Indus River Research Articles

Estimation of soil loss and sediment yield by using the modified RUSLE model in the Indus River basin, including the quantification of error and uncertainty in remote-sensing images

Context Indus River is the cradle of Pakistani lifeline, and its lower reaches are prone to soil loss owing to bank erosion. Aims The aim was to investigate the sediment yield in the Lower Indus River Basin (LIRB), while addressing challenges related to error or uncertainty in remote-sensing data. Methods We employed a modified revised universal soil loss equation (RUSLE) model, integrating high-resolution digital elevation model (DEM) and calibrated Climate Hazards Group InfraRed Precipitation with station data (CHIRPS). Additional data layers, including land use, soil and cropping data, were also utilised. Key results The extent of actual soil erosion ranges from minimum to maximum erosion; 38.9% area lies in the range >50 Mg ha‒1 year‒1, whereas 23.2% area lies in the range of 0–10 Mg ha‒1 year‒1, and 18.1% area lies in the range of 10–20 Mg ha‒1 year‒1. Conclusions The study identifies critical erosion areas and tackles uncertainties in remote-sensing data. The spatial analysis showed that higher distribution sediment erosion along the channel flow direction from the northern part of LIRB to the Arabian Sea. Implications The findings have provided critical information for policymakers and water managers to implement effective measures to reduce erosion, maintain soil integrity and promote the sustainability of the Indus River system.

Assessment of Basin‐Scale Concurrent Dry and Wet Extreme Dynamics Under Multimodel CORDEX Climate Scenarios

ABSTRACTThe impact of extreme events in risk analysis depends on factors such as magnitude, duration, timing and whether the system recovers fully before the next event occurs. While previous studies have primarily examined the drivers and characteristics of individual extremes, less focus has been given to the concurrent or compounding nature of extremes across adjacent seasons. Thus, understanding the dynamics of such compound extremes, particularly dryness and wetness, is crucial. To address these concerns, a Multi Scalar Drought Index (MSDI) is formulated using precipitation and temperature data from three river basins (Brahmani, Baitarani and Cauvery) of eastern and southern India. The combinations of dryness and wetness, such as Dry‐Dry, Dry‐Wet, Wet‐Dry and Wet‐Wet, between consecutive seasons are analysed across four seasons (summer, rainy, autumn and winter). The prolonged dryness/wetness along with dry/wet year are evaluated from baseline (1979–2018) to projected COrdinated Regional Climate Downscaling Experiment (CORDEX) future period (2020–2099). The spatio‐temporal variations in intra‐annual dry‐wet extremes are identified using the Mann–Kendall test. The results suggest that the eastern Indian river basins, particularly the Brahmani and Baitarani basins, experience more frequent occurrences of compounding dryness‐wetness compared to Cauvery river which is a southern Indian basin. Future scenarios indicate a trend towards dryness during the monsoon season in Brahmani and Baitarani basins, with frequent wet extremes in late autumn and winter. Abrupt transitions between dryness and wetness are prevalent during the Rainy‐Autumn and Autumn‐Winter seasons in Brahmani and Baitarani basins. The increased frequency of compound dry‐wet extremes poses significant socio‐economic risks, including reduced agricultural productivity, water management challenges and heightened vulnerability of local livelihoods dependent on consistent water availability. The results of this study provide a scientific reference for sustainable agriculture and water resource management to predict future seasonal dry and wet alternations and develop effective mitigation strategies.

