Retrieving soil-water retention curve at the wet part by remote sensing

Author(s):  
Zampela Pittaki-Chrysodonta ◽  
Per Moldrup ◽  
Bo V. Iversen ◽  
Maria Knadel ◽  
Lis W. de Jonge

<p>The soil water retention curve (SWRC) at the wet part is important for understanding and modeling the water flow and solute transport in the vadose zone. However, direct measurements of SWRC is often laborious and time consuming processes. The Campbell function is a simple method to fit the measured data. The parameters of the Campbell function have been recently proven that can be predicted using visible-near-infrared spectroscopy. However, predicting the SWRC using image spectral data could be an inexpensive and fast method. In this study, 100-cm<sup>3</sup> soil samples from Denmark were included and the soil water content was measured at a soil-water matric potential from pF 1 [log(10)= pF 1] up to pF 3. The anchored Campbell soil-water retention function was selected instead of the original. Specifically, in this function the equation is anchored at the soil-water content at pF 3 (θ<sub>pF3</sub>) instead at the saturated water content. The image spectral data were correlated with the Campbell parameters [θ<sub>pF3</sub>, and the pore size distribution index (Campbell b). The results showed the potential of remote sensing to be used as a fast and alternative method for predicting the SWRC in a large-scale.</p>

Biologia ◽  
2006 ◽  
Vol 61 (19) ◽  
Author(s):  
Andrea Hagyó ◽  
Kálmán Rajkai ◽  
Zoltán Nagy

AbstractWater retention characteristics, rainfall, throughfall and soil water content dynamics were investigated in a low mountain area to compare a forest and a grassland. The soil water retention curve of the topsoil has similar shape in both studied areas, however that of the deeper soil layer shows more difference. We determined the precipitation depth, duration and intensity values of rainfall events. The relationship between rainfall and throughfall depth was described in linear regressions. Interception was calculated as the difference between rainfall and throughfall plus stemflow, assuming stemflow to be 3% of rainfall. Soil water content dynamics show a similar trend in the two vegetation types but the drying is more intensive in the forest in the soil layers deeper than 20 cm during the growing-season.


2018 ◽  
Vol 22 (9) ◽  
pp. 4621-4632
Author(s):  
Chen-Chao Chang ◽  
Dong-Hui Cheng

Abstract. Traditional models employed to predict the soil water retention curve (SWRC) from the particle size distribution (PSD) always underestimate the water content in the dry range of the SWRC. Using the measured physical parameters of 48 soil samples from the UNSODA unsaturated soil hydraulic property database, these errors were proven to originate from an inaccurate estimation of the pore size distribution. A method was therefore proposed to improve the estimation of the water content at high suction heads using a pore model comprising a circle-shaped central pore connected to slit-shaped spaces. In this model, the pore volume fraction of the minimum pore diameter range and the corresponding water content were accordingly increased. The predicted SWRCs using the improved method reasonably approximated the measured SWRCs, which were more accurate than those obtained using the traditional method and the scaling approach in the dry range of the SWRC.


2015 ◽  
Vol 47 (2) ◽  
pp. 312-332 ◽  
Author(s):  
Hossein Bayat ◽  
Eisa Ebrahimi

This study investigated the impact of different input variables on the predictability of the water content using soil water retention curve (SWRC) models. The particle and aggregate size distribution model parameters were calculated by fitting the Perrier model to the related distributions for 75 soil samples. Nine SWRC models were fitted to the experimental data and their coefficients were obtained. The regression method was used to estimate the coefficients for nine SWRC models at three input levels. Cluster analysis classified the SWRC models into more homogeneous groups according to the accuracy of their predictions. The SWRC estimated using the Gardner model had the highest accuracy, but it was not an appropriate model for the soils because of its low fitting accuracy. Boltzman, Campbell, and Fermi models obtained the highest accuracy after the Gardner model. The Durner model yielded the lowest prediction accuracy due to the lack of correlation between the input variables and coefficients in this model. Thus, the water content predictions obtained using different SWRC models varied because different input variables were employed.


2017 ◽  
Vol 16 (4) ◽  
pp. 869-877
Author(s):  
Vasile Lucian Pavel ◽  
Florian Statescu ◽  
Dorin Cotiu.ca-Zauca ◽  
Gabriela Biali ◽  
Paula Cojocaru

Pedosphere ◽  
2006 ◽  
Vol 16 (2) ◽  
pp. 137-146 ◽  
Author(s):  
Guan-Hua HUANG ◽  
Ren-Duo ZHANG ◽  
Quan-Zhong HUANG

2015 ◽  
Vol 68 (2) ◽  
pp. 207-213
Author(s):  
Luciana Portugal Menezes ◽  
Waldyr Lopes Oliveira Filho ◽  
Cláudio Henrique Carvalho Silva

AbstractReliable measurements of the Soil Water Retention Curve, SWRC, are necessary for solving unsaturated flow problems. In this sense, a method to obtain the SWRC of a silty sand using a flow pump, as well as details about procedures and some results, are herein presented. The overall conclusion is that the new method is very convenient, fully automated, and produces reliable results in a fast and easy way, making the technique very promising.


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