Assessment of improved soil hydraulic parameters for soil water content simulation and irrigation scheduling

2015 ◽  
Vol 33 (4) ◽  
pp. 247-264 ◽  
Author(s):  
N. K. Garg ◽  
Manika Gupta
2011 ◽  
Vol 8 (1) ◽  
pp. 2019-2063 ◽  
Author(s):  
B. Scharnagl ◽  
J. A. Vrugt ◽  
H. Vereecken ◽  
M. Herbst

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.


HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 549f-550
Author(s):  
Mongi Zekri ◽  
Bruce Schaffer ◽  
Stephen K. O'Hair ◽  
Roberto Nunez-Elisea ◽  
Jonathan H. Crane

In southern Florida, most tropical fruit crops between Biscayne and Everglades National Parks are irrigated at rates and frequencies based on experience and observations of tree growth and fruit yield rather than on reliable quantitative information of actual water use. This approach suggests that irrigation rates may be excessive and could lead to leaching of agricultural chemicals into the groundwater in this environmentally sensitive area. Therefore, a study is being conducted to increase water use efficiency and optimize irrigation by accurately scheduling irrigation using a very effective management tool (EnviroScan, Sentek Environmental Innovations, Pty., Kent, Australia) that continuously monitors soil water content with highly accurate capacitance multi-sensor probes installed at several depths within the soil profile. The system measures crop water use by monitoring soil water depletion rates and allows the maintenance of soil water content within the optimum range (below field capacity and well above the onset of plant water stress). The study is being conducted in growers' orchards with three tropical fruit crops (avocado, carambola, and `Tahiti' lime) to facilitate rapid adoption and utilization of research results.


2021 ◽  
Author(s):  
Tailin Li ◽  
Nina Noreika ◽  
Jakub Jeřábek ◽  
Tomáš Dostál ◽  
David Zumr

<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>


Biologia ◽  
2007 ◽  
Vol 62 (5) ◽  
Author(s):  
Horst Gerke ◽  
Rolf Kuchenbuch

AbstractPlants can affect soil moisture and the soil hydraulic properties both directly by root water uptake and indirectly by modifying the soil structure. Furthermore, water in plant roots is mostly neglected when studying soil hydraulic properties. In this contribution, we analyze effects of the moisture content inside roots as compared to bulk soil moisture contents and speculate on implications of non-capillary-bound root water for determination of soil moisture and calibration of soil hydraulic properties.In a field crop of maize (Zea mays) of 75 cm row spacing, we sampled the total soil volumes of 0.7 m × 0.4 m and 0.3 m deep plots at the time of tasseling. For each of the 84 soil cubes of 10 cm edge length, root mass and length as well as moisture content and soil bulk density were determined. Roots were separated in 3 size classes for which a mean root porosity of 0.82 was obtained from the relation between root dry mass density and root bulk density using pycnometers. The spatially distributed fractions of root water contents were compared with those of the water in capillary pores of the soil matrix.Water inside roots was mostly below 2–5% of total soil water content; however, locally near the plant rows it was up to 20%. The results suggest that soil moisture in roots should be separately considered. Upon drying, the relation between the soil and root water may change towards water remaining in roots. Relations depend especially on soil water retention properties, growth stages, and root distributions. Gravimetric soil water content measurement could be misleading and TDR probes providing an integrated signal are difficult to interpret. Root effects should be more intensively studied for improved field soil water balance calculations.


Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1858 ◽  
Author(s):  
Jesús María Domínguez-Niño ◽  
Gerard Arbat ◽  
Iael Raij-Hoffman ◽  
Isaya Kisekka ◽  
Joan Girona ◽  
...  

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.


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