scholarly journals The importance of management information and soil moisture representation for simulating tillage effects on N<sub>2</sub>O emissions in LPJmL5.0-tillage

2020 ◽  
Vol 13 (9) ◽  
pp. 3905-3923
Author(s):  
Femke Lutz ◽  
Stephen Del Grosso ◽  
Stephen Ogle ◽  
Stephen Williams ◽  
Sara Minoli ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Meta Analysis ◽  
Agricultural Management ◽  
Water Dynamics ◽  
N2o Emissions ◽  
No Tillage ◽  
The Usa ◽  
Global Estimates ◽  
Daycent Model

Abstract. No-tillage is often suggested as a strategy to reduce greenhouse gas emissions. Modeling tillage effects on nitrous oxide (N2O) emissions is challenging and subject to great uncertainties as the processes producing the emissions are complex and strongly nonlinear. Previous findings have shown deviations between the LPJmL5.0-tillage model (LPJmL: Lund–Potsdam–Jena managed Land) and results from meta-analysis on global estimates of tillage effects on N2O emissions. Here we tested LPJmL5.0-tillage at four different experimental sites across Europe and the USA to verify whether deviations in N2O emissions under different tillage regimes result from a lack of detailed information on agricultural management, the representation of soil water dynamics or both. Model results were compared to observational data and outputs from field-scale DayCent model simulations. DayCent has been successfully applied for the simulation of N2O emissions and provides a richer database for comparison than noncontinuous measurements at experimental sites. We found that adding information on agricultural management improved the simulation of tillage effects on N2O emissions in LPJmL. We also found that LPJmL overestimated N2O emissions and the effects of no-tillage on N2O emissions, whereas DayCent tended to underestimate the emissions of no-tillage treatments. LPJmL showed a general bias to overestimate soil moisture content. Modifications of hydraulic properties in LPJmL in order to match properties assumed in DayCent, as well as of the parameters related to residue cover, improved the overall simulation of soil water and N2O emissions simulated under tillage and no-tillage separately. However, the effects of no-tillage (shifting from tillage to no-tillage) did not improve. Advancing the current state of information on agricultural management and improvements in soil moisture highlights the potential to improve LPJmL5.0-tillage and global estimates of tillage effects on N2O emissions.

scholarly journals The importance of management information and soil moisture representation for simulating tillage effects on N<sub>2</sub>O emissions in LPJmL5.0-tillage

2020 ◽  
Author(s):  
Femke Lutz ◽  
Stephen DelGrosso ◽  
Stephen Ogle ◽  
Stephen Williams ◽  
Sara Minoli ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Meta Analysis ◽  
Agricultural Management ◽  
Water Dynamics ◽  
N2o Emissions ◽  
No Tillage ◽  
Emissions Modeling ◽  
The Usa ◽  
Global Estimates

Abstract. No-tillage is often suggested as a strategy to reduce greenhouse gas emissions. Modeling tillage effects on nitrous oxide (N2O) emissions is challenging and subject to large uncertainties, as the processes producing the emissions are complex and strongly non-linear. Previous findings have shown deviations between the LPJmL5.0-tillage model and results from meta-analysis on global estimates of tillage effects on N2O emissions. Here we tested LPJmL5.0-tillage at four different experimental sites across Europe and the USA, to verify whether deviations in N2O emissions under different tillage regimes result from a lack of detailed information on agricultural management and/or the representation of soil water dynamics. Model results were compared to observational data and outputs from field-scale DayCent simulations. DayCent has been successfully applied for the simulation of N2O emissions and provides a richer data base for comparison than non-continuous measurements at the experimental sites. We found that adding information on agricultural management improved the simulation of tillage effects on N2O emissions in LPJmL. We also found that LPJmL overestimated N2O emissions as well as the effects of no-tillage on N2O emissions, whereas DayCent tended to underestimate the emissions of no-tillage treatments. LPJmL showed a general bias to over-estimate soil moisture content. Modifications of hydraulic properties in LPJmL in order to match properties assumed in DayCent, as well as of the parameters related to residue cover, improved the overall simulation of soil water as well as the N2O emissions simulated under tillage and no-tillage separately. However, the effects of no-tillage (shifting from tillage to no-tillage) did not improve. Advancing the current state of information on agricultural management as well as improvements in soil moisture highlight the potential to improve LPJmL5.0-tillage and global estimates of tillage effects on N2O emissions.

