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.

scholarly journals Inverse modelling of in situ soil water dynamics: investigating the effect of different prior distributions of the soil hydraulic parameters

2011 ◽  
Vol 15 (10) ◽  
pp. 3043-3059 ◽  
Author(s):  
B. Scharnagl ◽  
J. A. Vrugt ◽  
H. Vereecken ◽  
M. Herbst
Keyword(s):  
Soil Water ◽  
Prior Information ◽  
Water Dynamics ◽  
Hydraulic Parameters ◽  
Natural Boundary ◽  
Soil Water Dynamics ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic ◽  
Natural Boundary Conditions

Abstract. In situ observations of soil water state variables under natural boundary conditions are often used to estimate the soil hydraulic properties. However, many contributions to the soil hydrological literature have demonstrated that the information content of such data is insufficient to accurately and precisely estimate all the soil hydraulic parameters. In this case study, we explored to which degree prior information about the soil hydraulic parameters can help improve parameter identifiability in inverse modelling of in situ soil water dynamics under natural boundary conditions. We used percentages of sand, silt, and clay as input variables to the ROSETTA pedotransfer function that predicts the parameters in the van Genuchten-Mualem (VGM) model of the soil hydraulic functions. To derive additional information about the correlation structure of the predicted parameters, which is not readily provided by ROSETTA, we employed a Monte Carlo approach. We formulated three prior distributions that incorporate to different extents the prior information about the VGM parameters derived with ROSETTA. The inverse problem was posed in a formal Bayesian framework and solved using Markov chain Monte Carlo (MCMC) simulation with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. Synthetic and real-world soil water content data were used to illustrate the approach. The results of this study demonstrated that prior information about the soil hydraulic parameters significantly improved parameter identifiability and that this approach was effective and robust, even in case of biased prior information. To be effective and robust, however, it was essential to use a prior distribution that incorporates information about parameter correlation.

Exploring hydrological processes at a small agricultural catchment in the Czech Republic

2021 ◽  
Author(s):  
Tailin Li ◽  
Nina Noreika ◽  
Jakub Jeřábek ◽  
Tomáš Dostál ◽  
David Zumr
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Hydrological Processes ◽  
Hydraulic Parameters ◽  
Rainfall Runoff ◽  
The Czech Republic ◽  
Mike She ◽  
Stream Discharge ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

<p>A better understanding of hydrological processes in agricultural catchments is not only crucial to hydrologists but also helpful for local farmers. Therefore, we have built the freely-available web-based WALNUD dataset (Water in Agricultural Landscape – NUčice Database) for our experimental catchment Nučice (0.53 km<sup>2</sup>), the Czech Republic. We have included observed precipitation, air temperature, stream discharge, and soil moisture in the dataset. Furthermore, we have applied numerical modelling techniques to investigate the hydrological processes (e.g. soil moisture variability, water balance) at the experimental catchment using the dataset.</p><p>The Nučice catchment, established in 2011, serves for the observation of rainfall-runoff processes, soil erosion and water balance of the cultivated landscape. The average altitude is 401 m a.s.l., the mean land slope is 3.9 %, and the climate is humid continental (mean annual temperature 7.9 °C, average annual precipitation 630 mm). The catchment consists of three fields covering over 95 % of the area. There is a narrow stream which begins as a subsurface drainage pipe in the uppermost field draining the water at catchment. The typical crops are winter wheat, rapeseed, mustard and alfalfa. The installed equipment includes a standard meteorological station, several rain gauges distributed in the area of the basin, and an H flume to monitor the stream discharge, water turbidity and basic water quality indicators. The soil water content (at point scale) and groundwater level are also recorded. Recently, we have installed two cosmic-ray soil moisture sensors (StyX Neutronica) to estimate large-scale topsoil water content at the catchment.</p><p>Even though the soil management and soil properties in the fields of Nučice seem to be nearly homogeneous, we have observed variability in the topsoil moisture pattern. The method for the explanation of the soil water regime was the combination of the connectivity indices and numerical modelling. The soil moisture profiles from the point-scale sensors were processed in a 1-D physically-based soil water model (HYDRUS-1D) to optimize the soil hydraulic parameters. Further, the soil hydraulic parameters were used as input into a 3D spatially-distributed model, MIKE-SHE. The MIKE-SHE simulation has been mainly calibrated with rainfall-runoff observations. Meanwhile, the spatial patterns of the soil moisture were assessed from the simulation for both dry and wet catchment conditions. From the MIKE-SHE simulation, the optimized soil hydraulic parameters have improved the estimation of soil moisture dynamics and runoff generation. Also, the correlation between the observed and simulated soil moisture spatial patterns showed different behaviors during the dry and wet catchment conditions.</p><p>This study has been supported by the Grant Agency of the Czech Technical University in Prague, grant No. SGS20/156/OHK1/3T/11 and the Project SHui which is co-funded by the European Union Project: 773903 and the Chinese MOST.</p>

