Northwestern Himalaya Research Articles

Cryospheric changes and livelihood vulnerability in Lahaul Region of North-Western Himalaya, India

Cryospheric changes and livelihood vulnerability in Lahaul Region of North-Western Himalaya, India

Predicting rainfall using machine learning, deep learning, and time series models across an altitudinal gradient in the North-Western Himalayas

AbstractPredicting rainfall is a challenging and critical task due to its significant impact on society. Timely and accurate predictions are essential for minimizing human and financial losses. The dependence of approximately 60% of agricultural land in India on monsoon rainfall implies the crucial nature of accurate rainfall prediction. Precise rainfall forecasts can facilitate early preparedness for disasters associated with heavy rains, enabling the public and government to take necessary precautions. In the North-Western Himalayas, where meteorological data are limited, the need for improved accuracy in traditional modeling methods for rainfall forecasting is pressing. To address this, our study proposes the application of advanced machine learning (ML) algorithms, including random forest (RF), support vector regression (SVR), artificial neural network (ANN), and k-nearest neighbour (KNN) along with various deep learning (DL) algorithms such as long short-term memory (LSTM), bi-directional LSTM, deep LSTM, gated recurrent unit (GRU), and simple recurrent neural network (RNN). These advanced techniques hold the potential to significantly improve the accuracy of rainfall prediction, offering hope for more reliable forecasts. Additionally, time series techniques, including autoregressive integrated moving average (ARIMA) and trigonometric, Box-Cox transform, arma errors, trend, and seasonal components (TBATS), are proposed for predicting rainfall across the altitudinal gradients of India’s North-Western Himalayas. This approach can potentially revolutionise how we approach rainfall forecasting, ushering in a new era of accuracy and reliability. The effectiveness and accuracy of the proposed algorithms were assessed using meteorological data obtained from six weather stations at different elevations spanning from 1980 to 2021. The results indicate that DL methods exhibit the highest accuracy in predicting rainfall, as measured by the root mean squared error (RMSE) and mean absolute error (MAE), followed by ML algorithms and time series techniques. Among the DL algorithms, the accuracy order was bi-directional LSTM, LSTM, RNN, deep LSTM, and GRU. For the ML algorithms, the accuracy order was ANN, KNN, SVR, and RF. These findings suggest that altitude significantly affects the accuracy of the models, highlighting the need for additional weather stations in this mountainous region to enhance the precision of rainfall prediction.

Induced genetic variability for quantitative and biochemical traits of local landraces of rajmash (Phaseolus vulgaris) of north-western Himalayas

The present study was carried out during rainy (kharif) seasons of 2020 and 2021 at Regional Horticulture Research Station (Sher-e-Kashmir University of Agricultural Sciences and Technology, Jammu, Jammu and Kashmir), Bhaderwah, Doda, Jammu, Jammu and Kashmir to evaluate genetic variability for quantitative and biochemical traits of local landraces of rajmash (Phaseolus vulgaris L.) of north-western Himalayas. Twenty-two induced mutant lines of rajmash generated with gamma rays and ethyl methane sulphonate were screened for quantitative, qualitative and anthracnose reactions under natural and artificial conditions in the field during kharif 2020 (M3) and 2021 (M4). The highly significant differences imply that induced mutant lines for different traits exhibited substantial amount of genetic diversity. Zinc content (55.38) and grain yield/plant (33.24) both had high phenotypic coefficients of variation, while 1000-seed weight (10.14) and protein content had low values (9.83). Zinc content had highest genetic advance, measured as a percentage of the mean, and the highest heritability, followed by grain yield/plant, iron content, number of pods/plant, number of clusters/plant, days to flowering and number of seeds/pod, whereas days to maturity and 1000-seed weight were moderate. The number of pods/plant (0.774), number of seeds/pod (0.556), number of clusters/plant (0.729), length of pod (0.648) and 1000-seed weight (0.620) all exposed a highly significant relationship with grain yield/plant but the days to flowering (-0.636) and days to maturity showed negative correlation (-0.602). It is obvious that the 9 induced mutant lines of Bhaderwah local and Poonch local i.e. R-BL-M3-1, R-BL-M3-9, R-BL-M3-10, R-BL-M3-12, R-BL-M3-13, R-BL-M3-14, R-PL-M3-18, R-PL-M3-20 and R-PL-M3-22 showed the minimum anthracnose disease incidence along with early emergence and superiority in grain yield/plant compared to controls. These mutant lines may be carried forward for the development of mutant genetic stocks and varietal development programmes of rajmash for north-western Himalayan region.

