Water infrastructures have been implemented to support the vital activities of human society. The infrastructure developments at the same time have interrupted the natural catchment response characteristics, challenging society to implement effective water resources planning and management strategies. The Telemark area in southern Norway has seen a large number of water infrastructure developments, particularly hydropower, over more than a century. Recent developments in decision support tools for flood control and reservoir operation has raised the need to compute inflows from local catchments, most of which are regulated or have no observed data. This has contributed for the motivation of this PhD thesis work, with an aim of improving runoff estimation at ungauged catchments, and the research results are presented in four manuscript scientific papers.  The inverse distance weighting, inverse distance squared weighting, ordinary kriging, universal kriging and kriging with external drift were applied to analyse precipitation variability and estimate daily precipitation in the study area. The geostatistical based univariate and multivariate map-correlation concepts were applied to analyse and physically understand regional hydrological response patterns. The Sobol variance based sensitivity analysis (VBSA) method was used to investigate the HBV hydrological model parameterization significances on the model response variations and evaluate the model’s reliability as a prediction tool. The HBV hydrological model space transferability into ungauged catchments was also studied.  The analyses results showed that the inverse distance weighting variants are the preferred spatial data interpolation methods in areas where relatively dense precipitation station network can be found.  In mountainous areas and in areas where the precipitation station network is relatively sparse, the kriging variants are the preferred methods. The regional hydrological response correlation analyses suggested that geographic proximity alone cannot explain the entire hydrological response correlations in the study area. Besides, when the multivariate map-correlation analysis was applied, two distinct regional hydrological response patterns - the radial and elliptical-types were identified. The presence of these hydrological response patterns influenced the location of the best-correlated reference streamgauges to the ungauged catchments. As a result, the nearest streamgauge was found the best-correlated in areas where the radial-type hydrological response pattern is the dominant. In area where the elliptical-type hydrological response pattern is the dominant, the nearest reference streamgauge was not necessarily the best-correlated. The VBSA verified that varying up to a minimum of four to six influential HBV model parameters can sufficiently simulate the catchments' responses characteristics when emphasis is given to fit the high flows. Varying up to a minimum of six influential model parameters is necessary to sufficiently simulate the catchments’ responses and maintain the model performance when emphasis is given to fit the low flows. However, varying more than nine out of the fifteen HBV model parameters will not make any significant change on the model performance.  The hydrological model space transfer study indicated that estimation of representative runoff at ungauged catchments cannot be guaranteed by transferring model parameter sets from a single donor catchment. On the other hand, applying the ensemble based model space transferring approach and utilizing model parameter sets from multiple donor catchments improved the model performance at the ungauged catchments. The result also suggested that high model performance can be achieved by integrating model parameter sets from two to six donor catchments. Objectively minimizing the HBV model parametric dimensionality and only sampling the sensitive model parameters, maintained the model performance and limited the model prediction uncertainty.

Abstract This thesis describes the development of a new precipitation index-based conceptual water balance model with parameters easily regionalized through the functional relationship with catchment and climate attributes. It also presents a simple method for improving model dynamics for streamflow simulations in a non-stationary climate. The model was developed for streamflow modelling and prediction in high-latitude catchments, where model parameter regionalization is difficult due to limited availability of hydrological data for the region. The model couples a snow accumulation and melt formulation with a current precipitation index (CPI) formulation to simulate daily precipitation in runoff hydrograph pattern from catchments with seasonal snow cover. Using new runoff conversion factors CT and Lf, and a threshold flow factor ThQ, the simulated CPI hydrograph is converted into daily runoff and routed using the transformation function Maxbas. The model was developed in Microsoft Excel workbook and tested in 32 catchments in Finland, a region with considerable seasonal snow cover. The results showed that the model can adequately