The Characterization of Aquifer Parameters in Using Skimming Tubewells Through the Pumping Test Method: A Case Study of Tando Allahyar

Sindh is in the lower reaches of the Indus River; it is most vulnerable to a variety of upstream water development challenges. The aim of this research was to determine aquifer characteristics in the command area of Tando Allahyar-II distributary within the culmination of underground water potential. The hydraulic properties of the aquifer as well as the susceptibility of the formation to tedious extraction and saltwater upcoming were recognized. Three pumping tests were performed at head, middle, and tail reaches along the selected distributary. The drawdowns were measured at head reach (5.1667 h), at middle reach (6.0 h), and at tail reach (19.667 h) of the selected distributary by performing the pumping tests. Groundwater levels were lower at the tail reach compared to those at the head and middle reaches, likely due to a higher concentration of tubewells in the lower reach. The head and middle reaches showed higher groundwater levels, possibly due to constant head conditions promoting infiltration and recharge. The pumping test versus drawdown analysis revealed that the tubewells should be run with 7-h (on) and 4-h (off) operation. Further, the tubewells at all reaches (head, middle, and tail) should be closed for a minimum of 4 h between operations. This strategy would allow safe groundwater extraction, maintain water quality, and prevent water table depletion in the study area. The hydrodynamic and hydro-salinity behaviors were scrutinized in PWMIN 5.3 (version) by means of the MODFLOW mode. The results were estimated to compare the calibration and validation simulation outcomes using measured data. The model was successfully calibrated, and the root mean square (RMS) value of the head tubewell varied between 0.024 and 0.108, whereas it speckled between 0.0166 and 0.0349 for the middle tubewell and between 0.0659 and 0.0069 for the tail tubewell. The RMS values for hydrodynamic behavior for the head, middle, and tail reaches were less than 10%. These values represent a suitable match between the observed and simulated heads when a water table depletion of 1 to 2 m was observed due to extreme pumping. However, the average relative error values, for all validated procedures, were less than 10%.

Seasonal occurrence and ecological risk assessment of polycyclic aromatic hydrocarbons in the sediments and water in the left-bank canals of Indus River, Pakistan.

This study investigated a pressing environmental concern: the presence, distribution, sources, and ecological implications of sixteen polycyclic aromatic hydrocarbons (PAHs) in the left-bank canals of Kotri barrage-Akram, Pinyari, and Phuleli of the Indus River in Pakistan. These vital waterways, crucial for industrial, domestic, and agricultural activities, are experiencing contamination threats from anthropogenic sources, particularly PAHs. The study collected three water and two sediment samples from each canal in pre-monsoon and post-monsoon seasons. Then the EPA's liquid-liquid extraction method and gas chromatography determined the concentrations of PAHs. The findings of this study reveal alarming contamination levels, with pre-monsoon concentrations ranging from 22.256 to 836.455ng/L in water and 1,459.941 to 43,179.243ng/g in sediments. The post-monsoon concentrations ranged from 60.352 to 5663.058ng/L in water and 2976.770 to 15,238.335ng/g in sediments. The diagnostic ratios and principal component analysis (PCA) identified multiple sources of contamination, including industrial and domestic wastewater discharge, solid waste burning, vehicular emissions, biomass combustion, and petroleum residues. Furthermore, the assessment of the toxic equivalency factor (TEF) underscored the heightened carcinogenic potential of certain PAHs, notably benzo(a)pyrene and benzo(a)anthracene. Thus, the high levels of PAH contamination pose severe health risks to both human populations and aquatic ecosystems, emphasizing the urgency of addressing this issue. Stricter regulations governing industrial and domestic waste discharge, advocacy for cleaner fuel technologies, and the implementation of effective waste management practices must be initiated as crucial strategies in safeguarding the environmental integrity of the left-bank canals and the health of the surrounding communities.

