Mesopotamia marshlands constitute the largest wetland ecosystem in the Middle East and western Eurasia. These marshlands are located at the confluence of Tigris and Euphrates rivers in southern Iraq. Al-Huwaizah marsh is the biggest marsh in southern Iraq covered by an area (2400 Km2-3000 Km2) and depth (1.5 m-5 m). The construction dams by Turkey and Syrian for water storage as well as hydroelectric power generation along Tigris and Euphrates rivers, led to reduce and deteriorate water quality in Iraq's marshes. Salinity has become one of the major problems affecting crop production and food security in central and southern Iraq. The objective of this study to develop a new algorithm to retrieve salinity and normalized difference vegetation index (NDVI) from optical remote sensing Landsat-8 (OLI/TIRS) data based on differential equations algorithms. The mathematical algorithms are linear, power and exponential algorithm. The integration between remote sensing techniques and geographic information system (GIS) to map hydrodynamic and the spatial variation of salinity distribution. There is a pressing need to quantify and map the spatial extent and distribution of the salinity in Al-Huwaizah marsh of southern Iraq during March-2013. The findings of this study proved that the integration between Landsat-8 data and GIS with salinity algorithms could provide a powerful tool for retrieving salinity in marshes zone.

The aim of this research is compare between nine drought indices and evaluate their performance with respect to predict and monitoring drought over Middle Euphrates region during period from 1988 to 2017.These indices are RDI, Normal SPI, Gamma SPI, Log SPI, CZI, MCZI, RAI, PN, and DI.Season and annual time scale were used to calculate all indices at Dewaniya, Hilla, Karbala, Najaf, and Semawa stations. The Pearson correlation coefficient between nine drought indices were analyzed. Annual and seasonal results illustrated that the maximum value of correlation between RDI and the other indices was noted with Gamma SPI and Log SPI at all stations. In annual time scale, the correlation coefficient reached to (0.99) at all stations except Hilla station, where it reached to (0.98), while in seasonal time scale the correlation coefficient reached to (0.98) at all stations. The RDI, Gamma SPI and Log SPI indices have similarity of classes and frequencies for drought. They also have similarity of frequencies for wet but there are minimum differences between wet classes compared to other indices. The RDI, Gamma SPI and Log SPI are good indices to predict and monitoring drought in study area in comparison to other indices which mentioned above.

This study was conducted to monitor of meteorological drought over middle Euphrates region based on Reconnaissance Drought Index (RDI) during the period from 1988 to 2017.Average monthly of rainfall, temperature and sunshine hours data were used to calculate this Index. These data were acquired from Iraqi Meteorological Organization and Seismology at known five stations called Hilla, Diwaniya, Karbala, Semawa, and Najaf. The final results illustrated that the highest frequencies of drought, higher values of drought magnitude and intensity are recorded in the Hilla and Karbala stations followed by Najaf, Diwaniyah and Semawa stations respectively. Drought values ranged from moderate to severe in all stations of the study area. There is a high correlation between magnitude and intensity of drought in the study area. There are variations of drought over years between stations because of the difference of climate conditions for each station in the study area.

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