Sowing Environments and Yield of Maize (Zea mays L.) Cultivars under Changing Climate Conditions of North Western Himalayan Region

Sowing dates, as one of the primary agronomic practices have significant influence over yield of maize especially during the times of climate change. Therefore, the present field investigation was conducted during the Kharif cropping seasons of 2013 and 2014 to evaluate different sowing dates for their influence over maize (Zea mays L.) yield. The field experiment was conducted in a randomized block design with factorial arrangement consisting of four dates of sowing and three maize cultivars. The study results revealed that sowing of crop by 10th June can have taller plants (261.5 and 265.2 cm for 2013 and 2014, respectively), significantly better yield contributing characters of maize such as number of cobs per plant (1.1 and 1.1 for 2013 and 2014, respectively), number of grains per cob (258.7 and 268.3 for 2013 and 2014, respectively) and test weight (268.5 and 271.6 grams for 2013 and 2014, respectively). Similarly, the significantly higher maize grain (57.3 and 60.1 quintal/hectare for 2013 and 2014, respectively) and stover yield (108.8 and 109.2 quintal/hectare for 2013 and 2014, respectively) was recorded with sowing of maize crop by 10th June. Among the maize cultivars, HQPM-1 resulted in substantially higher maize grain (53.9 and 56.5 quintal/hectare for 2013 and 2014, respectively) and stover yield (102.9 and 104.1 quintal/hectare for 2013 and 2014, respectively). Based on the present field investigation, it can be concluded that sowing of maize by 10th June and maize cultivar HQPM-1 can be recommended for better yield levels under the given conditions of North-western Himalayas.

Integrated organic and mineral fertilizer strategies for achieving sustainable maize yield and soil quality in dry sub-humid inceptisols

Maize is one of the important cereal crops grown in rainfed regions of northwestern Himalayas, however, persistent use of chemical fertilizers coupled with poor soil nutrients and water holding capacity due to coarse textured soils poses serious threat to sustaining maize yield and soil health. To address these bottlenecks, a long-term experiment with application of organic manures and mineral fertilizer provides insights to quantify changes in soil organic carbon (SOC), crop yield and rain water use efficiency (RWUE) in rainfed area having low water use efficiency. A twelve years field experiment was conducted under dry sub-humid Inceptisols in northern India to study the potential impacts of organic and mineral fertilization on maize (Zea mays L.) productivity, water use efficiency and soil quality. Ten treatments were assessed, involving different nitrogen levels (20, 30, and 40 kg N ha⁻¹) combined with 10 tha⁻¹ year⁻¹ of farmyard manure (FYM), in-situ green manure from sunhemp, and the incorporation of Leucaena leucocephala leaves at 5 tha⁻¹ year⁻¹, including an unfertilized control. Maize yield increased linearly with increasing nitrogen application rates. The combination of FYM @ 10t ha−1 and 40 kg N ha−1(T4) yielded the highest maize production. Manure addition improved soil organic carbon (SOC) and major soil nutrients (N, P and K) while unfertilized control showed decline in soil nutrients compared to their initial values. Compared with control, incorporation of 10 t ha−1 FYM increased SOC by 1.3, 1.41, 1.44 times at application rate of 20, 30, 40 kg N ha−1, respectively. Application of N@40 kg ha−1 + 10t FYM ha−1 showed highest rain water use efficiency (RWUE) and relative production efficiency index (RPEI) (2.74 kg ha−1 mm−1 and 82, respectively) and the lowest rank sum of 6. Highly significant positive relationship existed between RPEI and RWUE, RPEI and sustainability yield index (SYI), RWUE and SYI indicated the superiority of FYM in combination with mineral fertilizer. Regression models, correlating yield with monthly rainfall and crop growing periods, indicated that the integration of FYM (10 tha⁻¹) with 40 kg N ha⁻¹ was most effective in achieving the highest relative soil quality index (RSQI) of 76 and the greatest sustainability yield index (SYI) of 49.3%. Based on results, we recommend balanced fertilization (N@40 kg ha−1 +10t FYM ha−1) which is easily manageable by farmers as the optimal strategy for improving soil quality and achieving sustainable maize productivity in nutrient depleted Inceptisols of northern India.