Tree-ring maximum latewood density reveals unprecedented warming and long-term summer temperature in the upper Indus Basin, northern Pakistan

Understanding long-term temperature variability in the Upper Indus Basin (UIB), northern Pakistan, and its driving mechanisms is challenging due to the scarcity of long observational records and available literature. In this study, we reconstructed a 651-year (1370–2020 CE) warm-season (March–September) temperature record using the tree-ring maximum latewood density (MXD) of blue pine (Pinus wallichiana). The reconstruction explains 57 % of the variance in actual temperature during the common calibration period (1972–2020 CE). Our analysis identified ten high-temperature periods (temperature > 20.9 °C) and nineteen low-temperature periods (temperature < 19.8 °C), with the coldest years being 1392, 1707, 1817, and 1837, and the warmest years being 2013, 2016, 2017, and 2018. Spatial correlation analysis reveals a significant positive correlation with field temperature, predominantly in neighboring regions, and a significant negative correlation with relative humidity and precipitation. Multi-taper spectral analysis shows inter-annual (1.9, 2.5, 2.7, 5.5 years) and interdecadal (11, 18, 23, 25, 40, 71 years) cycles, suggesting a potential linkage with the Atlantic Multidecadal Oscillation (AMO). The negative linkage between our reconstruction and the region's standardized Palmer Drought Severity Index (scPDSI) indicates that continued temperature increase could result in severe drought in northern Pakistan in the near future. During the 20th century, the UIB experienced two distinct warming phases: 1948–1970 CE and 1994–2020 CE. The warming rate during 1994–2020 CE was 0.5 °C higher, indicating unprecedented recent warming. The reconstructed temperature record also demonstrates a large-scale spatiotemporal signal and a strong connection with most recorded volcanic eruptions. These findings enhance our understanding of long-term temperature variability in the region, highlighting the significance of MXD in reconstructing past temperature patterns.

Drivers of Widespread Floods in Indian River Basins

Abstract Widespread floods affecting multiple subbasins in a river basin have implications for infrastructure, agriculture, environment, and groundwater recharge. However, the crucial linkage between widespread floods and their drivers remains unexplored for Indian subcontinental river basins. Here, we examine the occurrence and drivers of widespread flooding in seven Indian subcontinental river basins during the observed climate (1959–2020). The peninsular river basins have a high probability of widespread flooding, compared to the transboundary basins of the Ganga and Brahmaputra. Favorable antecedent baseflow and soil moisture conditions, uniform precipitation distribution, and precipitation seasonality determine the probability of widespread floods in Indian river basins. The widespread floods are associated with large atmospheric circulations that cause precipitation in a large part of a river basin. Our findings highlight the prominent drivers and mechanisms of widespread floods with implications for flood mitigation in India.

Multi-covariate non-stationary flood frequency analysis for assessing flood hazard over the Mahanadi River basin, India

ABSTRACT Due to climate change and anthropogenic activities, the river’s peak flow is changing, which prompts exploring the non-stationary flood frequency analysis. Most of the past studies modelled the non-stationarity of floods, considering time and/or a single dominant covariate influencing the flood flows, but they are inadequate. This study proposes a multi-covariate non-stationary flood frequency model (MC-NSFFM) and investigates the influence of different covariates, such as rainfall, modified reservoir index (MRI), and climate indices, for the Mahanadi River basin in India. The models’ performances are evaluated by comparing them with the results of stationary and single-covariate non-stationary flood frequency models (SC-NSFFMs) using standard performance measures and return period analysis. The study showed that the MC-NSFFMs performed better than stationary and SC-NSFFMs. The flood return levels corresponding to the MC-NSFFMs are 4% to 22% higher than the stationary models, indicating the rise in flood risks due to climate change and anthropogenic activities.

Linking curve number with environmental flows: a novel approach.

