Subarnarekha River Basin Research Articles

A Multi-criterian Approach to Identify Groundwater Potential Zones in the Subarnarekha River Basin Using Integrated Analytical Hierarchy Process and Geospatial Technology

The intense extraction of groundwater and changing climate patterns have strained global groundwater supplies. As the demand for drinkable water rises worldwide, assessing groundwater availability and aquifer output becomes increasingly important. Geographic information systems (GIS) are being used more frequently for groundwater exploration due to their speed and provision of preliminary data. This study focuses on mapping groundwater availability in a minor tropical river basin in India, using a combination of GIS and the analytical hierarchy process (AHP). Ten thematic layers were generated and analyzed, including Geology, Geomorphology, Land use and land cover (LULC), Lineament density, Drainage density, Rainfall, Soil type, Slope, Topographic Wetness Index ( TWI), and curvature to delineate groundwater potential zones. AHP was employed to assign weights to each category based on their water retention properties. The resulting map was validated against existing groundwater data, demonstrating an accuracy of approximately 85%. The groundwater potential zones were classified as high, moderate, and, low. The moderate potential zone covered 59% of the basin, while the low and high potential zones constituted 29% and 11% respectively. High and low potential regions were limited to small sections of the basin. In conclusion, this research successfully mapped the groundwater availability in the Rarhu River watershed using GIS and AHP. The findings highlight the distribution of different groundwater potential zones, providing valuable information for sustainable water resource management in the area.

Response of climate change and land use land cover change on catchment-scale water balance components: a multi-site calibration approach

Abstract The present study focused on evaluating the separate and combined response of land use land cover and climate change (CC) on future water balance components of a Subarnarekha River basin, spanning between the latitudes 21°33′N–23°18′N and longitudes 85°11′E–87°23′E, situated in the eastern India. The Soil and Water Assessment Tool is used for single-site calibration and multi-site calibration (MSC) of the model to characterize the future water balance components of the basin using the Cellular Automata-Markov model and climate projections under two representative concentration pathway (RCP) scenarios (4.5 and 8.5). The findings indicate that the model parameters obtained through MSC better represent spatial heterogeneity, making it the preferred calibration approach for model simulations. In the middle region of the basin, future annual water yield, groundwater recharge (GWR), and streamflow showed a reduction, respectively, by 46–47%, 29–30%, and 13–15%, while evapotranspiration showed an increase by 5–7% following projected CC under both RCP scenarios. The findings are relevant for policy-makers to mitigate the adverse effects of reduced GWR for sustainable water resources management. Future research may integrate reservoir operation frameworks to effectively address the water management issues of the basin.

Variation of extreme values of rainfall and temperature in Subarnarekha River basin in India

Abstract In recent years, the Subarnarekha River basin has frequently experienced harsh weather and has also observed extreme floods during monsoons and a shortage of water during lean periods. Hence, in this study, the data of extreme values of rainfall and maximum–minimum temperatures from the years 1990 to 2020 in the Subarnarekha River basin have been analysed. The trend analysis of annual extreme rainfall, maximum–minimum temperatures, extreme diurnal temperature range, and number of rainy days have been determined using the Mann–Kendall test and Sen's slope estimator. Further, the analysis has also been carried out to study the shifting of the onset date of monsoon. The results show that extreme rainfall showed a significant increasing trend at a 95% level of confidence in the upper and middle parts of the basin, whereas it had a decreasing trend in the lower part. Annual extreme maximum temperature indicated a decreasing trend of 0.03 and 0.08 °C/year in the upper and middle parts, respectively, and the decrease in extreme minimum temperature in the lower part was 0.03 °C/year. No significant variations in the number of rainy days have been observed; however, a major shift in the onset date of the monsoon was observed during the selected time-period.

