A Review of SWAT Studies in Southeast Asia: Applications, Challenges and Future Directions
Abstract
:1. Introduction
2. Overview of SWAT in Southeast Asia
2.1. SWAT Studies in Southeast Asia
2.2. SWAT Performance in Southeast Asia
2.3. Example SWAT Testing to Support Scenario Analyses
3. Analysis of SWAT Applications in Southeast Asia
3.1. Foundational SWAT Model Testing for Scenario Assessments
3.2. SWAT Studies on Climate Change
3.3. SWAT Studies on Land Use Change
3.4. SWAT Studies on Climate Change and Land Use Change
3.5. SWAT Studies on Best Management Practices
3.6. SWAT Studies on Water Quality
3.7. SWAT Studies on Hydropower
3.8. SWAT Model Uncertainty Analysis
4. Challenges and Future Recommendations
4.1. Applications
4.2. Data, Calibration and Validation
4.3. Model Modification
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Region | Number of Publications | Reference |
---|---|---|
Transnational | 20 | [39,43,44,45,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78] |
Cambodia | 5 | [53,79,80,81,82] |
Indonesia | 12 | [83,84,85,86,87,88,89,90,91,92,93,94] |
Lao PDR | 5 | [95,96,97,98,99] |
Malaysia | 12 | [46,47,100,101,102,103,104,105,106,107,108,109] |
Myanmar | 3 | [110,111,112] |
Philippines | 5 | [52,113,114,115,116] |
Thailand | 28 | [49,51,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142] |
Vietnam | 36 | [48,50,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176] |
Monthly | Daily | |||||||
---|---|---|---|---|---|---|---|---|
Frequency Ranges | Calibration | Validation | Calibration | Validation | ||||
NSE | R2 | NSE | R2 | NSE | R2 | NSE | R2 | |
0.90–1.00 | 52 | 32 | 49 | 36 | 14 | 1 | 17 | 3 |
0.80–0.89 | 81 | 45 | 55 | 27 | 20 | 19 | 17 | 16 |
0.70–0.79 | 40 | 11 | 59 | 51 | 31 | 17 | 37 | 19 |
0.60–0.69 | 26 | 6 | 28 | 49 | 22 | 18 | 35 | 13 |
0.50–0.59 | 12 | 1 | 34 | 12 | 27 | 13 | 22 | 14 |
0.40–0.49 | 3 | 0 | 34 | 8 | 17 | 5 | 10 | 5 |
0.30–0.39 | 1 | 0 | 4 | 2 | 9 | 1 | 10 | 0 |
0.20–0.29 | 1 | 0 | 2 | 3 | 3 | 1 | 2 | 1 |
0.10–0.19 | 0 | 0 | 3 | 3 | 1 | 0 | 1 | 0 |
0.00–0.09 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 1 |
<0 | 1 | 0 | 4 | 0 | 1 | 0 | 4 | 0 |
Total | 217 | 95 | 275 | 191 | 145 | 75 | 155 | 72 |
Monthly | Daily | |||||||
---|---|---|---|---|---|---|---|---|
Calibration | Validation | Calibration | Validation | |||||
NSE | R2 | NSE | R2 | NSE | R2 | NSE | R2 | |
Transnational | −0.01–0.96 | 0.68–0.96 | 0.07–0.95 | 0.11–0.97 | −0.33–0.95 | 0.54–0.89 | −0.4–0.97 | 0.53–0.89 |
Cambodia | 0.6 | - | 0.27 | - | 0.38 | - | −6.61–0.91 | 0.8–0.94 |
Indonesia | 0.55-0.88 | 0.78–0.89 | <0–0.88 | 0.51–0.81 | 0.4–1 | 0.49–0.91 | 0.41–1 | 0.5–0.92 |
Lao PDR | - | - | - | - | 0.6–0.66 | 0.6–0.66 | 0.57–0.82 | 0.66–0.74 |
Malaysia | 0.62–0.88 | 0.67–0.88 | 0.41–0.85 | 0.59–0.91 | 0.84 | 0.85 | 0.66–0.89 | 0.69–0.9 |
Myanmar | 0.82–0.86 | 0.81–0.93 | 0.81 | 0.82–0.93 | 0.5–0.73 | 0.53–0.79 | 0.5–0.81 | 0.56–0.82 |
Philippines | 0.84 | 0.86 | 0.61–0.7 | 0.68–0.95 | 0.22 | 0.42 | −2.87 | 0.1 |
Thailand | 0.45–0.92 | 0.57–0.93 | −7.89–0.93 | 0.23–0.93 | 0.2–0.83 | 0.26–0.81 | 0.16–0.87 | 0.27–0.81 |
Vietnam | 0.41–0.98 | 0.61–0.92 | 0.55–0.99 | 0.55–0.94 | 0.53–0.87 | 0.58–0.84 | 0.46–0.89 | 0.45–0.81 |
Application | Transnational | Cambodia | Indonesia | Lao PDR | Malaysia | Myanmar | Philippines | Thailand | Vietnam |
---|---|---|---|---|---|---|---|---|---|
Bioenergy crop impacts | • | ||||||||
BMP assessment | • | • | |||||||
Climate and land use Change | • | • | • | • | • | • | • | ||
Climate change | • | • | • | • | • | • | |||
Climate data effects | • | • | • | • | • | • | |||
Critical source area analysis | • | ||||||||
DEM data resolution effects | • | ||||||||
Evaporation assessment | • | ||||||||
Flood analysis | • | • | |||||||
Groundwater analysis | • | ||||||||
Impoundment effects | • | • | • | • | |||||
Input uncertainty analysis | • | ||||||||
Irrigation impact | • | ||||||||
Land use change | • | • | • | • | • | • | |||
Model comparison | • | • | |||||||
Nitrogen cycling and transport | • | • | |||||||
Nutrient cycling and transport | • | ||||||||
Pathogen fate and transport | • | ||||||||
Pesticide fate and transport | • | • | |||||||
Regionalization of input parameters | • | ||||||||
Sediment loss and transport | • | • | • | • | • | ||||
Soil data resolution effects | • | • | |||||||
Uncertainty analysis | • | • |
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Tan, M.L.; Gassman, P.W.; Srinivasan, R.; Arnold, J.G.; Yang, X. A Review of SWAT Studies in Southeast Asia: Applications, Challenges and Future Directions. Water 2019, 11, 914. https://doi.org/10.3390/w11050914
Tan ML, Gassman PW, Srinivasan R, Arnold JG, Yang X. A Review of SWAT Studies in Southeast Asia: Applications, Challenges and Future Directions. Water. 2019; 11(5):914. https://doi.org/10.3390/w11050914
Chicago/Turabian StyleTan, Mou Leong, Philip W. Gassman, Raghavan Srinivasan, Jeffrey G. Arnold, and XiaoYing Yang. 2019. "A Review of SWAT Studies in Southeast Asia: Applications, Challenges and Future Directions" Water 11, no. 5: 914. https://doi.org/10.3390/w11050914
APA StyleTan, M. L., Gassman, P. W., Srinivasan, R., Arnold, J. G., & Yang, X. (2019). A Review of SWAT Studies in Southeast Asia: Applications, Challenges and Future Directions. Water, 11(5), 914. https://doi.org/10.3390/w11050914