Water Resource Pollution and Impacts on the local livelihood: A case study of Beas River in Kullu District, India

The rivers are considered as the life line of any country since they make water available for our domestic, industrial and recreational functions. The quality of river water signifies the health status and hygienic aspects of a particular region, but the quality of these life lines is continuously deteriorating due to discharge of sewage, garbage and industrial effluents into them. Thrust on water demand has increased manifolds due to the increased population, therefore tangible efforts to make the water sources free from pollution is catching attention all across the globe. This paper attempts to highlight the trends in water quality change of River Beas, right from Manali to Larji in India. This is an important river in the state of Himachal Pradesh and caters to the need of water for Manali and Kullu townships, besides other surrounding rural areas. The Manali-Larji Beas river stretch is exposed to the flow of sewage, garbage and muck resulting from various project activities, thereby making it vulnerable to pollution. In addition, the influx of thousands of tourists to these towns also contributes to the pollution load by their recreational and other tourist related activities. Pollution of this river has ultimately affected the livelihood of local population in this region. Hence, water quality monitoring was carried out for the said stretch between January, 2010 and January, 2012 at 15 various locations on quarterly basis, right from the upstream of Manali town and up to downstream of Larji dam. Temperature, color, odor, D.O. , pH, BOD, TSS, TC and FC has been the parameters that were studied. This study gives the broad idea about the characteristics of water at locations in the said river stretch, and suggestions for improving water quality and livelihood of local population in this particular domain.

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.

Thermal Impacts on Building Integrated Photovoltaic (BIPV) (Electrical, Thermal and Mechanical Characteristics)

Ein Drittel des weltweiten gesamten Energiebedarfs wird durch Gebäude verbraucht. Um diesen Energiebedarf teilweise zu decken, den erheblichen Energieverbrauch zu reduzieren und weiterhin andere Gebäudefunktionen beizubehalten, ist Gebäudeintegrierte Photovoltaik (BIPV) eine der am besten geeigneten Lösungen für die Gebäudenanwendung. Im Bezug auf eine Vielzahl von Gestalltungsmöglichkeiten, sind die Randbedingungen der BIPV-Anwendungen eindeutig anders im Vergleich zu Standard-PV-Anwendungen, insbesondere bezüglich der Betriebstemperatur. Bisher gab es nicht viele Informationen zu den relevanten thermischen Auswirkungen auf die entsprechenden elektrischen Eigenschaften zusammen mit thermischen und mechanischen relevanten Gebäudenfunktionen. Die meisten Hersteller übernehmen diese Eigenschaften von entsprechenden PV-Modulen und konventionellen Bauprodukten Normen, die zur ungenauen System- und Gebäudeplanungen führen. Deshalb ist die Untersuchung des thermischen Einflusses auf elektrische, thermische sowie mechanische Eigenschaften das Hauptziel der vorliegenden Arbeit. Zunächst wird das Temperatur-Model mit dem Power-Balance-Konzept erstellt. Unter Berücksichtigung der variablen Installationsmöglichkeiten und Konfigurationen des Moduls wird das Model auf Basis dynamischer und stationär Eigenschaften entwickelt. Im Hinblick auf die dynamische Simulation können der Energieertrag und Leistung zusammen mit der thermischen Gebäudesimulation in Echtzeit simuliert werden. Für stationäre Simulationen können die relevanten Gebäudefunktionen von BIPV-Modulen sowohl im Sommer als auch im Winter simuliert werden. Basierend auf unterschiedlichen thermischen und mechanischen Last-Szenarien wurde darüber hinaus das mechanische Model zusammen mit Variationen von Belastungsdauer, Montagesystem und Verkapselungsmaterialien entwickelt. Um die Temperatur- und Mechanik-Modelle zu validieren, wurden die verschiedenen Prüfeinrichtungen zusammen mit neuen Testmethoden entwickelt. Bei Verwendung der Prüfanlage „PV variable mounting system“ und „mechanical testing equipment“ werden zudem die verschiedenen Szenarien von Montagesystemen, Modul-Konfigurationen und mechanischen Belastungen emuliert. Mit der neuen Testmethode „back-bias current concept“ können zum einen die solare Einstrahlung und bestimmte Betriebstemperaturen eingestellt werden. Darüber hinaus wurden mit den eingangs erwähnten validierten Modellen das jeweilige elektrische, thermische und mechanische Verhalten auf andere Konfigurationen bewertet. Zum Abschluss wird die Anwendung von Software-Tools bei PV-Herstellern im Hinblick auf die entsprechenden Modellentwicklungen thematisiert.