Mapping groundwater potential zone in the subarnarekha basin, India, using a novel hybrid multi-criteria approach in Google earth Engine

Assessing groundwater potential for sustainable resource management is critically important. In addressing this concern, this study aims to advance the field by developing an innovative approach for Groundwater potential zone (GWPZ) mapping using advanced techniques, such as FuzzyAHP, FuzzyDEMATEL, and Logistic regression (LR) models. GWPZ was carried out by integrating various primary factors, such as hydrologic, soil permeability, morphometric, terrain distribution, and anthropogenic influences, incorporating twenty-seven individual criteria using multi-criteria decision models along with a hybrid approach for the Subarnarekha River basin, India, in Google earth engine (GEE). The predictive capability of the model was evaluated using a Multi-Collinearity test (VIF <10.0), followed by applying a random forest model, considering the weighted impact of the five primary factors. The hybrid model for GWPZ classification showed that 21.97 % (4256.3 km2) of the area exhibited very high potential, while 11.37 % (2202.1 km2) indicated very low potential for GW in this area. Validation of the groundwater level data from 72 observation wells, performed by the Area under receiver operating characteristic (AUROC) curve technique, yielded values ranging between 75 % and 78 % for different models, underscoring the robust predictability of GWPZ. The hybrid and LR-FuzzyAHP models demonstrated remarkable effectiveness in GWPZ mapping, indicating that the downstream and southern regions boast substantial groundwater potential attributed to alluvial soil and favorable recharge conditions. Conversely, the central part grapples with a scarcity of groundwater. It holds the potential to assist planners and managers in formulating strategies for managing groundwater levels and alleviating the impacts of future droughts.

Assessment of the Impact of Land Use and Land Cover Change on Hydrological Components of the Upper Watershed of Subarnarekha River Basin, Jharkhand, India Using SWAT Model

Assessment of the Impact of Land Use and Land Cover Change on Hydrological Components of the Upper Watershed of Subarnarekha River Basin, Jharkhand, India Using SWAT Model

Assessment of Spatial Heterogeneity of Landscape Ecology of the Subarnarekha River Basin, India

Assessment of Spatial Heterogeneity of Landscape Ecology of the Subarnarekha River Basin, India

Land Use Land Cover (LULC) and Surface Water Quality Assessment in and around Selected Dams of Jharkhand using Water Quality Index (WQI) and Geographic Information System (GIS)

Abstract Surface water quality deterioration is mainly occurring due to anthropogenic activities at an alarming rate in developing countries. Jharkhand has been undergoing exponential urbanisation and mining, causing immense surface water pollution and water stress. The state is heavily dependent on artificial dams for its daily water supply demands. Therefore, an effort is made to monitor and ascertain the surface water quality and the influence of nearby land use pattern on water quality, in the selected five dams, namely, Hatia dam, Kanke dam, Getalsud dam, Galudih barrage, and Chandil dam are done. These dams are built on the Subarnarekha river basin, located in the Jharkhand state on a seasonal basis and associated land use land cover (LULC) changes, changes in vegetation cover using normalised difference vegetation index (NDVI) and water body changes using normalised difference water index (NDWI) that have occurred in a 5-year gap i.e. 2016 and 2021. The secondary data for the year 2016 was obtained from the Jharkhand pollution control board report published by the government of Jharkhand, India. For the year 2021, the samples were collected from sampling sites for pre, post and monsoon seasons. The chemical analysis of collected water samples was done in the laboratory for parameters like pH, dissolved oxygen, biological oxygen demand, total calcium and magnesium, hardness, total dissolved and suspended solids, alkalinity, chlorine etc. and compared with the standard values prescribed by world health organisation (WHO) and Indian standards (IS) 10500:2012. The seasonal water quality status was analysed using the water quality index (WQI) for the pre, post and monsoon seasons of 2016 and 2021. Then, the use of supervised classification method for land use land cover (LULC), normalised difference vegetation index (NDVI) and normalised difference water index (NDWI) was opted to understand the relation between the change in water quality and quantity concerning its land use and land cover, by comparison of results from the year 2016 to 2021. LULC were found using the supervised maximum likelihood classification method in ArcGIS and its accuracy was checked using the kappa accuracy method, which was found to be varying from 87 to 95% for all sites. The results showed that the overall water quality varied from good to poor indicating that it can be used for human activities but may need pre-treatment before drinking. NDWI showed a massive increase in severe drought areas for Hatia, Kanke, Chandil and Galudih barrage, whereas moderate drought regions increased for Hatia, Getalsud, and Kanke. NDVI showed dense and moderate vegetation both decreased massively for all the dam sites indicating an alarming situation and the need to adopt better land management practices.

