Special Issue "Hydrological Modelling and Remote Sensing: Selected Papers from the 2017 and 2018 SWAT International Conferences"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: 15 April 2019

Special Issue Editors

Guest Editor
Prof. Balaji Narasimhan

Indian Institute of Technology – Madras, Chennai - 600036, India
Website | E-Mail
Interests: hydrological modelling; remote Sensing; large-scale simulations; climate/landuse change impact studies
Guest Editor
Dr. Paul Wagner

Department of Hydrology and Water Resources Management, Kiel University, 24118 Kiel, Germany
Website | E-Mail
Phone: +49 431 880 1237
Interests: hydrologic modeling; impacts of land use change and climate change on water resources; integration of remote sensing and modeling
Guest Editor
Prof. Claire Baffaut

USDA-Agricultural Research Service - Cropping and Water Quality Research Unit, USA
Website | E-Mail
Phone: 573-882-1114 x315
Interests: hydrological modeling at plot, field and watershed scale; simulation and evaluation of management practices; impacts of climate change
Guest Editor
Dr. Mou Leong Tan

Geography Section, School of Humanities, Universiti Sains Malaysia, 11800 Penang, Malaysia
Website | E-Mail
Phone: +604-653 6036
Interests: hydrological modelling; remote sensing; climate/land use change impact analysis
Guest Editor
Dr. Abeyou Wale Worqlul

Blackland Research and Extension Center, Texas A&M Agrilife Research, USA
Website | E-Mail
Interests: watershed hydrology; GIS and remote sensing; crop yield; biomass simulation

Special Issue Information

Dear Colleagues,

Although considerable improvement has been made in hydrologic sciences, and the representation of the processes within the models, this has also led to increased data requirements for the spatial representation of a study area and model parameterization.  In the past decade, remote sensing data have become increasingly available to the hydrologic community for developing a representative spatially-distributed model for assessing the impacts of landuse change, and land and water management practices on water resources at the river basin scale. Further, data on hydrologic state variables, such as evapotranspiration from thermal sensors and soil moisture from microwave sensors, are also being explored for calibration and validation of hydrological models, either independently or within a data assimilation framework. Many research challenges are being actively explored, which aim toward calibration of hydrological models for watersheds and river basins taking into account the true spatial variability of observed processes as opposed to lumped calibration of the model parameters at the point of discharge measurements. This Special Issue of Water is envisioned to showcase the state of the art in the adaptation and use of remotely sensed data for hydrologic modelling using SWAT at different scales and climatic regions for model parameterization, calibration, validation and data assimilation. We sincerely hope that these research papers would address the lacuna that exists in the use of remote sensing data with the hydrologic models, methods to overcome them and identify issues that need further research.

Prof. Balaji Narasimhan
Dr. Paul Wagner
Prof. Claire Baffaut
Dr. Mou Leong Tan
Dr. Abeyou Wale Worqlul
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • Model Parameterization
  • Calibration and Validation
  • Data Assimilation
  • Large-Scale Modelling
  • Climate Change Impact
  • SWAT Model
  • Remote Sensing

Published Papers (1 paper)

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Open AccessArticle A Comparison of SWAT and ANN Models for Daily Runoff Simulation in Different Climatic Zones of Peninsular Spain
Water 2018, 10(2), 192; doi:10.3390/w10020192
Received: 18 December 2017 / Revised: 8 February 2018 / Accepted: 9 February 2018 / Published: 11 February 2018
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Streamflow data are of prime importance to water-resources planning and management, and the accuracy of their estimation is very important for decision making. The Soil and Water Assessment Tool (SWAT) and Artificial Neural Network (ANN) models have been evaluated and compared to find
[...] Read more.
Streamflow data are of prime importance to water-resources planning and management, and the accuracy of their estimation is very important for decision making. The Soil and Water Assessment Tool (SWAT) and Artificial Neural Network (ANN) models have been evaluated and compared to find a method to improve streamflow estimation. For a more complete evaluation, the accuracy and ability of these streamflow estimation models was also established separately based on their performance during different periods of flows using regional flow duration curves (FDCs). Specifically, the FDCs were divided into five sectors: very low, low, medium, high and very high flow. This segmentation of flow allows analysis of the model performance for every important discharge event precisely. In this study, the models were applied in two catchments in Peninsular Spain with contrasting climatic conditions: Atlantic and Mediterranean climates. The results indicate that SWAT and ANNs were generally good tools in daily streamflow modelling. However, SWAT was found to be more successful in relation to better simulation of lower flows, while ANNs were superior at estimating higher flows in all cases. Full article

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