Assessment of hydrologic impacts of climate change in Tunga-Bhadra river basin, India with HEC-HMS and SDSM

Climate change would significantly affect many hydrologic systems, which in turn would affect the water availability, runoff, and the flow in rivers. This study evaluates the impacts of possible future climate change scenarios on the hydrology of the catchment area of the TungaBhadra River, upstream of the Tungabhadra dam. The Hydrologic Engineering Center's Hydrologic Modeling System version 3.4 (HEC-HMS 3.4) is used for the hydrological modelling of the study area. Linear-regression-based Statistical DownScaling Model version 4.2 (SDSM 4.2) is used to downscale the daily maximum and minimum temperature, and daily precipitation in the four sub-basins of the study area. The large-scale climate variables for the A2 and B2 scenarios obtained from the Hadley Centre Coupled Model version 3 are used. After model calibration and testing of the downscaling procedure, the hydrological model is run for the three future periods: 20112040, 20412070, and 20712099. The impacts of climate change on the basin hydrology are assessed by comparing the present and future streamflow and the evapotranspiration estimates. Results of the water balance study suggest increasing precipitation and runoff and decreasing actual evapotranspiration losses over the sub-basins in the study area.

Spectral analysis of Cauvery river flows

A detalied study of the maonthly Convery river flows at the krishna raja sagara (KRS) reservoir is carried out by using the techniques of spectral analysis. The correlogram and power spectrum ate platted and used to identify the peridiocities inherent in the monthly inflows. The statistical significance of these periodicities is tested. Apart from the periodiocities at 12 months and 6 months, a significant of periodicity of 4 month was also observed in the monthly inflows. The analysis prepares ground for developing an appropriate stochastic model for the item series of the monthly flows.

Biogeochemical facsimile of the organic matter quality and trophic status of a micro-tidal tropical estuary

Seasonal studies were carried out from 21 stations, comprising of three zones, of Cochin Estuary, to assess the organic matter quality and trophic status. The hydographical parameters showed significant seasonal variations and nutrients and chlorophylls were generally higher during the monsoon season. However, chemical contamination along with the seasonal limitations of light and nitrogen imposed restrictions on the primary production and as a result, mesotrophic conditions generally prevailed in the water column. The nutrient stoichometries and delta C-13 values of surficial sediments indicated significant allochthonous contribution of organic matter. Irrespective of the higher content of total organic matter, the labile organic matter was very low. Dominance of carbohydrates over lipids and proteins indicated the lower nutritive aspect of the organic matter, and their aged and refractory nature. This, along with higher amount of phytodetritus and the low algal contribution to the biopolymeric carbon corroborated the dominance of allochthonous organic matter and the heterotrophic nature. The spatial and seasonal variations of labile organic components could effectively substantiate the observed shift in the productivity pattern. An alternative ratio, lipids to tannins and lignins, was proposed to ascertain the relative contribution of allochthonous organic matter in the estuary. This study confirmed the efficiency of an integrated biogeochemical approach to establish zones with distinct benthic trophic status associated with different degrees of natural and anthropogenic input. Nevertheless, our results also suggest that the biochemical composition alone could lead to erroneous conclusions in the case of regions that receive enormous amounts of anthropogenic inputs.

A general geomorphological recession flow model for river basins

Recession flows in a basin are controlled by the temporal evolution of its active drainage network (ADN). The geomorphological recession flow model (GRFM) assumes that both the rate of flow generation per unit ADN length (q) and the speed at which ADN heads move downstream (c) remain constant during a recession event. Thereby, it connects the power law exponent of -dQ/dt versus Q (discharge at the outlet at time t) curve, , with the structure of the drainage network, a fixed entity. In this study, we first reformulate the GRFM for Horton-Strahler networks and show that the geomorphic ((g)) is equal to D/(D-1), where D is the fractal dimension of the drainage network. We then propose a more general recession flow model by expressing both q and c as functions of Horton-Strahler stream order. We show that it is possible to have = (g) for a recession event even when q and c do not remain constant. The modified GRFM suggests that is controlled by the spatial distribution of subsurface storage within the basin. By analyzing streamflow data from 39 U.S. Geological Survey basins, we show that is having a power law relationship with recession curve peak, which indicates that the spatial distribution of subsurface storage varies across recession events. Key Points The GRFM is reformulated for Horton-Strahler networks. The GRFM is modified by allowing its parameters to vary along streams. Sub-surface storage distribution controls recession flow characteristics.

