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Soil mapping for land‐use planning in a karst area of N Thailand with due consideration of local knowledge
Author(s) -
Schuler Ulrich,
Choocharoen Chalathon,
Elstner Peter,
Neef Andreas,
Stahr Karl,
Zarei Mehdi,
Herrmann Ludger
Publication year - 2006
Publication title -
journal of plant nutrition and soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.644
H-Index - 87
eISSN - 1522-2624
pISSN - 1436-8730
DOI - 10.1002/jpln.200521902
Subject(s) - soil map , watershed , land use , digital soil mapping , unified soil classification system , soil series , soil fertility , environmental science , soil science , soil water , soil classification , geography , computer science , engineering , civil engineering , machine learning
For the development of sustainable land‐management systems in the highlands of N Thailand, detailed knowledge about soil distribution and soil properties is a prerequisite. Yet to date, there are hardly any detailed soil maps available on a watershed scale. In this study, soil maps on watershed level were evaluated with regard to their suitability for agricultural land‐use planning. In addition to common scientific methods (as underlying the WRB classification), participatory methods were used to exploit local knowledge about soils and to document it in a “Local Soil Map”. Where the WRB classification identified eight soil units, the farmers distinguished only five on the basis of soil color and “hardness”. The “Local Soil Map” shows little resemblance with the detailed, patchy pattern of the WRB‐based soil map. On the contrary, the “Local Soil Map” is fairly similar to the petrographic map suggesting that soil color is directly related to parent material. The farmers' perception about soil fertility and soil suitability for cropping could be confirmed by analytical data. We conclude that integrating local soil knowledge, petrographic information, and knowledge of local cropping practices allows for a rapid compilation of information for land‐evaluation purposes at watershed level. It is the most efficient way to build a base for regional land‐use planning.