Change in flow regime is one of the major reasons which influence the services offered by rivers and integrity of their aquatic ecosystems requiring certain amount of flow in the river known as environmental flow. In this study, the environmental flows described by Tennant's method are correlated with a very versatile index defined in terms of Curve Number (CN) that incorporates hydrometeorological and geomorphological characteristics of catchment. Parameter CN is commonly known to be closely related with catchment characteristics (viz., land use, soil type, etc.). The rainfall-runoff data of 17 catchments from five major Indian river basins (i.e., Brahmani-Baitarani, Godavari, Mahanadi, Mahi, and Narmada) of low flow season (October-June) are used to derive the relationship between percentage of average annual flow (%AAF) and CN. The %AAF is seen to increase linearly with increasing CN, and vice versa, for all catchments and the correlation (R) is found to be greater than 0.7 for 16 (out of 17) catchments. The correlation between %AAF and CN is maximum for Dhariawad (R2 = 0.899) and Baronda (R2 = 0.814) catchments, indicating excellent relationship between %AAF and CN, which can be useful for the environmental flow prediction based on catchment characteristics. The existence of such a relationship is further strengthened by the relation established between the standard normal deviate of CN and the Standard Flow Index (SQI), a variation of %AAF, using the same field data.

ExtendinG SUb-DAily River Discharge data over INdia (GUARDIAN).

River discharge information is crucial for various applications, but the measurement process often remains impeded by factors that hinder near real-time (NRT) data availability in India. However, leveraging telemetry-based water surface elevation (WSE) data across the country provides an opportunity to convert it into river discharge. This conversion is made possible by utilizing rating curves (RCs) derived from historical collocated measurements of WSE and discharge. In this study, NRT WSE from the Central Water Commission (CWC) flood portal is obtained via the web-scraping tool. Through the application of RCs, discharge data is extended across 210 gauging stations in India from the year 2020 to the present, encompassing sub-daily discharge during the non-monsoon and hourly discharge series during monsoon (June-September) across the Indian rivers. Annually, the study generated over 800,000 discharge data points for Indian rivers, accounting for more than 4000 discharge measurements per station annually. These comprehensive datasets provide valuable insights for water resource and flood management research, offering NRT access to WSE, and discharge, along with the local RCs.

Data-driven machine learning approaches for precise lithofacies identification in complex geological environments

ABSTRACT Reservoir characterization is a vital task within the oil and gas industry, with the identification of lithofacies in subsurface formations being a fundamental aspect of this process. However, lithofacies identification in complex geological environments with high dimensions, such as the Lower Indus Basin in Pakistan, poses a notable challenge, especially when dealing with limited data. To address this issue, we propose four common data-driven machine learning approaches: multi-resolution graph-based clustering (MRGC), artificial neural networks (ANN), K-nearest neighbors (KNN), and self-organizing map (SOM). We utilized these proposed approaches to assess their performance in scenarios with varying core sample availability, specifically evaluating their effectiveness in identifying lithofacies within the Lower Goru formation of the middle Indus Basin. The study reveals that in scenarios with a limited number of core samples, MRGC is the preferred choice, while KNN or MRGC is more suitable for larger datasets. The results demonstrate the superior performance of MRGC and KNN in lithofacies identification within the specified geological environment, with SOM following closely behind, and ANN exhibiting comparatively lower efficacy. The accurate identification of lithofacies from the selected model is complemented by the application of the truncated Gaussian simulation method for facies modeling. Comparative results confirm the excellent agreement between the model identification of lithofacies from well logs and electro-facies obtained from the truncated Gaussian simulation electro-facies volume. This study highlights the crucial role of selecting the right machine learning approach for precise lithofacies identification and modeling in complex geological environments. The comparative analysis provides practitioners in the petroleum industry with insights into the strengths and limitations of each method, enhancing existing knowledge. In conclusion, this research emphasizes the significance of comprehensive research and method selection for advancing lithofacies identification in diverse formations or study areas, ultimately benefiting the broader field of subsurface characterization in the petroleum industry.

Biogeography of the Iranian snakes.

