scholarly journals SoilKsatDB: global database of soil saturated hydraulic conductivity measurements for geoscience applications

2021 ◽  
Vol 13 (4) ◽  
pp. 1593-1612
Author(s):  
Surya Gupta ◽  
Tomislav Hengl ◽  
Peter Lehmann ◽  
Sara Bonetti ◽  
Dani Or
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Hydraulic Conductivity ◽  
Soil Properties ◽  
Bulk Density ◽  
Learning Algorithm ◽  
Field Measurements ◽  
Saturated Hydraulic Conductivity ◽  
Pedotransfer Functions ◽  
Global Database

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.

scholarly journals SoilKsatDB: global soil saturated hydraulic conductivity measurements for geoscience applications

2020 ◽  
Author(s):  
Surya Gupta ◽  
Tomislav Hengl ◽  
Peter Lehmann ◽  
Sara Bonetti ◽  
Dani Or
Keyword(s):  
Hydraulic Conductivity ◽  
Bulk Density ◽  
Regional Scale ◽  
Field Measurements ◽  
Soil Samples ◽  
Saturated Hydraulic Conductivity ◽  
Pedotransfer Functions ◽  
Tropical Regions ◽  
Global Database ◽  
Field Samples

Abstract. Saturated soil hydraulic conductivity (Ksat) is a key parameter in many hydrological and climatic modeling applications, as it controls the partitioning between precipitation, infiltration and runoff. Ksat values are primarily determined from soil textural properties and soil forming processes, and may vary over several orders of magnitude. Despite availability of Ksat datasets at catchment or regional scale, significant efforts are required to import and bind the data before it could be used for modeling. In this work, a total of 1,910 sites with 13,267 Ksat measurements were assembled from published literature and other sources, standardized, and quality-checked in order to provide a global database of soil saturated hydraulic conductivity (SoilKsatDB). The SoilKsatDB covers most global regions, with the highest data density from the USA, followed by Europe, Asia, South America, Africa, and Australia. In addition to Ksat, other soil variables such as soil texture (11,667 measurements), bulk density (11,151 measurements), soil organic carbon (9,787 measurements), field capacity (7,389) and wilting point (7,418) are also included in the dataset. The results of using the SoilKsatDB to fit Ksat pedotransfer functions (PTFs) for temperate climatic regions and laboratory based soil samples based on soil properties (sand and clay content, bulk density) show that reasonably accurate models can be fitted using Random Forest (best CCC = 0.70 and CCC = 0.73 for temperate and lab based measurements, respectively). However when temperate and laboratory based Ksat PTFs are applied to soil samples from tropical climates and field measurements, respectively, the model performance is significantly lower (CCC = 0.51 for tropical and CCC = 0.13 for field samples). PTFs derived for temperate soils and laboratory measurements might not be suitable for estimating Ksat for tropical regions or field measurements, respectively. The SoilKsatDB dataset is available at https://doi.org/10.5281/zenodo.3752721 and the code used to produce the compilation is publicly available under an open data license.

Global Mapping of Soil Saturated Hydraulic Conductivity Combining Legacy Data, Spatial Covariates and Machine Learning

2021 ◽  
Author(s):  
Surya Gupta ◽  
Peter Lehmann ◽  
Andreas Papritz ◽  
Tomislav Hengl ◽  
Sara Bonetti ◽  
...  
Keyword(s):  
Machine Learning ◽  
Hydraulic Conductivity ◽  
Cross Validation ◽  
Arable Land ◽  
Remotely Sensed ◽  
Saturated Hydraulic Conductivity ◽  
Pedotransfer Functions ◽  
Data Set ◽  
Global Database ◽  
Spatially Distributed

<p>Saturated soil hydraulic conductivity (Ksat) is a key parameter in many hydrological and climatic modeling applications, as it controls the partitioning between precipitation, infiltration and runoff. Values of Ksat are often deduced from Pedotransfer Functions (PTFs) using maps of soil attributes. To circumvent inherent limitations of present PTFs (heavy reliance of arable land measurements, ignoring soil structure, and geographic bias to temperate regions), we propose a new global Ksat map at 1–km resolution by harnessing technological advances in machine learning and availability of remotely sensed surrogate information (terrain, climate and vegetation). We compiled a comprehensive Ksat data set with 13,258 data geo-referenced points from literature and other sources. The data were standardized and quality-checked in order to provide a global database of soil saturated hydraulic conductivity (SoilKsatDB). The SoilKsatDB was then applied to develop a Covariate-based GeoTransfer Function (CoGTF) model for predicting spatially distributed Ksat values using remotely sensed information on various environmental covariates. The model accuracy assessment based on spatial cross-validation shows a concordance correlation coefficient (CCC) of 0.16 and a root meansquare error (RMSE) of 1.18 for log10 Ksat values in cm/day (CCC=0.79 and RMSE=0.72 for non spatial cross-validation). The generated maps of Ksat represent spatial patterns of soil formation processes more distinctly than previous global maps of Ksat based on soil texture information and bulk density. The validation indicates that Ksat could be modeled without bias using CoGTFs that harness spatially distributed surface and climate attributes, compared to soil information based PTFs. The relatively poor performance of all models in the validation (low CCC and high RMSE) highlights the need for the collection of additional Ksat values to train the model for regions with sparse data.</p>

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..

