Study region: The study focuses on the Indus River Basin and southern Pakistan, severely affected by flooding in 2022. Study focus: This study assessed how land surface temperature, snow cover, soil moisture, and precipitation contributed to the deluge of 2022. This study mainly investigated MODIS-AIRS land surface temperature, MODIS snow cover (NDSI), SMAP soil moisture, and GPM IMERG precipitation accumulation. Furthermore, different flood visualization and mapping techniques were applied to delineate the flood extent map using Landsat 8-9, Sentinel-2 MSI, and Sentinel-1 SAR data. New hydrological insights for the region: The region experienced some of the most anomalous climatic events in 2022, such as prolonged heatwaves as observed with higher-than-average land surface temperatures and subsequent rapid decline in snow cover extent during the spring, increased soil moisture followed by an abnormal amount of extreme monsoon precipitation in the summer. The upper subbasins experienced more than 8 degrees C in positive temperature anomaly, indicating a warmer climate in spring. Subsequently, the snow cover declined by more than 25 % in the upper subbasins. Further, higher surface soil moisture values (> 0.3 m3/m3) were observed in the basin during the spring due to the rapid snow and ice melt. Furthermore, the basin received more than 200 mm of rainfall compared to the long-term average rainfall of about 98 mm, translating to about 300 % more rainfall than usual in July and August. The analysis helps understand the spatial and temporal variability within the basin and facilitates the understanding of factors and their intricate connections contributing to flooding.

INTRODUCTION Tobacco farming plays a crucial role in the livelihoods of many rural communities in Pakistan, particularly in Khyber Pakhtunkhwa (KPK). However, this agricultural practice is associated with severe environmental degradation and significant health risks to workers during cropping. METHODS This study evaluates the ecological and health impacts of tobacco farming in Pakistan, employing both quantitative (surveys) including 200 respondents (farmers and field workers/laborers) and qualitative methods (in-depth interviews) involving 10 respondents (farmers, policy experts, agriculturist and environmental specialists). The research focuses on Swabi, a key tobacco-growing region, and highlights the negative effects of excessive pesticide use, fertilizer application, and deforestation, which contribute to soil erosion, water pollution, and biodiversity loss RESULTS Regression analysis shows that pesticide use ((3=0.65, p<0.001) and deforestation ((3=0.82, p<0.001) are the leading contributors to ecological degradation. The relationship between tobacco yield and environmental degradation, although showing a trend (p=0.062), is statistically negligible and unlikely to have practical significance ((3=-0.15). Health risks are equally concerning, with farmworkers (labor hired for farming, farmers, landlords) exposed to harmful agrochemicals and nicotine absorption leading to respiratory diseases, skin conditions, and green tobacco sickness (GTS). Pesticide exposure ((3=0.71, p<0.001) and contact with tobacco leaves ((3=0.53, p<0.001) significantly impact workers'health, while using personal protective equipment (PPE) helps mitigate these risks ((3=-0.43, p=0.001). The study also reveals that many farmers are interested in transitioning to alternative crops like maize or cotton, but they face financial and informational barriers. CONCLUSIONS The growing of tobacco in Pakistan entails significant ecological and health dangers, emphasizing the immediate need for the implementation of sustainable farming strategies to mitigate environmental harm and enhance the socio-economic conditions of farmers. Government support through financial incentives, educational programs, and sustainable farming techniques is essential to reduce the environmental damage and improve public health.

The Makran Subduction Zone (MSZ) represents a convergent plate boundary where the Arabian Plate is subducting beneath the Eurasian Plate. This study assessed liquefaction susceptibility and ground response in Gwadar region, located on the eastern side of MSZ. A comprehensive dataset of seismic records, compatible with Pakistan design code BCP: 2021 rock spectrum, was used as input motions at bedrock. A series of one-dimensional (ID) non-linear effective stress analyses (NL-ESA) was conducted using DEEPSOIL v7 numerical tool. The findings revealed that pore water pressure ratio (r(u)) exceeded the threshold value for liquefaction onset (r(u) > 0.8) at various depths within the site profiles. A significant de-amplification of peak ground acceleration values was observed at liquefiable depths in soft soils. The liquefied stratum exhibited a non-linear response, with high shear strain values manifesting plastic deformations. A comparison of computed design spectra with code spectra revealed significant discrepancies. It is demonstrated that BCP: 2021 underestimated site amplification for site class D profiles in the 0.1 to 0.8 s period range, while overestimating it for site class E profiles across the entire period range up to 1.6 s. The findings will benefit infrastructure development in the region, particularly within the China-Pakistan Economic Corridor.

The 2022 flood events in Quetta, Pakistan, caused severe damage to the economy, properties, and lives. Therefore, flood risk mapping to identify flood-prone areas is essential for planners and decision-makers to take critical protective measures to control the effects of flooding. This study focuses on mapping flood-prone regions in the Quetta district of Pakistan using an analytical hierarchy process (AHP) and a geographic information system (GIS). The factors influencing flood used in the present study were topographic witness index (TWI), elevation, slope, land use, land cover, precipitation, stream distance, drainage density, and soil type. Weights and ranks were allocated separately to all factors through AHP and were interpreted in a GIS environment. The produced flood hazard model of the study area depicted four zones. These zones ranged from low (19.49%), moderate (43.34%), high (28.30%), to very high (8.87%). The model was further validated through previous flood events in the study area. Around 90% of flood hazard events in the past took place mainly in the produced model's very high and high zones, which is why the current model is reliable. Finally, integrating geospatial approaches with AHP in flood hazard mapping is a quick, reliable, and affordable method that may be utilized in the area.

