📄 earth_science

Sub-Watershed Prioritization for Soil Erosion Risk Assessment in the Wadi Ouahrane Basin (Algeria) Using an Integrated Morphometric Analysis and Entropy-WASPAS Model

This study prioritizes sub-basins within Algeria's Wadi Ouahrane watershed for soil erosion risk by integrating morphometric analysis with an Entropy-WASPAS multi-criteria decision-making framework, identifying six high-risk areas to guide sustainable conservation planning.

Original authors: Mohammed Achite, İbrahim Dursun, Nikola M. Milentijević, Mehmet Ali Çelik

Published 2026-06-30

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Mohammed Achite, İbrahim Dursun, Nikola M. Milentijević, Mehmet Ali Çelik

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

The Big Picture: A "Health Check" for a River Valley

Imagine the Wadi Ouahrane in Algeria as a giant, natural bowl that collects rainwater. This bowl is made up of 14 smaller "sub-bowls" (sub-basins). The researchers wanted to answer a simple question: Which of these small bowls is most likely to get "sick" from soil erosion?

Soil erosion is like a slow-motion landslide where the top layer of dirt washes away, taking fertile land with it and clogging up dams with mud. To fix this, you need to know exactly where to put your "band-aids" (conservation efforts) first.

The Detective Work: Measuring the Shape of the Land

The team didn't just guess; they acted like geomorphological detectives. They used digital maps (like a high-tech GPS for mountains) to measure the physical shape of each of the 14 sub-basins. They looked at three main things:

The Shape of the Bowl (Areal): Is the basin round like a pizza, or long and skinny like a hot dog?
- The Finding: Most of these basins are long and skinny.
- The Analogy: Think of a round pizza versus a long hot dog. If you pour water on a round pizza, it rushes to the center all at once (like a flash flood). If you pour water on a long hot dog, the water has to travel a long distance to get to the end. This means the "hot dog" basins here actually drain water a bit slower, which is generally good for preventing sudden, violent floods.
The Road Network (Linear): How many tiny streams are there, and how are they connected?
- The Finding: The area is full of tiny, first-order streams (the smallest twigs on the tree), making up nearly half of all the water channels.
- The Analogy: Imagine a tree. The trunk is the main river, but the tiny leaves and twigs are the first-order streams. The researchers found that the "twigs" are very dense. This tells them the ground is good at soaking up some water, but the network is complex.
The Steepness (Relief): How high are the mountains compared to the valleys?
- The Finding: Some areas are very steep and rugged, while others are flatter.
- The Analogy: Imagine a slide at a playground. A steep slide (high relief) sends you flying fast (erosion). A gentle slope (low relief) lets you slide down slowly (stable soil).

The Brain Power: Letting the Data Decide (Entropy)

Once they had all these measurements, they needed to decide: Which measurement matters the most?

Usually, experts might guess, "Oh, steepness is probably the most important!" But the researchers wanted to be 100% fair and objective. They used a mathematical tool called Entropy.

The Analogy: Imagine you are judging a talent show. Instead of letting the judges (experts) vote based on their personal favorites, you let the audience's reaction decide the score. If the audience is wildly excited by one act but bored by another, the data "votes" that the exciting act is the most important.
The Result: The math showed that the Bifurcation Ratio (how the streams split apart) and the Stream Length Ratio (how long the streams get as they go down) were the "stars of the show." These two factors were the biggest drivers of erosion risk, not the overall shape of the basin.

The Final Ranking: Who is in Trouble? (WASPAS)

After the math decided which factors were most important, they used a second tool called WASPAS to rank the 14 sub-basins from "Safest" to "Most Dangerous."

Think of this like a school report card for the land.

The Top Students (Safest): Sub-basins SW-2 and SW-14 got the best grades. They are "Very Low Risk." They are stable, and the soil is likely staying put.
The Struggling Students (Most Dangerous): Sub-basins SW-3, SW-4, SW-5, SW-7, SW-12, and SW-13 are in the "Very High Risk" zone.
The Star Student (The Most Urgent Case): SW-4 got the highest "danger score" (0.857). It is the most critical area. If you only have enough money or time to fix one place, this is the one.

The Conclusion: A Smart Map for Saving Soil

The paper concludes that this combination of measuring the land's shape and using smart math to rank the risks works very well.

What they found: The whole area is generally shaped like long hot dogs (which is okay), but specific spots have steep slides and complex stream networks that make them prone to losing soil.
The Takeaway: You can't treat the whole valley the same way. You need to focus your energy on the "struggling students" (like SW-4) to stop the soil from washing away.

This study provides a clear, scientific "map" for the government or land managers to know exactly where to build walls, plant trees, or manage water to protect the land. It's a way of saying, "Don't guess; let the numbers tell you where the trouble is."