Prediction of three key hydraulic properties in a soil survey of a small forested catchment

Soil Research ◽  
2002 ◽  
Vol 40 (2) ◽  
pp. 191 ◽  
Author(s):  
D. A. O'Connell ◽  
P. J. Ryan
Keyword(s):  
Hydraulic Conductivity ◽  
Water Content ◽  
Bulk Density ◽  
Hydraulic Properties ◽  
Saturated Hydraulic Conductivity ◽  
Soil Survey ◽  
Coarse Grained ◽  
Pedotransfer Functions ◽  
Explanatory Variables ◽  
Tree Models

Direct measurement of ψ(θ) and K(θ) relationships at all observation sites in soil survey is not feasible. Three key hydraulic properties — water content at field capacity (θ–5 kPa), water content at wilting point (θ–1.5 MPa), and saturated hydraulic conductivity (Ks) — can be used to derive K(θ) and ψ(θ) when combined with bulk density. These properties were measured in 'calibration' horizons in a soil survey in Yambulla State Forest in south-east New South Wales. Pedotransfer functions (PTFs) for predicting θ-5 kPa, θ–1.5 MPa, and Ks from the physical and morphologic soil attributes are presented and evaluated here. Models for predicting θ–5 kPa and θ–1.5 MPa relied on per cent clay. An R2 of 0.64 (for θ–5 kPa) to 0.67 (for θ–1.5 MPa) was obtained for linear regressions using only morphologic explanatory variables. An R2 of 0.73 (for θ–5 kPa) to 0.90 (for θ–1.5 MPa) was obtained if laboratory-measured clay content was included as an explanatory variable. Ks was measured in situ using well permeameters, and used for developing PTFs. Large cores were taken from a small subsample of horizons and measurements of Ks, K–0.1 kPa, K–0.2 kPa, and K–0.5 kPa were made in the laboratory. Ks measurements from well permeameters were similar to K-0.5 kPa from laboratory measurements. Regression and tree models were used to predict Ks. The linear regression had an R2 of 0.55, while the tree models accounted for approximately 40% reduction in deviance. Bulk density was the most useful predictor in all Ks models. The inclusion of per cent rock fragments, bulk density, and estimated percentage clay as useful explanatory variables demonstrated the utility of functional descriptors not routinely measured in soil survey. The models are empirical and were locally calibrated for use in a soil survey. They may be applicable in target domains similar to the source domain (i.e. coarse-grained adamellite soils in similar climatic regimes). surrogates, saturated hydraulic conductivity, K(θ), ψ(θ), Ks, pedotransfer functions, soil survey, soil morphology, PTF.

scholarly journals Evaluation and Development of Pedotransfer Functions for Predicting Saturated Hydraulic Conductivity for Mexican Soils

2020 ◽  
Author(s):  
Josué Trejo-Alonso ◽  
Antonio Quevedo ◽  
Carlos Fuentes ◽  
Carlos Chávez
Keyword(s):  
Hydraulic Conductivity ◽  
Water Content ◽  
Bulk Density ◽  
Saturated Hydraulic Conductivity ◽  
Irrigation District ◽  
Pedotransfer Functions ◽  
Del Rio ◽  
Clay Percentage ◽  
Prediction Capability ◽  
Better Than

In the present work, we evaluate the prediction capability of six Pedotransfer functions (PTFs), reported in the literature, for the saturated hydraulic conductivity estimations (Ks). We used a database with 900 measured samples obtained from the Irrigation District 023, in San Juan del Rio, Queretaro, Mexico. Additionally, six new PTFs were construct for Ks from clay percentage, bulk density and saturation water content data. The results show, for the evaluated models, that one model present an overestimation for Ks>0.5 cm h-1 values, three models have a underestimation for Ks>1.0 cm h-1 and two models have a good correlation (R2>0.98) but are necessary more than three parameters. Nevertheless, the last two models requires from three to four parameters in order to get the optimization. By other hand, the models proposed in this work have a similar correlation with a less number of parameters: the fit is seen to be much better than using the existing ones, achieving a correlation of R2 = 0.9822 with only one variable and a R2 = 0.9901 when we use two.

scholarly journals Determining a composite value for the saturated hydraulic conductivity in a recharge area of the Guarani Aquifer System, using pedotransfer functions

RBRH ◽  
2021 ◽  
Vol 26 ◽  
Author(s):  
Marcelo Eduardo Dias de Oliveira ◽  
Didier Gastmans ◽  
Marcelo Donadelli Sacchi ◽  
Rodrigo Esteves Rocha ◽  
Camila de Lima ◽  
...  
Keyword(s):  
Hydraulic Conductivity ◽  
Field Measurements ◽  
Saturated Hydraulic Conductivity ◽  
Pedotransfer Functions ◽  
Essential Property ◽  
Sampling Point ◽  
Catchment Scale ◽  
Recharge Area ◽  
Aquifer System ◽  
Guarani Aquifer