A laboratory study of the effect of soil-water dynamics on the migration of gases from subsurface sources

2021 ◽  
Author(s):  
Ana M. C. Ilie ◽  
Tissa H. Illangasekare ◽  
Kenichi Soga ◽  
William R. Whalley
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Sandy Soil ◽  
Land Surface ◽  
Soil Gas ◽  
Water Dynamics ◽  
Gas Migration ◽  
Soil Water Dynamics ◽  
Scale Test ◽  
Properties Of Soil

&lt;p&gt;Understanding the soil-gas migration in unsaturated soil is important in a number of problems that include carbon loading to the atmosphere from the bio-geochemical activity and leakage of gases from subsurface sources from carbon storage unconventional energy development. The soil water dynamics in the vadose zone control the soil-gas pathway development and, hence, the gas flux's spatial and temporal distribution at the soil surface. The spatial distribution of soil-water content depends on soil water characteristics. The dynamics are controlled by the water flux at the land surface and water table fluctuations. Physical properties of soil give a better understanding of the soil gas dynamics and migration from greater soil depths. The fundamental process of soil gas migration under dynamic water content was investigated in the laboratory using an intermediate-scale test system under controlled conditions that is not possible in the field. The experiments focus on observing the methane gas migration in relation to the physical properties of soil and the soil moisture patterns. A 2D soil tank with dimensions of 60 cm &amp;#215; 90 cm &amp;#215; 5.6 cm (height &amp;#215; length &amp;#215; width) was used.&amp;#160; The tank was heterogeneously packed with sandy soil along with a distributed network of soil moisture, temperature, and electrical conductivity sensors. The heterogeneous soil configuration was designed using nine uniform silica sands with the effective sieve numbers #16, #70, #8, #40/50, #110, #30/40, #50, and #20/30 (Accusands, Unimin Corp., Ottawa, MN), and a porosity ranging in values from 0.31 to 0.42. Four methane infrared gas sensors and a Flame Ionization detector (HFR400 Fast FID) were used for the soil gas sampling at different depths within the soil profiles and at the land surface.&amp;#160; A complex transient soil moisture distribution and soil gas migration patterns were observed in the 2D tank. These processes were successfully captured by the sensors. These preliminary experiments helped us to understand the mechanism of soil moisture sensor response and methane gas migration into a heterogeneous sandy soil with a view to developing a large-scale test in a 3D tank (4.87 m &amp;#215; 2.44 m &amp;#215; 0.40 m) and finally transition to field deployment.&lt;/p&gt;

scholarly journals Parameterization of Soil Hydraulic Parameters for HYDRUS-3D Simulation of Soil Water Dynamics in a Drip-Irrigated Orchard

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1858 ◽  
Author(s):  
Jesús María Domínguez-Niño ◽  
Gerard Arbat ◽  
Iael Raij-Hoffman ◽  
Isaya Kisekka ◽  
Joan Girona ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Drip Irrigation ◽  
Water Dynamics ◽  
Hydraulic Parameters ◽  
Soil Water Dynamics ◽  
Heterogeneous Distribution ◽  
Neutron Probe ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

Although surface drip irrigation allows an efficient use of water in agriculture, the heterogeneous distribution of soil water complicates its optimal usage. Mathematical models can be used to simulate the dynamics of water in the soil below a dripper and promote: a better understanding, and optimization, of the design of drip irrigation systems, their improved management and their monitoring with soil moisture sensors. The aim of this paper was to find the most appropriate configuration of HYDRUS-3D for simulating the soil water dynamics in a drip-irrigated orchard. Special emphasis was placed on the source of the soil hydraulic parameters. Simulations parameterized using the Rosetta approach were therefore compared with others parameterized using that of HYPROP + WP4C. The simulations were validated on a seasonal scale, against measurements made using a neutron probe, and on the time course of several days, against tensiometers. The results showed that the best agreement with soil moisture measurements was achieved with simulations parameterized from HYPROP + WP4C. It further improved when the shape parameter n was empirically calibrated from a subset of neutron probe measurements. The fit of the simulations with measurements was best at positions near the dripper and worsened at positions outside its wetting pattern and at depths of 80 cm or more.

Soil water dynamics in forested and irrigated sites in Cyprus 

2021 ◽  
Author(s):  
Marinos Eliades ◽  
Adriana Bruggeman ◽  
Hakan Djuma ◽  
Melpomeni Siakou ◽  
Panagiota Venetsanou ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Potential ◽  
Soil Water ◽  
Water Flow ◽  
Water Retention ◽  
Soil Depth ◽  
Soil Water Potential ◽  
Water Dynamics ◽  
Annual Rainfall ◽  
Irrigation Amount

