Gis-Based Hydrological Modelling for Sustainable Water Resources Management

Dear Colleagues,

To comprehend, predict, and manage water resources, hydrologic and water resource models have been created all around the world. These are useful tools for bridging knowledge gaps about water quality, groundwater movement, groundwater recharge, river restoration, flood prediction and management etc. To manage the best use of water resources in a sustainable way, accurate estimation of the temporal and spatial distribution features of water resources is necessary. Moreover, as the hydrological cycle is essentially related to spatial variables (Heywood et al., 2006), hydrology is one of the burgeoning fields that employs GIS (and GIS-based models) and remote sensing (RS) to tackle different issues within the field. The major reason for such integration stems from the fact that the hydrological cycle and its related processes are dynamic systems wherein their elements are varying not just temporally but, more importantly, spatially. This inherent spatial dependency is easily covered by GIS, which provides support for a variety of spatial data formats to describe different variables needed for hydrological models. The involvement of a variety of spatial data could become very helpful, as there would be no necessity to make many simplified assumptions, such as constant or linear slopes. The application of GIS allows one to cover a greater extent of reality (Khatami and Khazaei, 2014). In addition, hydrologic models have served as a valuable tool in water resources management for many years. Simulation models are usually used to predict the impacts of proposed land use scenarios and to evaluate management strategies (Greene et al., 1995). During the last few decades, the application of computers for the planning and operation of water resource systems has rapidly become an important field of research. Recently, GIS has gained a great deal of attention in many research fields, wherein the output can be displayed at a high quality and be easily understood (Meyer et al., 1993; Schultz, 1996). Therefore, geographic information systems (GIS) and remote sensing (RS) technologies have recently seen increased application in domains linked to hydrologic and water resources modeling, and therefore in settings relevant to decision-making. A variety of hydrologic and water resource models’ input data have been effectively parameterized using GIS to represent the temporal and spatial characteristics of the factors affecting the hydrologic components. In order to fill the gaps between actual conditions and hydrologic models, the use of satellite datasets for water resource management has the potential to be very helpful. In order to fill the gap left by the absence of on-the-ground monitoring of water resources at different scales, a number of satellite tools have been developed, and are currently being used to deliver the essential data. Analysis of the system of water resources and hydrological modeling have enhanced the usage of GIS and RS in the last decade. In this context, there is an increasing need to enhance present RS and GIS technologies and get a deeper comprehension of how they are used in hydrology. Additionally, in recent years, deep learning and machine learning applications have quickly advanced the state-of-the-art, improving performance in a number of hydrological modeling applications that can be combined with GIS.

Therefore, the aim of this Special Issue is to promote advances in hydrologic and water resources modeling based on cutting-edge GIS and RS technologies. This Special Issue of Sustainability titled “GIS-Based Hydrological Modelling for Sustainable Water Resources Management” calls for original research papers that develop or apply GIS-based hydrological models useful for water resources sustainability assessment. Open challenges in water resources management that could be addressed with GIS-based tools include fully distributed and semi-distributed hydrological modelling, machine/deep learning applications in GIS-based modeling, modelling the impacts of land use change, climate change vulnerability assessment, remotely sensed data assimilation, decision-making tools, etc. We seek contributions that address these and other challenges, with a focus on sustainability assessment from local, regional or global perspectives.

Prof. Dr. Mohamed Ouessar
Prof. Dr. Luis Garrote
Dr. Vinay Nangia
Dr. Malak Henchiri
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 submissions that pass pre-check are 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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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.

• geomatics
• hydrology
• modelling
• water
• management