Middle Ganga Plain Research Articles

Integration of SPEI and machine learning for assessing the characteristics of drought in the middle ganga plain, an agro-climatic region of India.

Drought, as a natural and intricate climatic phenomenon, poses challenges with implications for both natural ecosystems and socioeconomic conditions. Evaluating the characteristics of drought is a significant endeavor aimed at mitigating its impact on society and individuals. This research paper explores the integration of the Standardized Precipitation Evapotranspiration Index (SPEI) and machine learning techniques for an assessment of drought characteristics in the Middle Ganga Plain, a crucial agro-climatic region in India. The study focuses on evaluating the frequency, intensity, magnitude, and recurrence interval of drought events. Various drought models, including Random Forest (RF), Artificial Neural Networks (ANN), and an ensemble model combining ANN and RF, were employed to analyze and predict drought patterns at different temporal scales (3-month, 6-month, and 12-month). The performance of these models was rigorously validated using key metrics such as precision, accuracy, proportion incorrectly classified, over-all area under the curve (AUC), mean absolute error (MAE), and root mean square error (RMSE). Furthermore, the research extends its application to delineating drought vulnerability zones by establishing demarcations for high and very high drought vulnerability areas for each model and temporal scale. Results indicate that the south-western part of the middle Ganga plain falls under the highly drought-vulnerable zone, which averagely covers 40% of the study region. The core and buffer regions of drought vulnerability have also been identified. The south-western part of the study area is identified as the core region of drought. Ground verification of the drought-vulnerable area has been done by using soil moisture meter. Validation metrics show that the ensemble model of ANN and RF exhibits the highest accuracy across all temporal scales. This research's findings can be applied to improve drought preparedness and water resource management in the Middle Ganga Plain. By identifying high-risk drought zones and utilizing accurate prediction models, policymakers and farmers can implement targeted mitigation strategies. This approach could enhance agricultural resilience, protect livelihoods, and optimize water allocation in this vital agro-climatic region.

Optimized ensemble-based flood hazard mapping in low altitude subtropical riverine terrane

Among various natural hazards, those induced by hydrological and meteorological factors have emerged as the most frequent and damaging. India is at the second from the top, after Bangladesh, of flood hazard-affected countries of the world, causing immense damage to life and property every year. The Middle Ganga Plain in the country is one of the most severely affected regions due to the convergence of Himalayan rivers in the Ganga (Ganges) plain. This study focuses on optimizing novel ensemble models to enhance the mapping of flood hazard susceptibility in specific topoclimatic setting, characterized by a low-altitude-range, sub-tropical monsoonal climate, and a riverine floodplain environment of the tectonically active Middle Ganga Plain. This region forms part of the Ganga Foreland Basin prone to frequent floods. We employ a comprehensive flood inventory and twelve selected flood conditioning factors and is the first study that has developed these ensemble models in low relief riverine floodplain environmental setting with high resolution geomorphology as one of the conditioning factors. Four artificial intelligence ensemble models were employed in this work: Logistic Regression-Evidential Belief Function (LR-EBF), Logistic Regression-Frequency Ratio (LR-FR), Multi-Layer Perceptron-Evidential Belief Function (MLP-EBF), and Multi-Layer Perceptron-Frequency Ratio (MLP-FR). Results showed that LR-based ensembles outperformed MLP-based ensembles in the studied topoclimatic setting, with LR-EBF model achieving 87.2% and 84.7% success and prediction rates respectively. Our results reveal consistent performance differences between LR-based ensembles with FR and EBF models across different environmental settings. MLP-based ensembles, particularly with Frequency Ratio, displayed more significant performance variations. The findings underscore the importance of considering specific topoclimatic and altitudinal range environments when applying flood hazard susceptibility models. Our study also provides valuable insights for planning and policymaking in flood management practices in similar topoclimatic settings worldwide.

Exploring climate shifts in the Ganga-Brahmaputra basin based on rainfall and temperature variability.

