Entropy-Based Temporal Downscaling of Precipitation as Tool for Sediment Delivery Ratio Assessment
Abstract
:1. Introduction
2. Materials and Methods
2.1. Maximum Entropy Distribution of Rainfall Intensity and Duration—MEDRID Method
Other Literature Approach
2.2. Sediment Yield-PoME—SYPOME Method
2.3. Monte Carlo and MEDRID-SYPoME Coupling
2.4. Gross Erosion and Siltation Assessment
2.5. Study Area
3. Results
3.1. Probability Distribution Functions—MEDRID
3.2. Sediment Yield Modeling
4. Discussion
4.1. Probability Distribution Functions—MEDRID
4.2. Sediment Yield Modeling
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Equation | B3 | G2 | G3 | |
---|---|---|---|---|
Constraints | i. | |||
ii. | ||||
iii. | ||||
System | i. | |||
ii. | ||||
iii. |
Basin | Area (km2) | Control System | Land Use | Location | Catchment Position | Bathymetry | Time Series | Automatic Weather Station | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Name | Position | Recording | ||||||||||||
Lon | Lat | First a | Second | Lon | Lat | Start | End | |||||||
Canabrava | 2.9 | Reservoir | Agriculture and open range cattle raising | Ceará | 39.56 W | 6.97 S | 1944 | 2000 | 57 | Aiuaba | 40.22 W | 6.69 S | 2004 | 2014 |
Aiuaba | 11.53 | Reservoir | Conservation area with native vegetation (Caatinga) | Ceará | 40.24 W | 6.65 S | 2003 | 2009 | 7 | Aiuaba | 40.22 W | 6.69 S | 2004 | 2014 |
Várzea da Volta | 155 | Reservoir | Agriculture and open range cattle raising | Ceará | 40.62 W | 3.50 S | 1917 | 1997 | 81 | Sobral | 40.36 W | 3.69 S | 2017 | 2019 |
Acarape | 208 | Reservoir | Agriculture and open range cattle raising | Ceará | 38.69 W | 4.20 S | 1924 | 1999 | 74 | Sobral | 40.36 W | 3.69 S | 2017 | 2019 |
Sumé 2 | 0.0107 | Sediment load | Experimental area—preserved vegetation | Paraíba | 36.88 W | 7.67 S | - | 10 | Sumé | 36.88 W | 7.67 S | 1982 | 1991 | |
Sumé 4 | 0.0048 | Sediment load | Experimental area—degraded land without vegetation | Paraíba | 36.9 W | 7.66 S | - | 10 | Sumé | 36.88 W | 7.67 S | 1982 | 1991 | |
Gilbués | 0.0004 | Check dam | Abandoned land under desertification process without vegetation | Piauí | 45.34 W | 9.88 S | 2018 | 2019 | 1 | Gilbués | 45.34 W | 9.88 S | 2018 | 2019 |
B3 | G2 | G3 | |||||
---|---|---|---|---|---|---|---|
a | b | a | b | a | b | c | |
Sobral | 1.124 | 4.316 | 0.250 | 1.525 | 0.066 | 2.114 | 0.678 |
Aiuaba | 1.584 | 10.686 | 0.138 | 1.855 | 0.004 | 3.306 | 0.488 |
Gilbués | 0.696 | 2.691 | 0.777 | 0.953 | 0.390 | 2.099 | 0.812 |
Sumé | 0.955 | 5.398 | 0.740 | 0.911 | 0.269 | 1.410 | 0.818 |
(a) Symmetric Divergence | ||||
---|---|---|---|---|
Sobral | Aiuaba | Gilbués | Sumé | |
Sobral | 0 | 0.198 | 1.210 | 0.097 |
Aiuaba | 0.198 | 0 | 2.494 | 0.536 |
Gilbués | 1.210 | 2.494 | 0 | 0594 |
Sumé | 0.097 | 0.536 | 0.594 | 0 |
(b) Kolmogorov–Smirnov Distance | ||||
Sobral | Aiuaba | Gilbués | Sumé | |
Sobral | 0 | 0.242 | 0.550 | 0.152 |
Aiuaba | 0.242 | 0 | 0.719 | 0.365 |
Gilbués | 0.550 | 0.719 | 0 | 0.404 |
Sumé | 0.152 | 0.365 | 0.404 | 0 |
Basin | Sediment yield | SDR | ||||||
---|---|---|---|---|---|---|---|---|
(Mg km−2 yr−1 ) | (%) | |||||||
CV | CI | CV | CI | |||||
Canabrava | 664.5 | 24.9 | 4% | 12.5 | 13.9 | 0.2 | 1.4% | 1.04 |
Aiuaba | 5.0 | 1.2 | 25% | 0.6 | 14.8 | 4.2 | 28.4% | 2.12 |
Várzea da Volta | 418.2 | 20.2 | 5% | 10.1 | 5.9 | 0.4 | 7.3% | 0.22 |
Acarape | 189.5 | 9.1 | 5% | 3.1 | 8.3 | 0.7 | 8.1% | 0.23 |
Sumé 2 | 13.1 | 1.8 | 14% | 0.9 | 23.5 | 2.6 | 11.1% | 1.32 |
Sumé 4 | 2345.6 | 264.1 | 11% | 132.9 | 20.4 | 3.0 | 14.6% | 1.50 |
Gilbués | 2141.7 | 540.5 | 25% | 272.0 | 29.7 | 8.9 | 29.9% | 4.47 |
Name | Brune Coefficient | Sediment Yield (Mg km−2 yr−1) | Relative Error (%) | |||
---|---|---|---|---|---|---|
Measured | Modeled | Modeled | Modeled | Modeled | ||
M1 | M2 | M1 | M2 | |||
Canabrava | 0.98 | 704 | 1042 | 664 | 48.0% | −5.6% |
Aiuaba | 1.00 | 4 | 2 | 5 | −50.0% | 27.5% |
Várzea da Volta | 0.95 | 164 | 824 | 418 | 402.3% | 155.1% |
Acarape | 0.98 | 233 | 473 | 191 | 102.9% | −18.1% |
Sumé 2 | 1.00 | 17 | 114 | 13 | 570.6% | −21.8% |
Sumé 4 | 1.00 | 3857 | 7644 | 2314 | 98.2% | −40.0% |
Gilbués | 1.00 | 2518 | 10305 | 2142 | 309.3% | −14.9% |
NSE | −4.49 | 0.96 |
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Alencar, P.H.L.; Paton, E.N.; de Araújo, J.C. Entropy-Based Temporal Downscaling of Precipitation as Tool for Sediment Delivery Ratio Assessment. Entropy 2021, 23, 1615. https://doi.org/10.3390/e23121615
Alencar PHL, Paton EN, de Araújo JC. Entropy-Based Temporal Downscaling of Precipitation as Tool for Sediment Delivery Ratio Assessment. Entropy. 2021; 23(12):1615. https://doi.org/10.3390/e23121615
Chicago/Turabian StyleAlencar, Pedro Henrique Lima, Eva Nora Paton, and José Carlos de Araújo. 2021. "Entropy-Based Temporal Downscaling of Precipitation as Tool for Sediment Delivery Ratio Assessment" Entropy 23, no. 12: 1615. https://doi.org/10.3390/e23121615
APA StyleAlencar, P. H. L., Paton, E. N., & de Araújo, J. C. (2021). Entropy-Based Temporal Downscaling of Precipitation as Tool for Sediment Delivery Ratio Assessment. Entropy, 23(12), 1615. https://doi.org/10.3390/e23121615