Economic Assessment of Hydrologic Ecosystem Services in Morocco’s Protected Areas: A Case Study of Ifrane National Park
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Methods
2.2.1. Quantification Methods
2.2.2. Economic Valuation Methods
- A.
- Market Price Method
- B.
- Damage Costs Avoided Method
- -
- r: Relative decrease in yield due to erosion (%).
- -
- EwP: Erosion rate (t/ha/year).
- -
- ∆R: Relative decrease in yield due to erosion (t/ha);
- -
- r: Relative decrease in yield due to erosion (%).
3. Results
3.1. Land Use Dynamic in INP
3.2. Economic Value of Sediment and Nutrient Retention
Evaluation of On-Site Effects (Cost of Avoided Forage and Crop Yield Losses)
- A.
- Avoided loss of agricultural yields
- B.
- Avoided loss in forage yields
- C.
- Assessment of offsite effects
- D.
- Water Quality Loss
- E.
- Evaluation of Mobilizing Water Lost through Siltation Cost
3.3. Economic Value of Water Yield
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A. InVEST Model Inputs
- InVEST models input rasters.
LULC_desc | Lucode | Usle_c | Usle_p |
---|---|---|---|
Rangelands | 1 | 1 | 1 |
Forests | 2 | 0.003 | 1 |
Agriculture | 3 | 0.19 | 1 |
Urban areas | 4 | 0.1 | 1 |
Water | 5 | 0.04 | 1 |
- -
- usle_c: Cover management factor for the USLE;
- -
- usle_p: Support practice factor for the USLE.
LULC_desc | lucode | Load_n | Eff_n | Load_p | Eff_p | crit_len_p | crit_len_n |
---|---|---|---|---|---|---|---|
Rangelands | 1 | 4.84 | 0.305 | 0.292 | 0.25 | 150 | 150 |
Forests | 2 | 2.89 | 0.8 | 0.07 | 0.74 | 150 | 150 |
Agriculture | 3 | 7.4 | 0.69 | 1.305 | 0.59 | 150 | 150 |
Urban areas | 4 | 11.86 | 0.43 | 2.55 | 0.02 | 150 | 150 |
water | 5 | 0 | 0.06 | 0 | 0.61 | 150 | 150 |
- -
- load_[NUTRIENT]: The nutrient loading for this land use class;
- -
- eff_[NUTRIENT]: The maximum proportion of the nutrient that is retained on this land use class;
- -
- crit_len_[NUTRIENT]: The distance after which it is assumed that this land use type retains the nutrient at its maximum capacity;
- -
- InVEST’s “Water yield” model.
LULC_desc | lucode | LULC_veg | Root_depth (mm) | Kc |
---|---|---|---|---|
Rangelands | 1 | 1 | 830 | 0.36 |
Forests | 2 | 1 | 4000 | 1 |
Agriculture | 3 | 1 | 1473 | 1.12 |
Urban areas | 4 | 0 | 1000 | 0.4 |
Water | 5 | 0 | 1 | 1 |
- -
- Lulc_veg: Code indicating whether the land use class is vegetated for the purpose of AET;
- -
- root_depth: Maximum root depth for plants in this land use class;
- -
- Kc: Crop coefficient for this land use class. Used to calculate potential evapotranspiration to modify the reference evapotranspiration.
