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This article in SSSAJ

  1. Vol. 75 No. 3, p. 1144-1160
    Received: Sept 22, 2009

    * Corresponding author(s): uttam_icar@yahoo.com
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Assessing Soil Quality in a Semiarid Tropical Watershed Using a Geographic Information System

  1. Uttam Kumar Mandal *a,
  2. Kausalya Ramachandrana,
  3. K. L. Sharmaa,
  4. B. Satyama,
  5. K. Venkannaa,
  6. M. Udaya Bhanua,
  7. Moumita Mandala,
  8. Rahul N. Masanea,
  9. B. Narsimlub,
  10. K. V. Raoc,
  11. Ch. Srinivasaraoc,
  12. G. R. Korwarc and
  13. B. Venkateswarluc
  1. a Central Research Institute for Dryland Agriculture Santoshnagar P.O. Saidabad Hyderabad 500 059, India
    b Indian Grassland and Fodder Research Institute Pahuj Dam Gwalior-Jhansi Road Jhansi, Uttar Pradesh 284 003, India
    c Central Research Institute for Dryland Agriculture Santoshnagar P.O. Saidabad Hyderabad 500 059, India


Subsistence agriculture under rainfed conditions and declining or stagnant yields on irrigated farmland has raised concerns about resource management and long-term sustainability in the subtropical, semiarid region of India. Soil quality assessment has been recognized as an important step toward understanding the effects of land management practices within an agricultural watershed. This study addressed the spatial variability of soil properties and their quality at the watershed level using geostatistical methods. Soil samples from the 0- to 20-cm depth were collected from 118 locations on a 100- by 100-m grid across an 88-ha watershed at Sakaliseripalli village in the Nalgonda District in Andhra Pradesh State, India. Geostatistical analysis showed that most of the soil parameters were moderately spatially dependent. An assessment framework, including a minimum data set, linear scoring technique, and additive indices, was used to evaluate the soil quality index (SQI). Principal component analysis identified cation exchange capacity, exchangeable Na percentage, DTPA-extractable Zn, available P, available water, and dehydrogenase activity as the most important indicators for evaluating soil quality. A kriged map of SQI was prepared for the watershed. The SQI was higher in irrigated systems (3.01) than under rainfed conditions (2.53), and it was 2.61 and 2.53 in fallow and permanent fallow fields, respectively. In this study, potential soil loss calculated using the Universal Soil Loss Equation and crop yield were identified as the quantifiable management goals; the results indicated that good soils having higher soil quality indices were also productive and less erosion prone.

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