What mainly controls recession flows in river basins?

The ubiquity of the power law relationship between dQ/dt and Q for recession periods (-dQ/dt kQ(alpha); Q being discharge at the basin outlet at time t) clearly hints at the existence of a dominant recession flow process that is common to all real basins. It is commonly assumed that a basin, during recession events, functions as a single phreatic aquifer resting on a impermeable horizontal bed or the Dupuit-Boussinesq (DB) aquifer, and with time different aquifer geometric conditions arise that give different values of alpha and k. The recently proposed alternative model, geomorphological recession flow model, however, suggests that recession flows are controlled primarily by the dynamics of the active drainage network (ADN). In this study we use data for several basins and compare the above two contrasting recession flow models in order to understand which of the above two factors dominates during recession periods in steep basins. Particularly, we do the comparison by selecting three key recession flow properties: (1) power law exponent alpha, (2) dynamic dQ/dt-Q relationship (characterized by k) and (3) recession timescale (time period for which a recession event lasts). Our observations suggest that neither drainage from phreatic aquifers nor evapotranspiration significantly controls recession flows. Results show that the value of a and recession timescale are not modeled well by DB aquifer model. However, the above mentioned three recession curve properties can be captured satisfactorily by considering the dynamics of the ADN as described by geomorphological recession flow model, possibly indicating that the ADN represents not just phreatic aquifers but the organization of various sub-surface storage systems within the basin. (C) 2014 Elsevier Ltd. All rights reserved.

Geochemical behaviour of dissolved trace elements in a monsoon-dominated tropical river basin, Southwestern India

The study presents a 3-year time series data on dissolved trace elements and rare earth elements (REEs) in a monsoon-dominated river basin, the Nethravati River in tropical Southwestern India. The river basin lies on the metamorphic transition boundary which separates the Peninsular Gneiss and Southern Granulitic province belonging to Archean and Tertiary-Quaternary period (Western Dharwar Craton). The basin lithology is mainly composed of granite gneiss, charnockite and metasediment. This study highlights the importance of time series data for better estimation of metal fluxes and to understand the geochemical behaviour of metals in a river basin. The dissolved trace elements show seasonality in the river water metal concentrations forming two distinct groups of metals. First group is composed of heavy metals and minor elements that show higher concentrations during dry season and lesser concentrations during the monsoon season. Second group is composed of metals belonging to lanthanides and actinides with higher concentration in the monsoon and lower concentrations during the dry season. Although the metal concentration of both the groups appears to be controlled by the discharge, there are important biogeochemical processes affecting their concentration. This includes redox reactions (for Fe, Mn, As, Mo, Ba and Ce) and pH-mediated adsorption/desorption reactions (for Ni, Co, Cr, Cu and REEs). The abundance of Fe and Mn oxyhydroxides as a result of redox processes could be driving the geochemical redistribution of metals in the river water. There is a Ce anomaly (Ce/Ce*) at different time periods, both negative and positive, in case of dissolved phase, whereas there is positive anomaly in the particulate and bed sediments. The Ce anomaly correlates with the variations in the dissolved oxygen indicating the redistribution of Ce between particulate and dissolved phase under acidic to neutral pH and lower concentrations of dissolved organic carbon. Unlike other tropical and major world rivers, the effect of organic complexation on metal variability is negligible in the Nethravati River water.

Climate change scenarios of surface solar radiation in data sparse regions: a case study in Malaprabha River Basin, India

A variety of methods are available to estimate future solar radiation (SR) scenarios at spatial scales that are appropriate for local climate change impact assessment. However, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. Three methodologies to guide the estimation of SR are discussed in this study, namely: Case 1: SR is measured, Case 2: SR is measured but sparse and Case 3: SR is not measured. In Case 1, future SR scenarios are derived using several downscaling methodologies that transfer the simulated large-scale information of global climate models to a local scale ( measurements). In Case 2, the SR was first estimated at the local scale for a longer time period using sparse measured records, and then future scenarios were derived using several downscaling methodologies. In Case 3: the SR was first estimated at a regional scale for a longer time period using complete or sparse measured records of SR from which SR at the local scale was estimated. Finally, the future scenarios were derived using several downscaling methodologies. The lack of observed SR data, especially in developing countries, has hindered various climate change impact studies. Hence, this was further elaborated by applying the Case 3 methodology to a semi-arid Malaprabha reservoir catchment in southern India. A support vector machine was used in downscaling SR. Future monthly scenarios of SR were estimated from simulations of third-generation Canadian General Circulation Model (CGCM3) for various SRES emission scenarios (A1B, A2, B1, and COMMIT). Results indicated a projected decrease of 0.4 to 12.2 W m(-2) yr(-1) in SR during the period 2001-2100 across the 4 scenarios. SR was calculated using the modified Hargreaves method. The decreasing trends for the future were in agreement with the simulations of SR from the CGCM3 model directly obtained for the 4 scenarios.