Tubaria armeniaca, a new species of Tubaria from Northwestern Himalayas of Uttarakhand, India

Tubaria armeniaca, a new species of Tubaria from Northwestern Himalayas of Uttarakhand, India

Multi-criteria assessment of PDGLs for GLOFs hazards in the Bhut and Warwan sub-basin of the Chenab basin Northwestern Himalaya

Multi-criteria assessment of PDGLs for GLOFs hazards in the Bhut and Warwan sub-basin of the Chenab basin Northwestern Himalaya

Northwestern Himalayan common beans: A Treasure Trove for breeding resistant bean cultivars for multiple foliar pathogens

Common bean (Phaseolus vulgaris. L) is attacked by a lot of important foliar diseases like anthracnose, Bean Common Mosaic Virus, angular leaf spot, Bean Golden Yellow Mosaic Virus, and common bacterial blight. In the present study, we exploited anthracnose resistant germplasm of 122 common bean genotypes for the identification of broad spectrum and durable resistance for multiple foliar diseases. We utilized linked molecular markers and found some promising genotypes with 11 resistance genes. These genotypes possess significant potential as parental lines for gene pyramiding strategies, to enhance disease resistance in common beans. We also highlighted the need for new generation markers over SCAR markers to streamline genotypic screening and expedite the breeding of disease-resistant common bean varieties. Our phenotypic studies identified a few bean landraces highly resistant to the new BCMV NL-1n strain. Consequently, the genome wide association study also confirms the presence of already identified resistance genes. Additionally, our study reconfirms the presence of the recently identified bc-urgene in our material. The bean landraces of northern India contain novel regions associated with BCMV resistance on Pv03, Pv05, Pv04, Pv06, Pv07, Pv09, and Pv11. This study provides the list of bean genotypes that can be used to breed resistant cultivars and may also contain new resistance genes to a most important viral disease of common beans.

Effect of Sowing Dates and Wheat Cultivars on Agro Meteorological Indices of Wheat under Conditions of North-western Himalayas, India

Climate change in recent times have presented a scenario of elevated susceptibility of wheat to rising temperatures. Agro-meteorological indices can present a scenario of variable response of wheat to diverse conditions. A field investigation was conducted in rabi season of 2016-17 at Research farm, Department of Agronomy, CSK Himachal Pradesh Krishi Vishvavidyalaya, Palampur to evaluate the influence of sowing dates and wheat cultivars on agro-meteorological indices such as growing degree days, photothermal units, Helio thermal units and phenothermal index of wheat crop. The field investigation involved five sowing dates (15th October, 30th October, 15th November, 30th November and 15th December) and wheat cultivars (HPW-349 and HPW-155) which were studied in a factorial randomized block design with three replications. The results of the investigation revealed that timely sown crop i.e., on 15th October recorded the highest values for agro-meteorological indices for both the wheat cultivars such as growing degree days, Helio thermal units, photothermal units and phenothermal index across various wheat development stages such as complete emergence, crown root initiation, tillering, ear emergence and physiological maturity. Therefore, timely sowing of wheat by 15th October was concluded to be the best for optimized agro-meteorological indices such as growing degree days, photothermal units, Helio thermal units and phenothermal index under conditions of North-Western Himalayas.

Modern Pollen Signatures and Vegetation Dynamics in Northwestern Himalaya, India

ABSTRACT Palynological studies have been conducted for the first time in the Renukaji Wildlife Sanctuary (RWS), a Sal-dominated region within the foothills of Northwestern (NW) Himalaya in Himachal Pradesh, India. This research enhances our understanding of the relationship between modern pollen rain and vegetation, as well as pollen representation in sediments. Furthermore, it contributes to palaeovegetation reconstruction based on paleoclimatic trends by improving our interpretation of pollen deposition patterns. The study area was delineated into three distinct zones based on biological niche characteristics: Zone 1 (Recreation Zone), Zone 2 (Buffer Zone), and Zone 3 (Core Zone). Pollen analysis conducted on 30 surface soil samples and moss cushions, collected from all three zones, reveals the dominance of dry deciduous taxa, followed by extra-terrestrial taxa and wet deciduous taxa. Land Use Land Cover (LULC) analysis performed using satellite data reveals that Shorea robusta (Sal) mixed forest covers 32% of land, followed by Pinus spp. (8%) and their associates (25%). Shorea robusta, a mixed wet deciduous taxon and high pollen producer, exhibits low pollen counts, possibly due to chemical and microbial decomposition or low pollen dispersal efficiency. This study utilises a comparative database correlating pollen data with contemporary vegetation patterns to establish a robust framework for assessing sedimentary pollen sequences. Through this approach, we aim to elucidate past vegetation dynamics and infer climate fluctuations within the NW Himalaya.

