Estimating the Economic Value of Landscape Restoration in Morocco: The Justdiggit Project
The study presents an ex ante estimate of the monetary value changes of selected ecosystem services (ES) resulting from the potential implementation of the Justdiggit landscape restoration project in Morocco. The project aims to combat desertification and improve livelihoods by enhancing rainwater filtration in soils. A core concept is the creation of a "hydrological corridor" by strategically connecting multiple restoration projects across a country to positively alter rainfall patterns and increase vegetation. In 5 months, including 3 months of field research, the study aims to quantify the economic benefits of these interventions to attract financing and increase support, turning the approach into a viable business case. Learn more about the restoration projects of Justdiggit here.
Overview of the project site
Land Use Land Cover classification using infra-red bands
Slope degrees on the project site, with the mountain region clearly visible in the south.
Research Framework and Methodology
The research employed a comparative approach, quantifying ecosystem services for a 'current situation' (before project implementation) and a 'future situation' (after project implementation), then calculating the net change and multiplying it by economic values to determine the net economic increase or decrease. The study focused on five selected ecosystem services (TEEB), chosen for their high potential value in dryland biomes and quantifiability within the six-month thesis timeframe:
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Carbon sequestration and storage: The ability of an ecosystem to capture and store atmospheric carbon dioxide in plant tissue and soil.
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Erosion prevention and maintenance of soil fertility: The capacity of vegetation to retain nutrients and prevent soil loss due to rainwater runoff.
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Food & Raw materials: Products harvested from the environment for human consumption or other uses, such as agricultural crops, livestock products, and firewood.
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Moderation of extreme events: The ability of ecosystems to mitigate the effects of natural disasters like floods and landslides. (Note: This service was later excluded due to data unreliability during fieldwork).
Our Approach
Our approach: Data Collection and Modeling Tools. Data collection involved a combination of desk research and 3.5 months of fieldwork in Marrakech followed by a data analysis of approximately 3 months. This included:
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Semi-structured interviews with approximately 24 local inhabitants/farmers to gather information on current agricultural practices, livestock products, market prices, and damages from extreme events.
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Market surveys on the nearest weekly farmers market to verify and acquire market prices for goods.
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Collaboration with the University of Marrakech for local expertise, translations. The university hosted plenary sessions with the farmers which we could sit in on.
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Analysis by satellite / remote sensing using ArcGIS and Sentinel data sets for land-use land cover classification, erosion maps etc.
Local market at which. the market data was gathered.
Models and software tools
Several theoretical models and software tools were crucial for quantifying the ecosystem services:
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ArcGIS (Geographic Information System - GIS): Used for spatial calculations and mapping within the project area. It enabled the creation of Land Use Land Cover (LULC) maps for both current and future scenarios, utilizing satellite imagery (Sentinel 2A) and employing a Maximum Likelihood Classification technique to categorize land use based on spectral reflectance.
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InVEST Carbon Model: Applied for estimating carbon stocks in Aboveground Biomass, Belowground Biomass, Soil Organic Carbon, and Dead Organic Matter. It provided a structured methodology and was used to sum the carbon stocks on a spatial level.
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Revised Universal Soil Loss Equation (RUSLE): This widely used model, developed by Wischmeier and Smith (1965, 1978), was employed to quantify the annual soil loss due to rainwater runoff. The RUSLE calculation multiplies five factors:
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Rainfall Erosivity (R): Intensity of rainfall.
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Soil Erodibility (K): Susceptibility of soil to erosion based on composition.
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Slope Length-Gradient (LS): Influence of topography (steepness and length of slope).
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Cover-Management (C): Impact of surface cover and agricultural practices (e.g., vegetation density).
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Support Practice (P): Effectiveness of erosion-reducing interventions (e.g., contouring, terracing).
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Each factor was mapped and calculated using ArcGIS, and their multiplication resulted in soil loss rates for both current and future scenarios.
Soil loss rates (before)
Slope Length-Gradient (LS) calculated from elevation map
Simplified Cover-Management (C)
Monetary valuation techniques
The quantified benefits were converted into monetary terms using specific valuation techniques:
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Direct Market Price (DMP): Used for Food & Raw Materials (based on local market prices) and Carbon Sequestration (based on international CO2e market prices).
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Replacement Cost (RC): Applied to Erosion Prevention and Maintenance of Soil Fertility, by calculating the cost of replacing lost nitrogen with commercial fertilizers.​
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Avoided Cost (AC): Intended for Moderation of Extreme Events (based on estimated damages), but this ecosystem service was ultimately excluded from the final monetary analysis due to insufficient data