The events of the Cenozoic era such as mountain formation caused Iran to become one of the most amazing biodiversity hotspots in the world today. This pioneering study on Iranian snake biogeography integrates historical and ecological analyses. A phylogeographic review traces speciation and dispersal, while cluster analysis with a new snake checklist assesses faunistic similarities within Iran and its surroundings. Jaccard and Sorenson indices generate similarity dendrograms, Indicator Species Analysis pinpoints regional key species, and Endemism index calculates regional endemism rates, enriching our knowledge of Iran's species diversity. Phylogeographic analyses identify four biogeographical corridors for snake ingress into Iran: the Arabian region through southwestern Iran, the Western Asian mountainous transition zone via northwestern Iran, the Turanian region into northeastern Iran, and the Indus River Valley into southeastern and eastern Iran. Dendrogram analysis divides snake fauna into three groups. The first group associates western Zagros and Khuzestan fauna with the Sahara and Arabian regions. The second group links Kopet Dagh and Turkmen Steppe fauna with the Turanian region, and Central Plateau and Baluchistan fauna with the Iranian region. The third group connects northwest highlands, Alborz and Zagros mountains, and Caspian Sea coasts with the Western Asian Mountain transition zone. The study validates broad biogeographic patterns via ecoregional associations and indicator species analysis, providing finer resolution. Species like Platyceps najadum in Caspian Hyrcanian mixed forests exemplify ecoregional alignment, while Zagros and Alborz mountains exhibit unique faunal indicators, indicating species-level divergence. Shared indicators among widespread ecoregions reflect habitat continuity; exclusive indicators emphasize regional distinctiveness. Despite endemic species prevalence, they seldom act as significant indicators due to various factors. Our research confirms the Zagros Mountains, Khuzestan Plain, Alborz Mountains, and Persian Gulf coasts as snake diversity hotspots, marked by higher species richness compared to other Iranian regions.

Seismic Imaging of Strata Truncating to Base Miocene Unconformity Integrated with Petrophysical Analysis of Mianwali Re-entrant, Pakistan: a Case Study from the Upper Indus Basin of Pakistan

Seismic Imaging of Strata Truncating to Base Miocene Unconformity Integrated with Petrophysical Analysis of Mianwali Re-entrant, Pakistan: a Case Study from the Upper Indus Basin of Pakistan

Reconstructing Tibetan Plateau lake bathymetry using ICESat-2 photon-counting laser altimetry

Lake bathymetry is important for quantifying and characterizing underwater morphology and its geophysical state, which is critical for hydrological and ecological studies. Due primarily to the harsh environment of the Tibetan Plateau, there is a severe lack of lake bathymetry measurements, limiting the accurate estimation of total lake volumes and their evolutions. Here, we propose a novel lake bathymetry reconstruction by combining ICESat-2/ATLAS (Advanced Topography Laser Altimetry System) data with a numerical model. An improved grid-based photon noise removal method is used to address the photon signal buried in the background noise during the local daytime. The developed model was validated for seven lakes on the Tibetan Plateau and showed good agreement between simulated and measured lake volumes, with an average absolute percentage error of 8.0 % for maximum water depth and 19.7 % for lake volume simulations. The model was then utilized to estimate the water volume of other lakes by combining it with the self-affine theory. The lake depths obtained from ICESat-2/ATLAS show good agreement (RMSE = 0.69 m; rRMSE = 10.3 %) with available in-situ measurements for lakes with depths <16.5 m, demonstrating the potential of ICESat-2/ATLAS for improved reconstruction of the bathymetry of clear water inland lakes. Our study reveals for the first time, that the Tibetan Plateau has an estimated total lake water volume of 1043.69 ± 341.31 km3 for 33,477 lakes (>0.01 km2) in 2022. Over 70 % (∼734.8 km3) of the lake water storage is concentrated in the Inner Plateau, with the Yellow River basin accounting for 10.9 % (∼113.9 km3), followed by the Indus River basin with 7.2 % (∼75.1 km3). Our study provides a robust method for estimating total lake volumes where in-situ measurements are scarce and can be extended to other clear water lakes, thus contributing to more accurate global assessments and towards comprehensive quantification of Earth's surface water resources distribution.

