Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / No presente trabalho as projeÃÃes de vazÃes para a bacia do Ãros (CearÃ) foram obtidas usando as precipitaÃÃes dos modelos globais do quarto relatÃrio do Intergovernmental Panel on Climate Change (IPCC-AR4) para o perÃodo de 2010 a 2099 do cenÃrio A1B. As vazÃes foram geradas pelo modelo hidrolÃgico Soil Moisture Account Procedure (SMAP). Para a obtenÃÃo destas, as precipitaÃÃes foram corrigidas estatisticamente a partir dos dados observados, considerando as sÃries distribuiÃÃes do tipo gama. Quanto à evaporaÃÃo de entrada do modelo chuva-vazÃo foram feitas duas consideraÃÃes, a primeira consideraÃÃo utiliza vazÃes obtidas pelo modelo hidrolÃgico SMAP inicializado com evaporaÃÃo fornecidas pelo INMET e a segunda considera que a inicializaÃÃo foi feita por evaporaÃÃes estimadas pelo mÃtodo de Penann Mothieth. Para a anÃlise das variaÃÃes interanuais foram observadas as caracterÃsticas de tendÃncias das sÃries (usando mÃtodo clÃssico de Mann-Kendall-Sen) nos padrÃes de variaÃÃo (anÃlise da mÃdia e do coeficiente de variaÃÃo da sÃrie) e a anÃlise de extremos (comparaÃÃo das curvas de distribuiÃÃo acumulada do sÃculo XX e XXI). Para anÃlise sazonal considerou-se a anomalia na climatologia mÃdia dos modelos do sÃculo XXI em relaÃÃo ao sÃculo XX. Para a anÃlise interanual foi observado que a inicializaÃÃo do modelo hidrolÃgico SMAP com evaporaÃÃes estimadas pelo mÃtodo de Penann Motheith modificado pode surgir como implementaÃÃo para o teste de hipÃtese de Mann Kendall Sen. O calculo do coeficiente de variaÃÃo demonstrou que apesar da pouca divergÃncia quanto a ocorrÃncia de variabilidade, tratando-se de sÃries de vazÃes obtidas pelo SMAP inicializado com evaporaÃÃes estimadas, as rodadas dos modelos MIROC3_2_MEDRES relatou aumentos de variabilidade para o sÃculo XXI em relaÃÃo ao sÃculo XX. Quando a inicializaÃÃo no SMAP ocorre por meio de evaporaÃÃes fornecidas pelo INMET ocorre uma grande diversificaÃÃo nos valores de variabilidade. Ainda na anÃlise interanual, a curva de funÃÃo de distribuiÃÃo acumulada (CDF) demonstrou que dos 8 modelos analisados (modelos inicializados com evaporaÃÃes estimadas pelo mÃtodo de Penann-Motheith modificado) 3 apresentam maior freqÃÃncia de eventos secos, 3 apresentam uma freqÃÃncia de eventos mais Ãmidos e 2 modelos nÃo apresentando anÃlises significativas aproximando-se da curva gerada pela sÃrie de vazÃo observada. Quanto à anÃlise sazonal das vazÃes à observado que quando se utiliza o mÃtodo de Penann Motheith modificado para evaporaÃÃo (na inicializaÃÃo do SMAP) os valores de vazÃes tornam-se menores do que os valores obtidos por sÃries geradas pelo modelo hidrolÃgico inicializado com evaporaÃÃes fornecidas pelo INMET, relacionando o sÃculo XXI com o sÃculo XX. / In the present work flow projections for the basin Ãros (CearÃ) were obtained using the precipitation of global models of the fourth report of the Intergovernmental Panel on Climate Change (IPCC-AR4) for the period 2010 to 2099 the A1B scenario. The flows were generated by the hydrologic model Soil Moisture Account Procedure (SMAP). To obtain these, the precipitations were statistically corrected from the observed data, considering the distributions of the type series range. The evaporation model input rainfall-runoff were two considerations, the first consideration obtained by using flow hydrologic model initialized with SMAP evaporation provided by INMET and considers that the second boot occur by evaporation estimated by the method of Penann Mothieth. For the analysis of interannual variations were observed the characteristics of trends of the series (using the classical method of Mann-Kendall-Sen), the changing patterns of variation (analysis of the mean and coefficient of variation of the series) and the analysis of extremes (compared cumulative distribution curves of the twentieth century and XXI). For seasonal analysis considered the climate anomaly in the middle of the XXI century models over the twentieth century. For analysis it was observed that interannual hydrologic model initialization SMAP with evaporation estimated by the modified Penann Motheith can arise as an implementation for the hypothesis test of Mann Kendall Sen. The calculation of the coefficient of variation showed that despite the short confrontation over the occurrence of variability, in the case of streamflow series obtained by SMAP initialized with estimated evaporation, the rounds of the models MIROC3_2_MEDRES reported increases in variability for the XXI century in relation to the twentieth century. When booting into SMAP occurs through evaporation provided by INMET is a great diversification in the values of variability. Although the interannual analysis, the curve of cumulative distribution function (CDF) showed that eight of the analyzed models (models initialized with evaporation estimated by the method of Penann Motheith-modified) 3 have a higher frequency of dry events, have a third event frequency wet and two models showing no meaningful analyzes approaching the curve generated by the series of observed flows. As for seasonal analysis of the flow is observed that when using the method of Penann Motheith modified to evaporation (initialization SMAP) values of flow rates become smaller than the values obtained by series generated by the hydrologic model initialized with evaporation provided by INMET , relating the new century, the twentieth century.

