Pedotransfer functions to estimate bulk density from soil properties and environmental covariates: Rio Doce basin

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.

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Relationships and Spatial Structure of Soil Physical Properties in a Ten-Year Corn-Cotton Rotation Field

International Journal of Applied Geospatial Research ◽

10.4018/ijagr.2021070103 ◽

2021 ◽

Vol 12 (3) ◽

pp. 34-46

Author(s):

Peter A. Y. Ampim ◽

Alton B. Johnson ◽

Samuel G. K. Adiku

Keyword(s):

Soil Properties ◽

Bulk Density ◽

Hydraulic Properties ◽

Soil Physical Properties ◽

Soil Samples ◽

Pedotransfer Functions ◽

Silt Loam ◽

Curve Shape ◽

Regression Analyses ◽

Shape Parameters

This study quantified the relationships between soil, textural, and hydraulic properties at the field-scale for a conventional tilled Memphis silt loam that had undergone a 10-year corn and cotton rotation and described their spatial variability. Composite soil samples collected from the plow layer at 272 nodes on 15 x 15 m grids were analyzed for texture and bulk density. These values were used as pedotransfer functions to predict unsaturated (Ko) and saturated hydraulic (Ks) conductivities as well as the van Genuchten curve shape parameters α and n. Regression analyses quantified relationships between the measured and model predicted soil properties. While correlations between textural and model predicted soil properties including bulk density were significant (p<0.05), those between sand and clay, clay and n, clay and α were not. Sand and silt appeared to be better predictors of soil hydraulic conductivity and the van Genuchten curve shape parameters for the soil investigated. Spatial dependence was strong for sand, silt, bulk density, Ko, α and n, and moderate for clay and Ks.

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A generally applicable pedotransfer function that estimates field capacity and permanent wilting point from soil texture and bulk density

Canadian Journal of Soil Science ◽

10.4141/cjss07120 ◽

2008 ◽

Vol 88 (5) ◽

pp. 761-774 ◽

Cited By ~ 23

Author(s):

J. A. P. Pollacco

Keyword(s):

Organic Matter ◽

Soil Moisture ◽

Bulk Density ◽

Soil Texture ◽

The United States ◽

Pedotransfer Functions ◽

Pedotransfer Function ◽

Data Set ◽

Wide Range ◽

Fitting Parameters

Hydrological models require the determination of fitting parameters that are tedious and time consuming to acquire. A rapid alternative method of estimating the fitting parameters is to use pedotransfer functions. This paper proposes a reliable method to estimate soil moisture at -33 and -1500 kPa from soil texture and bulk density. This method reduces the saturated moisture content by multiplying it with two non-linear functions depending on sand and clay contents. The novel pedotransfer function has no restrictions on the range of the texture predictors and gives reasonable predictions for soils with bulk density that varies from 0.25 to 2.16 g cm-3. These pedotransfer functions require only five parameters for each pressure head. It is generally accepted that the introduction of organic matter as a predictor improves the outcomes; however it was found by using a porosity based pedotransfer model, using organic matter as a predictor only modestly improves the accuracy. The model was developed employing 18 559 samples from the IGBP-DIS soil data set for pedotransfer function development (Data and Information System of the International Geosphere Biosphere Programme) database that embodies all major soils across the United States of America. The function is reliable and performs well for a wide range of soils occurring in very dry to very wet climates. Climatical grouping of the IGBP-DIS soils was proposed (aquic, tropical, cryic, aridic), but the results show that only tropical soils require specific grouping. Among many other different non-climatical soil groups tested, only humic and vitric soils were found to require specific grouping. The reliability of the pedotransfer function was further demonstrated with an independent database from Northern Italy having heterogeneous soils, and was found to be comparable or better than the accuracy of other pedotransfer functions found in the literature. Key words: Pedotransfer functions, soil moisture, soil texture, bulk density, organic matter, grouping

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Pedotransfer functions for predicting heavy metals in natural soils using magnetic measures and soil properties