Dynamical and rheological analysis of gas condensate reservoir characteristics and multiphase flow behavior of a well

This manuscript proposes dynamical and rheological analysis of gas condensate reservoir characteristics and multiphase flow behavior of a well located at the lower Indus basin gas condensate reservoir in Sindh, Pakistan. The main objective is to analyze the compositional variation impacts on the liquid dropout, flow behavior and well productivity. For the sake of data analysis, constant composition expansion and constant volume depletion capabilities have been tested via pressure, volume and temperature cell under measurement of dew point and liquid dropout flow. By invoking CMG: Win prop simulator on the basis of equation of state namely Peng Robenson and Soave Redlish Kwong equations, phase diagram and well stream physical parameters have been analyzed. Our result suggested crucial significance for the behavior of flow and well productivity that liquid generation changes with the physical properties of flowing stream namely vapor viscosity, compressibility factor and vapor density due to pressure depletion showing decreasing trend. Mole percent of lighter components C1 mole percent increases from 54.567 to 62.153. While mole percent of heavier components C18+ decreases from 3.453 to 1.513 with 45% liquid dropout. In brevity, maximum well productivity has been observed in composition-1 which is 5.005 MMscf/day at pressure of 3131 psig.

Groundwater quality assessment for drinking and irrigation purposes in arid to semiarid region of Indus Basin of South Punjab, Pakistan

&lt;p&gt;&lt;a name="_Hlk173243332"&gt;&lt;span style="background-color:white;color:black;font-family:&amp;quot;Times New Roman&amp;quot;,serif;font-size:12.0pt;line-height:150%;"&gt;As the groundwater pollution is increasing, it is crucial to assess groundwater quality and characterize hydrogeochemistry accurately for long term water supply.&amp;nbsp;&lt;/span&gt;&lt;/a&gt;&lt;span style="background-color:white;color:black;font-family:&amp;quot;Times New Roman&amp;quot;,serif;font-size:12.0pt;line-height:150%;"&gt;In this study groundwater samples were collected from 120 locations from Bahawalpur district and analyzed for electrical conductivity (EC), pH, total dissolved solids (TDS), sodium (Na&lt;sup&gt;+&lt;/sup&gt;), potassium (K&lt;sup&gt;+&lt;/sup&gt;), calcium (Ca&lt;sup&gt;2+&lt;/sup&gt;), magnesium (Mg&lt;sup&gt;2+&lt;/sup&gt;), carbonate (CO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;-&lt;/sup&gt;), bicarbonate (HCO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;-&lt;/sup&gt;), sulfate (SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt;), chloride (Cl&lt;sup&gt;-&lt;/sup&gt;), nitrate (NO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;-&lt;/sup&gt;), fluoride (F&lt;sup&gt;-&lt;/sup&gt;) and heavy metals. The results obtained from the analysis of samples showed that the SAR of nearly 65% of samples collected from Bahawalpur district were in acceptable limit (&amp;lt;6 meq L&lt;sup&gt;-1&lt;/sup&gt;), while 12% found to be unfit for irrigation (&amp;gt;10 meq L&lt;sup&gt;-1&lt;/sup&gt;). Similarly, the RSC values depicted that 8% samples were unfit while 64% samples were falling in the category of fit irrigation water. Most of the water samples were predominantly Ca&lt;sup&gt;2+&lt;/sup&gt;-HCO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;-&lt;/sup&gt; and Na&lt;sup&gt;+&lt;/sup&gt;-HCO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;-&lt;/sup&gt; type, that were controlled by various processes of cation exchange, water-rock interaction, dissolution and evaporation. Some samples fall in the&amp;nbsp;middle of diamond and lower triangles of Piper diagram are showing no dominant type of water (mixed water type) due to the complex influence of rock-water interactions as well as anthropogenic activities. The Water Quality Index (WQI) showed that&amp;nbsp;out of total 120 sampling sites in Bahawalpur the number of excellent water samples were only 2% while 18% water samples were characterized as hazardous. Moreover, the number of samples falling in the categories of good, poor and very poor quality water were 36%, 29% and 13% respectively.&lt;/span&gt;&lt;/p&gt;

