A comparison of measured and estimated saturated hydraulic conductivity of various soils in the Czech Republic

The study aims to indirectly determine the saturated hydraulic conductivity (Ks). The applicability of recently-published pedotransfer functions (PTFs) based on a machine learning approach has been tested, and their performance has been compared with well-known hierarchical PTFs (computer software R...

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Main Authors: Kamila Báťková, Svatopluk Matula, Eva Hrúzová, Markéta Miháliková, Recep Serdar Kara, Cansu Almaz
Format: Article
Language:English
Published: Czech Academy of Agricultural Sciences 2022-07-01
Series:Plant, Soil and Environment
Subjects:
Online Access:https://pse.agriculturejournals.cz/artkey/pse-202207-0005_a-comparison-of-measured-and-estimated-saturated-hydraulic-conductivity-of-various-soils-in-the-czech-republic.php
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author Kamila Báťková
Svatopluk Matula
Eva Hrúzová
Markéta Miháliková
Recep Serdar Kara
Cansu Almaz
author_facet Kamila Báťková
Svatopluk Matula
Eva Hrúzová
Markéta Miháliková
Recep Serdar Kara
Cansu Almaz
author_sort Kamila Báťková
collection DOAJ
description The study aims to indirectly determine the saturated hydraulic conductivity (Ks). The applicability of recently-published pedotransfer functions (PTFs) based on a machine learning approach has been tested, and their performance has been compared with well-known hierarchical PTFs (computer software Rosetta) for 126 soil data sets in the Czech Republic. The quality of estimates has been statistically evaluated in comparison with the measured Ks values; the root mean squared error (RMSE), the mean error (ME) and the coefficient of determination (R2) were considered. The eight tested models of PTFs were ranked according to the RMSE values. The measured results reflected high Ks variability between and within the study areas, especially for those areas where preferential flow occurred. In most cases, the tested PTFs overestimated the measured Ks values, which is documented by positive ME values. The RMSE values of the Ks estimate ranged on average from 0.5 (coarse-textured soils) to 1.3 (medium to fine-textured soils) for log-transformed Ks in cm/day. Generally, the models based on Random Forest performed better than those based on Boosted Regression Trees. However, the best estimates were obtained by Neural Network analysis PTFs in Rosetta, which scored for four best rankings out of five.
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spelling doaj.art-5a625e45a08143288a4d723f6546dd1b2023-02-23T03:47:06ZengCzech Academy of Agricultural SciencesPlant, Soil and Environment1214-11781805-93682022-07-0168733834610.17221/123/2022-PSEpse-202207-0005A comparison of measured and estimated saturated hydraulic conductivity of various soils in the Czech RepublicKamila BáťkováSvatopluk Matula0Eva Hrúzová1Markéta Miháliková2Recep Serdar Kara3Cansu Almaz4Department of Water Resources, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech RepublicDepartment of Water Resources, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech RepublicDepartment of Water Resources, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech RepublicDepartment of Water Resources, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech RepublicDepartment of Water Resources, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech RepublicThe study aims to indirectly determine the saturated hydraulic conductivity (Ks). The applicability of recently-published pedotransfer functions (PTFs) based on a machine learning approach has been tested, and their performance has been compared with well-known hierarchical PTFs (computer software Rosetta) for 126 soil data sets in the Czech Republic. The quality of estimates has been statistically evaluated in comparison with the measured Ks values; the root mean squared error (RMSE), the mean error (ME) and the coefficient of determination (R2) were considered. The eight tested models of PTFs were ranked according to the RMSE values. The measured results reflected high Ks variability between and within the study areas, especially for those areas where preferential flow occurred. In most cases, the tested PTFs overestimated the measured Ks values, which is documented by positive ME values. The RMSE values of the Ks estimate ranged on average from 0.5 (coarse-textured soils) to 1.3 (medium to fine-textured soils) for log-transformed Ks in cm/day. Generally, the models based on Random Forest performed better than those based on Boosted Regression Trees. However, the best estimates were obtained by Neural Network analysis PTFs in Rosetta, which scored for four best rankings out of five.https://pse.agriculturejournals.cz/artkey/pse-202207-0005_a-comparison-of-measured-and-estimated-saturated-hydraulic-conductivity-of-various-soils-in-the-czech-republic.phpsoil parametersoil texturesoil propertypredictioncomparative assessment
spellingShingle Kamila Báťková
Svatopluk Matula
Eva Hrúzová
Markéta Miháliková
Recep Serdar Kara
Cansu Almaz
A comparison of measured and estimated saturated hydraulic conductivity of various soils in the Czech Republic
Plant, Soil and Environment
soil parameter
soil texture
soil property
prediction
comparative assessment
title A comparison of measured and estimated saturated hydraulic conductivity of various soils in the Czech Republic
title_full A comparison of measured and estimated saturated hydraulic conductivity of various soils in the Czech Republic
title_fullStr A comparison of measured and estimated saturated hydraulic conductivity of various soils in the Czech Republic
title_full_unstemmed A comparison of measured and estimated saturated hydraulic conductivity of various soils in the Czech Republic
title_short A comparison of measured and estimated saturated hydraulic conductivity of various soils in the Czech Republic
title_sort comparison of measured and estimated saturated hydraulic conductivity of various soils in the czech republic
topic soil parameter
soil texture
soil property
prediction
comparative assessment
url https://pse.agriculturejournals.cz/artkey/pse-202207-0005_a-comparison-of-measured-and-estimated-saturated-hydraulic-conductivity-of-various-soils-in-the-czech-republic.php
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