Climate change has a significant impact on the Ganga-Brahmaputra (GB) basin, the major food belt of India, which frequently experiences flooding and varied incidences of drought. The current study examines the changing trend of rainfall and temperature in the GB basin over a period of 30years to identify areas at risk with an emphasis on the Paris Agreement's mandate to keep increasing temperatures below 2°C. The maximum temperature anomaly in the middle Ganga plains recorded an increase of more than 1.5°Cyear-1 in 1999, 2005, and 2009. Some extreme events were observed in the Brahmaputra basin during 1999, 2009, and 2010, where a prominent temperature increase of 1.5°Cyear-1 was observed. The minimum temperature revealed an increasing trend for the G-B basin with an anomalous increase of 0.04 to 0.06°Cyear-1. The rainfall variability across the Ganga basin shows a rising tendency over the lower Ganga region while the Brahmaputra basin showed a downward trend. To identify the statistical relation between the Global climatic oscillations and regional climate, Standardized Precipitation Index (SPI) and Niño 3.4 were used. The wet and dry period estimation shows a rise in flood conditions in the Ganga basin whereas, in the Brahmaputra basin, an increase in drought frequency was observed. The correlation based on Niño 3.4 and SPI3 presents a negative relation for the monsoon season in the G-B basin revealing a situation of drought occurrence (SPI3 below 0) with increased Nino 3.4 values (El Niño above + 0.4C).

Comprehensive climatic variability analysis and its significance on flood occurrences in the Middle Ganga Plain, India

Climate variability significantly affects rainfall, air temperature, relative humidity, and solar radiation. In subtropical regions like India, intense monsoon rainfall primarily causes floods. This study aims to analyze the climatic factors contributing to flood occurrence in the Middle Ganga Plain (MGP) by examining meteorological parameters through various analyses, including monthly and yearly trends, spatial variability, exceedance probability, historical highest intensity rainfall, and wind trajectory analysis. By establishing a strong link between climatic variables and flood events, this research provides valuable insights into the impact of climate variability on flood patterns in the MGP. Results indicate that monsoon rainfall peaks from July to October, correlating with major flood events. During these months, high relative humidity increases the likelihood of rainfall. Spatial analysis shows higher rainfall in the northern Middle Ganga Plain (MGP), which aligns with observed flood patterns. Trend detection tests reveal increasing annual rainfall and rising average temperatures. Geostatistical analysis identifies the western and eastern MGP as areas prone to extreme rainfall. Exceedance probability analysis confirms the occurrence of substantial monsoon rainfall events. Wind trajectory analysis uncovers seasonal shifts that lead to low-pressure systems and heavy monsoon rainfall. The study establishes a strong link between climatic variables and flood events in the MGP region.

Delving the influence of socio-economic, demographic and migration factors on utilization of remittances in the agricultural sector in a high out-migrating region in India

In developing nations, remittances play a vital role in the development of the society. Remittances serve as a substantial income stream for rural households, empowering them to invest in farming activities, procure resources, and enhance their overall quality of life. This study focuses on investigating remittance utilization patterns in agriculture and how do socio-economic, demographic and migration factors influence remittance utilization patterns in agriculture in the Middle Ganga Plain region (Eastern Uttar Pradesh and Bihar) of India? The study utilizes the data from the Middle Ganga Plain (MGP) migration survey (2021) conducted by the International Institute for Population Sciences, Mumbai. With the help of bivariate analysis, the study explores the relationship between socioeconomic and migration characteristics and the utilization of remittances in the agricultural sector. The Chi-Square test validates the findings, followed by a Binomial Logistic Regression Model for further analysis. The study reveals that marginalized social groups are more inclined to use remittances for agriculture due to their active involvement in agriculture. Furthermore, households with larger landholdings demonstrate an increased likelihood of remittance utilization across all agricultural sectors. Additionally, it was observed that remittances in agriculture were more prevalent among female-headed households. Moreover, parents who are recipients of remittances tend to allocate their funds to agricultural activities. The significant positive correlation between monthly remittance receivers and total agricultural expenses underscores the importance of remittances in rural development. This study provides valuable insights into remittance utilization patterns and associated factors in the agricultural sector, highlighting the need for targeted policies and interventions to enhance the efficient and effective use of remittances in agriculture, ultimately contributing to rural economic growth and development.

