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Numerical ice sheet modeling is a rather young discipline: it started in the 1950s. The "first generation" models developed at that time are currently being replaced by "new generations" ones, such as e.g. ARCTIC-TARAH. ARCTIC-TARAH is a Bert Bolin Center for Climate Research spin-off from the Pennsylvania State University Ice sheet model (PSUI). When the Bolin Center received PSUI for subsequent independent development and adaption of the code to Arctic settings in 2010, an initial inspection of the source code suggested that PSUI also contained a module that allows for the treatment of glacial hydraulics. A numerical ice sheet model including coupling of ice dynamics and hydraulics is an extremely important tool in testing new hypotheses of former geological events. E.g., based on the recent finding that Arctic Ocean sediments contain a very distinct signature, it has been suggested that ice dammed lakes at the south-eastern margin of the late Weichselian Eurasian ice sheet drained into the Arctic Ocean in a catastrophic event around 55.000 years ago. The aim of this thesis is to perform a reconnaissance analysis of the glacio-hydraulic algorithms in ARCTIC-TARAH, as "inherited" (but never with published record of functionality) from PSUI. The work is carried out in two steps: first the routines and algorithms describing the hydraulics are located and explored, and then these routines are tested and verified by performing experiment simulations. The investigation of the program code reveals the presence of two hydraulics related modules in ARCTIC-TARAH. The main tasks of the module Water are to initiate lakes and oceans and to adjust hydrostatic pressure in each lake. Further, with the module Move Water activated, transportation of water (e.g. in rivers) is possible. Results from idealized experiment simulations verify the functionality of the routines in the module Water. An in-depth analysis of the module Move Water suggests that there is a mismatch in time units when solving the equations describing flow of water. Experiment simulations also support this flaw detected in the flow model. Preliminary adjustments were made to the source code  of the module Move Water, which made it possible to simulate the transportation of water both under an ice sheet and in rivers on land. However, these adjustments do not solve the problem of mismatching time scales, and the numerical solutions obtained from the experiments were observed to be unstable and, therefore, possibly incorrect. To be able to perform more advanced simulations in support of the above mentioned hypothesis, the flow model in the module Move Water needs to be improved or replaced. One solution to the problem with mismatching time scales, could be to use a so called multiscale solution in time.

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FundaÃÃo Cearense de Apoio ao Desenvolvimento Cientifico e TecnolÃgico / Apresenta-se uma abordagem para o problema de otimizaÃÃo de projetos de redes de distribuiÃÃo de Ãgua (RDA), considerando-se o custo de implantaÃÃo (CI) e o custo de manutenÃÃo (CM) simultaneamente, aplicando-se um algoritmo multi-populaÃÃo e multiobjetivo. Uma RDA pode ser vista como um grafo cujas arestas sÃo os condutos e o vÃrtices sÃo os nÃs. Escolher os diÃmetros que tornam a rede mais econÃmica atendendo a restriÃÃes tÃcnicas à um problema combinatÃrio para o qual mÃtodos diretos podem se tornar inviÃveis ao se considerar nÃmeros crescentes de trechos. O problema de otimizaÃÃo abordado consiste em minimizar simultaneamente CI e CM de uma RDA, considerando para isso o custo dos condutos de acordo com seus diÃmetros e comprimentos. Para proceder a otimizaÃÃo foi desenvolvido o algoritmo evolucionÃrio (AE) hÃbrido Multi-Island Niched-Pareto Genetic Algorithm (MINPGA), resultado da junÃÃo adaptada de um algoritmo multi-populaÃÃo, o MIIGA, a outro algoritmo multi-objetivo baseado em Nicho de Pareto, o NPGA. Como simulador hidrÃulico foi utilizado o Environment Protection Agency Network Engine Tool (EPANET). O esquema Optimization of NEtwork By Evolutionary AlgoRithm (ONEBEAR) foi desenvolvido e aplicado a trÃs redes de tamanhos e traÃados distintos, sendo uma delas com 666 trechos. Um programa computacional foi escrito para implementar o ONEBEAR, conectando o EPANET ao MINPGA, possibilitando assim otimizaÃÃo pretendida. Mostrou-se, alÃm da importÃncia de se considerar o custo de manutenÃÃo ao longo da vida Ãtil de uma RDA, a viabilidade de abordar o problema de otimizaÃÃo multi-objetivo por meio de um AE multi-populaÃÃo. O esquema mostrou robustez e flexibilidade, resolvendo o problema de otimizaÃÃo tanto para redes ramificadas quanto para redes malhadas e com uma rede com 666 trechos. A frente de Pareto gerada para cada problema mostrou as soluÃÃes dominantes consideradas viÃveis. A viabilidade das redes foi verificada quanto ao atendimento ao requesito tÃcnico de pressÃo mÃnima por nÃ, calculada pelo EPANET. As redes de menor CI e / We present an approach for project optimization problem of networks water supply (RDA), considering the deployment cost (CI) and the cost of maintenance (MC) simultaneously applying a multi-population and multiobjective algorithm. An RDA can be seen as a graph whose edges are the conduits and the vertices are the nodes. Choose the diameters that make the most economical network given the restrictions techniques is a combinatorial problem for which direct methods may become unworkable when considering increasing numbers snippets. The optimization problem is tackled to minimize both CI and CM of an RDA, considering it to the cost of conduits according to their diameters and lengths. To carry out optimization was developed the evolutionary algorithm (EA) Hybrid Multi-Island-niched Pareto Genetic Algorithm (MINPGA), merge output adapted from a multi-population algorithm, MIIGA, another multi-objective algorithm based on Niche Pareto, the NPGA. How hydraulic simulator was used Environment Protection Agency Network Engine Tool (EPANET). The optimization scheme of Network By Evolutionary Algorithm (ONEBEAR) has been developed and applied to three different network sizes and layouts, one of with 666 snippets. A computer program was written to implement the ONEBEAR, connecting the EPANET to MINPGA, allowing desired optimization. It has been shown, and the importance of considering the cost of maintenance over the life of a RDA address the feasibility of multi-objective optimization problem using an AE multi-population. The scheme shown robustness and flexibility, solving the problem of optimization for both branched networks and for looped networks and a network with 666 excerpts. The Pareto front generated for each problem showed the dominant solutions considered viable. The viability of the networks was checked for compliance with technical requisite minimum pressure per node, calculated by EPANET. The smaller networks and CI