Temporal and spatial variations in water flow and sediment load in Narmada River Basin, India: natural and man-made factors

The Narmada River flows through the Deccan volcanics and transports water and sediments to the adjacent Arabian Sea. In a first-ever attempt, spatial and temporal (annual, seasonal, monthly and daily) variations in water discharge and sediment loads of Narmada River and its tributaries and the probable causes for these variations are discussed. The study has been carried out with data from twenty-two years of daily water discharge at nineteen locations and sediment concentrations data at fourteen locations in the entire Narmada River Basin. Water flow in the river is a major factor influencing sediment loads in the river. The monsoon season, which accounts for 85 to 95% of total annual rainfall in the basin, is the main source of water flow in the river. Almost 85 to 98% of annual sediment loads in the river are transported during the monsoon season (June to November). The average annual sediment flux to the Arabian Sea at Garudeshwar (farthest downstream location) is 34.29×10⁶ t year⁻¹ with a water discharge of 23.57 km³ year⁻¹. These numbers are the latest and revised estimates for Narmada River. Water flow in the river is influenced by rainfall, catchment area and groundwater inputs, whereas rainfall intensity, geology/soil characteristics of the catchment area and presence of reservoirs/dams play a major role in sediment discharge. The largest dam in the basin, namely Sardar Sarovar Dam, traps almost 60–80% of sediments carried by the river before it reaches the Arabian Sea.     

Assessment of spatial variations in water quality of Garra River at Shahjahanpur,Ganga Basin,India

Arabian Journal of Geosciences - A comprehensive study on the chemical considerations of thermal waters (springs and geothermal wells) on the performance of solute geothermometers in predicting the...     

Sorption of PAR–metal complexes on activated carbon as a rapid preconcentration method for the determination of Cu, Co, Cd, Cr, Ni, Pb and V in ground water

A simple, rapid and field-oriented preconcentration method is described for the determination of Cu, Co, Cd, Cr, Ni, Pb and V in ground water samples by flame AAS. The method is based on sorption of trace elements as metal-pyridyl azo resorcinol (M-PAR) complexes on activated carbon (AC) at pH 5.5±0.5. The effects of various parameters for quantitative sorption of M-PAR chelates on AC are discussed. The trace elements are desorbed from AC simply by treating AC with 1.6 M nitric acid, thus avoiding the tedious and time consuming operation of ashing AC. An enrichment factor of 200 or greater is easily achievable. The trace elements could be determined down to 1 ppb (V at 5 ppb) with ±15% relative error. The RSD of the method is ±15% at the practical determination limit of 1 ppb with an enrichment factor of 200. The major advantage of the method is the possibility of performing the preconcentration at the sampling site and hence a small preconcentrated volume could be sent for instrumental analysis, thus preventing sorption on a container during storage. The method has been applied to numerous ground water samples for the determination of these trace analytes at ppb levels in connection with the hydrogeochemical exploration for uranium.     

Diagenetic model of carbonate rocks of Guri Member of Mishan Formation (Lower to Middle Miocene) SE Zagros basin,Iran

In order to understand the post-depositional history of carbonate rocks of Guri Member (Lower to Middle Miocene), three stratigraphic sections were selected in north Bandar-Abbas in southeast of Iran. Sampling was carried out, analyzed for selective parameters such as oxygen and carbon isotopic compositions (δ¹⁸O and δ¹³C) and interpreted in the present study. We recognized several diagenetic processes including micritization, cementation, neomorphism, compaction, dissolution, silicification, dolomitization, fracturing and vein filling. Some of the diagenetic processes occurred at different conditions, so in order to achieve precise interpretation, samples from different carbonate components such as, micrite, fracture cement, solution pore cement, intergranular cement, and some biotic allochems were analyzed. In this study micrite samples were subdivided into two groups including micro-spary and micrite. They were recognized under Cathodoluminescence microscope. In addition, micrite samples were classified into five groups based on their depositional environments: supratidal, lagoon, coral bar, open sea, and open basin. There were minor changes in stable isotope ratios based on the sedimentary environments, stratigraphy successions, and micro-spary or micrite properties. In this study, similar calcite cements in petrography studies were differentiated by stable isotope data. Those calcite cements have formed in different diagenetic environments such as meteoric and burial cements. Paragenetic sequence of carbonate rocks were interpreted by integration of petrographic and isotopic studies. We have reconstructed diagenetic models of Guri Member into four stages including marine, meteoric, burial, and uplifting.     