&lt;p&gt;The water storage in soil is a dynamic process that changes with soil, vegetation and climate properties. Water retention curves, that describe the relationship between the soil water content (&amp;#952;) and the soil water potential (&amp;#968;), are used to model soil water flow and root water uptake by the plants. The overall objective of this study is to derive the retention curves of soils at two forested (Agia Marina, Platania) and two irrigated (Galata, Strakka) sites in Cyprus from in-situ soil moisture and soil water potential observations.&amp;#160;&lt;br&gt;The long-term (1980 &amp;#8211; 2010) average annual rainfall at Strakka olive grove (255 m elevation), Agia Marina P. brutia forest (640 m), Galata peach orchard (784 m) and Platania P. brutia forest (1160 m) is 298, 425, 502 and 839 mm, respectively. &amp;#160;The average soil depth at Agia Marina is 14 cm, while at other sites it is around 1 m. We installed a total of 18 TEROS21 soil water potential sensors, 37 5TM and 19 SMT100 soil moisture sensors, at different soil depths at the four sites.&amp;#160;&lt;br&gt;Results from January 2019 to January 2021 show differences in the water retention curves of the four sites due to different soil textures. At the forested sites, &amp;#952; reached wilting point at the summer period, indicating that trees extend their roots beyond the soil profile, to the bedrock in order to survive. At the irrigated sites, &amp;#952; exceeds field capacity during irrigation, indicating over-irrigation. We found different water retention relations after rainfall and after irrigation, indicating that irrigation has an uneven spatial distribution. These findings suggest that the irrigation in these fields is not optimal and farmers may need to increase the number of irrigation drippers, while reducing the irrigation amount per dripper. From a monitoring perspective, increasing the number of sensors may give a better representation of the soil moisture conditions.&amp;#160;&lt;br&gt;The research has received financial support from the ERANETMED3 program, as part of the ISOMED project (Environmental Isotope Techniques for Water Flow Accounting), funded through the Cyprus Research and Innovation Foundation.&lt;/p&gt;

scholarly journals A particle based model for soil water dynamics: how to match and step beyond Richards' equation?

2016 ◽  
Author(s):  
E. Zehe ◽  
C. Jackisch
Keyword(s):  
Soil Moisture ◽  
Random Walk ◽  
Soil Water ◽  
Drift Velocity ◽  
Maximum Velocity ◽  
Water Dynamics ◽  
Richards Equation ◽  
Particle Model ◽  
Soil Water Dynamics ◽  
Non Linear

Abstract. Within this study we propose a stochastic approach to simulate soil water dynamics in the unsaturated zone by using a non-linear, space domain random walk of water particles. Soil water is represented by particles of constant mass, which travel according to the Itô form of the Fokker Planck equation. The model concept builds on established soil physics by estimating the drift velocity and the diffusion term based on the soil water characteristics. A naive random walk, which assumes all water particles to move at the same drift velocity and diffusivity, overestimated depletion of soil moisture gradients compared to a Richards' solver. This is because soil water and hence the corresponding water particles in smaller pore size fractions, are, due to the non-linear decrease of soil hydraulic conductivity with decreasing soil moisture, much less mobile. After accounting for this subscale variability of particle mobility, the particle model and a Richards' solver performed similarly during simulated wetting and drying circles in three distinctly different soils. The particle model typically produced slightly smaller top soil water contents during wetting and was faster in depleting soil moisture gradients during subsequent drainage phases. Within a real world benchmark the particle model matched observed soil moisture response to a moderated rainfall event even slightly better than the Richards' solver. The proposed approach is hence a promising, easy to implement alternative to the Richards equation. This is particularly also because it allows one to step beyond the assumption of local equilibrium during rainfall driven conditions. This is demonstrated by treating infiltrating event water particles as different type of particle which travel initially, mainly gravity driven, in the largest pore fraction at maximum velocity, and yet experience a slow diffusive mixing with the pre-event water particles within a characteristic mixing time.

scholarly journals Hydrotropic Root Behavior in Water-Saving Cultivation: A High-Resolution Monitoring Study of Soil Water Dynamics

2021 ◽  
Author(s):  
Qichen Li ◽  
Toshiaki Sugihara ◽  
Sakae Shibusawa ◽  
Minzan Li
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Water Content ◽  
Root System ◽  
Soil Water ◽  
Water Saving ◽  
Water Dynamics ◽  
Soil Water Dynamics ◽  
Soil Moisture Sensors ◽  
Wet Zone

Abstract BackgroundSubsurface irrigation has been confirmed to have high water use efficiency due to it irrigating only the crop root zone. Hydrotropism allows roots to grow towards higher water content areas for drought avoidance, which has research interests in recent years. However, most hydrotropism studies focused on a single root and were conducted in air or agar systems. The performance of hydrotropism in subsurface irrigation is not clear. ResultsWe developed a method to observe and analyze hydrotropism in soil under water-saving cultivation. A wet zone was produced around the whole root system based on using subsurface irrigation method and micro soil water dynamics were observed using high-resolution soil moisture sensors. This method enabled the observation and analysis of plant water absorption activities and the hydrotropic response of the root system. In the analysis, we first applied a high-pass filter and fast Fourier transform to the soil water dynamics data. The results indicated that the plant’s biological rhythm of photosynthetic activities can be identified from the soil moisture data. We then observed root growth in response to the dynamics of soil water content in the wet zone. We quantified root distribution inside and outside the wet zone and observed the shape of the root system from the cross-section of the wet zone. The results showed that the root hydrotropic response is not uniform for all roots of an individual plant. ConclusionsThis study verified the feasibility of using high-resolution soil moisture sensors to study root hydrotropic responses in soil during water-saving cultivation. To further evaluate a plant’s hydrotropic ability, it is necessary to use statistical analysis and/or a non-deterministic approach. Future studies may also explore developing an automated experimental system and robotic manipulations for getting steady repeatable observation of hydrotropism in water-saving cultivation.