ABSTRACT The saturated hydraulic conductivity (Ks) is an essential property for modeling water and contaminants movement into aquifers. However, Ks is extremely variable, even when considering nearby locations, which poses a challenge for modeling at catchment scales. Field measurements of Ks are most of the time expensive, time-consuming and labor-intensive. This study aimed to obtain, for modeling purposes, and using pedotransfer functions (PTFs), a composite value of Ks at a catchment scale, in a recharge area of the Guarani Aquifer System. Soil samples were taken across the study area, and the Ks for each sampling point were determined by several PTF methods. At the same locations, Ks field measurements were taken using a Guelph permeameter. Average values of Ks for all the sampling points calculated by PTFs were similar to the average value obtained by field measurements. The use of PTFs proved to be a faster and simpler method to efficiently determine the Ks value for the watershed and to capture the stochastic variation in terms of soil pore combination at the watershed scale.

Temporal trends in soil properties at a soil quality benchmark site in the Lower Fraser Valley, British Columbia

2002 ◽  
Vol 82 (4) ◽  
pp. 499-509 ◽  
Author(s):  
E A Kenney ◽  
J W Hall ◽  
C. Wang
Keyword(s):  
British Columbia ◽  
Hydraulic Conductivity ◽  
Soil Properties ◽  
Bulk Density ◽  
Soil Quality ◽  
Soil Compaction ◽  
C:N Ratio ◽  
Penetration Resistance ◽  
Saturated Hydraulic Conductivity ◽  
Total N

A national soil quality monitoring program was established in 1990 to address concerns that the quality of Canada's agricultural soils was in decline. The British Columbia benchmark site (01-BC) was established in 1991 and is located on the Pelly soil series (Orthic Humic Gleysol) supporting a corn-forage-pasture rotation in the Lower Mainland ecoregion. The objectives of this study were to report on the differences in: (1) the measured soil properties for the 5-yr period between baseline data collection in 1991 and resampling in 1996 and (2) the properties measured annually as indicators of soil compaction. A 25-m (25-m grid was used at the site to locate sampling points for bulk density and collecting soil samples of the Ap, BCg, and Cg horizons, as well as the measurement locations for saturated hydraulic conductivity and penetration resistance. A 5-yr interval sampling regime was used to sample the Ap, BCg, and Cg horizons and bulk density. Saturated hydraulic conductivity and penetration resistance were sampled annually from 1992 to 1998. Between 1991 and 1996 in the A horizons, pH, available P, C:N ratio and bulk density increased by 4.6, 7.8, 2.5, and 8%, respectively, and available K, total C and total N decreased by 21, 16.5, and 18.3%, respectively. In the BCg horizon, pH, available P and C:N ratio increased by 5, 126, and 8%, respectively, and the available K and total N both decreased by 21%. Bulk density remained unchanged. The assumption that the soil chemical properties in the Cg horizon would remain stable during the study period did not hold. The trends detected for the Cg horizon were similar to those measured for the upper two horizons. However, only the reductions in available K and total N and increases in C:N were significant. The changes in the soil physical properties measured at this site indicate that some soil compaction has occurred. Both bulk density at 20 cm and penetration resistance increased at all depths between 1994 and 1998, which coincided with the time period that grazing was included in the crop rotation. Field saturated hydraulic conductivity at 25 cm (Ap2 horizon), although highly variable from year to year also tended to be lower during the pasture rotation. The penetration resistance measurements, which detected changes at all depths, appeared to be a more sensitive indicator of soil compaction than either bulk density or field saturated hydraulic conductivity. Key words: Soil quality, soil monitoring, soil properties, soil compaction, temporal change

scholarly journals Evaluation and Development of Pedotransfer Functions for Predicting Saturated Hydraulic Conductivity for Mexican Soils

Agronomy ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 1516
Author(s):  
Josué Trejo-Alonso ◽  
Antonio Quevedo ◽  
Carlos Fuentes ◽  
Carlos Chávez
Keyword(s):  
Hydraulic Conductivity ◽  
Bulk Density ◽  
Saturated Hydraulic Conductivity ◽  
The Other ◽  
Irrigation District ◽  
Pedotransfer Functions ◽  
Del Rio ◽  
Clay Percentage ◽  
Prediction Capability ◽  
Better Than

In the present work, we evaluate the prediction capability of six pedotransfer functions (PTFs), reported in the literature, for the saturated hydraulic conductivity estimations (KS). We used a database with 900 measured samples obtained from the Irrigation District 023, in San Juan del Rio, Queretaro, Mexico. Additionally, six new PTFs were constructed for KS from clay percentage, bulk density, and saturation water content data. The results show, for the evaluated models, that one model presents an overestimation for KS > 0.5 cm h−1 values, three models have an underestimation for KS > 1.0 cm h−1, and two models have a good correlation (R2 > 0.98) but more than three parameters are necessary. Nevertheless, the last two models require 3–4 parameters in order to obtain optimization. On the other hand, the models proposed in this work have a similar correlation with fewer parameters. The fit is seen to be much better than using the existing ones, achieving a correlation of R2 = 0.9822 with only one variable and R2 = 0.9901 when we use two.

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