Integrated water resource development in the Subarnarekha river basin

The Subarnarekha, an important rain-fed river basin in Eastern India, faces a large number of hydrological, utilization and managerial problems. The attributes and practical application of integrated water management require a detailed evaluation of its components to state its changing need. This paper presents a conceptual note on the status of water resources, problems associated with and perspectives on the integrated river water management in the Subarnarekha river basin. The study has used primary and secondary data sources to analyze the stated purpose. It was found that the key to mitigating water stress is to adopt a bottom-up approach by linking the watershed programme to the irrigation management project within IWRM at the sub-basin level which could address the participation of all stakeholders and strengthens local governance instead of a centralized administration. Intra-basin water transfer other than inter-linkages of rivers was also emphasized.

Spatio-temporal drought assessment of the Subarnarekha River basin, India, using CHIRPS-derived hydrometeorological indices.

Precipitation studies have a crucial role in deciphering climate change and monitoring natural disasters such as droughts. Such studies lead to better assessment of rainfall amounts and spatial variabilities; and have a vital role in impact assessment, mitigation, and prediction of occurrence. Thus, this study has been undertaken in the Subarnarekha River basin using Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset. Precipitation datasets helped in deriving hydrometeorological indices such as the Rainfall Anomaly Index (RAI) and Standardized Precipitation Index (SPI) for the identification of drought occurrences. The core objective was to infer spatio-temporal drought scenarios and their trend characterization covering four decades over the years 1981 to 2020. Quantitative drought assessment was done using run theory for identifying the Drought Duration (DD), Drought Severity (DS), Drought Intensity (DI), and Drought Frequency (DF). Mann-Kendall (MK) test was performed to understand the precipitation and drought trends at annual and seasonal scales. Eight severe drought events were identified in the Subarnarekha River basin for the past 40years and the average DI value of 0.8 was recorded. MK test results for the precipitation showed a significant positive trend (95% confidence level) for pre-monsoon periods. However, for SPI, a significant positive trend was observed over the intervals of 3 (SPI3), 6 (SPI6), and 12 (SPI12) months respectively at an annual timescale, suggesting wetter conditions within the study area. Moreover, there had been insignificant negative trends for SPI1 and SPI3 during winter. It indicates that during the short-term SPI scale, i.e., 1month (SPI1) and 3months (SPI3), the instances of negative SPI values inferred were high, which point to the increasing incidences of meteorological drought possibly due to deficient soil moisture. Thus, the results indicated that the CHIRPS precipitation product-derived hydrometeorological indices could act as a valuable tool for assessing the past spatio-temporal drought conditions of the Subarnarekha River basin. This may further be helpful in planning for sustainable water resource management of such river basins.

Spatio-temporal modeling of surface runoff in ungauged sub-catchments of Subarnarekha river basin using SWAT

In this present study, Soil and Water Assessment Tool (SWAT) embedded with ArcGIS interface has been used to simulate the surface runoff from the un-gauged sub-catchments in the upper catchment of Subarnarekha basin. Model calibration and validation were performed with the help of Sequential Uncertainty Fitting (SUFI-2) in-built in the SWAT-CUP package (SWAT Calibration Uncertainty Programs). The model was calibrated for a period from 1996 to 2008 with 3 years warm up period (1996-1998) and validated for a period of 5 years from 2009 to 2013. The model evaluation was performed by Nash - Sutcliffe coefficient (NSE), Coefficient of determination (R2) and Percentage Bias (PBIAS). The degree of uncertainty was evaluated by P and R factors. Basing upon the R2, NSE and PBIAS values respectively, of the order of 0.90, 0.90 and -12%, during calibration and 0.85, 0.83 and -15% during validation, substantiate performance of the model. All uncertainties of model parameters have been well taken by the P and R factors respectively, of the order of 0.95 and 0.77 during calibration and 0.82 and 0.87 during validation. The runoff generation from 19 sub-catchments of Adityapur catchment varies from 29.2-44.1% of the annual rainfall and average surface runoff simulated for the entire catchment is 545 mm. As the surface runoff generated in most of the sub-catchments amounts to above 30% of rainfall, it is recommended for adequate number of structural interventions at appropriate locations in the catchment to store the rainfall excess for providing irrigation, recharging groundwater and restricting the sediment and nutrient loss.

