Quantitative assessment of Urmia Lake water using spaceborne multisensor data and 3D modeling.

Preserving aquatic ecosystems and water resources management is crucial in arid and semi-arid regions for anthropogenic reasons and climate change. In recent decades, the water level of the largest lake in Iran, Urmia Lake, has decreased sharply, which has become a major environmental concern in Iran and the region. The efforts to revive the lake concerns the amount of water required for restoration. This study monitored and assessed Urmia Lake status over a period of 30 years (1984 to 2014) using remotely sensed data. A novel method is proposed that generates a lakebed digital elevation model (LBDEM) for Urmia Lake based on time series images from Landsat satellites, water level field measurements, remote sensing techniques, GIS, and 3D modeling. The volume of water required to restore the Lake water level to that of previous years and the ecological water level was calculated based on LBDEM. The results indicate a marked change in the area and volume of the lake from its maximum water level in 1998 to its minimum level in 2014. During this period, 86% of the lake became a salt desert and the volume of the lake water in 2013 was just 0.83% of the 1998 volume. The volume of water required to restore Urmia Lake from benchmark status (in 2014) to ecological water level (1274.10 m) is 12.546 Bm3, excluding evaporation. The results and the proposed method can be used by national and international environmental organizations to monitor and assess the status of Urmia Lake and support them in decision-making.

An application of MC-SDSS for water supply management during a drought crisis.

Climate change influences many countries' rainfall patterns and temperatures. In Iran, population growth has increased water demands. Tabriz is the capital of East Azerbaijan province, in northwestern Iran. A large proportion of the water required for this city is supplied from dams; thus, it is important to find alternatives to supply water for this city, which is the largest industrial city in northwestern Iran. In this paper, the groundwater quality was assessed using 70 wells in Tabriz Township. This work seeks to define the spatial distribution of groundwater quality parameters such as chloride, electrical conductivity (EC), pH, hardness, and sulfate using Geographic Information Systems (GIS) and geostatistics; map groundwater quality for drinking purposes employing multiple-criteria decision-making (MCDM), such as the Analytical Hierarchy Process (AHP) and fuzzy logic, in the study area; and develop an Spatial Decision Support System (SDSS) for managing a water crisis in the region. The map produced by the AHP is more accurate than the map produced using fuzzy logic because in the AHP, priorities were assigned to each parameter based on the weights given by water quality experts. The final map indicates that the groundwater quality increases from the north to the south and from the west to the east within the study area. During critical conditions, the groundwater quality maps and the presented SDSS core can be utilized by East Azerbaijan Regional Water Company to develop an SDSS to drill new wells or to select existing wells to supply drinking water to Tabriz City.