Estimating soil clay content using an agrogeophysical and agrogeological approach: a case study in Chania plain, GreeceEstimating soil clay content using an agrogeophysical and agrogeological approach: a case study in Chania plain, Greece Peer-Reviewed Journal Publication Δημοσίευση σε Περιοδικό με Κριτές 2023-09-142022enFieldwork, laboratory analysis and preliminary data analyis included in this work was funded by Project “DEcision system For Irrigation in Crete based on Innovative Technologies—DE.F.I.C.I.T”, RIS3Crete, National Strategic Reference Framework (NSRF) 2014–2020, co-funded by the European Regional Development Fund (ERDF), MIS: 5028242. Formal data analysis, data interpretation and manuscript preparation were supported by Project REACT4MED: Inclusive Outscaling of Agro-ecosystem REstoration ACTions for the MEDiterranean (Grant Agreement No. 2122), which is part of the PRIMA Programme of the European Union.Thorough knowledge of soil lithology and its properties are of considerable importance to agriculture. These parameters have a direct impact on water permeability and the content of the water in soil, which represent significant factors in crop yield, decisively determining the design of irrigation systems and farming processes. In the framework of this study, and considering the inevitable impacts of climate change, the rational management of water resources and the optimization of irrigation through innovative technologies become of significant importance. Thus, we propose an interdisciplinary approach based on robust techniques from the allied fields of earth (geological mapping, geophysical methods) and soil sciences (sampling, mechanical analysis) assisted by statistics and GIS techniques. Clay or the sum of clay and silt soil content is successfully determined from the normalized chargeability using induced polarization and electrical resistivity techniques. Finally, we distinguished three classes (S1, S2 and S3) considering the clay or the sum of clay and silt soil content in the study area (a) based on the dry period geophysical data and (b) using as classification criterion the spatial distribution of the geological formations.http://creativecommons.org/licenses/by/4.0/Water1417Kritikakis_et_al_Water_14(17)_2022.pdfChania [Greece]Library of TUC2023-09-14application/pdf17.3 MBfree Kritikakis Georgios Κρητικακης Γεωργιος Kokinou, Eleni Oikonomou Nikolaos Οικονομου Νικολαος Andronikidis Nikolaos Ανδρονικιδης Νικολαος Brintakis Ioannis Μπριντακης Ιωαννης Daliakopoulos Ioannis Δαλιακοπουλος Ιωαννης Kourgialas Nektarios Κουργιαλας Νεκταριος Pavlaki Aikaterini Παυλακη Αικατερινη Fasarakis Giorgos Markakis Nikolaos Soupios, Pantelis, 1973- Manios Thrassyvoulos Vafeidis Antonios Βαφειδης Αντωνιος MDPI Soil water Irrigation Geological formations Electrical resistivity Induced polarization