Assessment of climate change and its impact on hydrological regimes and biomass yield of a tropical river basin

Assessing climate change impact on hydrology and biomass yield of a tropical river basin is necessary for formulating a suitable coping strategy. A hydrological modelling framework was established for Subarnarekha river basin through calibration and validation of SWAT model with the observed river discharge at four gauging locations. The global sensitivity analysis was performed to establish the robustness and stability of the model to reproduce outputs resultant to various extremes of precipitation and other weather events. The 5-GCMs, namely HadGEM2-ES, MIROC-ESM, NCAR-CCSM4, CSIRO-MK3.6, and CESM1-CAM5 were analyzed and HadGEM2-ES was selected based on its performance with respect to ensemble of remaining 4 GCMs (p ≤ 0.05). The AR5-HadGEM2-ES monthly database (1 km2 resolutions) was used to generate bias factor for preparing daily climatic variables in the future projection which was employed as a forcing to simulate river discharge and other hydrological fluxes for the future climate scenario. Increase in precipitation from 14 to 36%, the runoff increased from 39.7 to 104.1%. When compared to the present period, an increase in monsoon runoff is expected 100 and 200% during 2030 and 2080, respectively. Higher degree of uncertainty in expected runoff volumes was expected in mid- and far future time period. Intra-RCP scenarios analyses indicated a significant surge in monsoon season runoff volume during 2070 and 2080 and insignificant surge during 2030 and 2050. As the basin constitute a rice ecosystem, the simulation approach involved a detailed accounting of the operational activities of a rice to realistically capture its manifestation in the annual accrual of actual evapotranspiration in the simulated hydrological fluxes. During monsoon season, potential evapotranspiration (PET) and actual evapotranspiration (AET) increased by 2.2–12.7% and 1.0–9.0%, respectively. Following simulation output, it was found that the basin was expected to suffer a crop biomass loss of 2 to 3% due to climate change. Simple yield response technique to estimate biomass yield losses was found to be promising alternatives to complex crop modeling studies.

Uncertainties and nonstationarity in streamflow projections under climate change scenarios and the ensuing adaptation strategies in Subarnarekha river basin, India

&lt;p&gt;The present study analyses the various uncertainties and nonstationarity in the streamflow projections of Subarnarekha river basin in Eastern India using two widely used hydrological climate models: 1) general circulation model (GCM), and 2) forcing climate change scenarios. These two climate models are used to force the ArcSWAT model. Subsequently this model is calibrated using SUFI-2 optimization technique. The downscaled and bias-corrected data from an ensemble of 10 climate projections with representative concentration pathways (RCP) 4.5 and 8.5 scenarios (five each) were used in first model, whereas in second model a total of 63 (7 perturbed precipitations and 9 perturbed temperatures) combinations of hypothetical climate change scenarios were used. The results show very good correlation during monthly calibration time steps and relatively good agreement between the observed and simulated streamflows in daily calibration time steps. The uncertainties are expressed in probabilistic terms using probability density function (PDF) and cumulative distribution function (CDF) as they provide significant information for decision process in climate change adaptation in the river basin. The uncertainties associated with climate models, return periods and streamflow extremes are also analysed in the present work. The RCP 8.5 scenarios seem more appropriate than RCP 4.5 scenarios in quantifying the uncertainties under nonstationarity assumptions. The mean values of water balance components and their percentage variation for both historic and future periods reveal that the water balance components get affected significantly due to climate change in a future period. Consequently, the streamflows are likely to decline in the river basin. The present study also highlights the comprehensive approaches that are being planned to facilitate adaptation to climate change as well as those that are specific to the water resources management in the study region. The findings in this work are useful for overall well-being of people in the study area.&lt;/p&gt;&#x0D;

