scholarly journals Development of Pedo-Transfer Functions for the Saturated Hydraulic Conductivity of Forest Soil in South Korea Considering Forest Stand and Site Characteristics

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2217
Author(s):  
Honggeun Lim ◽  
Hyunje Yang ◽  
Kun Woo Chun ◽  
Hyung Tae Choi
Keyword(s):  
Hydraulic Conductivity ◽  
South Korea ◽  
Soil Properties ◽  
Forest Soil ◽  
Transfer Functions ◽  
Forest Stand ◽  
Saturated Hydraulic Conductivity ◽  
Temperate Climate ◽  
Topographic Features ◽  
Site Characteristics

The saturated hydraulic conductivity (Ks) is one of the most important soil properties for many hydrological simulation models. Especially in South Korea, analyzing the Ks of the forest soil is essential for understanding the water cycle throughout the country, because forests cover almost two-thirds of the whole country. However, few studies have focused on the forest soil in the temperate climate zone on a nationwide scale. In this study, 1456 forest soil samples were collected throughout South Korea and pedo-transfer functions employed to predict the Ks were developed. The non-linearities of the soil and topographic features were considered with the pretreatment of variables, and the variance inflation factor was used for treating the multicollinearity problem. The forest stand and site characteristics were also categorized by an ANOVA and post hoc test due to their diversity. As a result, the Ks values were different for various forest stands and site characteristics, which was statistically significant. Additionally, the model performance was higher when both soil properties and topographic features were considered. The sensitivity analysis showed that the Ks was highly affected by the bulk density, sand fraction, slope, and upper catchment area. Therefore, the topographic features were as important in predicting the Ks as the soil properties of the forest soil.

scholarly journals Analysis of Hydraulic Properties of Indian Forest Soil

2018 ◽  
Vol 7 (1) ◽  
pp. 12
Author(s):  
Shwetha Prasanna
Keyword(s):  
Hydraulic Conductivity ◽  
Spatial Variability ◽  
Soil Properties ◽  
Forest Soil ◽  
Hydraulic Properties ◽  
Water Retention ◽  
Saturated Hydraulic Conductivity ◽  
Soil Hydraulic Properties ◽  
Soil Hydraulic ◽  
High Degree

Soils are a product of the factors of formation and continuously change over the earth’s surface. The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. Soils are characterized by high degree of spatial variability due to the combined effect of physical, chemical or biological processes that operate with different intensities and at different scales. The spatial variability of soil hydraulic properties helps us to find the subsurface flux of water. The most frequently used hydraulic properties are soil water retention curve and saturated hydraulic conductivity. Both these hydraulic properties exhibit a high degree of spatial and temporal variability. The primary objective of this study was to analyze the spatial variability of hydraulic properties of forest soils of Pavanje river basin. Correlation analysis technique has been used to analyze various soil properties. Spatial variability of the forested hillslope soils at different depths varied considerably among the soil hydraulic properties. The spatial variability of water retention at all the different pressure head is low at the top layers, and increases towards the bottom layers. The saturated hydraulic conductivity is almost same in the top layers, but more in the bottom layers of forest soil.

Spatial relationship between soil hydraulic and soil physical properties in a farm field

2009 ◽  
Vol 89 (4) ◽  
pp. 473-488 ◽  
Author(s):  
A Biswas ◽  
B C Si
Keyword(s):  
Hydraulic Conductivity ◽  
Physical Properties ◽  
Soil Properties ◽  
Shape Parameter ◽  
Spatial Relationship ◽  
Soil Physical Properties ◽  
Saturated Hydraulic Conductivity ◽  
Hydraulic Parameters ◽  
Curve Shape ◽  
Scaling Parameter