scholarly journals Modelling Soil Water Dynamics from Soil Hydraulic Parameters Estimated by an Alternative Method in a Tropical Experimental Basin

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1007 ◽  
Author(s):  
Bruno Silva Ursulino ◽  
Suzana Maria Gico Lima Montenegro ◽  
Artur Paiva Coutinho ◽  
Victor Hugo Rabelo Coelho ◽  
Diego Cezar dos Santos Araújo ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
River Basin ◽  
Time Domain Reflectometry ◽  
Water Dynamics ◽  
Hydraulic Parameters ◽  
Northeast Brazil ◽  
Mean Square Errors

Knowledge about soil moisture dynamics and their relation with rainfall, evapotranspiration, and soil physical properties is fundamental for understanding the hydrological processes in a region. Given the difficulties of measurement and the scarcity of surface soil moisture data in some places such as Northeast Brazil, modelling has become a robust tool to overcome such limitations. This study investigated the dynamics of soil water content in two plots in the Gameleira Experimental River Basin, Northeast Brazil. For this, Time Domain Reflectometry (TDR) probes and Hydrus-1D for modelling one-dimensional flow were used in two stages: with hydraulic parameters estimated with the Beerkan Estimation of Soil Transfer Parameters (BEST) method and optimized by inverse modelling. The results showed that the soil water content in the plots is strongly influenced by rainfall, with the greatest variability in the dry–wet–dry transition periods. The modelling results were considered satisfactory with the data estimated by the BEST method (Root Mean Square Errors, RMSE = 0.023 and 0.022 and coefficients of determination, R2 = 0.72 and 0.81) and after the optimization (RMSE = 0.012 and 0.020 and R2 = 0.83 and 0.72). The performance analysis of the simulations provided strong indications of the efficiency of parameters estimated by BEST to predict the soil moisture variability in the studied river basin without the need for calibration or complex numerical approaches.

scholarly journals A Lagrangian model for soil water dynamics during rainfall-driven conditions

2016 ◽  
Vol 20 (9) ◽  
pp. 3511-3526 ◽  
Author(s):  
Erwin Zehe ◽  
Conrad Jackisch
Keyword(s):  
Soil Moisture ◽  
Random Walk ◽  
Soil Water ◽  
Drift Velocity ◽  
Water Dynamics ◽  
Richards Equation ◽  
Particle Model ◽  
Soil Water Dynamics ◽  
Non Linear ◽  
Non Equilibrium

Abstract. Within this study we propose a stochastic approach to simulate soil water dynamics in the unsaturated zone by using a non-linear, space domain random walk of water particles. Soil water is represented by particles of constant mass, which travel according to the Itô form of the Fokker–Planck equation. The model concept builds on established soil physics by estimating the drift velocity and the diffusion term based on the soil water characteristics. A naive random walk, which assumes all water particles to move at the same drift velocity and diffusivity, overestimated depletion of soil moisture gradients compared to a Richards solver. This is because soil water and hence the corresponding water particles in smaller pore size fractions are, due to the non-linear decrease in soil hydraulic conductivity with decreasing soil moisture, much less mobile. After accounting for this subscale variability in particle mobility, the particle model and a Richards solver performed highly similarly during simulated wetting and drying circles in three distinctly different soils. Both models were in very good accordance during rainfall-driven conditions, regardless of the intensity and type of the rainfall forcing and the shape of the initial state. Within subsequent drying cycles the particle model was typically slightly slower in depleting soil moisture gradients than the Richards model. Within a real-world benchmark, the particle model and the Richards solver showed the same deficiencies in matching observed reactions of topsoil moisture to a natural rainfall event. The particle model performance, however, clearly improved after a straightforward implementation of rapid non-equilibrium infiltration, which treats event water as different types of particles, which travel initially in the largest pore fraction at maximum velocity and experience a slow diffusive mixing with the pre-event water particles. The proposed Lagrangian approach is hence a promising, easy-to-implement alternative to the Richards equation for simulating rainfall-driven soil moisture dynamics, which offers straightforward opportunities to account for preferential, non-equilibrium flow.

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