Das Projekt KliWES untersucht die Auswirkungen der prognostizierten Klimaänderungen auf den Wasser- und Stoffhaushalt in den Einzugsgebieten sächsischer Gewässer. Teil 1 beinhaltet die Erstellung flächendeckender und homogener Datengrundlagen und die Berechnung des Ist-Zustands des Wasserhaushalts mit dem Differenzenganglinienanalyseverfahren DIFGA. Ein umfangreicher Test der Wasserhaushaltsmodelle AKWA-M®, ArcEGMO, MIKE SHE und WaSiM-ETH bestätigte die prinzipielle Eignung aller vier Modelle für die sachsenweite Anwendung. Die vier Modelle wurden anhand definierter, unterschiedlich gewichteter Testkriterien verglichen und bewertet. Im Ergebnis wurde aufgrund geringfügiger Vorteile dem Modell ArcEGMO der Vorrang gegeben. Um die in KliWES berechneten Wasserhaushaltsdaten einem breiten Nutzerkreis zur Verfügung zu stellen, wurde eine benutzerfreundliche, interaktive Web-Anwendung mit GIS-Anbindung vorbereitet. Die Projektergebnisse sollen künftig in der zentralen Datenbank »Wasserhaushalt und Klimawandel in Sachsen« verwaltet und im Internet unter »Wasserhaushaltsportal Sachsen« abgerufen werden können.

Nebel, Tau, Reif, Raureif und Raufrost können mit den üblichen Verfahren der Niederschlagsmessung nicht erfasst werden. Dies ist besonders in der Erzgebirgsregion problematisch. Es wurde daher eine Niederschlagskorrektur für Sachsen erarbeitet. Mit dieser Methode kann der abgesetzte bzw. abgefangene Niederschlag quantifiziert und ein bilanzreiner Wasserhaushalt berechnet werden. Die nebelkorrigierten Daten stehen im Wasserhaushaltsportal Sachsen zur Verfügung. Die Untersuchung erfolgte im Rahmen des Projektes KliWES – Klimawandel und Wasserhaushalt.

Vietnam is considered as one of the countries having rich resources from forest and sea, with a high average annual rainfall. However, in view of IWRA, water volume per capita annually in Vietnam is lower than the standard for nations having water resources at average level. Vietnam was recognized by the World Wildlife Fund (WWF) as having three out of more than 200 biological zones of the world. Flora and fauna in Vietnam are very rich and abundant, but due to indiscriminate exploitation, along with weak management, biodiversity levels are significantly reduced. This is also one of the causes of environmental pollution and degradation in Vietnam, besides the impacts from production activities, population migration from rural areas to urban areas, rapid urbanization, climate change and sea level rise, etc. / Tảo đóng vai trò quan trọng trong mạng lưới thức ăn và chu trình sinh địa hóa của thủy vực và chúng chịu sự chi phối của nhiều yếu tố môi trường như ánh sáng, pH, nhiệt độ và dinh dưỡng. Nghiên cứu này trình bày đa dạng thành phần loài và biến động sinh khối thực vật phù du tại hồchứa Hòa Bình từ tháng 3 đến tháng 12 năm 2011. Các mẫu thực vật nổi được thu thập hàng tháng tại 4 điểm. Kết quả đã xác định được 6 lớp tảo chính bao gồm: Vi khuẩn lam, tảo lục, tảo silic, tảo mắt, tảo giáp và tảo lông roi hai rãnh. Nhóm tảo silic và Vi khuẩn lam chiếm ưu thế với độ phong phú tương đối là 61% và 32% tương ứng trong quần xã thực vật nổi. Vi khuẩn lam dạng tập đoàn và dạng sợi (Microcystis aeruginosa, M. wesenberg, Oscillatoria sp. tương ứng) chiếm ưu thế trong quần xã thực vật nổi vào các thời điểm đầu hè và mùa thu (tháng 4 và tháng 9). Tổng mật độ tế bào thực vật nổi dao động từ 84210 đến 100 x106 cell/L. Mật độ thực vật nổi biển động theo mùa với sinh khối tê bào cao vào đầu hè và mùa đông (tháng 4 và tháng 12) và sinh khối tếbào thấp vào các mùa hè và thu (tháng 6 đến tháng 10).