Artificial neural network simulation for prediction of suspended sediment concentration in the River Ramganga,Ganges Basin,India

The relation between the water discharge (Q) and suspended sediment concentration (SSC) of the River Ramganga at Bareilly, Uttar Pradesh, in the Himalayas, has been modeled using Artificial Neural Networks (ANNs). The current study validates the practical capability and usefulness of this tool for simulating complex nonlinear, real world, river system processes in the Himalayan scenario. The modeling approach is based on the time series data collected from January to December (2008-2010) for Q and SSC. Three ANNs (T1-T3) with different network configurations have been developed and trained using the Levenberg Marquardt Back Propagation Algorithm in the Matlab routines. Networks were optimized using the enumeration technique, and, finally, the best network is used to predict the SSC values for the year 2011. The values thus obtained through the ANN model are compared with the observed values of SSC. The coefficient of determination (R2), for the optimal network was found to be 0.99. The study not only provides insight into ANN modeling in the Himalayan river scenario, but it also focuses on the importance of understanding a river basin and the factors that affect the SSC, before attempting to model it. Despite the temporal variations in the study area, it is possible to model and successfully predict the SSC values with very simplistic ANN models.     

Biogeochemical records of paleoenvironmental changes in Nainital Lake,Kumaun Himalayas,India

Rapid urbanization and increased tourism around Nainital Lake in the Kumaun Himalayan region in north India has raised concerns about sediment and water pollution. Lead-210 dated sediment cores from the lake represent ~95 years of accumulation and yield a mean sedimentation rate of ~4.7 mm year⁻¹. Total organic carbon (TOC), percent N and S and their atomic C/N and C/S ratios, stable isotopes (δ¹³C, δ¹⁵N, and δ³⁴S), and specific biomarkers (n-alkanes and pigments) were measured in the core. Organic matter is primarily derived from in-lake algal production and TOC flux varies from 1.0 to 3.5 g m⁻² year⁻¹. Sediments are anoxic (Eh −328 to −187 mV) and have low (0.10–0.30 g m⁻² year⁻¹) N, but high (0.37–1.0 g m⁻² year⁻¹) S flux. Shifts in δ¹³C, δ¹⁵N, and δ³⁴S suggest in-lake microbial processes dominated by denitrification and sulfate reduction. The sediments are dominated by short-chain hydrocarbons with low Carbon Preference Index values. The pigments indicate a gradual shift to cyanobacterial domination of the phytoplankton community in recent years. Despite an increase in external input of nutrients, the trophic state of the lake has remained largely unchanged, and the perceived human-induced impacts are limited.     

Organic geochemical record of increased productivity in Lake Naukuchiyatal, Kumaun Himalayas, India

Organic geochemical proxies have been studied in a 45-cm-long core retrieved from Lake Naukuchiyatal in Kumaun Himalayas, India. Increase in TOC, N, hydrocarbons and pigments concentration from bottom to surface sediments of the core indicates increase in the lake productivity. Stable isotopes (δ¹³C and δ ¹⁵ N), biomarkers (TAR, CPI and n-ΣC_15,17,19) and C/N atomic (between 9 and 12) suggest dominance of algal derived organic matter in these sediments. Decrease in organic δ¹³C values (between ?27 and ?31‰) in surface sediments indicate influence of sewage and land runoff in shifting organic δ¹³C values, whereas low (between ?0.23 and 2.2‰) δ¹⁵N values together with high pigment concentrations (zeaxanthin and echinenone) represent dominance of cyanobacteria in the lake.     