simulate and reproduce the dynamics of daily runoff from catchments where the underlying physical conditions are not known. In addition, incorporating temperature conditions influencing inter-annual variability in streamflow into the model structure improved its structural dynamics, thereby improving its performance in a non-stationary climate. Most model parameters showed strong relationships with observable catchment characteristics, climate characteristics, or both. The parameter functional relationships derived from the model parameter-catchment relationships produced equally good model results when applied to independent test catchments used as mock-ungauged catchments. Inclusion of snow-water equivalent records and use of multiple objective functions for snow-water equivalent and runoff simulations during model optimization helped reduce the effect of parameter equifinality, making it easier to determine optimal parameter values. The current precipitation index (CPIsnow) model is a parsimonious tool for predicting streamflow in data-limited high-latitude regions. / Tiivistelmä Tämä väitöskirja käsittelee yksinkertaisen sadantaan perustuvan konseptuaalisen vesitasemallin kehitystä ja soveltamista boreaalisille valuma-alueille sekä malliin liittyvää alueellista parametrisointia valuma-alueominaisuuksien ja ilmastoaineiston perusteella. Hydrologinen malli on luotu laskemaan ja ennustamaan valuntaa pohjoisille valuma-alueille, joilta on vähän hydrologista tietoa. Malli yhdistää lumen kertymisen ja sulannan tunnettuun sadantaindeksiin perustuvaan malliin (CPI) ja edelleen simuloi päivittäisen hydrografin valuma-alueille, joilla on selkeä lumipeitteinen ajanjakso. Malli laskee MaxBas funktion avulla CPI:llä muodostetun hydrografin päivittäiseksi valunnaksi valuntaan liittyvien malliparametrien CT ja Lf sekä virtaaman kynnysarvon ThQ avulla. Malli kehitettiin Excel-ympäristössä ja sitä testattiin 32 valuma-alueella Suomessa. Valuma-alueet edustivat maantieteellisesti kattavasti alueita, joilla esiintyy tyypillisesti kausittainen lumipeite. Saadut tulokset osoittivat, että kehitetty malli simuloi ja tuottaa päivittäisen valunnan riittävällä tarkkuudella valuma-alueille, vaikka hydrologista ja fysikaalista tietoa alueilta olisi niukasti. Useimmat malliparametrit olivat vahvasti riippuvaisia joko valuma-alue ominaisuuksista tai ilmastollisista parametreista tai molemmista. Parametrien funktionaalinen yhteys muodostettiin valuma-alueiden ominaisuuksien perusteella ja testattiin riippumattomalla valuma-aluejoukolla hyvin tuloksin. Malliparametrien samatavoitteellisuutta eli ekvifinaliteettiä voitiin vähentää huomioimalla mallissa lumen vesiarvomittaukset sekä hyödyntämällä useita parametrisia funktioita. Tällöin myös optimaalisten parametrien löytyminen nopeutui ja helpottui. Tämän väitöstyön pohjalta syntynyt uusi sadannan indeksiin pohjautuva laskentamalli (CPIsnow) mahdollistaa valunnan arvioinnin pieniltä valuma-alueilta, joilta on niukasti aineistoa saatavilla ja joissa lumen sulanta ja kertyminen ovat keskeisiä hydrologisia prosesseja.

Depuis 2006, à EDF, les études de crues extrêmes sont réalisées avec la méthode SCHADEX (Simulation Climato-Hydrologique pour l'Appréciation des Débits EXtrêmes). Elle s'appuie sur un modèle probabiliste MEWP (distribution saisonnière utilisant une classification par type de temps) pour décrire l'aléa pluie et sur une simulation stochastique croisant l'aléa pluie et l'aléa de saturation du bassin. Les approches par simulation, type SCHADEX, ont montré de bonnes performances pour estimer les distributions de crues extrêmes (projet ANR ExtraFlo , 2013). Cependant, l'utilisation de SCHADEX en l'absence de données (pluie, température, débit) sur le bassin à étudier reste problématique. Cette thèse propose une adaptation de la méthode en site non jaugé en essayant de conserver ses points forts, à savoir: - une structuration spatiale et probabiliste des précipitations conditionnée par les types de temps. - un croisement des aléas pluie et saturation du bassin par simulation stochastique. Ce travail s'est limité au pas de temps journalier afin d'aborder la problématique de régionalisation avec un maximum de données. La démarche s'est alors articulée autour de quatre grands axes: - proposer une méthode de régionalisation des précipitations journalières extrêmes ponctuelles et construire des cartes de pluies aux temps de retour remarquables. Évaluer l'intérêt d'une classification par type de temps pour la régionalisation des distributions de pluies extrêmes et qualifier l'interpolateur de pluie SPAZM pour l'estimation des pluies extrêmes. - s'intéresser à la construction de pluies de bassin (ou pluies spatiales) et en particulier à l'impact des choix de construction de cette pluie sur l'estimation des précipitations extrêmes concernant le bassin. - développer une méthode de simulation stochastique régionale permettant de proposer une distribution de débits journaliers issue d'un croisement des aléas pluies et saturation du bassin. - étudier le passage de la distribution des débits journaliers à la distribution des débits de pointe. Les principaux apports de cette