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

<p>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 × 90 cm × 5.6 cm (height × length × width) was used.  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.  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 × 2.44 m × 0.40 m) and finally transition to field deployment.</p>

Soil Hydraulic Parameters and Surface Soil Moisture of a Tilled Bare Soil Plot Inversely Derived from L-Band Brightness Temperatures

2014 ◽  
Vol 13 (1) ◽  
pp. vzj2013.04.0075 ◽  
Author(s):  
M. Dimitrov ◽  
J. Vanderborght ◽  
K. G. Kostov ◽  
K. Z. Jadoon ◽  
L. Weihermüller ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Soil ◽  
Bare Soil ◽  
Hydraulic Parameters ◽  
Surface Soil Moisture ◽  
Brightness Temperatures ◽  
Soil Hydraulic Parameters ◽  
L Band ◽  
Soil Hydraulic

In-situ soil water dynamics under different irrigation methods in North East India

2017 ◽  
Vol 4 (2) ◽  
Author(s):  
JOY K DEY ◽  
LALA IP RAY ◽  
Y. MARWEIN
Keyword(s):  
Soil Water ◽  
Drip Irrigation ◽  
Clayey Soil ◽  
Root Zone ◽  
Soil Layer ◽  
Water Dynamics ◽  
Soil Water Dynamics ◽  
Irrigation Methods ◽  
North East

Availability of in-situ soil water plays a major role in exploiting the potential yield of crops under irrigated conditions. Depending on type of irrigation, variations of soil water is mostly observed at different soil depths within the root zone. The deviation of soil water at the edaphic zone becomes a deciding factor in assuring optimum yield. As availability of irrigation water is a great concern during non-rainy season, water saving irrigation techniques need to be adopted to maximize the productivity under hilly terrain. An experiment was laid out with potato as a test crop under the valley region of Meghalaya plateau on sandy clayey soil to study in-situ soil water dynamics under three different irrigation methods viz. furrow, micro-sprinkler and gravity-fed drip. Irrigation was scheduled at every weekly basis to restore back the soil water required to achieve the field capacity. Mean value of soil water up to 15 cm depth was 21.75, 22.65 and 23.45%, however, range (minimum to maximum) was 16.21-29.17; 15.56-29.21 and 17.84-28.97% for furrow, micro-sprinkler and gravity-fed drip irrigation, respectively. Co-efficient of variation was found to be the maximum (4.65%) for furrow over other two types of irrigations during the weekly interval. Deviation of in-situ soil water was found to vary rapidly at upper layer (30 cm) under furrow method of irrigation; but at deeper soil layer rapid variation was not observed. Water use efficiency of potato was evaluated to be 14.66, 18.78, 20.63 kg ha-1 mm-1 for furrow, micro-sprinkler and gravity-fed drip irrigation, respectively.

scholarly journals Bayesian inverse modelling of in situ soil water dynamics: using prior information about the soil hydraulic properties

2011 ◽  
Vol 8 (1) ◽  
pp. 2019-2063 ◽  
Author(s):  
B. Scharnagl ◽  
J. A. Vrugt ◽  
H. Vereecken ◽  
M. Herbst
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Vadose Zone ◽  
Hydraulic Properties ◽  
Prior Information ◽  
Hydraulic Parameters ◽  
Soil Hydraulic Properties ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

Abstract. In situ observations of soil water state variables under natural boundary conditions are often used to estimate field-scale soil hydraulic properties. However, many contributions to the soil hydrological literature have demonstrated that the information content of such data is insufficient to reliably estimate all the soil hydraulic parameters. In this case study, we tested whether prior information about the soil hydraulic properties could help improve the identifiability of the van Genuchten-Mualem (VGM) parameters. Three different prior distributions with increasing complexity were formulated using the ROSETTA pedotransfer function (PTF) with input data that constitutes basic soil information and is readily available in most vadose zone studies. The inverse problem was posed in a formal Bayesian framework and solved using Markov chain Monte Carlo (MCMC) simulation with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. Synthetic and real-world soil water content data were used to illustrate our approach. The results of this study corroborate and explicate findings previously reported in the literature. Indeed, soil water content data alone contained insufficient information to reasonably constrain all VGM parameters. The identifiability of these soil hydraulic parameters was substantially improved when an informative prior distribution was used with detailed knowledge of the correlation structure among the respective VGM parameters. A biased prior did not distort the results, which inspires confidence in the robustness and effectiveness of the presented method. The Bayesian framework presented in this study can be applied to a wide range of vadose zone studies and provides a blueprint for the use of prior information in inverse modelling of soil hydraulic properties at various spatial scales.

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