Sharavathi River Basin Flora Information System(SRFIS)

The INFORMATION SYSTEM with user friendly GUI’s (Graphical user Interface) is developed to maintain the flora data and generate reports for Sharavathi River Basin. The database consists of the information related to trees, herbs, shrubs and climbers. The data is based on the primary field survey and the information available in flora of Shimoga, Karnataka and Hassan flora. User friendly query options based on dichotomous keys are provided to help user to retrieve the data while data entry options aid in updating and editing the database at family, genus and species levels.

Daily relative humidity projections in an Indian river basin for IPCC SRES scenarios

A two-stage methodology is developed to obtain future projections of daily relative humidity in a river basin for climate change scenarios. In the first stage, Support Vector Machine (SVM) models are developed to downscale nine sets of predictor variables (large-scale atmospheric variables) for Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) (A1B, A2, B1, and COMMIT) to R (H) in a river basin at monthly scale. Uncertainty in the future projections of R (H) is studied for combinations of SRES scenarios, and predictors selected. Subsequently, in the second stage, the monthly sequences of R (H) are disaggregated to daily scale using k-nearest neighbor method. The effectiveness of the developed methodology is demonstrated through application to the catchment of Malaprabha reservoir in India. For downscaling, the probable predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis data set for the period 1978-2000 and (2) simulations of the third-generation Canadian Coupled Global Climate Model for the period 1978-2100. The performance of the downscaling and disaggregation models is evaluated by split sample validation. Results show that among the SVM models, the model developed using predictors pertaining to only land location performed better. The R (H) is projected to increase in the future for A1B and A2 scenarios, while no trend is discerned for B1 and COMMIT.

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.

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.

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).

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.

Values of inland fisheries in the Mekong river basin

Asia has the most productive inland fisheries in the world. The fishery sector contributes significantly to the national economies of the region. Inland fisheries also improve food security by providing a source of protein and a livelihood for millions of people in this part of the world, especially the rural poor. The purpose of this report is to provide information on the biological, economic, social and cultural values of river fisheries in the Lower Mekong Basin, and to identify the main impacts of environmental changes on these values. A review of fisheries-related literature, including project reports and gray literature, was undertaken. More than 800 documents were reviewed, and original information was extracted from 270 of them. The analysis identified a large number of localized studies leading to generic conclusions. The report addresses the basin wide issues and studies. It is then organized by nation, namely, the Chinese province of Yunnan, then Laos, Thailand, Cambodia and Vietnam. It first gives an overview of each country’s economic, fisheries and social situation, then details the values documented for river fisheries in each country.

Test well exploration in the Myakka River Basin area, Florida

In recent years, difficulties encountered in obtaining ground-water supplies with acceptable chemical characteristics in the Myakka River basin area led to the implementation of a test drilling program. Under this program, well drilling and data collection were executed in such a manner that all water-producing zones of the local aquifers, together with the quality and quantity of the water available, were effectively identified. A step-drilling method was utilized which allowed the collection of formation cuttings, water samples, and water-level data, from isolated zones in the well as drilling proceeded. The step drilling procedure is described. The driller's logs, geophysical logs, and chemical quality of water tables are presented.(Document has 66 pages.)

Low streamflow in the Myakka River Basin Area in Florida

The Sarasota-Manatee area is a water-short area and the study was undertaken in 1963 in order to determine the storage capability and discharge rates of the Myakka water shed. It was found that many of the streams of the water shed were virtually dry during part of every year. However, the basins of the Myakka lakes, through which the river flows offer some storage potential, that if properly developed would provide a continuance drift of about seven million gallons of water per day of good quality water that would be high in color and temperature upon occasion. With reasonable treatment some of this water could be used to meet the present needs of the rapidly expanding coastal areas. (PDF contains 40 pages.)

Springsheds of the Santa Fe River Basin

Powerpoint presentation (PDF has 45 pages.)

Evaluation of salmon and steelhead spawning habitat quality in the South Fork Trinity River Basin, 1997

Sediment sampling was used to evaluate chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) spawning habitat quality in the South Fork Trinity River (SFTR) basin. Sediment samples were collected using a McNeil-type sampler and wet sieved through a series of Tyler screens (25.00 mm, 12.50 mm, 6.30 mm, 3.35 mm, 1.00 mm, and 0.85 mm). Fines (particles < 0.85 mm) were determined after a l0-minute settling period in Imhoff cones. Thirteen stations were sampled in the SFTR basin: five stations were located in mainstem SFTR between rk 2.1 and 118.5, 2 stations each were located in EF of the SFTR, Grouse Creek, and Madden Creek, and one station each was located in Eltapom and Hayfork Creeks. Sample means for fines(particles < 0.85 mm) fer SFTR stations ranged between 14.4 and 19.4%; tributary station sample mean fines ranged between 3.4 and 19.4%. Decreased egg survival would be expected at 4 of 5 mainstem SFTR stations and at one station in EF of SFTR and Grouse Creek where fines content exceed 15%. Small gravel/sand content measured at all stations were high, and exceed levels associated with reduced sac fry emergence rates. Reduction of egg survival or sac fry emergence due to sedimentation in spawning gravels could lead to reduced juvenile production from the South Fork Trinity River. (PDF contains 18 pages.)

Age, growth and life history of Klamath River Basin steelhead trout (Onchorhynchus mykiss irideus) as determined from scale analysis

Adult steelhead (Oncorhynchus mykiss irideus) scales were analyzed from eight fall-run, two spring-run, and one winter-run stocks within the Klamath-Trinity River system, from 1981 through 1983, to provide basic information on age, growth, and life history. The higher degree of half-pounder occurrence of upper Klamath River steelhead stocks (86.7 to 100%) compared to Trinity River steelhead stocks (32.0 to 80.0%) was the major life history difference noted in scale analysis. Early life history was similar for all areas sampled with most juveniles (86.4%) remaining in freshwater during the first two years of life before migrating to sea. Repeat spawning ranged from 17.6 to 47.9% for fall-run, 40.0 to 63.6% for spring-run, and 31.1% for winter-run steelhead. Mean length of adults at first spawning was inversely related to percent half-pounder occurrence in each stock. Ages of returning spawners, back calculated lengths at various life stages, and growth information are presented. (PDF contains 22 pages)

Harnessing the fishery potential of man-made lakes for the partial commercialisation of Niger River Basin Development Authority, Minna, Nigeria

Niger River Basin Development Authority Minna (NRBDA) is one of the eleven river basins in Nigeria now undergoing transition towards partial commercialisation. In the light of this the need to be self-sustaining through exploration and exploitation of every possible areas along their operation to yield revenue cannot be over-emphasized. Therefore it is most pertinent to consider fisheries activities along their water bodies as one of the major sources of revenue by organising the local fishermen operating along the water into cooperative bodies and made to pay for fishing rights. Strategies to accomplish this objective is highlighted. The need to embark on aquaculture projects by construction of fish ponds at suitable sites along the reservoirs and developing the recreational potentials of their water bodies as sources of revenue is also stressed

Implementing Integrated Water Resources Management in the Ebro River Basin: From Theory to Facts

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