Studies On The Dynamics And Water Quality Of The Muvattupuzha River In Relation To Effluent Discharge

The present study aims at the investigation of the 1ysico—chemical features of a tropical tidal river viz. we Muvattupuzha river. This river is expected to receive Jderate to heavy pollution loads in years to come, from we lone industrial unit, already set up on its bank. ilike other rivers, the geographical disposition of this Lver attains unique importance as regards its dynamics for 3) availability of natural runoff water from catchment :eas, which becomes very heavy during the monsoon season 3) regular steady availability of tail race water from a /dro—electric power station throughout the yearThe study also aims at arriving at the balancing forces of inherent self~purification of the river verses pollution loads from the factory effluents. The investigation period falls ahead of actual pollution occurrence and so the ambient conditions for a period of nearly one-and-a—half years were investigated, the analyses of which providflz to formulate the inter-relations of parameters varying with seasons. Tracer experiments were carried out which revealed the dispersion and dilution characteristics of the river in the vicinity of effluent outfall. The studv covers the trial—cum-capacity production periods of the factory during which effluents of various strength and quantity were discharged into the river; a few computed values arQ’cjmpgrQdl ... with the observed values. The base data along with the profiles of Oxygen sag equation have been utilized fb develop a mathematical model of the river with regard to its water quality

Macrobenthos And Its Relation To Ecosystem Dynamics In The Cochin Estuary

Cochin estuary is a shallow brackish water body situated on the south west coast of India. It is a tropical positive estuary extending between 90 40’ and 100 12’ N and 760 10’and 760 30’ E with its northern boundary at Azhikode and southern boundary at Thannermukkom bund.The abundance of benthic fauna in an ecosystem shows the close relationship to its environment and reflects the characteristics of an ecological niche. Seasonal and monthly variations in the distribution of macrobenthos in relation to sediment characteristics were conducted in Cochin estuary from 2009-10 periods. Oxidation-reduction potential showed reducing trends that affected the distribution and diversity of fauna. Seasonal variations in water quality and river discharge pattern affected the faunal composition in the different stations. Sewage mixing was the principal source of organic pollution in the Cochin estuary. The sediment pH was generally on the alkaline side ranging from 4.99 at St.9 and 8.33 at St.1.The Eh ranged from -11mV at St.3 to -625mV at St.2.The temperature varied from 260C to 320C in the estuary. The moisture content ranged from 1.63 to 12.155%, that of organic carbon from 0 09 at St. 6 to 4.29% at St.9 and that of organic matter from 0.16 to 7.39%. Seasonally, the average of Eh was highest during the monsoon (156.22 mV) and in the pre monsoon (140.94 mV). The average pH for the 9 study stations was 7.68 during monsoon period and 7.08 during post monsoon. Based on group wise seasonal analysis, the average mean abundance was maximum for polychaetes (43.47) followed by nematodes (33.62), crustaceans (21.62), molluscs (11.94) and Pisces (0.05) in the estuary. Monsoon season was most favourable for benthic faunal abundance followed by the post monsoon period in the study. The series of human interventions like dredging, discharge of industrial effluents, urbanisation and related aspects had a strong influence on the distribution, abundance of benthic macrofauna in the wetland.

Seasonal Variability Of Dissolved Nutrients In Mangrove Ecosystems Along South West Coast Of Kerala, India

The mangroves of Kerala are fast disappearing due to developmental activities.There are very few studies conducted in the chemical aspects of these ecosystems.The main objective of this study is to assess the spatial and seasonal variation of hydrographical as well as nutrients in mangrove ecosystems along Kerala coast. Five sampling sites least intervened by industries were selected for the study. Sampling was done for a period of six months in monthly intervals. A monsoonal hike of dissolved nutrients was observed in all ecosystems except in the constructed mangrove wetland. The constructed wetland exhibited a different hydrography and nutrient level in all seasons. The mangrove forest in this area consists of the species Bruguiera gymnorrhiza which has been planted since forty years.

Ecology And Seasonal Variation Of Microalgal Community In An Oil Refinery Effluent Holding Pond: Monitoring And Assessment

The microalgal community as primary producers has to play a significant role in the biotic and abitoic interactions of any aquatic ecosystem. Whenever a community is exposed to a pollutant, responses can occur because individuals acclimate to pollutant caused changes and selection can occur favouring resistant genotypes within a population and selection among species can result in changes in community structure. The microalgal community of industrial effluent treatment systems are continuously exposed to pollutants and there is little data available on the structure and seasonal variation of microalgal community of industrial effluent holding ponds, especially of a complex effluent like that of refinery. The aim of the present study was to investigate the annual variation in the ecology, biomass, productivity and community structure of the algal community of a refinery effluent holding pond. The results of the study showed the pond to be a eutrophic system with a resistant microalgal community with distinct seasonal variation in species composition

Downscaling and Modeling the Effects of Climate Change on Hydrology and Water Resources in the Upper Blue Nile River Basin, Ethiopia