Dynamic changes, cycling and downward fate of dissolved carbon and nitrogen photosynthetically-derived from glaciers in upper Indus river basin

Glaciers play key roles in capturing, storing, and transforming global carbon and nitrogen, thereby contributing markedly to their cycles. However, an integrated mechanistic approach is still lacking regarding glacier's primary producers (PP), in terms of stable dissolved inorganic carbon isotope (δ13C-DIC) and its relationship with dissolved carbon and nitrogen transformation d ynamic changes/cycling. Here, we sampled waters from glaciers, streams, tributaries, and the Indus River (IR) mainstream in the Upper IR Basin, Western Himalaya. Dissolved organic matter (DOM) appears to increase, on average, by ∼2.5–23.4% with fluctuations when passing from glaciers to streams-tributaries-IR mainstream (the upper and lower parts, respectively) continuum, implying that DOM originates from glaciers PP and is subsequently degraded. The corresponding fluctuations are observed for fluorescent DOM (FDOM), dissolved organic nitrogen (8.0–106.8%), NO3−-N (−13.5/+16.6%), NH4+-N (−8.8/+13.0%), and NO2−-N (70.7–217.5%). These variations are associated with overall DOM/FDOM transformations, with the production of ending byproducts (e.g. CO2/DIC). The δ13C-DIC values fluctuated from glaciers (−5.3 ± 2.5‰) to streams (−4.4 ± 2.1‰), tributaries (−4.3 ± 1.6‰), and IR mainstream (−4.2 ± 1.3‰). The δ13C-DIC data are consistent with C transformations that involve lighter CO2 emission into the atmosphere, whereas highly depleted DIC/CO2 is the signature of DOM degradation after its fresh production from glaciers PP which originated by photosynthetic activities (e.g. uptake/sink of atmospheric CO2: −8.4‰). Finally, glacier-fed meltwaters would simultaneously contribute to the biogeochemical characteristics of downward margins and specific ecosystems (lake/pond/groundwater/hot springs) via transformation dynamics/cycling of dissolved C and N with high photo/microbial lability. Our results highlight the substantial contribution of western Himalayan glaciers-derived DOM to the global C and N cycles.

Unlocking thin sand potential: a data-driven approach to reservoir characterization and pore pressure mapping

The gradual decline of production of the major fields of the Indus Basin has influenced the field pressure. Therefore, the prospects need to be assessed by the petro-elastic relationship. This study highlights the value-addition for identifying gas pockets within the E-Sand of the Lower Goru Formation through estimating and populating petro-elastic properties. A probabilistic neural network (PNN) was employed to develop the relationship of pore pressure to the inverted properties. The outcomes will help identify the high-pressure areas in accordance with the petro-elastic relationship for optimizing production strategy. In order to evaluate the petro-elastic relationship, stochastic seismic inversion was employed to holistically capture the reservoir’s variability. Pore pressure volumetric was estimated from inverted attributes using a PNN, a non-linear algorithm that was more suited to heterogeneous reservoirs. The main objective of the research is achieved via enhanced resolution of elastic properties attained through the integration of stochastic inversion and PNN processes. The high-resolution elastic properties including P-impedance, S-impedance, and Vp/Vs ratio can delineate the heterogeneities more profoundly. The petrophysical volumes obtained via enhanced inverted properties combined with pore-pressure through PNN illuminated the potential facies and the correlations in predicting the properties. The procedure provides a linkage of elastic, petrophysical, and geomechanical properties that is helpful for professionals covering a broad field of the petroleum sector. The developed workflow can be followed globally where problems occur regarding heterogeneities and early depletion.