Northern Black Polished Ware: A Technological Enigma

In ancient India, complex technologies for forming and firing pottery were developed to meet the challenges of different types of clays and available fuels, as well as diverse cultural and ritual needs. Clays, slips, and firing processes were simultaneously customized through time and space, resulting in innovative region and period specific specialized wares. While the knowledge of some pottery making traditions was passed from one generation to the next, and can be documented to some extent today, other techniques, such as the manufacture of Northern Black Polished Ware (NBPW), have been lost. Attempts by scholars either to deconstruct this ware scientifically or reconstruct the technique experimentally have largely been unsuccessful. This article is yet another attempt to deconstruct NBPW manufacturing methods, primarily the preparation of the slip, using petrographic XRD, XRF, and microscopy on seven sherds of various shades coming from different sites and times within the peak NBPW period. KEYWORDS: Northern Black Polished Ware, middle Ganga Plain, ceramic, microscopy, XRF

Husband’s migration status and contraceptive behaviors of women: evidence from Middle-Ganga Plain of India

BackgroundMale out-migration is negatively associated with contraceptive use in developing countries. This study aimed to examine the effect of male out-migration on the contraceptive behaviour of women in the Middle-Ganga Plain (MGP) region.MethodsThe data has been collected from the Middle-Ganga Plain survey (2018–19), which was conducted by the International Institute for Population Sciences (IIPS). The overall sample size was 1314 wives left behind and 1402 non-migrant wives. Multivariate logistic regression analysis was used to examine the relationship between the variables. Statistical analyses were done using SPSS version 25.ResultThe result shows that female sterilization was the most common method used by both left behind wives (30.9%) and non-migrant wives (34.6%). Most of the left-behind women didn't use contraception because their husbands were away from home (30.86%). The result also shows that left behind wives were less likely to use any methods of contraception than the non-migrant wives. Left behind women were more tended to use the modern methods (OR-0.71, 95%CI = 0.57–0.88) than any traditional methods (OR-0.61, 95% CI = 0.46–0.80). Age, religion, family type, working status, and marital duration were strongly associated with women's contraceptive use.ConclusionThese results strengthen the existing literature that explains how migration affects women's health. Therefore, there is an important need to develop and implement comprehensive education programs and policy on contraception use.

Agriculture productivity and level of agricultural devel-opment in Eastern Uttar Pradesh of the Middle Ganga Plain

Agriculture is the primary source of occupation for the Indian rural people who directly or indirectly depend on agriculture. Today, India is facing two most vital problems which is di-rectly related to agriculture. The first one is to fulfil the growing demand of the ever-increasing population for food and other agricultural products, and the second is widespread disparities in agriculture development. This paper has attempted the measurement of agriculture productivity and the level of agricultural development in Eastern Uttar Pradesh of the Middle Ganga Plain. Taking into consideration this idea in mind, the present study attempts to calculate first the land productivity (per ha NSA) based on three indices viz. (i) Standardized crop Index(Isyi)(ii) Weight Crop Equivalent index (Iwei) and (iii) Cropping intensity index(Ici) and then labor productivity (per agricultural worker) with the help of agricultural worker index (Iewi). After this results here also calculate the level of agricultural development on the basis of 27 variables by the Z score method. The study area of Jaunpur is situated in Eastern Uttar Pradesh of the Middle Ganga Plain. The total area of the district is 4038 km2 having a population of 44, 94,204 persons. Several factors like water logging, salinity, relief variation, etc., and different modern agro-input have resulted in remarkable spatial disparity in agriculture productivity and level of development.

Assessment of river channel dynamics and its impact on land use/land cover in the middle Ganga plain, India

Assessment of river channel dynamics and its impact on land use/land cover in the middle Ganga plain, India

AGRICULTURAL CHARACTERISTICS IN FLOODPLAIN ZONE OF MIDDLE GANGA PLAIN

This paper has been attempted to study the difference dimensions of agriculture like crop diversification, cropping intensity, crop combination, crop ranking, irrigation intensity and land use efficiency in floodplain zone of middle Ganga plain. Agriculture plays a very important role in the economic development of our country (India), where 65 percent of rural population is directly or indirectly depended on the agricultural for survival. The largest population of India has been livening in Ganga floodplain so it has necessary to study the different agricultural characteristics. The major objectives of the study are to analyze the spatial pattern of agriculture diversification, crop ranking, crop combination and to calculate the irrigation intensity, cropping intensity, land use efficiency of Jaunpur district. The present study has been exclusively based on secondary data which collected from different offices and websites. Crop diversification measure by Singh (1976) formula which was slightly modified the Bhatia (1965) formula, cropping intensity analyzed with the help of Singh (1974) method and crop combination determined by Kikukazu Doi (1959) method. In the Jaunpur district the irrigation intensity has been 140.10, crop diversification index has been 38.69, cropping intensity index has 100.07. In study area wheat is the dominant crop, paddy dominated as the second crop and maize is the third crop. There are three types crop combinations like wheat-rice, wheat-rice-maize and wheat-maize- rice.

