Evaluation of MERRA-2 data for aerosols patterns over the Kingdom of Saudi Arabia.

Aerosol is one of the major climate-forcing parameters which affect the Kingdom of Saudi Arabia in particular. The most relevant consideration that characterizes the aerosol properties and distribution is the Aerosol Optical Depth (AOD). In this study Modern Era Retrospective Analysis for Research and Applications (MERRA-2) AOD product from the year 1980-2021 is used to investigate aerosols pattern over the Kingdom of Saudi Arabia. The validation of the MERRA-2 AOD product is made by using AOD data retrieved from Aerosol Robotic Network (AERONET) stations located at Solar Village (SV) and at King Abdullah University of Science and Technology (KAUST). Various statistical analyses are performed to test the reliability of MERRA-2 data in the study region. The results of the statistical analysis indicate that MERRA-2 is highly correlated with both AERONET stations data. Thus, annual and seasonal aerosol climatology maps based on 41 years of MERRA-2 data are prepared and analyzed over the study region. The annual and seasonal aerosol climatology analysis of MERRA-2 data shows high density of AOD at southern and eastern regions while the low density emerges over the western and northern regions of the country during the study period. The results of the study are very encouraging, which increases our confidence level to use historical MERRA-2 AOD product to improve the knowledge on aerosols distribution over the region in future.

Assessment of AOD variability over Saudi Arabia using MODIS Deep Blue products.

The aim of this study is to investigate the variability of aerosol over The Kingdom of Saudi Arabia. For this analysis, Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) Aerosol Optical Depth (AOD) product from Terra and Aqua satellites for the years 2000-2013 is used. The product is validated using AERONET data from ground stations, which are situated at Solar Village Riyadh and King Abdullah University of Science and Technology (KAUST) Jeddah. The results show that both Terra and Aqua satellites exhibit a tendency to show the spatial variation of AOD with Aqua being better than Terra to represent the ground based AOD measurements over the study region. The results also show that the eastern, central, and southern regions of the country have a high concentration of AOD during the study period. The validation results show the highest correlation coefficient between Aqua and KAUST data with a value of 0.79, whilst the Aqua and Solar Village based AOD indicates the lowest Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) values which are, 0.17 and 0.12 respectively. Furthermore, the Relative Mean Bias (RMB) based analysis show that the DB algorithm overestimates the AOD when using Terra and Solar Village data, while it underestimates the AOD when using Aqua with Solar Village and KAUST data. The RMB value for Aqua and Solar Village data indicates that the DB algorithm is close to normal in the study region.

Sediments deposition due to soil erosion in the watershed region of Mangla dam.

Soil erosion is the most important reason of sedimentation load of water reservoirs in the world. In Pakistan, Mangla dam is one of the most important water reservoirs used for the production of electricity and for the supply of water for irrigation purposes. However, the capacity of Mangla dam reservoir has reduced by more than 20% since its construction. This study highlights the impact of rainfall on soil erosion and consequently on sedimentation deposition in Mangla dam reservoir. Sedimentation, annual rainfall, and normal rainfall data of 39 years were used in this study. Shuttle Radar Topographic Mission data were used to calculate the total drainage area of the Mangla watershed region. The sedimentation data of Mangla reservoir from 1967 to 2005 were retrieved from Water and Power Development Authority in Pakistan. The meteorological observatories in the Mangla watershed region are identified. Annual rainfall data from 1967 to 2005 for the meteorological observatories in the Mangla watershed regions were retrieved from Pakistan Meteorological Department (PMD). In addition, normal rainfall data for the years 1949 to 1978 and for the years 1979 to 2008 were also retrieved from PMD. The impact of annual rainfall is observed on sedimentation load in Mangla dam. The correlation coefficient between annual rainfall and sedimentation load is 0.94. This study shows that with an increase in rainfall, the soil erosion of the area increases which subsequently is responsible for the increase in the rate of sedimentation load in Mangla dam. This study further demonstrates that better soil management can reduce the sedimentation load in the Mangla reservoir.