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HES Studied | Quantification Method | Economic Valuation Method |
---|---|---|
Erosion control | InVEST’s “Sediment Delivery Ratio” model | Damage costs avoided |
Water purification | InVEST’s “Nutrient Delivery Ratio” model | |
Water yield | InVEST’s “Annual Water Yield” model | Market price |
Inputs (*) | InVEST Models | Source of Inputs |
---|---|---|
Land use raster | All InVEST models | Obtained by digitizing, using Google Earth images |
Biophysical tables | All InVEST models | From literature [25,29,30] |
Rasters of climatic data (precipitation and evapotranspiration) | “Sediment Delivery Ratio” “Nutrient Delivery Ratio” “Water Yield” | Obtained from the measurements of the weather stations covering the study area, and from: https://climate.northwestknowledge.net/ (accessed on 29 March 2021) |
Digital Elevation Model | “Sediment Delivery Ratio” “Nutrient Delivery Ratio” “Water Yield” | From the Earth Data website of the National Aeronautics and Space Administration of the United States of America (https://earthdata.nasa.gov (accessed on 20 April 2021)) |
Erosivity raster (R Factor) | “Sediment Delivery Ratio” | Calculated from annual and monthly precipitation averages over a 30-year period (1985–2015), using the formula of Rango and Arnoldus (1987) [31] |
Soil erodibility raster (K factor) | Obtained by assigning the corresponding K-factor values [29] to the lithologic facies of the study area | |
Roots depth raster | “Water Yield” | Obtained by granting each land use the corresponding root depth |
Plants’ Available Water Content | Obtained by assigning the corresponding plant’s available water content values [32] to the lithologic facies of the study area |
Erosion Classes (t/ha/year) | Erosion Intensity | Loss of Forage Productivity (%) |
---|---|---|
0–5 | Very low | 2.5 |
5–25 | Low and medium | 25 |
>25 | Strong and very strong | 45 |
Soil Loss Class (t/ha/year) | Area in 2008 (ha) | Area in 2020 (ha) | The Difference (ha) | The Difference (ha/year) |
---|---|---|---|---|
0–7 | 2198.2 | 3116.9 | +918.7 | +76.5 |
7–12 | 658.1 | 897.5 | +239.4 | +19.9 |
12–20 | 612.6 | 988.4 | +375.7 | +31.3 |
20–35 | 618.5 | 1194.3 | +575.7 | +47.9 |
>35 | 738.2 | 2477.8 | +1739.6 | +144.9 |
Total | 4825.7 | 8674.9 | +3849.3 | +320.7 |
Soil Loss Class (t/ha/year) | Erosion Rate Ewp (t/ha/year) | Decrease in Yield: r (%) | Decline in Yield (*) ∆R = rxAverage Yield (2.44 t/Ha) (t/ha) | Price (USD/ha) | Annual Cost of Erosion (USD/year) |
---|---|---|---|---|---|
0–7 | 3.5 | 0.05 | 0.001 | 0.46 | +35.2 |
7–12 | 9.5 | 0.18 | 0.004 | 1.44 | +28.6 |
12–20 | 16 | 0.34 | 0.008 | 2.88 | +90.1 |
20–35 | 27.5 | 0.66 | 0.016 | 5.76 | +275.9 |
>35 | 38.5 | 0.99 | 0.024 | 8.64 | +2770.8 |
Total | +3200.6 |
Soil Loss Class (t/ha/year) | Area in 2008 (ha) | Area in 2020 (ha) | The Difference (ha) | The Difference (ha/year) |
---|---|---|---|---|
0–5 | 15,498.2 | 25,196.9 | +9698.8 | +808.2 |
5–25 | 16,560.4 | 11,877.8 | −4682.6 | −390.2 |
+25 | 22,621.9 | 7520.8 | −15,101.2 | −1258.4 |
Total | 54,680.5 | 44,595.6 | −10,084.9 | −840.4 |
Soil Losses (t/ha) | Loss of Forage Productivity (%) | Loss of Forage Productivity (UF/ha) | Cost (USD/ha) | Annual Cost (USD/year) |
---|---|---|---|---|
0–5 | 2.5 | 3.3 | 1.2 | 960.1 |
5–25 | 25 | 32.9 | 11.8 | −4621.5 |
+25 | 45 | 59.3 | 21.3 | −26,864.3 |
Total | −30,525.7 |
Losses | Cost (USD/year) | |
---|---|---|
Onsite | Loss in agricultural yields | +3200.6 |
Loss in forage yields | −30,525.7 | |
Offsite | Loss in water quality | −465.7 |
Loss in storage capacity | −67,340 | |
Total | −95,130.8 |
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Sadgui, O.; Khattabi, A. Economic Assessment of Hydrologic Ecosystem Services in Morocco’s Protected Areas: A Case Study of Ifrane National Park. Sustainability 2024, 16, 8800. https://doi.org/10.3390/su16208800
Sadgui O, Khattabi A. Economic Assessment of Hydrologic Ecosystem Services in Morocco’s Protected Areas: A Case Study of Ifrane National Park. Sustainability. 2024; 16(20):8800. https://doi.org/10.3390/su16208800
Chicago/Turabian StyleSadgui, Oumayma, and Abdellatif Khattabi. 2024. "Economic Assessment of Hydrologic Ecosystem Services in Morocco’s Protected Areas: A Case Study of Ifrane National Park" Sustainability 16, no. 20: 8800. https://doi.org/10.3390/su16208800
APA StyleSadgui, O., & Khattabi, A. (2024). Economic Assessment of Hydrologic Ecosystem Services in Morocco’s Protected Areas: A Case Study of Ifrane National Park. Sustainability, 16(20), 8800. https://doi.org/10.3390/su16208800