Journal of Geochemical Exploration ◽

10.1016/j.gexplo.2018.12.006 ◽

2019 ◽

Vol 197 ◽

pp. 212-219 ◽

Cited By ~ 13

Author(s):

Shamsollah Ayoubi ◽

Mostafa Karami

Keyword(s):

Heavy Metals ◽

Soil Properties ◽

Pedotransfer Functions ◽

Natural Soils

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Characterizing Soil Physical Properties for Soil Moisture Monitoring with the North Carolina Environment and Climate Observing Network

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-11-00104.1 ◽

2012 ◽

Vol 29 (7) ◽

pp. 933-943 ◽

Cited By ~ 14

Author(s):

Weinan Pan ◽

R. P. Boyles ◽

J. G. White ◽

J. L. Heitman

Keyword(s):

North Carolina ◽

Soil Moisture ◽

Physical Properties ◽

Soil Properties ◽

Water Content ◽

Bulk Density ◽

Soil Physical Properties ◽

The North ◽

Wide Range ◽

Soil Moisture Monitoring

Abstract Soil moisture has important implications for meteorology, climatology, hydrology, and agriculture. This has led to growing interest in development of in situ soil moisture monitoring networks. Measurement interpretation is severely limited without soil property data. In North Carolina, soil moisture has been monitored since 1999 as a routine parameter in the statewide Environment and Climate Observing Network (ECONet), but with little soils information available for ECONet sites. The objective of this paper is to provide soils data for ECONet development. The authors studied soil physical properties at 27 ECONet sites and generated a database with 13 soil physical parameters, including sand, silt, and clay contents; bulk density; total porosity; saturated hydraulic conductivity; air-dried water content; and water retention at six pressures. Soil properties were highly variable among individual ECONet sites [coefficients of variation (CVs) ranging from 12% to 80%]. This wide range of properties suggests very different behavior among sites with respect to soil moisture. A principal component analysis indicated parameter groupings associated primarily with soil texture, bulk density, and air-dried water content accounted for 80% of the total variance in the dataset. These results suggested that a few specific soil properties could be measured to provide an understanding of differences in sites with respect to major soil properties. The authors also illustrate how the measured soil properties have been used to develop new soil moisture products and data screening for the North Carolina ECONet. The methods, analysis, and results presented here have applications to North Carolina and for other regions with heterogeneous soils where soil moisture monitoring is valuable.

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Predicting Soil Bulk Density Using Advanced Pedotransfer Functions in an Arid Environment

Transactions of the ASABE ◽

10.13031/trans.56.9922 ◽

2013 ◽

pp. 963-976 ◽

Cited By ~ 1

Keyword(s):

Bulk Density ◽

Arid Environment ◽

Soil Bulk Density ◽

Pedotransfer Functions

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Profile Soil Property Estimation Using a VIS-NIR-EC-Force Probe

Transactions of the ASABE ◽

10.13031/trans.12049 ◽

2017 ◽

Vol 60 (3) ◽

pp. 683-692 ◽

Cited By ~ 5

Author(s):

Yongjin Cho ◽

Kenneth A. Sudduth ◽

Scott T. Drummond

Keyword(s):