An assessment of terrestrial water storage, rainfall and river discharge over Northern India from satellite data

Terrestrial water storage (TWS) plays a key role in the global water cycle and is highly influenced by climate variability and human activities. In this study, monthly TWS, rainfall and Ganga-Brahmaputra river discharge (GBRD) are analysed over India for the period of 2003-12 using remote sensing satellite data. The spatial pattern of mean TWS shows a decrease over a large and populous region of Northern India comprising the foothills of the Himalayas, the Indo-Gangetic Plains and North East India. Over this region, the mean monthly TWS exhibits a pronounced seasonal cycle and a large interannual variability, highly correlated with rainfall and GBRD variations (r > 0.8) with a lag time of 2 months and 1 month respectively. The time series of monthly TWS shows a consistent and statistically significant decrease of about 1 cm year(-1) over Northern India, which is not associated with changes in rainfall and GBRD. This recent change in TWS suggests a possible impact of rapid industrialization, urbanization and increase in population on land water resources. Our analysis highlights the potential of the Earth-observation satellite data for hydrological applications.

A Comparison of Machine Learning Techniques for Modeling River Flow Time Series: The Case of Upper Cauvery River Basin

Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).

Sources of major ions and processes affecting the geochemical and isotopic signatures of subsurface waters along a tropical river, Southwestern India

Systematic monitoring of subsurface hydrogeochemistry has been carried out for a period of one year in a humid tropical region along the Nethravati-Gurupur River. The major ion and stable isotope (delta O-18 and delta H-2) compositions are used to understand the hydrogeochemistry of groundwater and its interaction with surface water. In the study, it is observed that intense weathering of source rocks is the major source of chemical elements to the surface and subsurface waters. In addition, agricultural activities and atmospheric contributions also control the major ion chemistry of water in the study area. There is a clear seasonality in the groundwater chemistry, which is related to the recharge and discharge of the hydrological system. On a temporal scale, there is a decrease in major cation concentrations during the monsoon which is a result of dilution of sources from the weathering of rock minerals, and an increase in anion concentrations which is contributed by the atmosphere, accompanied by an increase in water level during the monsoon. The stable isotope composition indicates that groundwater in the basin is of meteoric origin and recharged directly from the local precipitation during the monsoonal season. Soon after the monsoon, groundwater and surface water mix in the subsurface region. The groundwater feeds the surface water during the lean river flow season.

Probable maximum precipitation estimation for catchments in Mahanadi river basin

Probable maximum precipitation (PMP) is a theoretical concept that is widely used by hydrologists to arrive at estimates for probable maximum flood (PMF) that find use in planning, design and risk assessment of high-hazard hydrological structures such as flood control dams upstream of populated areas. The PMP represents the greatest depth of precipitation for a given duration that is meteorologically possible for a watershed or an area at a particular time of year, with no allowance made for long-term climatic trends. Various methods are in use for estimation of PMP over a target location corresponding to different durations. Moisture maximization method and Hershfield method are two widely used methods. The former method maximizes the observed storms assuming that the atmospheric moisture would rise up to a very high value estimated based on the maximum daily dew point temperature. On the other hand, the latter method is a statistical method based on a general frequency equation given by Chow. The present study provides one-day PMP estimates and PMP maps for Mahanadi river basin based on the aforementioned methods. There is a need for such estimates and maps, as the river basin is prone to frequent floods. Utility of the constructed PMP maps in computing PMP for various catchments in the river basin is demonstrated. The PMP estimates can eventually be used to arrive at PMF estimates for those catchments. (C) 2015 The Authors. Published by Elsevier B.V.

