Pedogenic processes and soil–landform relationships for identification of yield-limiting soil properties

Soil Research ◽  
2017 ◽  
Vol 55 (3) ◽  
pp. 273 ◽  
Author(s):  
Duraisamy Vasu ◽  
Surendra Kumar Singh ◽  
Pramod Tiwary ◽  
Padikkal Chandran ◽  
Sanjay Kumar Ray ◽  
...  

Knowledge of soil–landform relationships helps in understanding the dominant pedogenic processes causing variations in soil properties within and between landforms. In this study, we investigated how major pedogenic processes in three landform positions of the semi-arid Deccan Plateau (India) have led to current plant yield-limiting soil properties. For this, we characterised 26 pedons from three landforms – piedmont, alluvial plain and valley – and performed factor analysis on the dataset. As the frequency distribution of the dataset was highly skewed for most of the soil properties, landform-wise partition and log-transformation were performed before studying soil variability within landforms. Results indicated that two factors explained 56, 71 and 64% of variability in soil properties in piedmonts, alluvial plains and valleys, respectively. The major soils in lower piedmonts (Typic Haplustalfs and Typic Rhodustalfs) were spatially associated with Vertisols (Sodic Haplusterts) occurring in alluvial plains and valleys. The soil properties in alluvial plains and valleys (Vertic Haplustepts, Sodic Haplusterts and Typic Ustifluvents) were modified due to regressive pedogenic processes. These soils were characterised by high pH (8.5–9.8), exchangeable sodium percentage (16.5–46.6) and poor saturated hydraulic conductivity (<1cmh–1). Subsoil sodicity induced by the presence of pedogenic calcium carbonate impaired the hydraulic conductivity. Subsoil sodicity and poor saturated hydraulic conductivity were identified as major yield-limiting soil properties. The relationships found between specific soil properties, surface and subsurface horizons, and position in the landscape helped to determine the dominant pedogenic processes and how these influenced current soil properties and their effects on crop yield.

2009 ◽  
Vol 89 (4) ◽  
pp. 473-488 ◽  
Author(s):  
A Biswas ◽  
B C Si

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


2020 ◽  
Vol 196 ◽  
pp. 104449 ◽  
Author(s):  
Mahsa H. Kashani ◽  
Mohammad Ali Ghorbani ◽  
Mahmood Shahabi ◽  
Sujay Raghavendra Naganna ◽  
Lamine Diop

Author(s):  
E.O. Ogundipe

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..


CATENA ◽  
2021 ◽  
Vol 207 ◽  
pp. 105680
Author(s):  
Yurong Cai ◽  
Yuchun Yan ◽  
Chu Wang ◽  
Dawei Xu ◽  
Xu Wang ◽  
...  

2021 ◽  
Vol 13 (4) ◽  
pp. 1593-1612
Author(s):  
Surya Gupta ◽  
Tomislav Hengl ◽  
Peter Lehmann ◽  
Sara Bonetti ◽  
Dani Or

Abstract. The saturated soil hydraulic conductivity (Ksat) is a key parameter in many hydrological and climate models. Ksat values are primarily determined from basic soil properties and may vary over several orders of magnitude. Despite the availability of Ksat datasets in the literature, significant efforts are required to combine the data before they can be used for specific applications. In this work, a total of 13 258 Ksat measurements from 1908 sites were assembled from the published literature and other sources, standardized (i.e., units made identical), and quality checked in order to obtain a global database of soil saturated hydraulic conductivity (SoilKsatDB). The SoilKsatDB covers most regions across the globe, with the highest number of Ksat measurements from North America, followed by Europe, Asia, South America, Africa, and Australia. In addition to Ksat, other soil variables such as soil texture (11 584 measurements), bulk density (11 262 measurements), soil organic carbon (9787 measurements), moisture content at field capacity (7382), and wilting point (7411) are also included in the dataset. To show an application of SoilKsatDB, we derived Ksat pedotransfer functions (PTFs) for temperate regions and laboratory-based soil properties (sand and clay content, bulk density). Accurate models can be fitted using a random forest machine learning algorithm (best concordance correlation coefficient (CCC) equal to 0.74 and 0.72 for temperate area and laboratory measurements, respectively). However, when these Ksat PTFs are applied to soil samples obtained from tropical climates and field measurements, respectively, the model performance is significantly lower (CCC = 0.49 for tropical and CCC = 0.10 for field measurements). These results indicate that there are significant differences between Ksat data collected in temperate and tropical regions and Ksat measured in the laboratory or field. The SoilKsatDB dataset is available at https://doi.org/10.5281/zenodo.3752721 (Gupta et al., 2020) and the code used to extract the data from the literature and the applied random forest machine learning approach are publicly available under an open data license.


2018 ◽  
Vol 7 (1) ◽  
pp. 12
Author(s):  
Shwetha Prasanna

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.


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