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Application of MODIS Data for Water Resources Management

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainability in Geographic Science".

Deadline for manuscript submissions: closed (26 March 2023) | Viewed by 3860

Special Issue Editor


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Guest Editor
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, SE-223 62 Lund, Sweden
Interests: surface water hydrology; snow hydrology; remote sensing; hydrological modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Controlling water in different conditions is an essential knowledge around the world. And water resources management is directly related to quality of human life. Hydrological variables modeling is one of the most complex environmental modeling due to the involvement of different climate parameters. Then researchers are trying to use new technology for overcoming to water extreme events. Satellite data-set as a new technology can provide the vital component of global observing systems for helping to control of water. Through this Special Issue invites contributions from researchers working in the field of water sciences using any MODIS dataset. The contribution can be related to (but not restricted to) the following: Using of MODIS data in water science; Prediction of water cycle variables via MODIS product; Assessment of long-term water changes; Flood control and forecasting; Drought monitoring and prediction; Data fusion approaches; Comparison hydrological variables with station-based observations; Spatial-temporal analysis; Investigating effects of climate change on water resources systems; Algorithm development

Dr. Babak Mohammadi
Guest Editor

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Keywords

  • Remote Sensing
  • MODIS, Water resources, Water control
  • Modeling
  • Statistical hydrology
  • Time series data

Published Papers (2 papers)

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Research

15 pages, 5234 KiB  
Article
Drought Assessment across Erbil Using Satellite Products
by Mohammed Mustafa Alee, Ali Danandeh Mehr, Ozgun Akdegirmen and Vahid Nourani
Sustainability 2023, 15(8), 6687; https://doi.org/10.3390/su15086687 - 14 Apr 2023
Cited by 4 | Viewed by 1539
Abstract
In this article, meteorological and agricultural droughts across the Erbil province, Iraq, were assessed using remote sensing data and satellite products. To this end, the long-term (2000–2022) Standardized Precipitation Evapotranspiration index (SPEI) at 1- and 3-month accumulation periods (SPEI-1 and SPEI-3) as well [...] Read more.
In this article, meteorological and agricultural droughts across the Erbil province, Iraq, were assessed using remote sensing data and satellite products. To this end, the long-term (2000–2022) Standardized Precipitation Evapotranspiration index (SPEI) at 1- and 3-month accumulation periods (SPEI-1 and SPEI-3) as well as the Normalized Difference Vegetation Index (NDVI) across Erbil were utilized. While the former was retrieved from the global SPEI data repository, the latter was derived from Moderate Resolution Imaging Spectroradiometer (MODIS) products. The spatiotemporal variations in the SPEI indices indicated that two to nine extreme drought events occurred in the province with an increasing northward pattern. An increasing trend in the long-term NDVI series was also detected, having more diversity in vegetation coverage in the northern part of the province. The relationship between the SPEI and MODIS-NDVI was found to be positive but insignificant. Thus, we concluded that short-term meteorological droughts were not the only reason for the agricultural droughts in Erbil. Furthermore, the climate characteristics related to the cumulative water balance over a previous season is not an important trigger for the spatial variation in vegetation coverage across the province. Full article
(This article belongs to the Special Issue Application of MODIS Data for Water Resources Management)
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21 pages, 5761 KiB  
Article
Approximation of the Discharge Coefficient of Radial Gates Using Metaheuristic Regression Approaches
by Parveen Sihag, Meysam Nouri, Hedieh Ahmadpari, Amin Seyedzadeh and Ozgur Kisi
Sustainability 2022, 14(22), 15145; https://doi.org/10.3390/su142215145 - 15 Nov 2022
Cited by 1 | Viewed by 1592
Abstract
Radial gates are widely used for agricultural water management, flood controlling, etc. The existence of methods for the calculation of the discharge coefficient (Cd) of such gates are complex and they are based on some assumptions. The development of new [...] Read more.
Radial gates are widely used for agricultural water management, flood controlling, etc. The existence of methods for the calculation of the discharge coefficient (Cd) of such gates are complex and they are based on some assumptions. The development of new usable and simple models is needed for the prediction of Cd. This study investigates the viability of a metaheuristic regression method, the Gaussian Process (GP), for the determination of the discharge coefficient of radial gates. For this purpose, a total of 2536 experimental data were compiled that cover a wide range of all the effective parameters. The results of GP were compared with the Group Method of Data Handling (GMDH), Multivariate Adaptive Regression Splines (MARS), and linear and nonlinear regression models for predicting Cd of radial gates in both free-flow and submerged-flow conditions. The results revealed that the radial basis function-based GP model performed the best in free-flow condition with a Correlation Coefficient (CC) of 0.9413 and Root Mean Square Error (RMSE) of 0.0190 while the best accuracy was obtained from the Pearson VII kernel function-based GP model for the submerged flow condition with a CC of 0.9961 and RMSE of 0.0132. Full article
(This article belongs to the Special Issue Application of MODIS Data for Water Resources Management)
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