Soil Properties ◽

Water Content ◽

Bulk Density ◽

Soil Property ◽

Soil Strength ◽

Reflectance Spectra ◽

Land Resource ◽

Strength Data ◽

Soil Sensors ◽

Combining Data

Abstract. Combining data collected in-field from multiple soil sensors has the potential to improve the efficiency and accuracy of soil property estimates. Optical diffuse reflectance spectroscopy (DRS) has been used to estimate many important soil properties, such as soil carbon, water content, and texture. Other common soil sensors include penetrometers that measure soil strength and apparent electrical conductivity (ECa) sensors. Previous field research has related these sensor measurements to soil properties such as bulk density, water content, and texture. A commercial instrument that can simultaneously collect reflectance spectra, ECa, and soil strength data is now available. The objective of this research was to relate laboratory-measured soil properties, including bulk density (BD), total organic carbon (TOC), water content (WC), and texture fractions to sensor data from this instrument. At four field sites in mid-Missouri, profile sensor measurements were obtained to 0.9 m depth, followed by collection of soil cores at each site for laboratory measurements. Using only DRS data, BD, TOC, and WC were not well-estimated (R2 = 0.32, 0.67, and 0.40, respectively). Adding ECa and soil strength data provided only a slight improvement in WC estimation (R2 = 0.47) and little to no improvement in BD and TOC estimation. When data were analyzed separately by major land resource area (MLRA), fusion of data from all sensors improved soil texture fraction estimates. The largest improvement compared to reflectance alone was for MLRA 115B, where estimation errors for the various soil properties were reduced by approximately 14% to 26%. This study showed promise for in-field sensor measurement of some soil properties. Additional field data collection and model development are needed for those soil properties for which a combination of data from multiple sensors is required. Keywords: NIR spectroscopy, Precision agriculture, Reflectance spectra, Soil properties, Soil sensing.

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Agro-forestry Systems as a Means to Achieve Carbon Co-benefits in Nepal

Journal of Forest and Livelihood ◽

10.3126/jfl.v13i1.15366 ◽

2016 ◽

Vol 13 (1) ◽

pp. 59-68

Author(s):

Roshan M. Bajracharya ◽

Him Lal Shrestha ◽

Ramesh Shakya ◽

Bishal K. Sitaula

Keyword(s):

Organic Carbon ◽

Soil Properties ◽

Soil Carbon ◽

Bulk Density ◽

Agricultural Land ◽

Carbon Stocks ◽

Community Forests ◽

C Stocks ◽

Soil Carbon Stocks ◽

Agro Forestry

Land management regimes and forest types play an important role in the productivity and accumulation of terrestrial carbon pools. While it is commonly accepted that forests enhance carbon sequestration and conventional agriculture causes carbon depletion, the effects of agro-forestry are not well documented. This study investigated the carbon stocks in biomass and soil, along with the selected soil properties in agro-forestry plots compared to community forests (CF) and upland farms in Chitwan, Gorkha and Rasuwa districts of Central Nepal during the year 2012-2013. We determined the total above ground biomass carbon, soil organic carbon (SOC) stocks and soil properties (bulk density, organic carbon per cent, pH, total nitrogen (TN), available phosphorus (P), exchangeable potassium (K), and cation exchange capacity (CEC)) on samples taken from four replicates of 500 m2 plots each in community forests, agro-forestry systems and agricultural land. The soil was sampled in two increments at 0-15 cm and 15-30 cm depths and intact cores removed for bulk density and SOC determination, while loose samples were separately collected for the laboratory analysis of other soil properties. The mean SOC percent and corresponding soil carbon stocks to 30 cm depth were generally highest in CF (3.71 and 3.69 per cent, and 74.98 and 76.24 t ha-1, respectively), followed by leasehold forest (LHF) (2.26 and 1.13 per cent and 40.72 and 21.34 t ha-1, respectively) and least in the agricultural land (3.05 and 1.09 per cent, and 63.54 and 19.42 t ha-1, respectively). This trend was not, however, observed in Chitwan, where agriculture (AG) had the highest SOC content (1.98 per cent) and soil carbon stocks (42.5 t ha-1), followed by CF (1.8 per cent and 41.2 t ha-1) and leasehold forests (1.56 per cent and 35.3 t ha-1) although the differences were not statistically significant. Other soil properties were not significantly different among land use types with the exceptions of pH, total N, available P and CEC in the Chitwan plots. Typically, SOC and soil carbon stocks (to 30cm depth) were positively correlated with each other and with TN and CEC. The AGB-C was expectantly highest in Rasuwa district CF (ranging from 107.3 to 260.3 t ha-1) due to dense growth and cool climate, followed by Gorkha (3.1 to 118.4 t ha-1), and least in Chitwan (17.6 to 95.2 t ha-1). The highest C stocks for agro-forestry systems in both above ground and soil were observed in Rasuwa, followed by Chitwan district. Besides forests, agro-forestry systems also hold good potential to store and accumulate carbon, hence they have scope for contributing to climate change mitigation and adaptation with co-benefits.Journal of Forest and Livelihood 13(1) May, 2015, page: 56-68