thèse sont les suivants: - la prise en compte des types de temps permet d'améliorer la description des structures spatiales des précipitations extrêmes. - l'information apportée par les pluies SPAZM se révèle être précieuse pour l'estimation des pluies extrêmes en site non jaugé. - une étude de sensibilité du calcul de la pluie spatiale en fonction du nombre de postes utilisés (comparaison des pluies SPAZM et Thiessen) donne une indication sur le biais d'estimation. - le générateur de champs de pluie par bandes tournantes SAMPO permet d'étudier l'abattement sur les précipitations extrêmes et de mettre en place un modèle de correction pour les quantiles élevés des pluies spatiales SPAZM. - une nouvelle méthode de simulation stochastique peu paramétrée mais analogue à la méthode SCHADEX (croisement d'un aléa pluie et d'un aléa de saturation du bassin pour produire une distribution des débits journaliers) est proposée pour l'estimation en site non jaugé. - enfin, un travail préliminaire donne des premiers éléments sur le passage à la distribution des débits de pointe par un générateur d'hydrogrammes s'adaptant à la séquence des débits journaliers simulés. Tous ces développements et conclusions sont détaillés et justifiés dans le mémoire de thèse. / Since 2006, at EDF, extreme flood estimations are computed with the SCHADEX method (Climatic-hydrological simulation of extreme floods). This method relies on a MEWP probabilistic model (seasonal rainfall distribution using a weather pattern concept) and on a stochastic simulation to cross rainy events hazard and catchment saturation states. Simulation approaches, as SCHADEX, have shown good performances to estimate extreme flood distributions. However, the use of SCHADEX method without data for a considered catchment (rain, temperature, runoff) remains a main issue. This thesis suggests an adaptation of the method in ungauged context, trying to keep the key points of the SCHADEX method: - spatial and probabilistic structure of rainfall conditioned by weather patterns. - a cross of rainfall and catchment saturation hazards by stochastic simulation. This work is limited to a daily step to address the issue of regionalization with a maximum of data. The approach is then structured around four main points: - regionalize punctual daily extreme precipitations and construct maps of return period rainfalls. Evaluate the contribution of a weather type classification for the regionalization of extreme rainfall distributions and qualify the SPAZM interpolator for the estimation of extreme rainfall. - wonder about the construction of an areal rainfall and in particular about the impact of its construction choices on the estimation of extreme precipitations. - develop a regional stochastic simulation method to estimate a distribution of daily runoffs which crosses rainy events and catchment saturation hazards. - study the transposition from a daily runoff distribution to a peak flow distribution. The main contributions of this thesis are: - taking into account the weather types improves the description of spatial patterns of extreme precipitations. - information provided by the SPAZM rainfall interpolator proves to be valuable for the estimation of extreme rainfall in ungauged site. - a sensitivity analysis of the calculation of the areal rainfall based on the number of stations used (comparison SPAZM and Thiessen areal rainfalls) gives an indication of the estimation bias. - the SAMPO rainfall generator used to study the areal reduction factor of extreme precipitation and implement a correction model for high quantiles of SPAZM areal rainfall. - a simplified method of stochastic simulation similar to SCHADEX method (cross between a rainfall hazard and a catchment saturation hazard) is developed to produce a distribution of daily flows in ungauged site. - finally, preliminary work provides a way for the transition to the peak flow distribution using a hydrograph generator adapted to the sequence of daily simulated runoffs. All these developments and conclusions are detailed and justified in the thesis.STAR

Atualmente, uma atividade que se tornou estratégica a nível nacional é o cultivo de espécies oleaginosas para o mercado alimentício e energético, em especial o plantio da palma de óleo (dendê) na região nordeste do estado do Pará, na Amazônia oriental. Esta cultura, assim como tem apresentado benefícios, como fixação do homem no campo, recuperação de áreas degradadas e redução da perda de solo, também tem apresentado riscos de ordem social e ambiental, como possíveis expropriações de terras e aumento do desmatamento e empobrecimento da diversidade ecológica. Mas se conhece pouco ainda dos impactos da expansão dessa cultura sobre o balanço hídrico e processos erosivos. Por isso, este trabalho estimou os impactos da expansão da cultura da palma de óleo na dinâmica de mudança de uso e cobertura da terra, bem como no escoamento superficial e na produção de sedimentos. Para isto, aplicou-se o modelo hidrossedimentológico Soil and Water Assessment Tool (SWAT) e o modelo de dinâmica espacial Conversion of Land Use and its Effects at Small region extent (CLUES) sobre as