Elevation-Dependent Snow Cover Dynamics and Associated Topo-Climate Impacts in Upper Indus River Basin

In the present study, Improved Moderate Resolution Imaging Spectro-radiometer (MODIS) snow cover product (MOYDGL06*) has been used to evaluate the snow cover area (SCA) in Kabul, Jhelum, and Indus river basins for the time period of 2003 – 2020 with available MODIS land surface temperature (LST), and CHIRPS (precipitation) with objectives to evaluate the spatio-temporal SCA, and climate variables with respect to different elevations analyzed from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model Version 3 (GDEM v3) and also to correlate the climatic variables with SCA. The results presented average annual SCA is around 50.7% – 64.7% in sub-basins of UIB, further it has been observed that SCA is decreasing on annual and seasonal timescale in all three basins. Elevation-dependent SCA, temperature, and precipitation presented a mix of trend on annual, seasonal, and monthly timescale at lower and higher altitude in all selected basins. Moreover, it was noticed that topography (slope, & aspect) also influences the SCA in the region. Furthermore, it has been examined that temperature has significant inverse relationship with SCA at middle and higher altitude in Indus, while in Kabul, and Jhelum no significant relationship observed at extreme lower and higher altitudes. It is also evident from relationship between SCA and climate variable that temperature is significantly responsible for decreasing trend of SCA rather than intense precipitation in all three river basins. Thus, all these elevation-dependent changes can improve our hydrological understanding which can have a considerable implication for hydrology, climate science, water resource management and socio-economic activities.

Remote sensing applications to identify devastated lagoons of the Indus Delta Pakistan

A reduction in river flows is a major cause of the shrinking of river deltas. The Ramsar protected Indus Delta is one such example. Due to a consistent reduction in the flows of the Indus River, 15 out of 17 allied creeks facing back flows from the sea, while the remaining two are flowing during flooding years only. The connected wetlands and lagoons of these creeks have turned brackish, resulting in the devastation of associated habitats and ecosystems. This situation also increased seawater intrusion and coastal erosion. This study spatially detect the devastated lagoons, employing the Arc-Hydro tools in ArcGIS, conduct community meetings and draft evidence-based recommendations to revive the abandoned wetlands. The study identified 130 waterbodies using maximum likelihood and supervised classification methods on Landsat imagery. Through ground trothing 20 abandoned waterbodies have been visited and verified with community engagement. The revival of wetlands will improve biodiversity and coastal habitat, along with the re-plantation of mangrove, which provides a shield against tsunamis and cyclones and is also home to hundreds of species of shrimp. The sustainable wetlands may also provide immediate drinking and agricultural needs for the local population, as well as repel seawater from intruding inland.

Snow runoff modelling in the upper Indus River Basin and its implication to energy water food nexus

Pakistan's hydropower sector depends heavily on glacier and snowmelt water that originates from the Upper Indus Basin (UIB). It is expected that climate change may adversely affect future hydropower generation capacity as a result of fluctuations in the magnitude, seasonality and hydrological extremes of the Indus River flow. This study employed the Degree-Day Snowmelt Runoff Model alongside the Moderate Resolution Imaging Spectroradiometer MODIS and daily ground-based hydro-meteorological data to model the snowmelt runoff response in the UIB. The results indicated a significant increase in the annual and seasonal runoff under both RCP4.5 and RCP8.5 scenarios, suggesting more water availability for hydropower and irrigation. By the end of the century, annual river flow is projected to increase by 28 % to 69 % under the RCP4.5 and RCP8.5 climate scenarios. Consequently, rise in annual river flow is expected to increase the electricity generation capacity of future hydropower projects by 93 % to 167 % under the RCP4.5 and RCP8.5 scenarios, respectively. The construction of robust multipurpose dams may potentially reduce flood risks in downstream areas during peak flows, while also supplying water for hydropower generation and irrigation during low flows. This, in turn, may enhance the resilience of both the hydropower and agriculture sectors in the face of climate change.