Evidence map›Paper›PMID 36772286›Full record

ArticleSensors (Basel, Switzerland)2023

The Application of SWAT Model and Remotely Sensed Products to Characterize the Dynamic of Streamflow and Snow in a Mountainous Watershed in the High Atlas.

Soufiane Taia, Lamia Erraioui, Youssef Arjdal, Jamal Chao, Bouabid El Mansouri, Andrea Scozzari

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Soufiane TaiaNatural Resources and Sustainable Development Laboratory, Ibn Tofail University, Campus Maamora, Kenitra 14000, Morocco.ORCID 0000-0002-3886-095X
Lamia ErraiouiNatural Resources and Sustainable Development Laboratory, Ibn Tofail University, Campus Maamora, Kenitra 14000, Morocco.
Youssef ArjdalNatural Resources and Sustainable Development Laboratory, Ibn Tofail University, Campus Maamora, Kenitra 14000, Morocco.ORCID 0000-0002-6954-073X
Jamal ChaoNatural Resources and Sustainable Development Laboratory, Ibn Tofail University, Campus Maamora, Kenitra 14000, Morocco.
Bouabid El MansouriNatural Resources and Sustainable Development Laboratory, Ibn Tofail University, Campus Maamora, Kenitra 14000, Morocco.
Andrea ScozzariInstitute of Information Science and Technologies (CNR-ISTI), National Research Council of Italy, 56124 Pisa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

High Atlashydrological modellingMODISMoroccoOum Er-Rbiasatellite hydrologic productssnowstreamflowSWATwater cycle

Identifiers

PMID36772286
PMCPMC9921827

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.