Technical Summary: Sub-Watershed Prioritization for Soil Erosion Risk Assessment in the Wadi Ouahrane Basin

Problem Statement
Soil erosion represents a critical environmental challenge in the Mediterranean Basin, particularly in arid and semi-arid regions like Algeria, where topographical steepness, sparse vegetation, and anthropogenic pressures exacerbate land degradation. In Algeria, over 50 million hectares are at risk, leading to significant sedimentation in dams and a loss of storage capacity. Effective watershed management requires the identification of priority areas for conservation; however, traditional planning often lacks a comprehensive, objective framework to rank sub-basins based on erosion susceptibility. The study addresses the need for a robust decision-support mechanism to objectively prioritize sub-watersheds within the Wadi Ouahrane Basin for soil conservation and sustainable management.

Methodology
The research employs an integrated framework combining Geographic Information Systems (GIS), morphometric analysis, and Multi-Criteria Decision Making (MCDM) techniques. The study area, the Wadi Ouahrane Basin (270 km²), was delineated into 14 sub-basins using ArcGIS 10.2 and the ArcHydro extension.

Morphometric Analysis: Three categories of morphometric parameters were calculated from Digital Elevation Model (DEM) and drainage network data:
- Linear: Stream order, bifurcation ratio ( $R_b$ ), stream length ratio ( $R_l$ ), and length of overland flow ( $L_o$ ).
- Areal: Form factor ( $F_f$ ), elongation ratio ( $R_e$ ), circularity ratio ( $R_c$ ), drainage density ( $D_d$ ), drainage texture ( $D_t$ ), and compactness coefficient ( $C_c$ ).
- Relief: Basin relief ( $R$ ), relief ratio ( $R_r$ ), relative relief ( $R_{hp}$ ), ruggedness number ( $R_n$ ), and hypsometric integral ( $H_i$ ).
Entropy Weighting: To eliminate subjective bias in assigning importance to these parameters, the Entropy method was applied. This data-driven approach calculated objective weights based on the variance within the dataset, determining which morphometric criteria most significantly influence erosion susceptibility.
WASPAS Ranking: The Weighted Aggregated Sum Product Assessment (WASPAS) model was utilized to rank the 14 sub-basins. This hybrid MCDM method synthesizes the Weighted Sum Model (WSM) and Weighted Product Model (WPM) using a joint generalized criteria parameter ( $\lambda = 0.5$ ) to ensure a balanced and stable evaluation of erosion risk.

Key Results

Morphometric Characteristics: The Wadi Ouahrane Basin is characterized by elongated geometries, evidenced by low form factor ( $0.36–0.42$ ), elongation ratio ( $0.38–0.41$ ), and circularity ratio ( $0.23–0.50$ ) values. The drainage network is a fifth-order system with 428 segments, where first-order streams constitute 45.56% of the total. Drainage density ranges from $1.60$ to $1.95$ km/km², and all sub-basins fall into the "very coarse" drainage texture class ( $D_t < 2$ ), suggesting favorable infiltration conditions generally, though with localized variations.
Entropy Weighting: The analysis revealed that the bifurcation ratio ( $R_b$ ) and stream length ratio ( $R_l$ ) were the most influential factors controlling erosion susceptibility, with weights of $0.283$ and $0.252$, respectively. Conversely, shape-related parameters like elongation ratio and form factor had negligible weights ( $<0.002$ ).
Prioritization and Risk Classification: The WASPAS model identified significant spatial heterogeneity in erosion risk.
- Very High Risk: Sub-basins SW-3, SW-4, SW-5, SW-7, SW-12, and SW-13 were classified as critical areas. SW-4 exhibited the highest susceptibility with a final score ( $V_{SPM}$ ) of 0.857, making it the top priority for intervention.
- Very Low Risk: Sub-basins SW-2 and SW-14 were identified as having the lowest risk, with scores of $0.541$ and $0.505$, respectively.
- The risk scores across the basin ranged from $0.505$ to $0.857$, allowing for a clear stratification into five distinct risk classes.

Significance and Claims
The paper posits that the integration of Entropy and WASPAS with GIS-based morphometric analysis provides a scientifically sound, transparent, and repeatable decision-support tool for watershed management. The study claims that this hybrid approach effectively minimizes subjectivity by relying on data variance for weighting, thereby offering a robust basis for prioritizing soil conservation measures.

The authors assert that the methodology successfully identifies specific sub-basins requiring urgent rehabilitation, moving beyond general basin-level assessments to targeted, sub-watershed interventions. By highlighting SW-4 as the most critical area, the study provides concrete data for developing sustainable land and water resource management policies. The paper concludes that while the current assessment is static and relies primarily on morphometric parameters, the framework is scalable and can serve as a foundational model for future studies that may incorporate socio-economic variables, land-use changes, and climate scenarios to enhance predictive capabilities.