Evolution of terminal fans in the Indo-Gangetic foreland basin: A process-response model

The present and paleo-drainage networks, depositional surfaces, fault throw, slope of the downthrown fault blocks, soil properties, sediment characteristics and published optically stimulated luminescence (OSL) ages are used to define the role of tectonics and climate in the growth of forty-five terminal fans (TFs) in the Indo-Gangetic foreland basin. Twenty-three TFs show a single exposed surface throughout, suggesting no or imperceptible breaks in sedimentation during their formation. In contrast, twenty-two TFs show multiple growth surfaces, separated by soil profiles and erosional surfaces. The available optically stimulated luminescence (OSL) dates of these depositional surfaces suggest different phases of TF growth.Tectonically triggered surface faulting altered accommodation space, slope of the substrate, and sediment supply and initiated new TF depositional cycles. The tectonically stable periods, in contrast, did not form TFs, despite the favourable humid climate conditions. Instead, the dry and humid climatic regimes, when combined with frequent surface faulting, produced and remobilized sediments more quickly, promoting TF growth. The humid climate TFs are spatially extensive (average area = 2000 km2), with clay horizons interspersed between sand facies. The dry climates TFs are smaller (average area = 1370 km2), with intervening calcrete horizons and surface salt-efflorescence. Low precipitation and inadequate sediment supply hampered the growth of these dry climate TFs. Despite a considerable period of surface exposure, the surfaces of dry climate TFs lack a well-developed soil profile.The upper Ganga Plain provides more accommodation space across the faults than the middle Ganga Plain. Accommodation space and substrate slope have little effect on TF area unless climatically triggered sediment remobilization occurs. For a given accommodation space and substrate slope, steeper sloping TFs occupy less area than lower sloping ones. Faults with throws of <5 m and substrate slopes of <2° do not form TFs; instead sediment wedges are formed across fault slope breaks.The TFs in the upper Ganga Plain show more growth surfaces than the middle Ganga Plain. The older growth surfaces are either progressively arranged across the direction of channel shift or occur as inliers in between the younger alluvium. Well-developed distributaries on the older TFs disperse sediment more readily, rather than accumulating it in proximal fan regions. However, the younger TFs, with relatively less-developed distributary channel networks, vertically stack sediments in their proximal part and occasionally transport sediment as sheet floods to their distal end regions. The combined geomorphic response of TFs to tectonic events and climatic fluctuations is, therefore, simultaneous for TF growth and stabilization.

Comprehensive Assessment of Meta-Analysis and Contingent Valuation Technique for Sustainable Management of Wetland of Middle Ganga Plain

Abstract In this study, the functions and threats of Suraha Tal Wetland are identified by the stated preference method and weightage is given according to their rank. The objective of the study is to determine the total economic value of Suraha Tal Wetland. The direct value can be drawn from the market price and from a survey of the stakeholders. Suraha Tal Wetland is also famous for the presence of the Jai Prakash Narayan Birds Sanctuary, which makes it a biodiversity-enriched area. The indirect value has been drawn from a review of the literature on Suraha Tal Wetland and the relevance of this literature is justified through the comprehensive meta-analysis (CMA) software. The total valuation of the wetland has been calculated. The paper concludes with suggestions for a few management strategies for better wetland management.

SERVICE CENTRES IN RURAL DEVELOPMENT : A CASE STUDY OF JAUNPUR DISTRICT, UTTAR PRADESH

This paper attempts to deal with the identifying the service centers and calculation of the spatial arrangement with complementary area of service centres in Jaunpur district Jaunpur district of Uttar Pradesh. The study area is situated in Eastern Uttar Pradesh of the Middle Ganga Plain. The study is exclusively based on secondary data collected at block level from different offices. The centrality score has been calculated on the basis of three type of indices like functional centrality index, working population index and tertiary population index. There are 31 function or services selected judicially from five sectors (administrative, agricultural and financial, educational, health and transport and communication) to measure the centrality of service centre. The thissen polygon and berry breaking point method has been used for measure the complementary area. Total 88 service centres have been identified as first, second, third, fourth and fifth order service centre. The number of I, II, III, IV, and V order centres accounts for 43, 24, 16, 4, and 1 respectively.