Integrative taxonomic review of the genus Rhodostrophia Hübner, 1823 and its allied genus Tanaotrichia Warren, 1893 (Lepidoptera: Geometridae) from the Western Himalaya

The genus Rhodostrophia Hübner, 1823 and its close ally Tanaotrichia Warren, 1893 (Geometridae: Sterrhinae) are reviewed from the North Western and Trans Himalayan regions of the Indian Himalaya along with some specimens from the Pakistan. In total, eight species were studied—seven Rhodostrophia spp. and one species of Tanaotrichia—with detailed morphological and genital characteristics. Rhodostrophia borealis stat. n. is raised from subspecies of R. cinerascens to species level after studying external morphology and distinct genitalia-based diagnostic features. However, this warrants further validation following the barcode sequencing of R. cinerascens. Illustrations of habitus, including type specimens, are provided along with images of genitalia and the sequence data of the mitochondrial cytochrome c oxidase subunit I (COI 5′ terminus) gene. A checklist of Indian Rhodostrophia and Tanaotrichia species is included with information on their documented distributional range.

Elucidating the genetic potential of hybrids derived from elite maize (Zea mays L.) inbreds for economic traits under North-Western Himalayan condition

Abstract This study was conducted to evaluate the combining ability of newly acquired maize inbred lines over the environments. Twenty-eight crosses developed by crossing eight elite inbreds in a half-diallel mating design were evaluated during kharif, 2019 for 12 agro-morphological traits in RBD with two replications at two different environments reflecting diverse agro-climatic and ecological conditions of North-Western Himalayas (SAREC, Kangra and HAREC, Bajaura). Analysis of variance showed that there was sufficient amount of genetic variability in the material studied. In accordance to Bartlett’s test, error variance was homogeneous only for six traits. Estimates of σ2SCA were higher as compared to σ2GCA both within and across environments for all the traits, except days to 75 per cent brown husk at Kangra, representing prevalence of non-additive gene action for these traits. The inbred line B73 at Bajaura, and LM14 at Kangra were found to be good general combiner for most traits. The inbreds with good GCA can be used as potential parents for the development of high yielding single cross maize hybrids. The hybrid combinations namely, B73 × BAJIM1811 and BAJIM1522 × BAJIM1811 were identified as potentially superior ones at Kangra and Bajaura environments. The identified promising hybrids need further assessment for their superiority in performance across the locations and over years. Keywords: General combining ability, specific combining ability, gene action and maize.

Geochemistry of Mafic Rocks From the Nagrota–Kathindi Section, Himachal Pradesh, Northwestern Himalaya: A Probable Example of Plume–Lithosphere Interaction

ABSTRACTThe Northwest Himalayan region has a record of several phases of mafic magmatic activity spanning from Precambrian to Cenozoic in a dynamic tectonic setting. Here, we studied detailed petrography and new whole‐rock geochemistry of mafic volcanic and dykes from the Nagrota–Kathindi Section (NKS), Himachal region of the NW Himalaya, to understand the petrogenesis and possible tectonic setting. Both rock types have comparable mineralogical compositions (clinopyroxene + plagioclase + actinolite‐tremolite + chlorite + iron oxides ± hornblende ± epidote ± quartz ± carbonates) overprinted by greenschist to lower amphibolite facies metamorphism. The mafic volcanic and dykes of NKS exhibit subalkaline basalts to basaltic andesites and a typical tholeiite compositional character. The chondrite‐normalized rare earth element pattern exhibits similar LREE‐enrichment and strong HREE‐fractionation, whereas primitive mantle‐normalized multi‐element patterns show pronounced LILE‐enrichment of Rb, Ba, Th, LREE, and HFSE depletion of Nb, K, P, and Ti. The Zr–Y–Nb–Th relationships indicate that both rock types were derived from the plume source, whereas low Nb/La (< 1), similar high large‐ion lithophile element concentrations, and pronounced negative Nb, Zr, P, and Ti anomalies suggest that components other than mantle plume must have been involved in the generation and evolution of both rock types, that is, most likely plume and subcontinental lithosphere mantle (SCLM) interaction. The genesis of parent magma for the NKS volcanic and dykes was derived by 4%–6% and 10%–20% partial melting from the spinel + garnet lherzolite stability field. The majority of the studied samples correspond to spinel + garnet peridotite melting on (Gd/Yb)N versus CaO/Al2O3 diagram, thereby corroborating residual garnet in the mantle restite. All the basalts and dykes from the NK section did erupt/intrude in an intracontinental rift setting based on geochemical discrimination. The key petro‐tectonic processes attributed to the formation of these rocks are as follows: (i) the melting of the ascending plume by adiabatic decompression; (ii) the partial melting of this plume–SCLM source in the melting regime, which produces basaltic magma with a tholeiitic composition; and (iii) the release of heat that provides the thermal condition for melting of SCLM and interaction between upwelling mantle plume and subduction metasomatized SCLM.