The relationship between soil properties may vary with their spatial separation. Understanding this relationship is important in predicting hydraulic parameters from other soil physical properties. The objective of this study was to identify spatially dependent relationships between hydraulic parameters and soil physical properties. Regularly spaced (3-m) undisturbed soil samples were collected along a 384 m transect from a farm field at Smeaton, Saskatchewan. Saturated hydraulic conductivity, the soil water retention curve, and soil physical properties were measured. The scaling parameter, van Genuchten scaling parameter α (VGα), and curve shape parameter, van Genuchten curve shape parameter n (VGn), were obtained by fitting the van Genuchten model to measured soil moisture retention data. Results showed that the semivariograms of soil properties exhibited two different spatial structures at spatial separations of 20 and 120 m, respectively. A strong spatial structure was observed in organic carbon, saturated hydraulic conductivity (Ks), sand, and silt; whereas a weak structure was found for VGα and VGn. Correlation circle analysis showed strong spatially dependent relationships of Ks and VGα; with soil physical properties, but weak relationships of θs and VGn with soil physical properties. The spatially dependent relationships between soil physical and soil hydraulic parameters should be taken into consideration when developing pedotransfer functions. Key words: Spatial relationship, geostatistics, linear coregionalization model, principal component analysis, pedotransfer function

Multiple AI model integration strategy—Application to saturated hydraulic conductivity prediction from easily available soil properties

2020 ◽  
Vol 196 ◽  
pp. 104449 ◽  
Author(s):  
Mahsa H. Kashani ◽  
Mohammad Ali Ghorbani ◽  
Mahmood Shahabi ◽  
Sujay Raghavendra Naganna ◽  
Lamine Diop
Keyword(s):  
Hydraulic Conductivity ◽  
Soil Properties ◽  
Saturated Hydraulic Conductivity ◽  
Model Integration ◽  
Integration Strategy

Evaluation of some selected soil properties of a drip irrigated tomato field at different moisture regimes in South-Western Nigeria

2021 ◽  
Vol 6 (2) ◽  
Author(s):  
E.O. Ogundipe
Keyword(s):  
Organic Matter ◽  
Hydraulic Conductivity ◽  
Soil Properties ◽  
Bulk Density ◽  
Soil Texture ◽  
Organic Matter Content ◽  
Infiltration Rate ◽  
Matter Content ◽  
Saturated Hydraulic Conductivity ◽  
Tomato Field

Soil properties are important to the development of agricultural crops. This study determined some selected soil properties of a drip irrigated tomato (Lycopersicon esculentum M.) field at different moisture regime in South-Western Nigeria. The experiment was carried out using Randomized Complete Block Design with frequency and depth of irrigation application as the main plot and sub-plot, respectively in three replicates. Three frequencies (7, 5 and 3 days) and three depths equivalent to 100, 75 and 50% of water requirement were used. Undisturbed and disturbed soil samples were collected from 0-5, 5-10, 10-20 and 20-30 cm soil layers for the determination of some soil properties (soil texture, organic matter content, bulk density, infiltration rate and saturated hydraulic conductivity) were determined using standard formulae. Soil Water Content (SWC) monitoring was conducted every two days using a gravimetric technique. The soil texture was sandy loam for all the soil depths; average value of soil organic matter was highest (1.8%) in the 0-5 cm surface layer and decreased with soil depth; the soil bulk density value before and after irrigation experiment ranged from 1.48 and 1.73 g/cm3 and 1.5 and 1.76 g/cm3, respectively; there was a rapid reduction in the initial infiltration and final infiltration rate. Saturated hydraulic conductivity show similar trend although the 20-30 cm layer had the lowest value (50.84 mm/h); the SWC affect bulk density during the growing season. The study showed that soil properties especially bulk density and organic matter content affect irrigation water movement at different depth..

Data forcing errors resulting from lack of harmonization and standardization in measurement methodologies: A comparison of soil hydrophysical data from a large EU database.