sub-bacias não monitoradas dos rios Bujaru (SBRB) e Mariquita (SBRM), com calibração do SWAT realizada a partir da técnica de regionalização de vazão por regressão não linear e medições em campo com o molinete hidrométrico. A princípio, as equações de regressão se apresentaram eficientes nas estimativas de dados de vazão para as sub-bacias, fundamentadas no bom resultado da calibração e validação sobre as estações reais. Nas áreas de palma de óleo, o modelo foi capaz de estimar com bom grau de eficiência a evapotranspiração nestas Unidades de Resposta Hidrológica da SBRB (1089,2 mm) e da SBRM (1093,1 mm), em relação a literatura e medidas em torre de monitoramento micrometeorológico. O modelo CLUE-S foi capaz de integralizar as variáveis explanatórias com as demandas agregadas e as características de elasticidade com o objetivo de gerar cenários futuros de uso e cobertura da terra, bem como modelar a palma de óleo nas sub-bacias, identificando as variáveis biofísicas como as principais forçantes de mudança de uso e cobertura da terra. As estimativas de escoamento superficial e produção de sedimentos apontaram para uma redução na SBRB e um aumento na SBRM entre os cenários de 2008, 2013 e o cenário projetado com o CLUE-S para 2023 em especial por razão da grande variação das áreas de vegetação secundária. As áreas de Palma de Óleo tiveram menor escoamento superficial e produção de sedimentos médio mensal do período mais chuvoso em ambas sub-bacias e em todos os cenários em relação as áreas de Agricultura Geral e Pastagem. Os resultados também mostraram a boa capacidade do uso integrado dos modelos SWAT e CLUE-S na geração de dados que contribuem para a análise do impacto ambiental da expansão da palma de óleo na região nordeste do estado do Pará, sendo também importante para o planejamento e gestão ambiental rural em bacias hidrográficas não monitoradas na Amazônia Oriental, pois demonstra a eficiência do método em proporcionar o aumento dos conhecimentos do comportamento hidrológico destas bacias em relação a dinâmica espacial de uso e cobertura do solo. / Nowadays, oilseed production for food and energy has become a strategic activity at national level in Brazil, particularly oil palm crops located in the Northeast of Pará State, Eastern Amazon. Oil palm crops have shown benefits such as keeping farmers on the land, recovering degraded areas and reducing soil loss. Conversely, it may also increase social and environmental risks linked to land tenure instability and land expropriation, deforestation and biodiversity losses. In such context, there is still a lack of knowledge concerning the impacts of such crop on the local water balance and erosion processes. Thus, this research estimated the impacts of increasing oil palm crops on land use and land cover change dynamics, as well as on runoff and soil erosion processes. To do so, it was applied the Soil and Water Assessment Tool (SWAT) and the spatial explicit framework Conversion of Land Use and its Effects at Small region extent (CLUE-S) over two ungauged sub-basins of Bujaru (SBRB) and Mariquita (SBRM) rivers. SWAT calibration was done by the regionalization streamflow method that adopts nonlinear regression and field measurements using a current meter. Initially, regression equations were effective in streamflow data estimation for the subbasins, this was based on effective calibration and validation results upon real stations. In the oil palm crop areas, the SWAT modeling was able to successfully estimate evapotranspiration on both hydrologic response unit of SBRB (1089,2 mm) and SBRM (1093,1mm) when compared to the literature and measures in micrometeorological monitoring tower. When applying CLUE-S model it was capable to integrate explanatory variables to scenario demands and elasticity parameters determining land use/cover change. Such integration allowed modelling oil palm spatial-temporal dynamics in current and future scenario demands within the two sub-basins SBRB and SBRM, as well as the identification of biophysical variables as the core drivers of land use/cover change. Runoff and sediment yield pointed out towards a decline in SBRB and an increase in SBRM in the current scenario between 2008 and 2013, as well as in the future scenario modelled using CLUE-S land use/cover change maps for 2023, particularly because of a large variation in the dynamics of secondary vegetation between the two sub-basins. Oil palm areas had smaller monthly average runoff and sediment yield in the rainiest period in both sub-basins and in current and future scenarios regarding agriculture and pasture areas. The results also show a suitable capability of integration between SWAT and CLUE-S models when generating data that contribute to the analysis of environmental impact of oil palm expansion in the Northeast of Para State. Such contribution is also relevant to the rural environmental planning and management in ungauged river-basins in Eastern Amazon, since the results found here demonstrate the efficiency of the method in providing an improved knowledge of the hydrological behavior of these basins concerning land use and land cover changes dynamics.