Exploring spatial and temporal trends of diurnal temperature range in the region of the Subarnarekha river basin India

This study analyzed the spatial and temporal trends of diurnal temperature range (DTR) for 35-years (1983–2017) in the region of the Subarnarekha river basin of Jharkhand, India. The daily data of maximum temperature (Tmax) and minimum temperature (Tmin) were habituated to compute the DTR, whereas rainfall data is used to measure its relationship with DTR, on a monthly annual and seasonal basis. Mann–Kendall test and Sen’s slope method has been used to detect the increasing or decreasing trends in climatic data with their statistical significance. The annual mean DTR of the basin is 11.97 °C With a maximum in pre-monsoon (16.36 °C) and minimum in monsoon (6.94 °C). A significant negative trend (− 0.31 °C/decade) was observed in annual DTR over the basin. On a seasonal basis, all four seasons show a negative trend in DTR with the largest significant decreasing trend in the pre-monsoon season (− 0.49 °C/decade). On an annual and seasonal basis, a significant negative correlation between DTR and rainfall is found, indicating that rainfall has a significant impact on the variation of DTR in this basin. A concomitant increase in rainfall might be one of the possible causes of the decreases in DTR in the basin.

Assessment of hydrological response in Subarnarekha river basin under anticipated climate change scenarios

&lt;p&gt;Two hydrological climate modelling techniques, general circulation model (GCM) and hypothetical climate change scenarios, were used to analyse the hydrological response to the anticipated climate change scenarios in the Subarnarekha river basin in Eastern India. Both models verified individually for the same river basin and a comparative performance of the models was evaluated to relate the two models for the near (2014-2040) period climate. The hydrological response under the anticipated climate change in the Subarnarekha river basin is well assessed by GCM under the RCP 8.5 scenarios compared to the RCPs 4.5. Results indicate GCM best suited over the hypothetical climate change scenarios as GCM has demonstrated their potential in accurately reproducing the past observed climatic changes. The strong performance of the hypothetical climate change scenarios model, particularly for warming climate scenarios, suggests that it may have distinct advantages for the analysis of water balance components in the river basin. The monthly streamflows of Subarnarekha river basin was simulated using a total of 14 years (2000-2013) daily observed streamflow data in the ArcSWAT model integrated with model calibration and uncertainty analysis by means of SUFI-2 algorithm. The results indicate during the calibration the coefficient of determination (R2) and Nash-Sutcliff Efficiency (NSE) were reported as 0.98 and 0.97, respectively, while during the validation the R2 and NSE were obtained as 0.94 and 0.94, respectively, confirms the hydrological model performance was very good both in calibration and validation. The obtained climate change water impact index (ICCWI) values reveal the Subarnarekha river basin is more responsive to climate change. The reduction in precipitation along with the significant warming under the projected future climate is likely to reduce availability of water substantially in the study region. This work would be useful for the effective management of water resources for sustainable agriculture and in mitigating natural hazards such as droughts and floods in the study region.&lt;/p&gt;&#x0D;

Eco-potential of Aspergillus penicillioides (F12): bioremediation and antibacterial activity

A total of 112 soil-inhabiting fungal isolates were recorded from different stretches of Subarnarekha river basin (21° 33′ to 23° 32′ north latitude and 85° 9′ to 87° 27′ east longitude), mainly its stretch within the state of West Bengal, India. All isolated fungal groups were grown into potato dextrose agar (PDA) media. Fungal extracts were collected from the grown-up fungus colony after incubation of fungal culture in a liquid medium. Tests for estimation of coliform bacteria were conducted by MPN and MFT methods. Heavy metals were estimated by atomic absorption spectrophotometer, and experimental designs were made following standard literature to observe antibacterial activity as well as to assess heavy metals removing potential of isolated fungal strains. The highest coliform count in MPN test (> 2400 MPN/100 ml) was recorded at S-II followed by S-I and S-III during monsoon season. Out of five identified fungal species (Fusarium sp., Rhizopus sp., Penicillium sp., Aspergillus sp. Pythium sp.), the fungal strain, Aspergillus penicillioides F12 (MN210327) has exhibited the highest heavy metal tolerance activity. It showed resistance against Pb(II) and Cd(II) up to 1000 ppm and Hg(II) up to 200 ppm. Alongside, the specific fungal extracts of this species have also revealed antibacterial activity by proving their effectiveness as potential inhibitor against human pathogenic gram-negative bacteria, Escherichia coli and Vibrio cholerae, and gram-positive bacteria, Staphylococcus aureus and Bacillus subtilis.