Climate change could aggravate periodic and chronic shortfalls of water, particularly in arid and semi-arid areas of the world (IPCC, 2001). Climate change is likely to accelerate the global hydrological cycle, with increase in temperature, changes in precipitation patterns, and evapotranspiration affecting the water quantity and quality, water availability and demands. The various components of a surface water resources system affected by climate change may include the water availability, irrigation demands, water quality, hydropower generation, ground water recharge, soil moisture etc. It is prudent to examine the anticipated impacts of climate change on these different components individually or combinedly with a view to developing responses to minimize the climate change induced risk in water resources systems. Assessment of climate change impacts on water resources essentially involves downscaling the projections of climatic variables (e.g., temperature, humidity, mean sea level pressure etc.) to hydrologic variables (e.g., precipitation and streamflow), at regional scale. Statistical downscaling methods are generally used in the hydrological impact assessment studies for downscaling climate projections provided by the General Circulation Models (GCMs). GCMs are climate models designed to simulate time series of climate variables globally, accounting for the greenhouse gases in the atmosphere. The statistical techniques used to bridge the spatial and temporal resolution gaps between what GCMs are currently able to provide and what impact assessment studies require are called as statistical downscaling methods. Generally, these methods involve deriving empirical relationships that transform large-scale simulations of climate variables (referred as the predictors) provided by a GCM to regional scale hydrologic variables (referred as the predictands). This general methodology is characterized by various uncertainties such as GCM and scenario uncertainty, uncertainty due to initial conditions of the GCMs, uncertainty due to downscaling methods, uncertainty due to hydrological model used for impact assessment and uncertainty resulting from multiple stake holders in a water resources system. The research reported in this thesis contributes towards (i) development of methodologies for climate change impact assessment of various components of a water resources system, such as water quality, water availability, irrigation and reservoir operation, and (ii) quantification of GCM and scenario uncertainties in hydrologic impacts of climate change. Further, an integrated reservoir operation model is developed to derive optimal operating policies under the projected scenarios of water availability, irrigation water demands, and water quality due to climate change accounting for various sources of uncertainties. Hydropower generation is also one of the objectives in the reservoir operation. The possible climate change impact on river water quality is initially analyzed with respect to hypothetical scenarios of temperature and streamflow, which are affected by changes in precipitation and air temperature respectively. These possible hypothetical scenarios are constructed for the streamflow and river water temperature based on recent changes in the observed data. The water quality response is simulated, both for the present conditions and for conditions resulting from the hypothetical scenarios, using the water quality simulation model, QUAL2K. A Fuzzy Waste Load Allocation Model (FWLAM) is used as a river water quality management model to derive optimal treatment levels for the dischargers in response to the hypothetical scenarios of streamflow and water temperature. The scenarios considered for possible changes in air temperature (+1 oC and +2 oC) and streamflow (-0%, -10%, -20%) resulted in a substantial decrease in the Dissolved Oxygen (DO) levels, increase in Biochemical Oxygen Demand (BOD) and river water temperature for the case study of the Tunga-Bhadra River, India. The river water quality indicators are analyzed for the hypothetical scenarios when the BOD of the effluent discharges is at safe permissible level set by Pollution Control Boards (PCBs). A significant impairment in the water quality is observed for the case study, under the hypothetical scenarios considered. A multi-variable statistical downscaling model based on Canonical Correlation Analysis (CCA) is then developed to downscale future projections of hydro¬meteorological variables to be used in the impact assessment study of river water quality. The CCA downscaling model is used to relate the surface-based observations and atmospheric variables to obtain the simultaneous projection of hydrometeorological variables. Statistical relationships in terms of canonical regression equations are obtained for each of the hydro-meteorological predictands using the reanalysis data and surface observations. The reanalysis data provided by National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) are used for the purpose. The regression equations are applied to the simulated GCM output to model future projections of hydro-meteorological predictands. An advantage of the CCA methodology in the context of downscaling is that the relationships between climate variables and the surface hydrologic variables are simultaneously expressed, by retaining the explained variance between the two sets. The CCA method is used to model the monthly hydro-meteorological variables in the Tunga-Bhadra river basin for water quality impact assessment study. A modeling framework of risk assessment is developed to integrate the hydro¬meteorological projections downscaled from CCA model with a river water quality management model to quantify the future expected risk of low water quality under climate change. A