Floods and droughts are frequent in Central America and cause large social, economic and environmental impacts. A crucial step in disaster risk reduction is to have a good understanding of the causing mechanisms of extreme events and their spatio-temporal characteristics. For this, a key aspect is access to a dense network of long and good-quality hydro-meteorological data. Unfortunately, such ideal data are sparse or non-existent in Central America. In addition, the existing methods for hydro-climatic studies need to be revised and/or improved to find the most suitable for the region’s climate, geography and hydro-climatic data situation. This work has the ultimate goal to support the reduction of risks associated with hydro-climatic-induced disasters in Central America. This was sought by developing ways to reduce data-related uncertainties and by improving the available methods to study and understand hydro-climatic variability processes. In terms of data-uncertainty reduction, this thesis includes the development of a high resolution air temperature dataset and a methodology to reduce uncertainties in a hydrological model at ungauged basins. The dataset was able to capture the spatial patterns with a detail not available with existing datasets. The methodology significantly reduced uncertainties in an assumed-to-be ungauged catchment. In terms of methodological improvements, this thesis includes an assessment of the most suitable combination of (available) meteorological datasets and drought indices to characterise droughts in Central America. In addition, a methodology was developed to analyse drought propagation in a tropical catchment, in an automated, objective way. Results from the assessment and the drought propagation analysis contributed with improving the understanding of drought patterns and generating processes in the region. Finally, a methodology was proposed for assessing changes in both hydrological extremes in a consistent way. This contrasts with most commonly used frameworks that study each extreme individually. The method provides important characteristics (frequency, duration and magnitude), information that can be useful for decisions within risk reduction and water management. The results presented in this thesis are a contribution, in terms of hydro-climatic data and assessment methods, for supporting risk reduction of disasters related with hydro-climatic extremes in Central America. / Översvämningar och torka inträffar ofta i Mellanamerika och orsakar stora skador på samhälle, ekonomi och miljö. En kritisk del av riskreduceringen är förståelsen av mekanismerna bakom extremhändelserna, och deras rumsliga och tidskarakteristik. En nyckelfaktor är tillgång till långa tidsserier av rumsligt täckande hydrometeorologiska data av bra kvalitet. I Mellanamerika är sådana ideala data tyvärr sällsynta eller saknas helt. Dessutom behöver befintliga metoder för hydro-klimatisk analys revideras och/eller förbättras för att identifiera de mest lämpade metoderna för regionens klimat, geografi och situationen vad gäller hydrologiska och meteorologiska data. Det övergripande syftet med denna avhandling har varit att stödja arbetet med riskreducering i Mellanamerika vid hydrologiska extremhändelser som sätts igång av extrema väderhändelser. För att bidra till detta utvecklades metoder för att minska datarelaterade osäkerheter och för att förbättra tillgängliga metoder för att studera och förstå de processer som ligger bakom variabiliteten i hydrologi och klimat. Dataosäkerheten