
A Pedotransfer Function for Field‐Scale Saturated Hydraulic Conductivity of a Small Watershed
Author(s) -
Picciafuoco Tommaso,
Morbidelli Renato,
Flammini Alessia,
Saltalippi Carla,
Corradini Corrado,
Strauss Peter,
Blöschl Günter
Publication year - 2019
Publication title -
vadose zone journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.036
H-Index - 81
ISSN - 1539-1663
DOI - 10.2136/vzj2019.02.0018
Subject(s) - pedotransfer function , hydraulic conductivity , soil science , infiltration (hvac) , watershed , linear regression , regression analysis , scale (ratio) , hydrology (agriculture) , mathematics , environmental science , soil water , statistics , geotechnical engineering , geology , geography , computer science , cartography , machine learning , meteorology
Core Ideas Measurements of field‐scale saturated hydraulic conductivity (< K s f >) were performed. Two pedotransfer functions for field‐scale < K s f > were developed. A map of field‐scale < K s f > at catchment scale was obtained using two approaches. Classical experimental techniques to determine point values of saturated hydraulic conductivity ( K s ) are complex and time consuming; therefore, the development of pedotransfer functions, PTFs, to derive K s from easily available soil properties is of great importance. However, PTFs have been generally developed at the local scale, while hydrological modeling requires K s estimates at larger scales. A small Austrian catchment, where detailed soil characteristics were available, was selected to address this issue. Values of field‐scale saturated hydraulic conductivity (< K s f >), observed in a number of catchment areas by double‐ring infiltrometers, were used to develop two PTFs, one by multiple linear regression (PTF MLR ) and one by ridge regression (PTF R ). Training and validation of the PTFs in the monitored areas indicate that the PTF R provides better outcomes with smaller average errors. This suggests that the ridge regression is a valid alternative to the classical multiple linear regression technique. Predictions of < K s f > by the PTFs in the remaining areas, where infiltration measurements were not performed, were also made to obtain a map of < K s f > for the whole catchment. Two alternative approaches were used: Method A—soil properties were first interpolated and then the PTFs applied; Method B—the PTFs were first applied to sites with available soil properties and then interpolated. The maps of < K s f > obtained by the PTF MLR are not representative of the < K s f > spatial variability. On the other hand, the map generated by the PTF R with Method A is consistent with catchment morphology and soil characteristics.