Land use and altitudinal variability in biomass and carbon storage potential in mid-hill and sub-humid conditions of north-western Himalayas

Land use and altitudinal variability in biomass and carbon storage potential in mid-hill and sub-humid conditions of north-western Himalayas

First Comprehensive Evaluation of Genetic Variability for Bacterial Blight Resistance in Wild Punica granatum L. Populations from the North-Western Himalayas

Identifying and selecting disease-resistant sources from wild germplasm pools is pivotal due to their ecological benefits and cost-effectiveness. This study encompassed the survey and collection of wild pomegranate genotypes alongside commercial cultivars, followed by screening against native pathogens. Additionally, biochemical analyses were conducted to elucidate defense mechanisms in both resistant and susceptible genotypes. Cuttings from selected germplasm across four districts were obtained, grown for one year, and assessed for pathogenicity and biochemical responses. Microscopic and molecular analyses confirmed the pathogen as Xanthomonas axonopodis pv. punicae (Xap), identified by its distinctive morphology and a 1500 bp amplicon along with phylogeny analysis. Germplasm screening via detached and attached leaf assays identified genotypes with minimal disease severity, highlighting SH-14 and SH-16 as highly resistant in the attached leaf assay. Principal component analysis categorized genotypes based on disease parameters, with PC1 explaining approximately 75% of the variability. Agglomerative hierarchical clustering further grouped genotypes into ten clusters, emphasizing clusters IX and X for their significant resistance traits. Biochemical studies revealed that the resistant genotype SH-16 exhibited higher levels of constitutive defense components like chlorophyll and vitamin C, as well as induced defense components such as phenols, flavonoids, and antioxidants, compared to the susceptible cultivar Bhagwa. These findings underscore the critical roles of both constitutive and induced defense mechanisms in conferring pomegranate resistance to Xap. The study's comprehensive approach in evaluating genetic and biochemical resistance provides valuable insights for breeding disease-resistant pomegranate varieties, marking a significant advancement in exploring pomegranate wild relatives from the Himalayan region for their resistance to bacterial blight.

Assessment of shift in GWPZs in Kashmir Valley of Northwestern Himalayas

Groundwater is a critical resource for the Kashmir Valley, which is increasingly pressured by urbanization and climate change. This study aims to delineate Groundwater Potential Zones (GWPZs) in the Kashmir Valley using the Analytical Hierarchy Process (AHP) and Geographical Information Systems (GIS). The research integrates eight thematic layers, including geology, geomorphology, slope, drainage density, land use/land cover (LULC), lineament density, rainfall, and topographic wetness index (TWI), to assess GWPZs for 1995, 2010, and 2020. Weights for each layer were assigned based on their influence on groundwater dynamics. The generated GWPZs were classified into five classes: very high, high, moderate, low, and very low. Over 25 years, significant changes in GWPZs were observed: very low potential zones decreased by 45.17%, low potential zones by 26.17%, and very high potential zones by 72.95%. Conversely, moderate potential zones increased by 50.87%, and high potential zones saw a slight increase of 9.00%. Results indicated that high and very high GWPZs are predominantly located in the valley's alluvial plains, primarily covered by agricultural and partially horticultural land. Validation of the generated GWPZs using bore well locations, discharge data, and Receiver Operating Characteristic (ROC) curves demonstrated high accuracy, with Area Under the Curve (AUC) values of 0.915, 0.898, and 0.890 for the respective years. These findings underscore the adverse impact of urbanization on groundwater potential zonation and emphasize the need for sustainable water management practices. This study provides valuable insights into the long-term shifts in groundwater potential in response to urban expansion and climate change. It highlights the importance of continuous monitoring and adaptive management to safeguard groundwater resources.