minskades genom utveckling av ett nytt dataset för lufttemperatur med hög rumslig upplösning och en metodik för att begränsa osäkerheten i modellberäknad vattenföring i ett område där det saknas observationer. Det nya datasetet kunde fånga rumsliga mönster på en detaljnivå som hittills inte varit möjlig. Metodiken möjliggjorde en klar minskning i osäkerheten hos vattenföringen i ett avrinningsområde som behandlades som om det saknade data. Avhandlingen innehåller också en metodik för att fastlägga den mest lämpade kombinationen av tillgängliga klimatdataset och torkindex för att karakterisera torka i Mellanamerika. Därutöver utvecklades en metod för att studera torkans fortplantning i ett tropiskt avrinningsområde på ett objektivt och automatiserat sätt. Slutligen föreslås en metod för att hantera förändringar av både översvämning och torka på ett konsistent sätt  som förenklar användningen av resultaten  för en beslutsfattare. Dessa metoder bedömdes användbara för att förbättra karakteriseringen och förståelsen av extrema hydrologiska händelser i Mellanamerika. Resultaten i denna avhandling ger bidrag till förståelsen av hydrologiska och klimatextremer genom förbättrade data och analysmetoder som i förlängningen kommer att stödja riskreduceringsarbetet i Mellanamerika. / Las sequías e inundaciones son frecuentes en Centroamérica y causan grandes problemas sociales, económicos y ambientales. Un aspecto crucial en la reducción del riesgo consiste en entender los mecanismos que causan dichos eventos, y sus características espacio-temporales. Para lograr esto es necesario tener acceso a una red de datos hidro-meterológicos densa, con series largas, y de buena calidad. Desafortunadamente, este no es el caso en Centroamérica. Además, los métodos para hacer estudios hidro-climáticos requieren ser evaluados y/o mejorados para asegurar su aplicabilidad en la región (su clima, su geografía y los datos disponibles). Este trabajo tiene como meta apoyar la reducción del riesgo de desastres asociados a eventos hidro-meteorológicos extremos en Centroamérica. Esto se consigue a partir de la reducción de incertidumbres asociadas a los datos, y de la mejora de métodos para el estudio de la variabilidad hidro-climática. Para reducir la incertidumbre de los datos, este trabajo incluye el desarrollo de una base de datos de temperatura de alta resolución y el desarrollo de una metodología para reducir las incertidumbres en datos simulados de caudal. Con la nueva base de datos se logra reconocer patrones espaciales a un nivel de detalle no antes captado por otras bases de datos. Por otro lado, la metodología redujo significativamente las incertidumbres de los datos simulados de caudal. En cuanto a métodos, esta tesis incluye una evaluación para encontrar la mejor combinación de índices de sequía y base de datos para la caracterización de sequías en la región. Además, se desarrolló una metodología para analizar la propagación de la sequía en una cuenca tropical, de una manera objetiva y automatizada. Los resultados de estos dos pasos ayudaron a mejorar la comprensión de los patrones y los mecanismos de generación de las sequías. Finalmente, se incluyó un método para evaluar los cambios en los patrones de sequías e inundaciones de una manera consistente, y no de manera individual como usualmente se ha hecho. Así fue posible obtener la frecuencia, duración y magnitud en ambos extremos hidrológicos. Esta información podría constituir una herramienta  útil para el manejo del riesgo y del recurso hídrico.

