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Modified SWAT to Forecast Water Availability in Mediterranean Mountainous Watersheds with Snowmelt Dominated Runoff

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Abstract

The assessment of the hydrological response to projected changes in climatic variables is imperative for water resources management, especially in watersheds where snowmelt represents a significant source of runoff. In this study, we modify the source code of the snow accumulation and melting algorithm of the Soil and Water Assessment Tool (SWAT) model to improve runoff simulations in snow dominated basins. A sinusoidal snowmelt function under the degree-day factor method was adopted with its parameters calibrated based on historical data. River flow simulations were compared to measured data under the modified and unmodified SWAT models. Model differences in future predictions of river flows (2032- RCP 4.5) were also assessed. The results showed that the modifications improved runoff simulations by better capturing flow dynamics as represented by daily flows and corresponding variability during the snowmelt period. The modified model increased the Nash–Sutcliffe Efficiency (from 0.64 to 0.79; 0.60 to 0.80; 0.70 to 0.75) and the coefficient of determination (from 48 to 67%, 48 to 69%, 58 to 70%) at three gauging stations. While both models predicted a decrease of water availability in the basin, future simulations with the modified snowmelt algorithm predicted that the drop in water availability as compared to baseline year (2008) will be less dramatic (24%) compared to predictions from the unmodified SWAT (31%). We argue that the proposed source code modifications to the snowmelt algorithm of SWAT provide better insights about future water availability in snow-dominated watersheds.

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Notes

  1. SWE = HSρs/ρw; HS is the snow height in cm; ρs is the density of snow g/cm3; ρw is the density of water 1 g/cm3

  2. Snowfall temperature, snowmelt base temperature, maximum melt factor, minimum melt factor, snowpack lag temperature (i.e. influence of the snowpack temperature of the previous and current day), and the minimum snow water content.

  3. The NDSI employs Landsat Thematic Mapper (TM) visible (0.56 /spl mu/m) and near-infrared (1.65 /spl mu/m) data. The snow algorithm uses the NDSI in combination with near-infrared reflectance to identify snow cover and discriminate snow from clouds.

  4. The source code of SWAT 2012 revision 664 was accessed from http://swat.tamu.edu/ and modified in Fortran 2013.

  5. Permanent sites established by the government to measure snow parameters (https://doi.org/10.5281/zenodo.583733): Cedars (1800 – 2900 m asl), Mzar (1350 – 2350 m asl), and Laqlouq (1350 – 2350 m asl) at about 40 to 120 kms North of the study area with a total of 649 snow course measurements (30 different snow courses during snow season 2015 and 2016 with an average revisit time of 11.4 days)

  6. Nahr Ibrahim about 50 kms north of the study area

  7. 3. Jisr El-Qadi, 4. Al Hammam, 5. Damour Sea Mouth

  8.  0.75 < NSE ≤ 1.00 

    PBIAS| ≤ ± 10%

    0.75 < R2 ≤ 1.00

    Very good

    0.60 < NSE ≤ 0.75 

    ± 10% < |PBIAS| ≤ ± 15%

    0.60 < R2 ≤ 0.75

    Good

    0.36 < NSE ≤ 0.60

    ± 15% < |PBIAS| ≤ ± 25%

    0.50 < R2 ≤ 0.60

    Satisfactory

    0.00 < NSE ≤ 0.36 

    ± 25% < |PBIAS| ≤ ± 50%

    0.25 < R2 ≤ 0.50 B

    Bad

    NSE ≤ 0.00

    ± 50% ≤ |PBIAS|

    R2 ≤ 0.25

    Inappropriate

    1. NSE Nash-Sutcliffe Efficiency, PBIAS Percentage bias, R2 Coefficient of determination 

  9. ALPHA_BF: Baseline flow recession constant (days); CH_K2 Effective hydraulic conductivity of the channel (mm/h); GW_DELAY: Time interval for recharge of the aquifer (days); GWQMN: Water limit level in the shallow aquifer for the occurrence of base flow (mm); REVAPMN: Aquifer water depth for the occurrence of water rise to the unsaturated zone (mm); SURLAG: Delay time of direct surface runoff (days)

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Funding

This study was funded by the US Agency for International Development through the US Geological Survey, under the terms of Grant Number G17AC00079. The opinions expressed herein are those of the authors and do not necessarily reflect the views of the U.S. Agency for International Development or the U.S. Geological Survey (USGS).

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Authors and Affiliations

  1. Department of Civil Infrastructure & Environmental Engineering, Khalifa University, Abu Dhabi, UAE

    G. Harik & M. El-Fadel

  2. Department of Civil & Environmental Engineering, American University of Beirut, Beirut, Lebanon

    G. Harik, I. Alameddine & M. El-Fadel

  3. Department of Land, Air, and Water Resources, University of California, Davis, Davis, USA

    M. Abou Najm

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Contributions

Ghinwa Harik: Conceptualization; Data curation; Formal analysis; Methodology; Calibration & Validation; Visualization; Writing - original draft. Ibrahim Alameddine: Conceptualization; Formal analysis; Methodology; Visualization; Writing - review & editing. Majdi Abou Najm: Formal analysis; Methodology; Visualization; Writing - review & editing. Mutasem El-Fadel: Conceptualization; Formal analysis; Methodology; Visualization; Writing - review & editing; Funding & Resource acquisition; Supervision & Project administration.

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Correspondence to M. El-Fadel.

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Harik, G., Alameddine, I., Najm, M.A. et al. Modified SWAT to Forecast Water Availability in Mediterranean Mountainous Watersheds with Snowmelt Dominated Runoff. Water Resour Manage 37, 1985–2000 (2023). https://doi.org/10.1007/s11269-023-03466-4

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