The Upper Niger Basins (UNB) and the Inner Niger Delta (IND) are integral parts of the Niger River Basin, which flows through 10 countries and constitutes the third longest river in Africa. Natural climate variability and human interventions are two major factors affecting the hydrological regime in the UNB and IND. This study focuses on the later factor, by assessing the hydrological impacts of key existing and planned manmade structures and irrigation schemes in the UNB: the Sélingué (existing dam in Mali), four variants of the Fomi/Moussako dam (planned in Guinea), and Office du Niger (irrigation scheme located in Mali). The Fomi /Moussako dam will be located in the headwaters of the UNB and therefore, is expected to alter the hydrological regime in large parts of the watershed. Expected impacts include a reduction of the flood peak which will adversely affect critical ecosystems in the IND, and higher flows directly downstream of the dams in the dry season to sustain irrigation. These higher flows will, however, be consumed by Office du Niger irrigation scheme, leading to possible severe water shortages downstream of the irrigation scheme and in the IND. This is likely to affect the Malian economy and the poorest parts of its population, as the IND is crucial for the socio-economic and ecological preservation and development of the population surrounding it. The hydrological impacts of the dams and the irrigation scheme were evaluated in this study by developing a model of the IND and UNB using SWAT (Soil and Water Assessment Tool). After the model was calibrated, the effects of the dams and the irrigation scheme on selected flow statistics (mean and standard deviation) were determined at fourteen hydrological stations. In general, the results have shown that (1) the Fomi/Moussako dam will noticeably reduce the downstream high flows, and reduce the average flow; (2) if the Fomi/Moussako dam was to be built, the alternatives with the least storage volume (Moussako 388.5') will have the least impacts on the downstream flows. To assist in related decision making for various users, a Decision Support System (DSS) was also developed. The goal of the DSS is to help users analyze the effects of dams and irrigation on the flow regime by performing a comparative analysis (presence and absence of dams and irrigation in the river). A number of potential adaptation measures were also proposed.

Modificações da cobertura natural dos solos podem ocasionar alterações no ciclo hidrológico, que por sua vez podem impactar a disponibilidade de água. Na Bacia Hidrográfica do Rio Paraíba do Sul (BHPS) vem ocorrendo uma substituição de coberturas vegetais em função da expansão de monoculturas de eucalipto. O objetivo desta pesquisa foi verificar os impactos de ordem hidrológica sobre a disponibilidade hídrica (quali e quantitativa) no trecho paulista da BHPS, em decorrência da implantação da atividade de silvicultura de eucalipto para produção de celulose. Para isso, foi utilizado o método de Pegada Hídrica (PH) para avaliar a alocação de água da produção de madeira de floresta nativa e de eucalipto, método que vem sendo aplicado pelo setor silvícola. Foram empregados também métodos de Balanço Hídrico Climatológico, Balanço Hídrico Geral e a abordagem de Serviços Ecossistêmicos para avaliar a relação entre a água e as principais coberturas vegetais da bacia (pastagem, floresta nativa e eucalipto), de forma a permitir uma análise ampliada e integrada do comportamento hidrológico da bacia. Ao analisar os métodos empregados, observou-se que a PH de produtos avalia apenas a eficiência do uso da água, o que pode mascarar altos consumos de água em função de maior produtividade por hectare. Isto porque se obteve menor valor de PH da madeira, em m³ por tonelada para o caso do eucalipto, e maior alocação total de água, em m³ por hectare por ano, em comparação à floresta nativa. Os resultados obtidos pela análise de Balanço Hídrico Climatológico para as principais coberturas vegetais mostraram que o eucalipto apresentou maior evapotranspiração e menor excedente hídrico. Já o Balanço Hídrico Geral, analisado mensalmente, permitiu visualizar que as coberturas vegetais influenciam o serviço de provisão de água e concorrem pelo uso de água com os demais usuários da bacia (naturais e antrópicos) em períodos de menor precipitação. Por fim, concluiu-se que são necessárias medições locais para determinação de volumes de escoamento (superficial e subterrâneo), infiltração, bem como do processo de lixiviação e perdas de solo para apontar de forma mais precisa os impactos hídricos da monocultura de eucalipto. / Modifications in the natural land cover can change the hydrological cycle, which might have an impact on water availability. In the river basin of the Paraíba do Sul river (RBPS), the natural vegetation has been being replaced due to the expansion of eucalyptus monocultures. This research assessed the impacts on water availability (both qualitative and quantitative), caused by eucalyptus forestry for pulp production in the RBPS part in Sao Paulo. The water footprint (WF) method was applied to assess the water used on the cellulose production of native forest and eucalyptus, given the use of this method by the industry. Also, the Climatic Water Balance, General Water Balance methods and the Ecosystem Services approach were used in order to perform an extended and integrated analysis of the hydrological behavior of the basin. By analyzing these methods, it was found that the products WF only assesses the efficiency in water use, which can mask high water consumption with higher productivity per hectare. This because a smaller value for wood WF was observed, in m³/ton for eucalyptus, and higher total water use, in m³ per hectare per year, compared to the native forest. The results observed by the Climatic Water Balance analysis for the main vegetation cover showed that the eucalyptus presented higher evapotranspiration and smaller water surplus. The General Water Balance, analyzed on a monthly basis, showed that the vegetation has an impact on the water provision service and competes for water with other users in the basin (natural and anthropic) in periods with less precipitation. Finally, it was concluded that local measurements are required to determine the runnof volumes (superficial and subsurface), infiltration, as well as the process of leaching and soil loss in order to have a more accurate assessment of the hydrological impacts of the eucalyptus monoculture.