Impact of river runoff into the ocean on Indian summer monsoon

Rivers of the world discharge about 36000 km 3 of freshwater into the ocean every year. To investigate the impact of river discharge on climate, we have carried out two 100 year simulations using the Community Climate System Model (CCSM3), one including the river runoff into the ocean and the other excluding it. When the river discharge is shut off, global average sea surface temperature (SST) rises by about 0.5 degrees C and the Indian Summer Monsoon Rainfall (ISMR) increases by about 10% of the seasonal total with large increase in the eastern Bay of Bengal and along the west coast of India. In addition, the frequency of occurrence of La Nina-like cooling events in the equatorial Pacific increases and the correlation between ISMR and Pacific SST anomalies become stronger. The teleconnection between the SST anomalies in the Pacific and monsoon is effected via upper tropospheric meridional temperature gradient and the North African-Asian Jet axis.

Environmental monitoring of bacterial contamination and antibiotic resistance patterns of the fecal coliforms isolated from Cauvery River, a major drinking water source in Karnataka, India

The present study focuses prudent elucidation of microbial pollution and antibiotic sensitivity profiling of the fecal coliforms isolated from River Cauvery, a major drinking water source in Karnataka, India. Water samples were collected from ten hotspots during the year 2011-2012. The physiochemical characteristics and microbial count of water samples collected from most of the hotspots exhibited greater biological oxygen demand and bacterial count especially coliforms in comparison with control samples (p <= 0.01). The antibiotic sensitivity testing was performed using 48 antibiotics against the bacterial isolates by disk-diffusion assay. The current study showed that out of 848 bacterial isolates, 93.51 % (n=793) of the isolates were found to be multidrug-resistant to most of the current generation antibiotics. Among the major isolates, 96.46 % (n=273) of the isolates were found to be multidrug-resistant to 30 antibiotics and they were identified to be Escherichia coli by 16S rDNA gene sequencing. Similarly, 93.85 % (n=107), 94.49 % (n=103), and 90.22 % (n=157) of the isolates exhibited multiple drug resistance to 32, 40, and 37 antibiotics, and they were identified to be Enterobacter cloacae, Pseudomonas trivialis, and Shigella sonnei, respectively. The molecular studies suggested the prevalence of blaTEM genes in all the four isolates and dhfr gene in Escherichia coli and Sh. sonnei. Analogously, most of the other Gram-negative bacteria were found to be multidrug-resistant and the Gram-positive bacteria, Staphylococcus spp. isolated from the water samples were found to be methicillin and vancomycin-resistant Staphylococcus aureus. This is probably the first study elucidating the bacterial pollution and antibiotic sensitivity profiling of fecal coliforms isolated from River Cauvery, Karnataka, India.

Use of Sr isotopes as a tool to decipher the soil weathering processes in a tropical river catchment, southwestern India

River water composition (major ion and Sr-87/Sr-86 ratio) was monitored on a monthly basis over a period of three years from a mountainous river (Nethravati River) of southwestern India. The total dissolved solid (TDS) concentration is relatively low (46 mg L-1) with silica being the dominant contributor. The basin is characterised by lower dissolved Sr concentration (avg. 150 nmol L-1), with radiogenic Sr-87/Sr-86 isotopic ratios (avg. 0.72041 at outlet). The composition of Sr and Sr-87/Sr-86 and their correlation with silicate derived cations in the river basin reveal that their dominant source is from the radiogenic silicate rock minerals. Their composition in the stream is controlled by a combination of physical and chemical weathering occurring in the basin. The molar ratio of SiO2/Ca and Sr-87/Sr-86 isotopic ratio show strong seasonal variation in the river water, i.e., low SiO2/Ca ratio with radiogenic isotopes during non-monsoon and higher SiO2/Ca with less radiogenic isotopes during monsoon season. Whereas, the seasonal variation of Rb/Sr ratio in the stream water is not significant suggesting that change in the mineral phase being involved in the weathering reaction could be unlikely for the observed molar SiO2/Ca and Sr-87/Sr-86 isotope variation in river water. Therefore, the shift in the stream water chemical composition could be attributed to contribution of ground water which is in contact with the bedrock (weathering front) during non-monsoon and weathering of secondary soil minerals in the regolith layer during monsoon. The secondary soil mineral weathering leads to limited silicate cation and enhanced silica fluxes in the Nethravati river basin. (C) 2015 Elsevier Ltd. All rights reserved.