2020 ◽  
Author(s):  
Martine van der Ploeg ◽  
Attila Nemes
Keyword(s):  
Organic Matter ◽  
Hydraulic Conductivity ◽  
Bulk Density ◽  
Large Scale ◽  
Water Retention ◽  
Transfer Functions ◽  
Landscape Heterogeneity ◽  
Organic Matter Content ◽  
Saturated Hydraulic Conductivity ◽  
Soil Water Retention

<p>Soil hydro-physical properties —such as soil water retention, (un)saturated hydraulic conductivity, shrinkage and swelling, organic matter content, texture (particle distribution), structure (soil aggregation/pore structure)and bulk density— are used in many sub(surface) modeling applications. Reliable soil-hydrophysical properties are key to proper predictions with such models, yet the harmonization and standardization of these properties has not received much attention. Lack of harmonization and standardization may lead to heterogeneity in data as a result of differences in methodologies, rather than real landscape heterogeneity. A need and scope has been identified to better harmonize, innovate, and standardize methodologies regarding measuring soil hydraulic properties that form the information base of many derived products in support of EU policy. With this identified need in mind the Soil Program on Hydro-Physics via International Engagement (SOPHIE) was initiated in 2017. Besides developing new activities that may advise future measurements, we also explore historic data and metadata and mine its relevant contents. The European Hydro-pedological Data Inventory (EU-HYDI), the largest European database on measured soil hydrophysical properties, is – to date – rather under-explored in this sense, which served as motivation for this work.</p><p>From EU-HYDI we selected those records that were complete for soil texture, bulk density and organic matter, and fitted pedo-transfer functions separately for particular water retention points (at heads of 0, 2.5, 10, 100, 300, 1000, 3000, 15000 cm) and saturated hydraulic conductivity by multi-linear regression. We then subtracted the observed retention and hydraulic conductivity values from their estimated counterparts, and grouped the residuals by measurement methodologies. The results show that there can be significant differences between different methodologies and sample sizes used to obtain the water retention and hydraulic conductivity in the laboratory. The results thus show that the EU-data that may underlie large scale modelling may introduce errors in the forcing data that are attributed to a lack of harmonization and standardization in currently used measurement protocols.</p>

scholarly journals Improved calibration of the Green–Ampt infiltration module in the EROSION-2D/3D model using a rainfall-runoff experiment database

SOIL ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 241-253
Author(s):  
Hana Beitlerová ◽  
Jonas Lenz ◽  
Jan Devátý ◽  
Martin Mistr ◽  
Jiří Kapička ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Hydraulic Conductivity ◽  
Soil Erosion ◽  
3D Model ◽  
Transfer Functions ◽  
State Of The Art ◽  
The State ◽  
Saturated Hydraulic Conductivity ◽  
Infiltration Process ◽  
Calibration Parameter

Abstract. Soil infiltration is one of the key factors that has an influence on soil erosion caused by rainfall. Therefore, a well-represented infiltration process is a necessary precondition for successful soil erosion modelling. Complex natural conditions do not allow the full mathematical description of the infiltration process, and additional calibration parameters are required. The Green–Ampt-based infiltration module in the EROSION-2D/3D model introduces a calibration parameter “skinfactor” to adjust saturated hydraulic conductivity. Previous studies provide skinfactor values for several combinations of soil and vegetation conditions. However, their accuracies are questionable, and estimating the skinfactors for other than the measured conditions yields significant uncertainties in the model results. This study brings together an extensive database of rainfall simulation experiments, the state-of-the-art model parametrisation method and linear mixed-effect models to statistically analyse relationships between soil and vegetation conditions and the model calibration parameter skinfactor. New empirically based transfer functions for skinfactor estimation significantly improving the accuracy of the infiltration module and thus the overall EROSION-2D/3D model performance are provided in this study. Soil moisture and bulk density were identified as the most significant predictors explaining 82 % of the skinfactor variability, followed by the soil texture, vegetation cover and impact of previous rainfall events. The median absolute percentage error of the skinfactor prediction was improved from 71 % using the currently available method to 30 %–34 % using the presented transfer functions, which led to significant decrease in error propagation into the model results compared to the present method. The strong logarithmic relationship observed between the calibration parameter and soil moisture however indicates high overestimation of infiltration for dry soils by the algorithms implemented in EROSION-2D/3D and puts the state-of-the-art parametrisation method in question. An alternative parameter optimisation method including calibration of two Green–Ampt parameters' saturated hydraulic conductivity and water potential at the wetting front was tested and compared with the state-of-the-art method, which paves a new direction for future EROSION-2D/3D model parametrisation.

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