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Showing 2 results for Rashidi

N. Rashidi, M. Naderi, Sh. Ghorbani Dashtaki,
Volume 21, Issue 4 (Winter 2018)
Abstract

Nowadays application of soil conditioners for mitigation and reduction of runoff is a current method. Considering the advantages of Polyacrylamide (PAM), this study was arranged to evaluate impacts of this soil conditioner on soil infiltration rate, runoff and erosion control. To fulfill the goal, a factorial experiment in a completely randomized design was carried out with four PAM treatments (0, 6, 10, 20 kgha-1), three slope levels (3, 6 and 9 %), three irrigation treatments and three replications. Surficial (0-10 cm) soil samples were collected from Shahrekord University campus and poured into square plots (55×55cm) with 15 cm depth, after pretreatments. The plots were treated with a simulated rainfall intensity of 36 mm.h-1 for 15 minutes and the attributed runoff, sediment load and drained water were collected and measured. The results showed significant differences among the runoff and soil erosion of control and of PAM treated soils. PAM minimized the raindrop negative impacts on soils and improved water infiltration and diminished the attributed runoff. Soil treatment with PAM as a soil conditioner significantly reduced soil erosion and sediment yield in all treatments.

J. Karami, M. Habibi Nokhandan, M. Azadi, A. Rashidi Ebrahim Hesari,
Volume 29, Issue 3 (Fall 2025)
Abstract

The present study investigates shoreline changes along the southern Caspian Sea coast in Mazandaran Province over 24 years (2000-2023) using Landsat 8 and Sentinel-2 satellite imagery. The images were obtained from the USGS and Google Earth Engine platforms, and after geometric and radiometric corrections were processed using near-infrared and shortwave Infrared bands to accurately detect the boundary between land and water. Shorelines were visually extracted from the imagery and digitized for each time interval. Spatial variations in the shoreline were analyzed using the Digital Shoreline Analysis System (DSAS) within the ArcGIS environment, applying statistical methods including Net Shoreline Movement (NSM), Shoreline Change Envelope (SCE), End Point Rate (EPR), and Linear Regression Rate (LRR). The results indicate a significant shoreline retreat in many areas of the study region, alongside a continuous decline in the Caspian Sea water level during the last decade. The integration of remote sensing analyses with atmospheric and hydrological data (temperature, precipitation, and river discharge) improved the accuracy of the results and suggests that the southern coastlines—particularly in Mazandaran—may experience more severe retreat by 2050, if current trends continue. These findings underscore the need for intelligent water resource management and the adoption of climate-adaptive policies in the region.


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