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THE CHANGE OF SANDY SOIL PROPERTIES AFTER ADDING CHARCOAL PRODUCED FROM A TRADITIONAL KILN IN THE MEKONG DELTA, VIET NAM

Scientific Journal of Tra Vinh University ◽

10.35382/18594816.1.42.2021.698 ◽

2021 ◽

Vol 1 (42) ◽

pp. 109-115

Author(s):

Binh Phan Khanh Huynh ◽

Tho Van Nguyen ◽

Vien My Tran

Keyword(s):

Soil Properties ◽

Bulk Density ◽

Sandy Soil ◽

Organic Matter Content ◽

Mekong Delta ◽

Exchange Capacity ◽

Matter Content ◽

Raw Material ◽

Control Treatment ◽

Viet Nam

This study aimed to use charcoal derived from the bamboo and melaleuca produced by traditional kiln applied to sandy soil growing mustard green (Brassica juncea L.). The charcoals were applied at three ratio (1%,2%, and 3%, which correspond to 10, 20, and 30 g charcoal/kg soil in pots) and the control treatment without charcoal. Soil properties were investigated including bulk density, pH, electrical conductivity (EC), cation exchange capacity (CEC), organic matter content, total nitrogen, and total phosphorous. The results showed that bulk density decreased in charcoal-treated soils. pH and EC were in the suitable range for plants.Nutrients and CEC of the soil in the charcoal treatment were significantly higher compared with the control (CEC increase 6.8% to 16%; TC increase 80% to 115%; TN increase 37.5 to 75%). Green mustard growing on charcoalamended soil had greater height (higher 3% to 21%), bigger leaves, and higher yield (increase18% to 81%) than those of plants groomed in the control treatment. This study showed the potential of using charcoal as supplying nutrient to the poor soil. Moreover, the abundant of raw material and easy to produce, it is suitable for applying in the Mekong Delta, Viet Nam, and other countries with similar conditions and infrastructure.

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Global soil-climate-biome diagram: linking surface soil properties to climate and biota

10.5194/bg-2018-449 ◽

2019 ◽

Cited By ~ 1

Author(s):

Xia Zhao ◽

Yuanhe Yang ◽

Haihua Shen ◽

Xiaoqing Geng ◽

Jingyun Fang

Keyword(s):

Soil Properties ◽

Bulk Density ◽

Soil Ph ◽

Surface Soil ◽

Global Scale ◽

Mean Annual Precipitation ◽

Global Soil ◽

Soc Density ◽

Surface Soil Properties ◽

Soil Climate

Abstract. Surface soils interact strongly with both climate and biota and provide fundamental ecosystem services that maintain food, climate, and human security. However, the quantitative linkages between soil properties, climate, and biota at the global scale remain unclear. By compiling a comprehensive global soil database, we mapped eight major soil properties (bulk density; clay, silt, and sand fractions; soil pH; soil organic carbon [SOC] density; soil total nitrogen [STN] density; and soil C : N mass ratios) in the surface (0–30 cm) soil layer based on machine learning algorithms, and demonstrated the quantitative linkages between surface soil properties, climate, and biota at the global scale (i.e., global soil-climate-biome diagram). On the diagram, bulk density increased significantly with higher mean annual temperature (MAT) and lower mean annual precipitation (MAP); soil clay fraction increased significantly with higher MAT and MAP; Soil pH decreased with higher MAP and lower MAT, and the critical MAP for the transition from alkaline to acidic soil decreased with decreasing MAT; SOC density and STN density both were jointly affected by MAT and MAP, showing an increase at lower MAT and a saturation tendency towards higher MAP. Surface soil physical and chemical properties also showed remarkable variations across biomes. The soil-climate-biome diagram suggests the co-evolution of the soil, climate, and biota under global environmental change.

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