Spatially Explicit River Basin Models for Cost-Benefit Analyses to Optimize Land Use
Abstract
:1. Introduction
2. Literature Search
3. Results and Discussion
3.1. Analysis of Selected Land-Use-Based Models
3.1.1. Input Variables and Data Needed
3.1.2. User Convenience
3.2. Steps in Modeling
3.2.1. Data Collection
3.2.2. Model Development and/or Training
3.2.3. Model Application
3.3. SWOT Analysis
3.3.1. Strengths
3.3.2. Weaknesses
3.3.3. Opportunities
3.3.4. Threats
3.4. River Basin Models in the Context of Sustainable River Basin Management
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Models | Data Needed | User Convenience | References | |
---|---|---|---|---|
Process-Based Models | ||||
1 | Soil and Water Assessment Tool | 52 | L | Tuo, et al. [38], Sun, et al. [39], Strehmel, et al. [40], Liu, et al. [41], Rocha, et al. [42], Mtibaa, et al. [43] |
2 | Soil and Water Integrated Model | 40 | L | Tuo, Chiogna and Disse [38] |
3 | Generalized Watershed loading Function | 16 | L | Tuo, Chiogna and Disse [38] |
4 | Annualized agricultural Non-Point Source pollution model | 35 | L | Tuo, Chiogna and Disse [38] |
5 | Hydrological simulation program-FORTRAN | 27 | L | Tuo, Chiogna and Disse [38] |
6 | MIKE-SHE | 20 | L | Thorsen, et al. [44] |
7 | Land Use Change Assessment | 11 | M | Liu, et al. [45] |
8 | Integrated Valuation of Ecosystem Services and Trade-offs Sediment Retention model | 10 | L | Udayakumara and Gunawardena [46] |
Statistical models | ||||
9 | Simple statistical bivariate analysis | 10 | H | Conforti, et al. [47] |
10 | Multivariate regression model (Olive trees) | 22 | H | Noori and Panda [48] |
11 | Spatial prediction | 20 | H | Qiu, et al. [49] |
Probabilistic models | ||||
12 | Favorability function approach | 4 | L | Chung and Fabbri [50] |
Data-driven models | ||||
13 | Decision tree model | 6 | H | Crossman, et al. [51] |
Integrated models/modeling frameworks | ||||
14 | Integrated modeling framework (peatlands) | 8 | L | Van Hardeveld, et al. [52] |
15 | GeoImpress-Patrical model | 13 | L | Ferrer, et al. [53] |
16 | DPSIR framework (The Climate change Project) | 5 | M | Pouget, et al. [54] |
17 | Integrated assessment framework and spatial decision support system (IA-SDSS) | 18 | L | Wang, et al. [55] |
18 | Spatial model | 7 | M | Zarei, et al. [56] |
19 | Deterministic finite time horizon dynamic optimization model | 5 | L | Cerdá and Martín-Barroso [57] |
20 | Integrated assessment framework (flood Netherlands) | 6 | M | Brouwer and Van Ek [26] |
21 | Deterministic optimization approach with Monte Carlo methods | 5 | L | Monge, et al. [58] |
22 | Multicriteria decision analysis | 49 | L | Mwambo, et al. [59] |
23 | Meta-Analysis Benefit Transfer—Strengths Weaknesses Opportunities Threats and Fuzzy Analytic Hierarchical process analysis | 44 | L | Jahanifar, et al. [60] |
24 | Cost-benefit analysis and land use modeling | 19 | L | Pan, et al. [61] |
25 | Cost-benefit evaluation based on ecosystem services (Simulation scenarios) | 10 | M | Li, et al. [62] |
26 | Multinomial logistic regression and environmental and economic effect estimations | 13 | H | Bertoni, et al. [63] |
Strengths Expert knowledge and empirical data can be used Analyses of various (spatially explicit) scenarios Applicable to various scales Provides time and spatial-specific output Some models includes both economic and environmental costs and benefits | Weaknesses Lack of model validation Presence of errors in data Limited data availability Models are too complex and some are too simple Some models are unable to incorporate other factors affecting the spatial variables such as land use Assumptions (e.g., spatial generalization) are used for the estimation of economic impacts |
Opportunities Spatial explicit models becoming more reliable Spatial data availability and quality are increasing Modeling is advancing The growing interest in river basin modeling | Threats Data collection is expensive Limited data availability Over or under prediction Results (e.g., land use changes) of some scenarios are unfeasible environmentally or/and economically |
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Ghafoor, J.; Forio, M.A.E.; Goethals, P.L.M. Spatially Explicit River Basin Models for Cost-Benefit Analyses to Optimize Land Use. Sustainability 2022, 14, 8953. https://doi.org/10.3390/su14148953
Ghafoor J, Forio MAE, Goethals PLM. Spatially Explicit River Basin Models for Cost-Benefit Analyses to Optimize Land Use. Sustainability. 2022; 14(14):8953. https://doi.org/10.3390/su14148953
Chicago/Turabian StyleGhafoor, Jawad, Marie Anne Eurie Forio, and Peter L. M. Goethals. 2022. "Spatially Explicit River Basin Models for Cost-Benefit Analyses to Optimize Land Use" Sustainability 14, no. 14: 8953. https://doi.org/10.3390/su14148953