Flood Susceptibility Modeling in a Subtropical Humid Low-Relief Alluvial Plain Environment: Application of Novel Ensemble Machine Learning Approach

This study has developed a new ensemble model and tested another ensemble model for flood susceptibility mapping in the Middle Ganga Plain (MGP). The results of these two models have been quantitatively compared for performance analysis in zoning flood susceptible areas of low altitudinal range, humid subtropical fluvial floodplain environment of the Middle Ganga Plain (MGP). This part of the MGP, which is in the central Ganga River Basin (GRB), is experiencing worse floods in the changing climatic scenario causing an increased level of loss of life and property. The MGP experiencing monsoonal subtropical humid climate, active tectonics induced ground subsidence, increasing population, and shifting landuse/landcover trends and pattern, is the best natural laboratory to test all the susceptibility prediction genre of models to achieve the choice of best performing model with the constant number of input parameters for this type of topoclimatic environmental setting. This will help in achieving the goal of model universality, i.e., finding out the best performing susceptibility prediction model for this type of topoclimatic setting with the similar number and type of input variables. Based on the highly accurate flood inventory and using 12 flood predictors (FPs) (selected using field experience of the study area and literature survey), two machine learning (ML) ensemble models developed by bagging frequency ratio (FR) and evidential belief function (EBF) with classification and regression tree (CART), CART-FR and CART-EBF, were applied for flood susceptibility zonation mapping. Flood and non-flood points randomly generated using flood inventory have been apportioned in 70:30 ratio for training and validation of the ensembles. Based on the evaluation performance using threshold-independent evaluation statistic, area under receiver operating characteristic (AUROC) curve, 14 threshold-dependent evaluation metrices, and seed cell area index (SCAI) meant for assessing different aspects of ensembles, the study suggests that CART-EBF (AUCSR = 0.843; AUCPR = 0.819) was a better performant than CART-FR (AUCSR = 0.828; AUCPR = 0.802). The variability in performances of these novel-advanced ensembles and their comparison with results of other published models espouse the need of testing these as well as other genres of susceptibility models in other topoclimatic environments also. Results of this study are important for natural hazard managers and can be used to compute the damages through risk analysis.

River space: A hydro-bio-geomorphic framework for sustainable river-floodplain management

The lateral dimension of an alluvial river – floodplains – provides a plethora of goods and services for human needs. Also, it supports the richest and diverse riverine ecosystems on Earth. But over-utilization of floodplain resources had impacted functions of river system adversely. So, the present study attempts to formulate a hydro-bio-geomorphological framework to assess the lateral dimension of a river system for sustainable management of river-floodplains and termed as river space in this paper. The study illustrates river space at seven hydro-meteorological sites situated on the main stem of the Ganga river in the ~750 km stretch that lies between Haridwar and Prayagraj cities. For hydrological aspect, the flood frequency analysis is used to identify flood inundation widths for floods of different return periods with the help of the rating curve and derived cross-section from satellite imagery. Bio-geomorphological aspects are taken into consideration for corroborating the hydrologically assessed river widths (lateral dimension). The present study suggests that the minimum river space should be equal to the lateral width corresponding to the 1-year return period flood. In the present hydro-meteorological sites in the middle Ganga plains, it ranges from 2 to 21 km. Overall, the present study gives an insight of a simple and logical approach that could be beneficial for the biomic restoration of rivers and their floodplains.

Large strain dynamic characteristics of quaternary alluvium sand with emphasis on empirical pore water pressure generation model

The present study focuses on the cyclic behaviour of cohesionless soil collected from the quaternary alluvium deposit at the Middle Ganga Plain (MGP). A series of strain-controlled cyclic triaxial tests have been carried out on collected soil samples at various effective confining stresses, shear strain amplitudes and motion frequencies to estimate the dynamic parameter at large strain. From the results, it has been shown that dynamic properties and liquefaction strength substantially affected by the shear strain amplitude of input motion. However, effective confining stress and motion frequency have no significant effect on dynamic properties and liquefaction strength at large strain. Regression equations have been developed for dynamic and liquefaction strength parameters for the studied soil. It has been found that the consideration of asymmetricity in the shape of hysteresis loops significantly influences the damping ratio estimation at a particular shear strain. Another novel aspect that has been presented in this study is the effect of effective confining stress on the EPWP model parameter F using a mathematical equation. The regression equation for model parameter F proposed in this study has been validated by predicting the maximum EPWP development of studied soil and other quarternary alluvium soils available worldwide.