The Upper Blue Nile River Basin (UBNRB) located in the western part of Ethiopia, between 7° 45’ and 12° 45’N and 34° 05’ and 39° 45’E has a total area of 174962 km2 . More than 80% of the population in the basin is engaged in agricultural activities. Because of the particularly dry climate in the basin, likewise to most other regions of Ethiopia, the agricultural productivity depends to a very large extent on the occurrence of the seasonal rains. This situation makes agriculture highly vulnerable to the impact of potential climate hazards which are about to inflict Africa as a whole and Ethiopia in particular. To analyze these possible impacts of future climate change on the water resources in the UBNRB, in the first part of the thesis climate projection for precipitation, minimum and maximum temperatures in the basin, using downscaled predictors from three GCMs (ECHAM5, GFDL21 and CSIRO-MK3) under SRES scenarios A1B and A2 have been carried out. The two statistical downscaling models used are SDSM and LARS-WG, whereby SDSM is used to downscale ECHAM5-predictors alone and LARS-WG is applied in both mono-model mode with predictors from ECHAM5 and in multi-model mode with combined predictors from ECHAM5, GFDL21 and CSIRO-MK3. For the calibration/validation of the downscaled models, observed as well as NCEP climate data in the 1970 - 2000 reference period is used. The future projections are made for two time periods; 2046-2065 (2050s) and 2081-2100 (2090s). For the 2050s future time period the downscaled climate predictions indicate rise of 0.6°C to 2.7°C for the seasonal maximum temperatures Tmax, and of 0.5°C to 2.44°C for the minimum temperatures Tmin. Similarly, during the 2090s the seasonal Tmax increases by 0.9°C to 4.63°C and Tmin by 1°C to 4.6°C, whereby these increases are generally higher for the A2 than for the A1B scenario. For most sub-basins of the UBNRB, the predicted changes of Tmin are larger than those of Tmax. Meanwhile, for the precipitation, both downscaling tools predict large changes which, depending on the GCM employed, are such that the spring and summer seasons will be experiencing decreases between -36% to 1% and the autumn and winter seasons an increase of -8% to 126% for the two future time periods, regardless of the SRES scenario used. In the second part of the thesis the semi-distributed, physically based hydrologic model, SWAT (Soil Water Assessment Tool), is used to evaluate the impacts of the above-predicted future climate change on the hydrology and water resources of the UBNRB. Hereby the downscaled future predictors are used as input in the SWAT model to predict streamflow of the Upper Blue Nile as well as other relevant water resources parameter in the basin. Calibration and validation of the streamflow model is done again on 1970-2000 measured discharge at the outlet gage station Eldiem, whereby the most sensitive out the numerous “tuneable” calibration parameters in SWAT have been selected by means of a sophisticated sensitivity analysis. Consequently, a good calibration/validation model performance with a high NSE-coefficient of 0.89 is obtained. The results of the future simulations of streamflow in the basin, using both SDSM- and LARS-WG downscaled output in SWAT reveal a decline of -10% to -61% of the future Blue Nile streamflow, And, expectedly, these obviously adverse effects on the future UBNRB-water availibiliy are more exacerbated for the 2090’s than for the 2050’s, regardless of the SRES.

The prediction of seasonal and inter-annual climate variations and their impacts on the water resources in the eastern seaboard of Thailand

The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.

Seasonal adjustment and cointegration

El documento examina el efecto de filtros de ajuste en el tamaño y poder de prueba de cointegración que usan los residuales como pruebas ADF y PP, mediante procedimientos MonteCarlo y una aplicación empírica. Nuestros resultados indican que el uso de filtros distorsiona el tamaño y reduce el poder de estas pruebas.

Nonbreeding-Season Drivers of Population Dynamics in Seasonal Migrants: Conservation Parallels Across Taxa

For seasonal migrants, logistical constraints have often limited conservation efforts to improving survival and reproduction during the breeding season only. Yet, mounting empirical evidence suggests that events occurring throughout the migratory life cycle can critically alter the demography of many migrant species. Herein, we build upon recent syntheses of avian migration research to review the role of non-breeding seasons in determining the population dynamics and fitness of diverse migratory taxa, including salmonid fishes, marine mammals, ungulates, sea turtles, butterflies, and numerous bird groups. We discuss several similarities across these varied migrants: (i) non-breeding survivorship tends to be a strong driver of population growth; (ii) non-breeding events can affect fitness in subsequent seasons through seasonal interactions at individual- and population-levels; (iii) broad-scale climatic influences often alter non-breeding resources and migration timing, and may amplify population impacts through covariation among seasonal vital rates; and (iv) changes to both stationary and migratory non-breeding habitats can have important consequences for abundance and population trends. Finally, we draw on these patterns to recommend that future conservation research for seasonal migrants will benefit from: (1) more explicit recognition of the important parallels among taxonomically diverse migratory animals; (2) an expanded research perspective focused on quantification of all seasonal vital rates and their interactions; and (3) the development of detailed population projection models that account for complexity and uncertainty in migrant population dynamics.