A Hybrid WSA and AHP-TOPSIS Modeling for Soil Erosion Assessment and Prioritization of the Sub-watershed of Karmanasa River Basin

Technical Summary: A Hybrid WSA and AHP-TOPSIS Modeling for Soil Erosion Assessment and Prioritization of the Sub-watershed of Karmanasa River Basin

Problem Statement
The Karmanasa River Basin (KRB), a perennial tributary of the Ganga in the Middle Ganga Plain, faces severe soil erosion and land degradation driven by climate change, human-induced activities, and its specific geological setting. The basin, characterized by erodible Vindhyan sandstone, shale, and limestone formations, supports extensive agriculture but suffers from recurrent flooding and sediment transport. While previous studies have addressed erosion in the Vindhyan and Gangetic plains, the KRB remains underexplored regarding systematic sub-watershed prioritization using advanced, integrated modeling techniques. The lack of detailed watershed characterization and prioritization hinders effective soil conservation planning and sustainable land management in this data-scarce region.

Methodology
The study employs an integrated geospatial and multi-criteria decision-making (MCDM) framework to assess and prioritize soil erosion susceptibility. The workflow consists of four primary stages:

1. Data Acquisition and Delineation: Using 30 m resolution Shuttle Radar Topography Mission (SRTM) DEM data, the basin was delineated into six sub-watersheds (SW1–SW6). Geological, soil, and topographic data were sourced from the Geological Survey of India (GSI) and the National Bureau of Soil Survey and Land Use Planning (NBSS&LUP).
2. Morphometric Analysis: Twenty-two morphometric parameters were extracted and classified into linear, areal, and relief aspects. These included stream order, bifurcation ratio, drainage density, form factor, compactness coefficient, relief ratio, and ruggedness number.
3. Modeling and Prioritization: Three distinct models were applied to rank the sub-watersheds based on erosion susceptibility:
   • Weighted Sum Analysis (WSA): A composite index was generated by assigning normalized weights to morphometric parameters based on their correlation coefficients with erosion.
   • Sediment Production Rate (SPR): A logarithmic model linking sediment yield to geomorphological parameters (form factor, circulatory ratio, and compactness coefficient).
   • Hybrid AHP-TOPSIS: The Analytical Hierarchy Process (AHP) was used to derive weights for 14 selected parameters based on expert judgment (15 specialists), ensuring a consistency ratio (CR) of 0.016. These weights were then integrated into the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank alternatives based on their distance from ideal and anti-ideal solutions.
4. Statistical Validation: The reliability and consistency of the three models were evaluated using non-parametric statistical tests: the Spearman Rank Correlation Coefficient (SCCT) and Kendall Tau Correlation Coefficient (KTCCT).

Key Results

• Morphometric Characteristics: The basin exhibits a 6th-order drainage network with a mean drainage density of 0.535 km/km². Sub-watershed SW3 is the largest (2,142.21 km²), while SW6 is the smallest (804.51 km²). Drainage texture is generally coarse, and the basin is in a youthful-to-mature stage of geomorphic evolution.
• Model Outputs:
  • WSA: Identified approximately 38–40% of the watersheds as vulnerable. SW4 received the highest priority (lowest score), while SW1 was the lowest priority.
  • SPR: Indicated that 42.6% of the basin is vulnerable. SW5 showed the highest sediment production rate (0.50), classifying it as very high priority, while SW6 had the lowest (0.000013).
  • AHP-TOPSIS: Classified SW3, SW1, and SW2 as high-priority zones. The model yielded a closeness coefficient ($C_i^+$) ranging from 0.22 to 0.75.
• Statistical Validation: The AHP-TOPSIS model demonstrated the highest stability and consistency. It showed a positive correlation with the SPR model (SCCT = 0.37), whereas the WSA model exhibited weaker relationships with the other two approaches. Both statistical tests confirmed that AHP-TOPSIS provides the most reliable prioritization for this basin.
• Spatial Patterns: High erosion susceptibility is concentrated in the Kaimur Plateau and the transition zones between the plateau and the alluvial plain. These areas are characterized by steep slopes, high drainage density, and erodible Rewa Shale and sandstone formations.

Key Contributions

• Integrated Framework: The study successfully applies a hybrid AHP-TOPSIS approach combined with morphometric analysis to a previously underexplored tributary of the Ganga, offering a structured method for decision-making in data-limited regions.
• Comparative Model Evaluation: By statistically comparing WSA, SPR, and AHP-TOPSIS using SCCT and KTCCT, the research identifies AHP-TOPSIS as the superior model for this specific geological context, validating its use over traditional weighted sum methods.
• Prioritization for Action: The research provides a specific, ranked list of sub-watersheds (SW3, SW1, SW2 as high priority) to guide targeted soil conservation interventions, moving beyond general basin-level assessments.

Significance and Claims
The authors assert that this study bridges a critical research gap by providing the first systematic sub-watershed prioritization for the Karmanasa River Basin using advanced MCDM techniques. The findings offer a practical, cost-effective framework for river basin management that can be applied to other Vindhyan and Gangetic tributary basins. By identifying priority zones, the study supports the development of restoration measures and strategies to mitigate soil erosion, thereby contributing to sustainable land management and the achievement of Sustainable Development Goals (SDGs). The work emphasizes that integrated geospatial and morphometric approaches are essential for effective watershed assessment where field-based erosion data is limited.