Evaluation of loss models and effect of LU/LC changes on surface runoff in Subarnarekha river basin

ABSTRACT The main focus of study is to compute the surface runoff and to assess the impact of land use/land cover changes (LU/LCC) with the help of hydrological model (SWAT) in Subarnarekha River Basin (SRB) over a period of 1999–2014. For runoff simulation, two different loss models were employed like SCS-CN (Soil Conservation Services – Curve Number) model and Green-Ampt model (GA). Drainage map, elevation map, land use/land cover map, slope map, and soil map of the watershed are prepared using remote sensing and GIS approaches as input data to the model. Simulation has been done at six observing stations located at Adityapur, Jamshedpur, Ghatsila, Jamsholaghat, Fekoghat, and Rajghat. During this period, runoff is found to increase by 6.06% due to decrease in infiltration rate. The comparison between the observed and estimated data shows the Nash–Sutcliffe efficiency (NSE) values are 0.91 and 0.90, and coefficient of determination (R 2) values are 0.89 and 0.88 for SCS-CN and GA methods, respectively. Thus, SCS model is found to do well than GA model in Subarnarekha River Basin. This type of study would be beneficial for the watershed development at that particular watershed.

A century scale hydro-climatic variability and associated risk in Subarnarekha river basin of India

Assessment of risk caused by extreme rain plays a significant role in the management of water resources for the tropical region of India, which is solely dependent on the monsoon rainfall. In the present paper, a century scale characterisation of hydro-meteorological parameters is done to evaluate fluctuations, climatological features, long-term trend, periodicity, and sensitivity of water-balance parameters to temperature change in the Subarnarekha basin of the Eastern Gangetic plains of India. Theory of extreme value is applied to characterize risk of the extreme events in the basin. A long-term prediction of the behavior of extreme rain events is performed. At seasonal, annual, and monthly scales, it is observed that there is no long-term trend in the rainfall. Short-term fluctuations dominate the total variance of annual rainfall, which is of less than 10 years. Percentage change of water-balance parameters (actual evapotranspiration, surplus, and precipitation) AE/P and S/P are highly sensible to temperature change. Subarnarekha basin is found to be highly susceptible to extreme rainfall event with a 20 year return level of 163 mm daily rainfall.

Dynamic evolution of riverbed potholes in the granitic bedrock of Chota Nagpur Plateau, middle part of Subarnarekha River basin, India

Potholes are an extraordinary abiotic micro geomorphic feature on the granite and quartzite topography of the Subarnarekha River basin. These erosional features are carved by the running water actions of River Subarnarekha and its tributaries. The study has been conducted on 17 sites (n = 1707) which are exemplary for the development of this micro fluvial feature located on the rejuvenated middle part of Subarnarekha River basin. Hydrological and geological factors are imperative for their formation. Joint length, joint density, joint orientation, rock hardness, variations of fluvial hydraulic, bed roughness, river bed slope and hydraulic gradient are conducive factors for the development of this geomorphic feature. Monsoon is the ideal season for carving these features by river turbulence, when abrasive work of river is predominant on the river bed (monsoon = 3000–6500kg.m2s-3, non-monsoon = 0.50–3.0kg.m2s-3). The evolutionary sequence of potholes is from round to oval and then elongated with vertical scouring. The relation between pothole radius and depth has been established to explain the process of its expansion. Joint length shows positive relation (R2 = 0.71) with pothole area while joint density has a negative relation (R2 = 0.29) as these are structurally weaker zones, characterised by destruction of these features. Suspended load is also a hindrance in their formation. Sites with high suspended load are delineated as pothole destructive zones. The mean dynamic evolution of circular, oval and elongated shaped potholes occurs at spatio-temporal level (Δoe=0.005-0.60m3,Δce=0.01-0.25m3,Δee = 0.005–0.30m3) and the initiation of this development depends on inner depth and radius of individual pothole.

