Soil erosion vulnerability and soil loss estimation for Siran River watershed, Pakistan: an integrated GIS and remote sensing approach.

Soil erosion is a problematic issue with detrimental effects on agriculture and water resources, particularly in countries like Pakistan that heavily rely on farming. The condition of major reservoirs, such as Tarbela, Mangla, and Warsak, is crucial for ensuring an adequate water supply for agriculture in Pakistan. The Kunhar and Siran rivers flow practically parallel, and the environment surrounding both rivers' basins is nearly identical. The Kunhar River is one of KP's dirtiest rivers that carries 0.1 million tons of suspended sediment to the Mangla reservoir. In contrast, the Siran River basin is largely unexplored. Therefore, this study focuses on the Siran River basin in the district of Manshera, Pakistan, aiming to assess annual soil loss and identify erosion-prone regions. Siran River average annual total soil loss million tons/year is 0.154. To achieve this, the researchers integrate Geographical Information System (GIS) and remote sensing (RS) data with the Revised Universal Soil Loss Equation (RUSLE) model. Five key variables, rainfall, land use land cover (LULC), slope, soil types, and crop management, were examined to estimate the soil loss. The findings indicate diverse soil loss causes, and the basin's northern parts experience significant soil erosion. The study estimated that annual soil loss from the Siran River basin is 0.154 million tons with an average rate of 0.871 tons per hectare per year. RUSLE model combined with GIS/RS is an efficient technique for calculating soil loss and identifying erosion-prone areas. Stakeholders such as policymakers, farmers, and conservationists can utilize this information to target efforts and reduce soil loss in specific areas. Overall, the study's results have the potential to advance initiatives aimed at safeguarding the Siran River watershed and its vital resources. Protecting soil resources and ensuring adequate water supplies are crucial for sustainable agriculture and economic development in Pakistan.

Impact of COVID-19 lockdown upon the air quality and surface urban heat island intensity over the United Arab Emirates.

The 2019 pandemic of Severe Acute Respiratory Syndrome-Corona Virus Diseases (COVID-19) has posed a substantial threat to public health and major global economic losses. The Northern Emirates of the United Arab Emirates (NEUAE) had imposed intense preventive lockdown measures. On the first of April 2020, a lockdown was implemented. It was assumed, due to lower emissions, that the air quality and Surface Urban Heat Island Intensity (SUHII) had been strengthened significantly. In this research, three parameters for Nitrogen Dioxide (NO2), Aerosol Optical Depth (AOD), and SUHII variables were examined through the NEUAE. we evaluated the percentage of the change in these parameters as revealed by satellite data for 2 cycles in 2019 (March 1st to June 30th) and 2020 (March 1st to June 30th). The core results showed that during lockdown periods, the average of NO2, AOD, and SUHII levels declined by 23.7%, 3.7%, and 19.2%, respectively, compared to the same period in 2019. Validation for results demonstrates a high agreement between the predicted and measured values. The agreement was as high as R2=0.7, R2=0.6, and R2=0.68 for NO2, AOD, and night LST, respectively, indicating significant positive linear correlations. The current study concludes that due to declining automobile and industrial emissions in the NEUAE, the lockdown initiatives substantially lowered NO2, AOD, and SUHII. In addition, the aerosols did not alter significantly since they are often linked to the natural occurrence of dust storms throughout this time of the year. The pandemic is likely to influence several policy decisions to introduce strategies to control air pollution and SUHII. Lockdown experiences may theoretically play a key role in the future as a possible solution for air pollution and SUHII abatement.