moisture relationship, the analytical formulation for flow through unsaturated soils is highly nonlinear. An approximate linear analysis of this problem, which was originally proposed by Peter Mitchell, was investigated. One advantage of this approximate analysis is that it can provide the practical basis for measuring soil moisture diffusion characteristics in laboratory tests. A second advantage is that the linear formulation provides an analytical tool accessible to practitioners. Mitchell originally based his formulation on a relatively restrictive assumption on the permeability-versus-suction relationship. An approach to circumventing that restriction is proposed. The findings of a laboratory test program that uses Mitchell’s formulation to estimate a soil’s moisture diffusion characteristics are presented. Finally, some simple analytical predictions demonstrate the practical significance of the soil moisture diffusion properties.

scholarly journals Multi-variable, multi-configuration testing of ORCHIDEE land surface model water flux and storage estimates across semi-arid sites in the southwestern US

2019 ◽  
Author(s):  
Natasha MacBean ◽  
Russell L. Scott ◽  
Joel A. Biederman ◽  
Catherine Ottlé ◽  
Nicolas Vuichard ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Moisture Diffusion ◽  
Bare Soil ◽  
Soil Evaporation ◽  
Arid Ecosystems ◽  
Soil Hydrology ◽  
Soil Fraction ◽  
Bare Soil Evaporation ◽  
Semi Arid

Abstract. Plant activity in semi-arid ecosystems is largely controlled by pulses of precipitation, making them particularly vulnerable to increased aridity expected with climate change. Simple bucket-model hydrology schemes in land surface models (LSMs) have had limited ability in accurately capturing semi-arid water stores and fluxes. Recent, more complex, LSM hydrology models have not been widely evaluated against semi-arid ecosystem in situ data. We hypothesize that the failure of older LSM versions to represent evapotranspiration, ET, in arid lands is because simple bucket models do not capture realistic fluctuations in upper layer soil moisture. We therefore predict that including a discretized soil hydrology scheme based on a mechanistic description of moisture diffusion will result in an improvement in model ET when compared to data because the temporal variability of upper layer soil moisture content better corresponds to that of precipitation inputs. To test this prediction, we compared ORCHIDEE LSM simulations from (1) a simple conceptual 2-layer bucket scheme with fixed hydrological parameters; and (2) a 11-layer discretized mechanistic scheme of moisture diffusion in unsaturated soil based on Richards equations against daily and monthly soil moisture and ET observations, together with data-derived transpiration / evaporation, T / ET, ratios, from six semi-arid grass, shrub and forest sites in the southwestern USA. The 11-layer scheme also has modified calculations of surface runoff, bare soil evaporation, and water limitation to be compatible with the more complex hydrology configuration. To diagnose remaining discrepancies in the 11-layer model, we tested two further configurations: (i) the addition of a term that captures bare soil evaporation resistance to dry soil; and (ii) reduced bare soil fraction. We found that the more mechanistic 11-layer model results better representation of the daily and monthly ET observations. We show that is likely because of improved simulation of soil moisture in the upper layers of soil (top 5 cm). Some discrepancies between observed and modelled soil moisture and ET may allow us to prioritize future model development. Adding a soil resistance term generally decreased simulated E and increased soil moisture content, thus increasing T and T / ET ratios and reducing the negative T / ET model-data bias. By reducing the bare soil fraction in the model, we illustrated that modelled leaf T is too low at sparsely vegetated sites. We conclude that a discretized soil hydrology scheme and associated developments improves estimates of ET by allowing the model to more closely match the pulse precipitation dynamics of these semi-arid ecosystems; however, the partitioning of T from bare soil evaporation is not solved by this modification alone.

scholarly journals Correlation between the Soil Moisture Reading Obtained with Soil Moisture Sensors and Gravimetric Method for Scheduling of Irrigation in Maize

2021 ◽  
pp. 72-80
Author(s):  
C. Durga ◽  
V. Ramulu ◽  
M. Umadevi ◽  
K. Suresh ◽  
E. Sathyanarayana
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Drip Irrigation ◽  
Gravimetric Method ◽  
Irrigation Scheduling ◽  
Furrow Irrigation ◽  
Irrigation Method ◽  
Irrigation Methods ◽  
Soil Moisture Sensors ◽  
Positive Significant Correlation

A field experiment was conducted at Water Technology Centre farm (WTC), College of Agriculture, Rajendranagar, Hyderabad for studying the correlation between the soil moisture reading obtained with soil moisture sensors and gravimetric method. The experiment was designed in split plot with two main treatments comprising of surface furrow (M1) and drip irrigation (M2) methods and six irrigation schedules were assigned to sub treatments and replicated thrice. Significantly higher grain yield (7.05 t ha-1) of maize was observed with nano sensor (IITB) based irrigation scheduling over rest of the irrigation schedules except gypsum block. The results revealed that correlation between the tensiometer readings and gravimetric moisture content showed a negative non significant correlation before irrigation in surface furrow irrigation method and negative significant correlation for drip irrigation method. But in case of after irrigation a positive non significant correlation was observed in both drip and surface furrow irrigation methods. The gypsum block reading and gravimetric moisture content studies showed a negative significant correlation before irrigation in both surface furrow and drip irrigation methods, where as a positive non significant correlation between gypsum block readings and gravimetric moisture content readings were noticed after irrigation in both drip and surface furrow irrigation methods. Similar trend was recorded in nano sensor, except that it showed a positive significant correlation in both irrigation methods before irrigation. The correlation studies between the profile probe readings and gravimetric moisture content showed a negative significant correlation in surface furrow irrigation method at before and after irrigation, whereas, a positive significant correlation was observed after irrigation in drip irrigation method.

PROTOTIPE APLIKASI PENYIRAMAN TANAMAN MENGGUNAKAN SENSOR KELEMBABAN TANAH BERBASIS MICRO CONTOLLER ATMEGA 328

2019 ◽  
Vol 5 (1) ◽  
pp. 97-106
Author(s):  
Rudi Budi Agung ◽  
Muhammad Nur ◽  
Didi Sukayadi
Keyword(s):  
Soil Moisture ◽  
Growth And Development ◽  
Large Scale ◽  
Simple Method ◽  
Moisture Sensor ◽  
Sensor Development ◽  
Soil Moisture Sensor ◽  
Application Systems ◽  
Harvesting Systems ◽  
Working Principle

The Indonesian country which is famous for its tropical climate has now experienced a shift in two seasons (dry season and rainy season). This has an impact on cropping and harvesting systems among farmers. In large scale this is very influential considering that farmers in Indonesia are stilldependent on rainfall which results in soil moisture. Some types of plants that are very dependent on soil moisture will greatly require rainfall or water for growth and development. Through this research, researchers tried to make a prototype application for watering plants using ATMEGA328 microcontroller based soil moisture sensor. Development of application systems using the prototype method as a simple method which is the first step and can be developed again for large scale. The working principle of this prototype is simply that when soil moisture reaches a certainthreshold (above 56%) then the system will work by activating the watering system, if it is below 56% the system does not work or in other words soil moisture is considered sufficient for certain plant needs.

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