article · Sensors
Mountainous watersheds rely heavily on snow processes, but a lack of ground-level snow data often limits hydrological modelling. This study demonstrates how satellite snow cover data from the Moderate Resolution Imaging Spectroradiometer (MODIS) can be combined with the Soil and Water Assessment Tool (SWAT) to improve water flow and snowpack estimates. Focused on the snow-dominated Oued El Abid watershed in the High Atlas, the model was tested using daily records from four gauging stations between 1981 and 2015. The evaluation compared a lumped method with an approach where snow parameters varied across space. The model produced satisfactory to good discharge simulations and reasonably estimated snow-covered areas against MODIS observations. Allowing snow parameters to vary spatially yielded results that matched both streamflow and satellite data more closely.
Mountain snowmelt is a critical water source, but accurately tracking it without extensive ground sensors is challenging. Combining satellite observations with watershed models allows water managers to simulate seasonal snow dynamics and river discharge over long periods. This provides clearer insights into water availability and river flow patterns in remote mountain environments where direct measurements are scarce.
The methodology represents applied and tested modelling that could assist regional water management authorities, river basin agencies, and environmental consultancies working in snow-fed catchment areas. By integrating public satellite data with an established hydrological modelling framework, it offers a practical approach for discharge monitoring and resource planning without requiring dense networks of physical monitoring stations.
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Snowfall, snowpack, and snowmelt are among the processes with the greatest influence on the water cycle in mountainous watersheds. Hydrological models may be significantly biased if snow estimations are inaccurate. However, the unavailability of in situ snow data with enough spatiotemporal resolution limits the application of spatially distributed models in snow-fed watersheds. This obliges numerous modellers to reduce their attention to the snowpack and its effect on water distribution, particularly when a portion of the watershed is predominately covered by snow. This research demonstrates the added value of remotely sensed snow cover products from the Moderate Resolution Imaging Spectroradiometer (MODIS) in evaluating the performance of hydrological models to estimate seasonal snow dynamics and discharge. The Soil and Water Assessment Tool (SWAT) model was used in this work to simulate discharge and snow processes in the Oued El Abid snow-dominated watershed. The model was calibrated and validated on a daily basis, for a long period (1981-2015), using four discharge-gauging stations. A spatially varied approach (snow parameters are varied spatially) and a lumped approach (snow parameters are unique across the whole watershed) have been compared. Remote sensing data provided by MODIS enabled the evaluation of the snow processes simulated by the SWAT model. Results illustrate that SWAT model discharge simulations were satisfactory to good according to the statistical criteria. In addition, the model was able to reasonably estimate the snow-covered area when comparing it to the MODIS daily snow cover product. When allowing snow parameters to vary spatially, SWAT model results were more consistent with the observed streamflow and the MODIS snow-covered area (MODIS-SCA). This paper provides an example of how hydrological modelling using SWAT and snow coverage products by remote sensing may be used together to examine seasonal snow cover and snow dynamics in the High Atlas watershed.
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DOI: 10.3390/s23031246
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