Droughts cause significant economic damage worldwide. Evaluating their impacts on crop yield and water resources can help mitigate these losses. Using single variables such as precipitation, temperature, the soil moisture condition index (SMCI) and the vegetation condition index (VCI) to estimate drought impacts does not provide sufficient information on these complex conditions. Therefore, this study uses station-based and remote-sensingbased data to develop new composite drought indexes (CDIs), including the principal component analysis drought index (PSDI) and the gradient boosting method drought index (GBMDI). The first dataset includes historical observations of the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), and the self-calibrated Palmer drought severity index (SC-PDSI) at the 1-, 3-, 6-, and 12month timescales. The second dataset consists of remote-sensing-based data including the VCI, SMCI, temperature condition index (TCI), and precipitation condition index (PCI). We validated the results of PSDI and GBMDI by comparing them with historical drought events, in-situ drought indices, and annual winter wheat crop yield data from 2003 to 2022 using a regression model. Our temporal analysis revealed extreme to severe drought events during1990s and 2010s. GBMDI typically aligned with actual drought events and exhibited stronger correlations with in-situ drought indices than PSDI. We observed that drought intensity in winter were more severe than in summer. GBMDI was the most effective method, followed by PSDI, for assessing drought impacts on winter wheat yields. Thus, the proposed integrated monitoring framework and indexes offered a valuable and innovative approach to addressing the complexities of agricultural drought, particularly in evaluating its effects.

A massive landslide occurred in Domeshi area, District Muzaffarabad, Pakistan, in two distinct phases: an initial movement on August 1, followed by complete failure on August 4, 2023. The landslide movement persisted for 96 h, with a runout distance of 500 m. The event destroyed numerous residential structures, impacting multiple families, and causing extensive damage to cultivated land and road infrastructure. To comprehensively understand the failure mechanisms, a detailed study was undertaken, encompassing site investigations, unmanned aerial vehicle (UAV) photography, geotechnical and geophysical investigations, petrographic analysis, kinematics, and numerical simulations. The field evidence indicates that the active deformation along the Jhelum Fault (JF) within the landslide's main body weakened the surrounding rock formations. Intense rainfall saturated pre-existing fractures, creating critical zones of weakness. Highly plastic clays along fault plane contributed significantly to volume changes, especially during and after rainfall events. Kinematic analysis identified bedding joints as prevalent failure planes for planar sliding. Geophysical survey revealed a layer of unconsolidated material extending 25-30 m below the landslide's scarp, accompanied by various fractures, including a deep fracture (i.e., JF) up to 300 m depth. Petrographic investigations showed microfractures, micro faults, and intragranular mineral breakage, indicative of intense tectonic stresses. Slope stability analysis indicated factors of safety (FoS) and strength reduction factor (SRF) less than 1, suggesting the potential for further failure in the lower sections of the landslide. Multiple factors, including slope geometry, active tectonics, material composition, and anthropogenic factors (i.e., slope loading and cutting for road and building construction, improper drainage distribution), contributed to the landslide's occurrence, however, the rainfall emerged as the primary triggering event.

In 2022, the Pakistan witnessed the hottest spring and wettest summer in history. And devastating floods inundated a large portion of Pakistan and caused enormous damages. However, the primary water source and its contributions to these unprecedented floods remain unclear. Based on the reservoir inflow measurements, Multi-Source Weighted-Ensemble Precipitation (MSWEP), the fifth generation ECMWF atmospheric reanalysis (ERA5) products, this study quantified the contributions of monsoon precipitation, antecedent snowmelts, and orographic precipitation enhancement to floods in Pakistan. We found that the Indus experienced at least four inflow uprushes, which was mainly supplied by precipitation and snowmelt; In upper Indus, abnormally high temperature continued to influence the whole summer and lead to large amounts of snowmelts which not only was a key water supply to the flood but also provided favorable soil moisture conditions for the latter precipitation. Before July, the snowmelt has higher contributions than the precipitation to the streamflow of Indus River, with contribution value of more than 60%. Moreover, the snowmelt could still supply 20%-40% water to the lower Indus in July and August; The leading driver of 2022 mega-floods over the southern Pakistan in July and August was dominated by the precipitation, where terrain disturbance induced precipitation account to approximately 33% over the southern Pakistan. The results help to understand the mechanisms of flood formation, and to better predict future flood risks over complex terrain regions.