Major and trace element geochemistry in upper Ganga river in the Himalayas, India

Chemical weathering and resulting water compositions in the upper Ganga river in the Himalayas were studied. For the first time, temporal and spatial sampling for a 1 year period (monthly intervals) was carried out and analyzed for dissolved major elements, trace elements, Rare Earth Elements (REE), and strontium isotopic compositions. Amounts of physical and chemical loads show large seasonal variations and the overall physical load dominates over chemical load by a factor of more than three. The dominant physical weathering is also reflected in high quartz and illite/mica contents in suspended sediments. Large seasonal variations also occur in major elemental concentrations. The water type is categorized as HCO₃^––SO₄^2––Ca²⁺ dominant, which constitute >60% of the total water composition. On an average, only about 5–12% of HCO₃^– is derived from silicate lithology, indicating the predominance of carbonate lithology in water chemistry in the head waters of the Ganga river. More than 80% Na⁺ and K⁺ are derived from silicate lithology. The silicate lithology is responsible for the release of low Sr with extremely radiogenic Sr (⁸⁷Sr/⁸⁶ Sr>0.75) in Bhagirathi at Devprayag. However, there is evidence for other end-member lithologies for Sr other than carbonate and silicate lithology. Trace elements concentrations do not indicate any pollution, although presence of arsenic could be a cause for concern. High uranium mobilization from silicate rocks is also observed. The REE is much less compared to other major world rivers such as the Amazon, perhaps because in the present study, only samples filtered through <0.2 m were analysed. Negative Eu anomalies in suspended sediments is due to the excess carbonate rock weathering in the source area.     

Geochemistry,dissolved elemental flux rates,and dissolution kinetics of lithologies of Alaknanda and Bhagirathi rivers in Himalayas,India

Alaknanda and Bhagirathi (AB) river basins in the Himalayan region in India expose lithologies comprising mainly of granites, low–high-grade metamorphics, shales and carbonates which, in conjunction with the monsoon rains and glacial melt, control water chemistry and dissolved elemental flux rates. In the present study, we monitored two locations: (a) Srinagar on the Alaknanda river and (b) Maneri on the Bhagirathi river for daily variations in total suspended sediments, major ions and dissolved silica over one complete year (July 2004–June 2005). Based on long-term discharge data, discharge-weighted composition and dissolved elemental flux rates (with respect to Ca, Mg, HCO₃, Si) of the river were estimated. The information thus obtained has substantially added up to the existing chemical data of these rivers and has refined the flux rates. Our high-frequency samples provide informations such as (a) water chemical compositions that show a large temporal and spatial variation and (b) carbonate lithology that controls water chemistry predominantly. The dissolution kinetics of various lithologies namely leucogranite, gneiss, quartzite, phyllite and shale of the AB river basins were studied through batch experiments at controlled temperature (25 and 5°C) and pH (8.4) condition. In laboratory, these lithologies undergo slow rates of dissolution (10⁻¹³ to 10⁻¹⁵ mol/m² s), while field weathering rates based on dissolved elemental flux rates in the AB rivers are much higher (10⁻⁸ to 10⁻⁹ mol/m² s). Extremely high physical weathering rates in AB rivers, which enhance chemical weathering significantly, mainly attribute this wide discrepancy in laboratory-derived rates of representative basin rocks and dissolved elemental fluxes in the field. However, laboratory-simulated experiments facilitate to quantify elemental release rates, understand the kinetics of the dissolution reactions, and compare their roles at individual level.     

Neural network model for discharge and water-level prediction for Ramganga River catchment of Ganga Basin,India

ABSTRACT

Discharges and water levels are essential components of river hydrodynamics. In unreachable terrains and ungauged locations, it is quite difficult to measure these parameters due to rugged topography. In the present study an artificial neural network model has been developed for the Ramganga River catchment of the Ganga Basin. The modelled network is trained, validated and tested using daily water flow and level data pertaining to 4 years (2010–2013). The network has been optimized using an enumeration technique and a network topology of 4-10-2 with a learning rate set at 0.06, which was found optimum for predicting discharge and water-level values for the considered river. The mean square error values obtained for discharge and water level for the tested data were found to be 0.046 and 0.012, respectively. Thus, monsoon flow patterns can be estimated with an accuracy of about 93.42%.

Editor M.C. Acreman; Associate editor E. Gargouri