Fluvial geochemistry of Subarnarekha River basin, India

The fluvial geochemistry of the Subarnarekha River and its major tributaries has been studied on a seasonal basis in order to assess the geochemical processes that explain the water composition and estimate solute fluxes. The analytical results show the mildly acidic to alkaline nature of the Subarnarekha River water and the dominance of \(\hbox {Ca}^{2+}\) and \(\hbox {Na}^{+}\) in cationic and \(\hbox {HCO}_{3}^{-}\) and \({\hbox {Cl}}^{-}\) in anionic composition. Minimum ionic concentration during the monsoon and maximum concentration in the pre-monsoon seasons reflect concentrating effects due to decrease in the river discharge and increase in the base flow contribution during the pre-monsoon and dilution effects of atmospheric precipitation in the monsoon season. The solute acquisition processes are mainly controlled by weathering of rocks, with minor contribution from marine and anthropogenic sources. Higher contribution of alkaline earth \((\hbox {Ca}^{2+}{+}\,\hbox {Mg}^{2+})\) to the total cations \((\hbox {TZ}^{+})\) and high \((\hbox {Na}^{+}+\hbox {K}^{+})/\hbox {Cl}^{-}\), \((\hbox {Na}^{+}+\hbox {K}^{+})/\hbox {TZ}^{+}\), \(\hbox {HCO}_{3}^{-}/(\hbox {SO}_{4}^{2-}+\hbox {Cl}^{-})\) and low \((\hbox {Ca}^{2+}+\hbox {Mg}^{2+})/(\hbox {Na}^{+}+\hbox {K}^{+})\) equivalent ratios suggest that the Subarnarekha River water is under the combined influence of carbonate and silicate weathering. The river water is undersaturated with respect to dolomite and calcite during the post-monsoon and monsoon seasons and oversaturated in the pre-monsoon season. The pH–log \(\hbox {H}_{4}\hbox {SiO}_{4}\) stability diagram demonstrates that the water chemistry is in equilibrium with the kaolinite. The Subarnarekha River annually delivered \(1.477\times 10^{6}\) ton of dissolved loads to the Bay of Bengal, with an estimated chemical denudation rate of \(77\hbox { ton km}^{-2}\hbox { yr}^{-1}\). Sodium adsorption ratio, residual sodium carbonate and per cent sodium values placed the studied river water in the ‘excellent to good quality’ category and it can be safely used for irrigation.

Flood susceptibility mapping using geospatial frequency ratio technique: a case study of Subarnarekha River Basin, India

Flood is one of the most damaging catastrophic natural hazards affecting human lives in India. So, flood susceptibility mapping is essential for urban hydrology management. In this study, a Geographical Information System based-bivariate statistical analysis namely frequency ratio (FR) model was used to assess flood susceptibility of the middle and lower catchments of Subarnarekha River. The flood inventory map was made using field surveys and formal reports in the study area. In general, 32 flood locations (70%) that were inundated in June, 2008 was used for statistical analysis as training dataset, while the remaining 30% (14 flood locations) flooded areas were applied to validate the developed model. Eight flood conditioning factors namely elevation, slope, topographical wetness index, geomorphology, soil type, drainage, rainfall, and LULC (land use/land cover) were considered in this study. All these variables were resampled into 20 × 20 m pixel size. Each variable was classified using the quantile method and the FR probability model was used to evaluate the relationship of each class with flood occurrences. Finally, the flood susceptibility map was prepared and classified into very low, low, moderate, high, and very high susceptibility. Results of the built model was validated with the ground data (30% flood locations) using the area under the curves (AUC). The AUC for success rate was estimated as 84.80%, while the prediction rate was 81.20%. The produced flood susceptibility mapping using FR model could be important for researchers, planners, and local governments in order to flood mitigation strategies.