The risk of floods has increased in South Asia due to high vulnerability and exposure. The August 2022 Pakistan flood shows a glimpse of the enormity and devastation that can further rise under the warming climate. The deluge caused by the floods in 2022, which badly hit the country's southern provinces, is incomparable to any recent events in terms of the vast spatial and temporal scale. The flood event is ranked second in human mortality, while this was the top event that displaced about 33 million people in Pakistan. Using observations and climate projections, we examine the causes and implications of the 2022 flood in Pakistan. Multiday (& SIM;15 days) extreme precipitation on wet antecedent soil moisture conditions was the primary driver of the flood in August 2022. The extreme precipitation in August was caused by two atmospheric rivers that passed over southern Pakistan. Streamflow simulations from the multiple hydrological models show that multiday extreme precipitation was the primary driver of floods. Several flood-affected stations experienced anomalously higher flow than the upstream stations. The 2022 Pakistan flood highlights the adaptation challenges South Asia is facing along with the substantial need for climate mitigation to reduce the risk of such events. Plain Language Summary The Pakistan flood of 2022 received a considerable attention. However, the causes and implications of the events have not been examined. Using observations, satellite data, and reanalysis products, we show that the event was caused by multiday extreme rainfall on wet antecedent conditions. The extreme rainfall was associated with the two atmospheric rivers that transported significant moisture from the Arabian Sea. The flood was primarily driven by the extreme precipitation and other factors (glacier-melt) played a secondary role. Extreme precipitation is projected to increase in a warming climate, which highlight the strong need of adaptation and mitigation.

Characteristics of carbonaceous aerosol (CA) and its light absorption properties are limited in Karachi, which is one of the most polluted metropolitan cities in South Asia. This study presents a comprehensive measurement of seasonality of CA compositions and mass absorption cross- (MAC) of elemental carbon (EC) and water-soluble organic carbon (WSOC) in total suspended particles (TSP) collected from February 2015 to March 2017 in the southwest part of Karachi. The average TSP, organic carbon (OC), and EC concentrations were extremely high with values as 391.0 +/- 217.0, 37.2 +/- 28.0, and 8.53 +/- 6.97 mg/m(3), respectively. These components showed clear seasonal variations with high concentrations occurring during fall and winter followed by spring and summer. SO42-, NO3-, K+, and NH4+ showed similar variations with CA, implying the significant influence on atmospheric pollutants from anthropogenic activities. Relatively lower OC/EC ratio (4.20 +/- 2.50) compared with remote regions further indicates fossil fuel combustion as a primary source of CA. Meanwhile, sea salt and soil dust are important contribution sources for TSP. The average MAC of EC (632 nm) and WSOC (365 nm) were 6.56 +/- 2.70 and 0.97 +/- 0.37 m(2)/g, respectively. MACEC is comparable to that in urban areas but lower than that in remote regions, indicating the significant influence of local emissions. MACWSOC showed opposite distribution with EC, further suggesting that OC was significantly affected by local fossil fuel combustion. In addition, dust might be an important factor increasing MACWSOC particularly during spring and summer. (C) 2020 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.

Absorbing aerosols mainly Black Carbon (BC) have potential effects on the hydrological cycle and climate change over the high-altitude regions particularly in South Asia. The BC measurements are sparse in high altitude locations of the world particularly over the Northern regions of Pakistan. This study investigated the diurnal/monthly variations of BC and its climatic impacts during the period of 2016-2017 over four high altitude locations, i.e., Astore, Gilgit, Sost and Skardu located in the Himalaya-Karakorum-Hindukush (HKH) mountain ranges in Northern Pakistan. The Optical Properties of Aerosols and Clouds (OPAC) model was used for the estimation of aerosol optical properties, e.g., Aerosol Optical Depth (AOD), Asymmetry Parameter (AP) and Single Scattering Albedo (SSA) using the BC number density corresponding to the BC mass concentration. Then the model derived optical properties (AOD, AP and SSA), surface reflectance, ozone and water vapor were used in Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model for the calculation of BC aerosol radiative forcing (ARF) at the Top Of Atmosphere (TOA), Surface (SUR) and within the ATMosphere (ATM). The results revealed that the mean monthly BC concentrations were maximum during November (3.05 +/- 0.7 mu g/m(3)) as well as in December (3.05 +/- 0.5 mu g/m(3)) at Gilgit and minimum during August (1.1 +/- 0.3 mu g/m(3)) at Sost. Correspondingly, the diurnal variation of BC concentrations displayed strong fluctuations, with high concentrations in the late night and early morning during November and December for Astore and Gilgit, respectively. Generally, the BC concentrations were maximum/minimum in the morning/evening during May, June, August and September at all locations. The correlation of BC with different meteorological parameters showed that the BC has positive correlation with temperature and wind speed, while negative with relative humidity and rainfall. The HYSPLIT back trajectory analysis revealed that air masses arrived the study locations from both long distance (Turkmenistan, Tajikistan, Uzbekistan, Iran, Afghanistan, India, and China) and local sources. The monthly mean maximum and minimum BC ARF values at SUR (TOA) were found to be 43.7 +/- 3.0 W/m(2) (8.2 +/- 0.2 W/m(2)) and 16.4 +/- 1.0 W/m(2) (1.2 +/- 0.1 W/m(2)), respectively, giving an averaged atmospheric forcing of 35.7 +/- 2.3 W/m(2) and 15.2 +/- 1.9 W/m(2).