Assessment of lumped particles effect on dynamic behaviour of fine and medium grained sands

One novel aspect addressed here is the effect of the lumped particle on the dynamic behaviour of cohesionless soil. The effects of particle size and fines content on cyclic soil behaviour have been previously studied by mixing fine particles separately with cohesionless soil. The studied cohesionless soil in the quaternary alluvium deposit on Middle Ganga Plain in India contains a significant amount (10%–20%) of soil lumps. Therefore, the present study using strain-controlled cyclic triaxial tests addressed the effect of parameters mentioned above on the liquefaction resistance of sand where the fines were present in a lumped form. A series of undrained cyclic triaxial experiments have been performed on isotropically consolidated samples to quantify the effects of soil lumps present in various types of sand. Experimental results have shown less cyclic resistance for soil samples with lumps compared to clean sands of equivalent grain size. This is believed to be due to lumped particle crushing, and soil particle rearrangement during the sample saturation and loading. This affects dynamic properties such as shear modulus. From the results, it can be concluded that the presence of such soil lumps in cohesionless soil is reducing the initial shear modulus and the soil becomes more susceptible to liquefaction.

Microscopic Imaging of Entrapped Slag in Ancient IronArtifact (300 BCE) from the Middle Ganga Plains of India

Microscopic Imaging of Entrapped Slag in Ancient IronArtifact (300 BCE) from the Middle Ganga Plains of India

Spatiotemporal Migration of the River Ganga in Middle Ganga Plane: Application of Remote Sensing and GIS Technique

The process of channel migration becomes crucial to a populace living in or near the floodplain or to government organizations involved in planning or upholding the infrastructure within or nearby the floodplains. Spatiotemporal migration of the River Ganga in the Middle Ganga Plain for about forty years (1972–2018) was measured using Landsat images, coupled with extensive ground checks. Assessment of satellite images of 1972, 1990, 2000, 2010, and 2018 reveals the Ganga River migrated within its valley, demonstrating significant changes in the channel geometry on a decadal scale. Heavy rains promote the enhancement of the sediment load in the channel triggering a further increase in the sinuosity index. However, the overall sinuous nature of the Ganga River channel is mainly fault-controlled. The variable lateral migration of the channel seems related to heavy rains and reactivation of chute channels within the river valleys. The lateral movement of the river is one of the critical factor responsible for the failure of the older floodplain (bank) within the valley by the undercutting process.

Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, India

This study is an attempt to quantitatively test and compare novel advanced-machine learning algorithms in terms of their performance in achieving the goal of predicting flood susceptible areas in a low altitudinal range, sub-tropical floodplain environmental setting, like that prevailing in the Middle Ganga Plain (MGP), India. This part of the Ganga floodplain region, which under the influence of undergoing active tectonic regime related subsidence, is the hotbed of annual flood disaster. This makes the region one of the best natural laboratories to test the flood susceptibility models for establishing a universalization of such models in low relief highly flood prone areas. Based on highly sophisticated flood inventory archived for this region, and 12 flood conditioning factors viz. annual rainfall, soil type, stream density, distance from stream, distance from road, Topographic Wetness Index (TWI), altitude, slope aspect, slope, curvature, land use/land cover, and geomorphology, an advanced novel hybrid model Adaptive Neuro Fuzzy Inference System (ANFIS), and three metaheuristic models-based ensembles with ANFIS namely ANFIS-GA (Genetic Algorithm), ANFIS-DE (Differential Evolution), and ANFIS-PSO (Particle Swarm Optimization), have been applied for zonation of the flood susceptible areas. The flood inventory dataset, prepared by collected flood samples, were apportioned into 70:30 classes to prepare training and validation datasets. One independent validation method, the Area-Under Receiver Operating Characteristic (AUROC) Curve, and other 11 cut-off-dependent model evaluation metrices have helped to conclude that the ANIFS-GA has outperformed other three models with highest success rate AUC = 0.922 and prediction rate AUC = 0.924. The accuracy was also found to be highest for ANFIS-GA during training (0.886) & validation (0.883). Better performance of ANIFS-GA than the individual models as well as some ensemble models suggests and warrants further study in this topoclimatic environment using other classes of susceptibility models. This will further help establishing a benchmark model with capability of highest accuracy and sensitivity performance in the similar topographic and climatic setting taking assumption of the quality of input parameters as constant.