The ability to anticipate and evaluate the combined impacts of urbanization and climate change on streamflow regimes is critical to developing proactive strategies that protect aquatic ecosystems. I developed an interdisciplinary modeling framework to compare and contrast the effectiveness of integrated stormwater management, or its absence, with two regional growth patterns for maintaining streamflow regimes in the context of climate change. In three adjacent urbanizing watersheds in Oregon's Willamette Valley, I conducted a three-step sequence to: 1) simulate land use change under four future development scenarios with the agent-based model Envision; 2) model resultant hydrological change under the recent past and two future climate regimes using the Soil and Water Assessment Tool; and 3) assess scenario impacts on streamflow regimes using 10 ecologically significant flow metrics. I evaluated each scenario in each basin using a flow metric typology based on the magnitude of change in each metric and the degree to which such changes could be mitigated, i.e., insensitive, sensitive and manageable, and sensitive and resistant. My results demonstrated distinct signatures of urbanization and climate change on flow regimes. Urbanization and climate change in isolation led to significant flow alterations in all three basins. Urbanization consistently led to increases in flow regime flashiness and severity of extreme flow events, whereas climate change primarily caused a drying trend. Climate change tended to exacerbate the impacts of urbanization but also mitigated urban impacts on several metrics. The combined impacts of urbanization and climate change caused substantial changes to metric sensitivities, which further differed by basin and climate regime, highlighting the uncertainties of streamflow regime responses to development and the value of spatially explicit modeling that can reveal complex interactions between natural and human systems. Scenario comparisons demonstrated the importance of integrated stormwater management and, secondarily, compact regional growth. My findings reveal the need for regional flow-ecology research that substantiates the ecological significance of each flow metric, develops specific targets for manageable ones, and explores potential remedies for resistant ones. The interdisciplinary modeling framework shows promise as a transferable tool for local watershed management. This dissertation includes previously unpublished co-authored material.

Modificações da cobertura natural dos solos podem ocasionar alterações no ciclo hidrológico, que por sua vez podem impactar a disponibilidade de água. Na Bacia Hidrográfica do Rio Paraíba do Sul (BHPS) vem ocorrendo uma substituição de coberturas vegetais em função da expansão de monoculturas de eucalipto. O objetivo desta pesquisa foi verificar os impactos de ordem hidrológica sobre a disponibilidade hídrica (quali e quantitativa) no trecho paulista da BHPS, em decorrência da implantação da atividade de silvicultura de eucalipto para produção de celulose. Para isso, foi utilizado o método de Pegada Hídrica (PH) para avaliar a alocação de água da produção de madeira de floresta nativa e de eucalipto, método que vem sendo aplicado pelo setor silvícola. Foram empregados também métodos de Balanço Hídrico Climatológico, Balanço Hídrico Geral e a abordagem de Serviços Ecossistêmicos para avaliar a relação entre a água e as principais coberturas vegetais da bacia (pastagem, floresta nativa e eucalipto), de forma a permitir uma análise ampliada e integrada do comportamento hidrológico da bacia. Ao analisar os métodos empregados, observou-se que a PH de produtos avalia apenas a eficiência do uso da água, o que pode mascarar altos consumos de água em função de maior produtividade por hectare. Isto porque se obteve menor valor de PH da madeira, em m³ por tonelada para o caso do eucalipto, e maior alocação total de água, em m³ por hectare por ano, em comparação à floresta nativa. Os resultados obtidos pela análise de Balanço Hídrico Climatológico para as principais coberturas vegetais mostraram que o eucalipto apresentou maior evapotranspiração e menor excedente hídrico. Já o Balanço Hídrico Geral, analisado mensalmente, permitiu visualizar que as coberturas vegetais influenciam o serviço de provisão de água e concorrem pelo uso de água com os demais usuários da bacia (naturais e antrópicos) em períodos de menor precipitação. Por fim, concluiu-se que são necessárias medições locais para determinação de volumes de escoamento (superficial e subterrâneo), infiltração, bem como do processo de lixiviação e perdas de solo para apontar de forma mais precisa os impactos hídricos da monocultura de eucalipto. / Modifications in the natural land cover can change the hydrological cycle, which might have an impact on water availability. In the river basin of the Paraíba do Sul river (RBPS), the natural vegetation has been being replaced due to the expansion of eucalyptus monocultures. This research assessed the impacts on water availability (both qualitative and quantitative), caused by eucalyptus forestry for pulp production in the RBPS part in Sao Paulo. The water footprint (WF) method was applied to assess the water used on the cellulose production of native forest and eucalyptus, given the use of this method by the industry. Also, the Climatic Water Balance, General Water Balance methods and the Ecosystem Services approach were used in order to perform an extended and integrated analysis of the hydrological behavior of the basin. By analyzing these methods, it was found that the products WF only assesses the efficiency in water use, which can mask high water consumption with higher productivity per hectare. This because a smaller value for wood WF was observed, in m³/ton for eucalyptus, and higher total water use, in m³ per hectare per year, compared to the native forest. The results observed by the Climatic Water Balance analysis for the main vegetation cover showed that the eucalyptus presented higher evapotranspiration and smaller water surplus. The General Water Balance, analyzed on a monthly basis, showed that the vegetation has an impact on the water provision service and competes for water with other users in the basin (natural and anthropic) in periods with less precipitation. Finally, it was concluded that local measurements are required to determine the runnof volumes (superficial and subsurface), infiltration, as well as the process of leaching and soil loss in order to have a more accurate assessment of the hydrological impacts of the eucalyptus monoculture.