Unveiling the microbiome and metabolites of traditional dairy and alcoholic products from North-western Himalayan region

The people of the Indian North-western Himalayas consume various traditional fermented foods, which may contribute to their healthy lifestyle. However, the probiotic diversity of the region is largely unknown. In the current study, indigenous Himalayan traditional foods (dairy products and alcoholic beverages) were investigated for probiotic diversity via culture-based and culture-independent methods and metabolites study. The culture-based taxonomic classification revealed the prevalence of probiotic genera Levilactobacillus, Latilactobacillus, Limosilactobacillus, Lactiplantibacillus, Lacticaseibacillus, and Companilacobacillus, which differed from the genera identified through amplicon sequencing. Alpha diversity analysis revealed higher probiotic diversity in fermented dairy products (FDPs) than in the alcoholic beverages samples. Redundancy analysis revealed that food’s properties, like fat, ash, & moisture content, temperature, and electrical conductivity, influence the probiotic diversity in the samples. Additionally, Gas chromatography-mass spectrometry (GC-MS) analysis identified high levels of methyl hexadecanoate and methyl linoleate in the food products. Metabolic functional predictions showed the dominance of anabolic pathways in dairy samples and catabolic pathways in alcoholic beverage samples. Overall, FDPs with superior nutritional properties and probiotic diversity could be considered a better choice as functional food.

Optimizing Sowing Windows for Wheat (Triticum aestivum L.) in the Sub-temperate Climate of the North-western Himalayas of India

Optimizing Sowing Windows for Wheat (Triticum aestivum L.) in the Sub-temperate Climate of the North-western Himalayas of India

Biomass tables and allometric equations for predicting the fodder and fuelwood production of prominent tree resources in agricultural landscapes of the mid-hills of the North-Western Himalayas

Biomass tables and allometric equations for predicting the fodder and fuelwood production of prominent tree resources in agricultural landscapes of the mid-hills of the North-Western Himalayas

Evaluation of probability distribution methods for flood frequency analysis in the Jhelum Basin of North-Western Himalayas, India

The Kashmir Valley has frequently endured devastating floods, presenting significant challenges for flood management due to unpredictable flood magnitudes and limited pre-disaster preparedness. A major difficulty in addressing these challenges is the lack of reliable flood frequency analysis (FFA) for effective planning and mitigation. This study seeks to overcome these issues by employing a rigorous quantitative analysis of annual peak discharge data over a 51-year period (1971–2021). One key challenge was the presence of low outliers, which could compromise the integrity of the data. To address this, the Multiple Grubbs-Beck test was applied to remove these outliers before conducting FFA. The study's original achievement lies in its application of multiple distribution models which include Gumbel (EV1), Generalized Extreme Variations (GEV), Log-Normal, Log Pearson III (LP III), Gamma and Normal distribution. Goodness-of-fit tests, including Kolmogorov-Smirnov (KS), Anderson-Darling (AD), and Chi-square at the 5 % significance level, along with visualization techniques such as Probability plots (PP), Quantile plots (QQ), and Probabilistic distribution (PD) graphs, were used to identify the most suitable distribution methods. The Log Pearson Type III (LP-III) was identified as the best fit for the Sangam gauge site (Upper Jhelum), the gamma distribution for Ram Munshibagh (Middle Jhelum), and the Generalized Extreme Value (GEV) and LP-III for Asham (Lower Jhelum). For Sangam, the estimated discharges for 2, 5, 10, 50, 100, 150, 200, and 250-year return periods were 549.63, 1028.43, 1471.34, 2907.64, 3758.92, 4338.61, 4790.99, and 5167.23 cumecs, respectively, using LP-III. For Ram Munshibagh, the discharges were 602.13, 911.03, 1107.04, 1512.12, 1674.35, 1767.0, 1831.87, and 1881.74 cumecs using the gamma distribution. For Asham, the discharges were 685.8, 998.0, 1193.3, 1593.2, 1750.6, 1839.4, 1901.0, and 1948.0 cumecs using the GEV distribution. The findings indicate that the Jhelum River cannot accommodate excess discharge for return periods of 5 years or more, underscoring the need for enhanced flood management strategies.