The Håga river, located west of the Swedish city Uppsala, is currently without a proper gauging station. Knowing the streamflow is nonetheless important to, for example, be able to calculate the nutrient transport in the river. This project aimed to evaluate different indirect methods of streamflow estimation to investigate how they perform, in particular in relation to SMHI’s S-HYPE model. Two of the methods used were based on transferring streamflow of nearby catchments to Håga, either by using relationships between the mean and standard deviation of the streamflow time series (MOVE), or by simply scaling relative to catchment size (DAR). Furthermore, a hydrological model, HBV, was calibrated for Håga using different amounts and types of calibration data. All the methods were then compared to streamflow data from a previously active gauging station in Håga.  It was found that the overall best method to estimate the streamflow in Håga was using the MOVE method with one particular donor catchment. However, the performance of the simpler MOVE and DAR methods varied a lot from catchment to catchment. HBV was found to be able to produce better performing simulations than S-HYPE, despite being a simpler model. Even HBV-calibrations using alternative or limited data could perform rather well, although rarely at the level of a calibration utilising all available streamflow data. A big uncertainty of the study was the fact that the most recent available validation data for the Håga catchment was from two decades ago, when the old gauging station was decommissioned. Most likely the methods that worked well during the 90s would work well today as well, but this is a matter that could be studied further. / Hågaån, ett vattendrag som ligger väster om Uppsala, saknar i nuläget en mätstation för vattenföring. Att känna till flödet är dock ändå intressant, bland annat för att kunna beräkna näringstransporten i ån. Syftet med detta projekt var därmed att utvärdera och jämföra olika metoder för att uppskatta vattenflödet i Hågaån, särskilt för att undersöka hur de presterade i jämförelse med SMHI:s S-HYPE-modell. Två av metoderna som användes för detta baserades på att överföra flöden från närliggande vattendrag till Håga, antingen genom att använda förhållanden mellan medelvärde och standardavvikelse för flödes-datan (MOVE), eller genom att bara utgå från skillnader i områdenas storlek (DAR). Utöver det kalibrerades även den hydrologiska modellen HBV för Håga med olika typer och mängder av kalibreringsdata. Alla metoderna jämfördes sedan med data från en mätstation som tidigare funnits i Hågaån. Resultaten visade att den över lag bästa metoden för att uppskatta flödet i Håga var MOVE-metoden i kombination med ett av de närliggande vattendragen. Hur väl dessa simplare MOVE- och DAR-metoder presterade varierade dock mycket beroende på vilket vattendrag som användes som donator. Det visade sig även att det gick att erhålla bättre resultat med HBV än de som gavs av S-HYPE, trots att HBV är en enklare modell. Även HBV-kalibreringar baserade på alternativ eller begränsad data kunde producera välpresterande simulationer, dock sällan på samma nivå som den kalibrering som använt all tillgänglig flödesdata. En stor osäkerhet i projektet kretsar kring att den nyaste tillgängliga valideringsdatan från Hågaån var över två decennier gammal, då den mätstation som funnits stängdes ner. Med stor sannolikhet kommer metoderna som fungerade väl under 90-talet även fungera bra i modern tid, men detta är något som kräver vidare studier.

Water is essential for human well-being and healthy ecosystems, but population growth and changes in climate and land-use are putting increased stress on water resources in many regions. To ensure water security, knowledge about the spatiotemporal distribution of these resources is of great importance. However, estimates of global water resources are constrained by limitations in availability and quality of data. This thesis explores the quality of both observational and modelled data, gives an overview of models used for large-scale hydrological modelling, and explores the possibilities to deal with the scarcity of data by prediction of flow-duration curves. The evaluation of the quality of observational data for large-scale hydrological modelling was based on both hydrographic data, and model forcing and evaluation data for basins worldwide. The results showed that a GIS polygon dataset outperformed all gridded hydrographic products analysed in terms of representation of basin areas. Through a screening methodology based on the long-term water-balance equation it was shown that as many as 8–43% of the basins analysed displayed inconsistencies between forcing (precipitation and potential evaporation) and evaluation (discharge) data depending on how datasets were combined. These data could prove disinformative in hydrological model inference and analysis. The quality of key hydrological variables from a numerical weather prediction model was assessed by benchmarking against observational datasets and by analysis of the internal land-surface water budgets of several different model setups. Long-term imbalances were found between precipitation and evaporation on the global scale and between precipitation, evaporation and runoff on both cell and basin scales. These imbalances were mainly attributed to the data assimilation system in which soil moisture is used as a nudge factor to improve weather forecasts. Regionalisation, i.e. transfer of information from data-rich areas to data-sparse areas, is a necessity in hydrology because of a lack of observed data in many areas. In this thesis, the possibility to predict flow-duration curves in ungauged