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| Format: | Preprint |
| Veröffentlicht: |
2026
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| Online-Zugang: | https://arxiv.org/abs/2602.00893 |
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| _version_ | 1866915890467962880 |
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| author | Ghanbarian, Behzad Patrignani, Andres |
| author_facet | Ghanbarian, Behzad Patrignani, Andres |
| contents | In soil physics, saturated hydraulic conductivity, K_sat, is among the most important hydraulic properties with broad applications to modeling flow and transport under saturated conditions. Its accurate estimation, however, is challenging and requires precise characterization of pore space. In this study, we applied concepts of critical path analysis (CPA) to estimate K_sat from soil water retention curve. To evaluate the CPA, we used 313 undisturbed soil samples from the Kansas Mesonet database in which the value of K_sat spans over five orders of magnitude in variation. We found that the CPA estimated K_sat reasonably well with root mean square log-transformed error RMSLE = 0.87. For most samples, the predicted values were around the 1:1 line within a factor of 10 of the measurements. We also estimated K_sat using five other methods but none was more accurate than the CPA. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_00893 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Regional-Scale Estimation of Soil Hydraulic Conductivity Using the Kansas Mesonet Ghanbarian, Behzad Patrignani, Andres Geophysics In soil physics, saturated hydraulic conductivity, K_sat, is among the most important hydraulic properties with broad applications to modeling flow and transport under saturated conditions. Its accurate estimation, however, is challenging and requires precise characterization of pore space. In this study, we applied concepts of critical path analysis (CPA) to estimate K_sat from soil water retention curve. To evaluate the CPA, we used 313 undisturbed soil samples from the Kansas Mesonet database in which the value of K_sat spans over five orders of magnitude in variation. We found that the CPA estimated K_sat reasonably well with root mean square log-transformed error RMSLE = 0.87. For most samples, the predicted values were around the 1:1 line within a factor of 10 of the measurements. We also estimated K_sat using five other methods but none was more accurate than the CPA. |
| title | Regional-Scale Estimation of Soil Hydraulic Conductivity Using the Kansas Mesonet |
| topic | Geophysics |
| url | https://arxiv.org/abs/2602.00893 |