Mapping field surface soil moisture for hydrological modeling

Tombul M.

WATER RESOURCES MANAGEMENT, vol.21, no.11, pp.1865-1880, 2007 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 21 Issue: 11
  • Publication Date: 2007
  • Doi Number: 10.1007/s11269-006-9134-z
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1865-1880
  • Keywords: soil moisture, topographic index, Xinanjiang distribution, wetness index, heterogeneity, BASIN
  • Anadolu University Affiliated: Yes


Soil moisture is a major control variable on hydrological processes both at the storm event scale and in the long term. The aggregate effect on the mean water balance over an area can be quantified successfully using hydrological models. However, determination of soil moisture distribution for semi or fully distributed models is difficult. In some types of landscape, the distribution of soil moisture is dictated by topography, in others by soil characteristics, or by a combination of both. Distribution of area-average soil moisture according to the likely effect of local topography is presented and tested. The heterogeneity of the soil moisture is described by the Xinanjiang distribution, commonly used to describe the natural spatial heterogeneity of the landscape. This distribution is then mapped onto the terrain using topographic index to locate the wettest and driest areas. Soil moisture data from Bilecik-Kurukavak catchments are used to test the method. Cumulative density functions (CDF) for soil moisture data obtained from 68 locations in eight different dates and corresponding topographic index values are obtained. From these functions the deviations of the wet values from the mean soil moisture are observed as positive and larger compared to the dry values. The temporal stability of moisture patterns was studied in order to identify optimal sampling points for field-average soil moisture. Such points were identified by calculating their deviation over time from field average. Topographic data were analyzed to determine if these sampling points could be identified from time-invariant data.