General Circulation Models (GCMs), which are mathematical models based on principles of fluid dynamics, thermodynamics and radiative transfer, are the most reliable tools available for projecting climate change. However, the spatial scale on which typical GCMs operate is very coarse as compared to that of a hydrologic process and hence, the output from a GCM cannot be directly used in hydrologic models. Statistical Downscaling (SD) derives a statistical or empirical relationship between the variables simulated by the GCM (predictors) and a point-scale meteorological series (predictand). In this work, a new downscaling model called CRF-downscaling model, is developed where the conditional distribution of the hydrologic predictand sequence, given atmospheric predictor variables, is represented as a conditional random field (CRF) to downscale the predictand in a probabilistic framework. Features defined in the downscaling model capture information about various factors influencing precipitation such as circulation patterns, temperature and pressure gradients and specific humidity levels. Uncertainty in prediction is addressed by projecting future cumulative distribution functions (CDFs) for a number of most likely precipitation sequences. Direct classification of dry/wet days as well as precipitation amount is achieved within a single modeling framework, and changes in the non-parametric distribution of precipitation and dry and wet spell lengths are projected. Application of the method is demonstrated with the case study of downscaling to daily precipitation in the Mahanadi basin in Orissa, with the A1B scenario of the MIROC3.2 GCM from the Center for Climate System Research (CCSR), Japan. An uncertainty modeling framework is presented in this work, which combines GCM, scenario and downscaling uncertainty using the Dempster-Shafer (D-S) evidence theory for representing and combining uncertainty. The methodology for combining uncertainties is applied to projections of hydrologic drought in terms of monsoon standardized streamflow index (SSFI-4) from streamflow projections for the Mahanadi river at Hirakud. The results from the work indicate an increasing probability of extreme, severe and moderate drought and decreasing probability of normal to wet conditions, as a result of a decrease in monsoon streamflow in the Mahanadi river due to climate change. In most studies to date, the nature of the downscaling relationship is assumed stationary, or remaining unchanged in a future climate. In this work, an uncertainty modeling framework is presented in which, in addition to GCM and scenario uncertainty, uncertainty in the downscaling relationship itself is explored by linking downscaling with changes in frequencies of modes of natural variability. Downscaling relationships are derived for each natural variability cluster and used for projections of hydrologic drought. Each projection is weighted with the future projected frequency of occurrence of that cluster, called ‘cluster-linking’, and scaled by the GCM performance with respect to the associated cluster for the present period, called ‘frequency scaling’. The uncertainty modeling framework is applied to a case study of projections of hydrologic drought or SSFI-4 classifications, using projected streamflows for the Mahanadi river at Hirakud. It is shown that a stationary downscaling relationship will either over- or under-predict downscaled hydrologic variable values and associated uncertainty. Results from the work show improved agreement between GCM predictions at the regional scale, which are validated for the 20th century, implying that frequency scaling and cluster-linking may indeed be a valid method for constraining uncertainty. To assess the impact of climate change on reservoir performance, in this study, a range of integrated hydrologic scenarios are projected for the future. The hydrologic scenarios incorporate increased irrigation demands; rule curves dictated by increased need for flood storage and downscaled projections of streamflow from an ensemble of GCMs and emission scenarios. The impact of climate change on multipurpose reservoir performance is quantified, using annual hydropower and RRV criteria, under GCM and scenario uncertainty. The ‘business-as-usual’ case using Standard Operating Policy (SOP) is studied initially for quantifying impacts. Adaptive Stochastic Dynamic Programming (SDP) policies are subsequently derived for the range of future hydrologic scenarios, with the objective of maximizing reliabilities with respect to multiple reservoir purposes of hydropower, irrigation and flood control. It is shown that the hydrologic impact of climate change is likely to result in decreases in performance criteria and annual hydropower generation for Hirakud reservoir. Adaptive policies show that a marginal reduction in irrigation and flood control reliability can achieve increased hydropower reliability in future. Hence, reservoir rules for flood control may have to be revised in the future.

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.