This research including lineament automated extraction by using PCI Geomatica program, depending on satellite image and lineament analysis by using GIS program. Analysis included density analysis, length density analysis and intersection density analysis. When calculate the slope map for the study area, found the relationship between the slope and lineament density.The lineament density increases in the regions that have high values for the slope, show that lineament play an important role in the classification process as it isolates the class for the other were observed in Iranian territory, clearly, also show that one of the lineament hit shoulders of Galal Badra dam and the surrounding areas dam. So should take into consideration the lineaments because its plays an important role in the study area.
The primary objective of this study is to employ the remote sensing data and Soil & Water Assessment Tool model to estimate sediment volume and assess the water balance of the Badra Basin (2,615km2) in eastern Iraq. Remote sensing data was utilized as the main input with the Soil & Water Assessment Tool model. These data involved a land use-land cover map that was constructed by the classification of the Landsat-8 satellite imagery for the year 2020, STMR digital elevation model, soil map was acquired from the Food and Agriculture Organization and climatic data were sourced from the NASA-funded prediction of Worldwide Energy Resource The results discovered that about 40 % and 18% of the yearly rainfall are losing by evapotranspiration and filtration. The average amount of annual sediment transported was predicted at 120.47 tons /ha, 2018 recorded the highest value of transported sediment which is about 360 tons /ha. The volume of annual runoff was assessed at about 340.74 million m3. These results proved that the Soil & Water Assessment tool model has the ability to estimation the sediment and runoff volume. The climatic elements, especially rainfall, in addition to soil classes, topography, and land use-land cover had a significant impact on the amount of transported sediments and the volume of runoff.
Earthquakes are significant natural geohazards that threaten life and property. Iraq lies in a seismically active region, and most earthquakes result from the collision of the Eurasian-
Arabian plates. On Nov. 12, 2017, an earthquake with 7.3 MW shook a large area of the
Zagros Belt at the Iran-Iraq border. This work aims to use the InSAR technique for emphasis on the processing and analysis of Sentinel-1 data pre and post-earthquake supported by field, geological and tectonic information to map the ground deformation and fault activity caused by the Nov.12 earthquake. The case study involves a region located at the Iraq-Iran political boundaries. The results reveal that InSAR is a powerful tool to detect ground displacement and allow positioning faults. The interferogram results show that deformation extends to an area ~ 6300 km 2 and 7000 km 2 , with a maximum line-of-sight horizontal displacement ~87 cm and ~55 cm, vertical displacement ~121 cm uplifting and ~59 cm subsidence for ascending and descending data respectively, While pre-earthquake results show clearly neither displacement nor deformation took place. According to InSAR analysis, displacement direction, fault position detection, aftershock distribution, and the general geometric fault context, the blind back-thrust fault SW-dipping steeply occurred on the Zagros Front Fault was interpreted, in addition to new minor faults ruptured on the surface and displacement on old faults were detected. Many faults derived from the geological map coincide with the results of interferometric phase maps. Most recentlydiscovered faults appear to be related to the Nov.12 earthquake.
Different three maize field experiments represent the main agro ecological zones (Sakha, Giza and Qena), including full and deficit irrigation, were conducted in Egypt along the river Nile. The last updated version of AquaCrop model was evaluated with maize yield and water productivity under different irrigation water treatments (1.2, 1, 0.8 and 0.6 from actual evapotranspiration ET c ). The model was evaluated after parameterization using field observations relative to canopy cover (CC), total biomass and yield data as well as using conservative parameters. The treatments show highly agreement between measured and simulated values of CC except the highest severe irrigation treatment (I4). The determination coefficients are higher (R 2 >60), thus indicating that the CC model explains significantly the variance of observed CC values. Also, estimated errors are then small, with RMSE ranging between (0.3 to 13%), and d varying between 0.6 and 0.98. Also, the agreement between simulated and observed maize grain yield, final biomass and water productivity were good with R 2 , RMSE and d. Results cleared that the model is considered a good decision support tool for exploring irrigation management and maize production in Egypt. Nevertheless, the model showed slightly uncertainty specially under sever deficit irrigation. It is supposed that, AquaCrop would be useful if it included some calibrated parameters about root distribution system in soil, because it is a water driven model and relies mainly on soil water balance and uptake.
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