Estimation of Annual Maximum and Minimum Flow Trends in a Data-Scarce Basin. Case Study of the Allipén River Watershed, Chile
Abstract
:1. Introduction
2. Study Area and Data
2.1. Study Area
2.2. Data
3. Hydrological Model and Methods
3.1. HBV Model Description
3.2. Model Calibration
3.2.1. Regional Sensitivity Analysis
3.2.2. Root Mean Square Error (RMSE)
3.2.3. Transformed Root Mean Square Error (TRMSE)
3.2.4. Nash–Sutcliffe Efficiency (NSE)
3.3. Trend Calculation and Analysis
4. Results
4.1. Model Calibration and Validation
4.2. Trend Uncertainty Analysis
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Parameter | Description | Range |
---|---|---|
Mass balance | ||
A | Precipitation modification parameter | 0.8–2.5 |
Snow module | ||
TT (°C) | Threshold temperature that indicates the initiation of snowmelt (normally 0 °C) | 0 |
Cmelt | Fraction of snow that melts above the threshold temperature (TT) from the beginning of snowmelt. | 0.5–7 |
Snow accumulation adjustment factor | 0.5–1.2 | |
Moisture module | ||
FC (mm) | Field capacity (storage in the soil layer) | 0–2000 |
Empirical coefficient that represents the soil moisture variation in the area | 0–7 | |
LP | Fraction of field capacity to calculate the permanent wilting point (PWP = LP*FC) | 0.3–1 |
C () | Correction factor for potential evapotranspiration | 0.01–0.3 |
Response module | ||
L (mm) | Threshold for quick runoff response | 0–100 |
() | Quick response coefficient (upper reservoir) | 0.3–0.6 |
() | Slow response coefficient (upper reservoir) | 0.1–0.2 |
() | Lower reservoir response coefficient | 0.01–0.1 |
() | Maximum flow coefficient for percolation | 0.01–0.1 |
Process | Period | Peak Flows | Low Flows | ||
---|---|---|---|---|---|
RMSE | NSE | TRMSE | NSE | ||
Calibration | 2001–2005 | 45.1 (<54.8) | 0.81 (>0.6) | 0.89 (<2.0) | 0.77 (>0.6) |
Validation | 2007–2010 | 39.4 (<40.1) | 0.73 (>0.6) | 0,91 (<1.1) | 0.84 (>0.6) |
Parameter | Peak Flows | Low Flows |
---|---|---|
A | 1.2 | 1.2 |
TT (°C) | 0 | 0 |
4.01 | 3.65 | |
FC (mm) | 1280 | 1030 |
0.15 | 0.18 | |
0.50 | 0.60 | |
L (mm) | 115 | 180 |
0.44 | 0.44 | |
0.15 | 0.14 | |
0.015 | 0.008 | |
0.11 | 0.12 | |
LP | 0.68 | 0.68 |
0.83 | 0.85 |
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Medina, Y.; Muñoz, E. Estimation of Annual Maximum and Minimum Flow Trends in a Data-Scarce Basin. Case Study of the Allipén River Watershed, Chile. Water 2020, 12, 162. https://doi.org/10.3390/w12010162
Medina Y, Muñoz E. Estimation of Annual Maximum and Minimum Flow Trends in a Data-Scarce Basin. Case Study of the Allipén River Watershed, Chile. Water. 2020; 12(1):162. https://doi.org/10.3390/w12010162
Chicago/Turabian StyleMedina, Yelena, and Enrique Muñoz. 2020. "Estimation of Annual Maximum and Minimum Flow Trends in a Data-Scarce Basin. Case Study of the Allipén River Watershed, Chile" Water 12, no. 1: 162. https://doi.org/10.3390/w12010162
APA StyleMedina, Y., & Muñoz, E. (2020). Estimation of Annual Maximum and Minimum Flow Trends in a Data-Scarce Basin. Case Study of the Allipén River Watershed, Chile. Water, 12(1), 162. https://doi.org/10.3390/w12010162