Spatial Analysis of Land Resources for Enhancing Watershed Resilience: A Study from Pashupathihal-4 Micro-Watershed, Kundgol Taluk, Dharwad District, Karnataka, India
Jakir Hussain K N *
Department of Soil Science and Agricultural Chemistry, UAS, Dharwad, India.
Jagadeesh B R
Department of Soil Science and Agricultural Chemistry, UAS, Dharwad, India.
Manjunath M V
Department of Agricultural Engineering, UAS, Dharwad, India.
Gundlur S S
Department of Soil Science and Agricultural Chemistry, UAS, Dharwad, India.
Rajkumar G R
Department of Soil Science and Agricultural Chemistry, UAS, Dharwad, India.
Priya P
Department of Agronomy, UAS, Dharwad, India.
*Author to whom correspondence should be addressed.
Abstract
Background: This study highlights the significance of the Land Resource Inventory (LRI) in the context of farm-level watershed planning, especially for sustainable agricultural development. In India, the degradation of natural resources due to unsustainable land use practices has led to compromised watershed health.
Methods: The study involved an in-depth LRI of the Pashupathihal-4 micro-watershed (973.47 ha) in Dharwad, Karnataka, utilizing remote sensing (RS) and Geographical Information System (GIS) technologies. This integration created high-resolution soil and nutrient maps that captured spatial variability across the watershed's terrain, classified into 16 distinct soil mapping units. The study incorporated FAO land evaluation guidelines to assess land capability and crop suitability, while also analyzing soil properties such as phosphorus, potassium, sulfur, nitrogen and organic carbon.
Results and Conclusion: Results revealed significant spatial variability in soil characteristics, especially in soil depth, texture, erosion and slope, influencing land use potential. The BTPmA1 soil series was the most widespread, covering 35.04% of the area, with over 94% of the watershed classified under Land Classes II and III, indicating moderate constraints and suitability for various crops. Nutrient analysis indicated medium phosphorus (92.33%), high potassium (73.84%) and high sulfur (94.82%) levels, with low nitrogen and organic carbon in most areas, necessitating targeted nutrient management. Crop suitability analysis revealed that 90.15% of the area was highly suitable for sorghum, with maize showing moderate to high suitability. Soybean, groundnut, and cotton were categorized as moderately suitable due to slope, gravelliness and fertility limitations. The study concluded that integrating LRI with geospatial tools enables precise micro-watershed planning.
Keywords: Land resources inventory, spatial database, remote sensing, GIS