Multiple Logistic Regression (MLR) is used to quantify the risk of Low Water Quality (LWQ) corresponding to a threshold DO level, by considering the streamflow and water temperature as explanatory variables. An Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is adopted to evaluate the future fractional removal policies for each of the dischargers by including the predicted future risk levels. The hydro-meteorological projections of streamflow, air temperature, relative humidity and wind speed are modeled using MIROC 3.2 GCM simulations with A1B scenario. The river water temperature is modeled by using an analytical temperature model that includes the downscaled hydro-meteorological variables. The river water temperature is projected to increase under climate change, for the scenario considered. The IFWLAM uses the downscaled projections of streamflow, simulated river water temperature and the predicted lower and upper future risk levels to determine the fraction removal policies for each of the dischargers. The results indicate that the optimal fractional removal levels required for the future scenarios will be higher compared to the present levels, even if the effluent loadings remain unchanged. Climate change is likely to impact the agricultural sector directly with changes in rainfall and evapotranspiration. The regional climate change impacts on irrigation water demands are studied by quantifying the crop water demands for the possible changes of rainfall and evapotranspiration. The future projections of various meteorological variables affecting the irrigation demand are downscaled using CCA downscaling model with MIROC 3.2 GCM output for the A1B scenario. The future evapotranspiration is obtained using the Penman-Monteith evapotranspiration model accounting for the projected changes in temperature, relative humidity, solar radiation and wind speed. The monthly irrigation water demands of paddy, sugarcane, permanent garden and semidry crops quantified at nine downscaling locations covering the entire command area of the Bhadra river basin, used as a case study, are projected to increase for the future scenarios of 2020-2044, 2045-2069 and 2070-2095 under the climate change scenario considered. The GCM and scenario uncertainty is modeled combinedly by deriving a multimodel weighted mean by assigning weights to each GCM and scenario. An entropy objective weighting scheme is proposed which exploits the information contained in various GCMs and scenarios in simulating the current and future climatology. Three GCMs, viz., CGCM2 (Meteorological Research Institute, Japan), MIROC3.2 medium resolution (Center for Climate System Research, Japan), and GISS model E20/Russell (NASA Goddard Institute for Space Studies, USA) with three scenarios A1B, A2 and B1 are used for obtaining the hydro-meteorological projections for the Bhadra river basin. Entropy weights are assigned to each GCM and scenario based on the performance of the GCM and scenario in reproducing the present climatology and deviation of each from the projected ensemble average. The proposed entropy weighting method is applied to projections of the hydro-meteorological variables obtained based on CCA downscaling method from outputs of the three GCMs and the three scenarios. The multimodel weighted mean projections are obtained for the future time slice of 2020-2060. Such weighted mean hydro-meteorological projections may be further used into the impact assessment model to address the climate model uncertainty in the water resources systems. An integrated reservoir operation model is developed considering the objectives of irrigation, hydropower and downstream water quality under uncertainty due to climate change, uncertainty introduced by fuzziness in the goals of stakeholders and uncertainty due to the random nature of streamflow. The climate model uncertainty originating from the mismatch between projections from various GCMs under different scenarios is considered as first level of uncertainty, which is modeled by using the weighted mean hydro-meteorological projections. The second level of uncertainty considered is due to the imprecision and conflicting goals of the reservoir users, which is modeled by using fuzzy set theory. A Water Quantity Control Model (WQCM) is developed with fuzzy goals of the reservoir users to obtain water allocations among the different users of the reservoir corresponding to the projected demands. The water allocation model is updated to account for the projected demands in terms of revised fuzzy membership functions under climate change to develop optimal policies of the reservoir for future scenarios. The third level of uncertainty arises from the inherent variability of the reservoir inflow leading to uncertainty due to randomness, which is modeled by considering the reservoir inflow as a stochastic variable. The optimal monthly operating polices are derived using Stochastic Dynamic Programming (SDP), separately for the current and for the future periods of 2020-2040 and 2040-2060 The performance measures for Bhadra reservoir in terms of reliability and deficit ratios for each reservoir user (irrigation, hydropower and downstream water quality) are estimated with optimal SDP policy derived for current and future periods. The reliability with respect to irrigation, downstream water quality and hydropower show a decrease for 2020-2040 and 2040-2060, while deficit ratio increases for these periods. The results reveal that climate change is likely to affect the reservoir performance significantly and changes in the reservoir operation for the future scenarios is unable to restore the past performance levels. Hence, development of adaptive responses to mitigate the effects of climate change is vital to improve the overall reservoir performance.