basins was explored by testing several different methodologies including machine learning. The results were mixed, with some well predicted curves, but many predicted curves exhibited large biases and several methods resulted in unrealistic curves. / Vatten är en förutsättning för människors och ekosystems hälsa, men befolkningsökning och förändringar av klimat och markanvändning förväntas öka trycket på vattenresurserna i många regioner i världen. För att kunna säkerställa en god tillgång till vatten krävs kunskap om hur dessa resurser varierar i tid och rum. Tillförlitligheten hos skattningar av globala vattenresurser begränsas dock både av begränsad tillgänglighet av och kvalitet hos observerade data. Denna avhandling utforskar kvaliteten av såväl observations- som modellbaserade data, ger en överblick över modeller som används för storskalig hydrologisk modellering och utforskar möjligheterna att förutsäga varaktighetskurvor som ett sätt att hantera bristen på data i många områden. Utvärderingen av observationsbaserade datas kvalitet baserades på hydrografiska data och driv- och utvärderingsdata för storskaliga hydrologiska modeller. Resultaten visade att en uppsättning data över hydrografin baserad på GIS-polygoner representerade avrinningsområdesareorna bättre än alla de som byggde på rutor. En metod baserad på långtidsvattenbalansen identifierade att kombinationen av drivdata (nederbörd och potentiell avdunstning) och utvärderingsdata (vattenföring) var fysiskt orimlig för så många som 8–43 % av de analyserade avrinningsområdena beroende på hur olika datauppsättningar kombinerades. Sådana data kan vara desinformativa för slutsatser som dras av resultat från hydrologiska modeller och analyser. Kvaliteten hos hydrologiskt viktiga variabler från en numerisk väderprognosmodell utvärderades dels genom jämförelser med observationsdata och dels genom analys av landytans vattenbudget för ett flertal olika modellvarianter. Resultaten visade obalanser mellan långtidsvärden av nederbörd och avdunstning i global skala och mellan långtidsvärden av nederbörd, avdunstning och avrinning i både modellrute- och avrinningsområdesskala. Dessa obalanser skulle till stor del kunna förklaras av den data assimilering som görs, i vilken markvattenlagret används som en justeringsfaktor för att förbättra väderprognoserna. Regionalisering, som innebär en överföring av information från områden med god tillgång på mätdata till områden med otillräcklig tillgång, är i många fall nödvändig för hydrologisk analys på grund av att mätdata saknas i många områden. I denna avhandling utforskades möjligheten att förutsäga varaktighetskurvor för avrinningsområden utan vattenföringsdata genom flera metoder inklusive maskininlärning. Resultaten var blandade med en del kurvor som förutsas väl, och andra kurvor som visade stora systematiska avvikelser. Flera metoder resulterade i orealistiska kurvor (ickemonotona eller med negativa värden).

Knowledge about spatial and temporal variability of hydrological processes is central for sustainable water-resources management, and such knowledge is created from observational data. Hydrologic models are necessary for prediction for time periods and areas lacking data, but are affected by observational uncertainties. Methods for estimating and accounting for such uncertainties in water-resources modelling are of high importance, especially in regions such as Central America. Observational uncertainties were addressed in three ways in this thesis; quality control, quantitative estimation and development of model-evaluation techniques that addressed unquantifiable uncertainties. A first step in any modelling study should be the quality control and concurrent analysis of the representativeness of the observational data. In the characterisation of the precipitation regime in the Choluteca River basin in Honduras, four different quality problems were identified and 22% of the daily data had to be rejected. The monitoring network was found to be insufficient for a comprehensive characterisation of the high spatiotemporal variability of the precipitation regime. Quantitative estimations of data uncertainties can be made when sufficient information is available. Discharge-data uncertainties were estimated with a fuzzy regression for time-variable rating curves and from official rating curves for 35 stations in Honduras. The uncertainties were largest for low flows, as a result of measurement uncertainties and natural variability. A method for calibration with flow-duration curves was developed which enabled calibration to the whole flow range, accounting for discharge uncertainty and calibration with non-overlapping time periods for model input and evaluation data. The method compared favourably to traditional calibration in a test using two models applied in basins with different runoff-generation processes. A post-hoc analysis made it possible to identify potential model-structure errors and periods of disinformative data. Flow-duration curves were regionalised and used for calibration of a Central-American water-balance model. The initial model uncertainty for the ungauged basins was reduced by 70%. Non-representative precipitation data were found to be the main obstacle to comprehensive regional water-resources modelling in Central America. These methods bridged several problems related to observational uncertainties in water-balance modelling. Estimates of prediction uncertainty are an important basis for all types of decisions related to water-resources management. / Kännedom om hur hydrologiska processer varierar i tid och rum är grundläggande för hållbar vattenresursförvaltning och skapas utifrån observerade data. Hydrologiska modeller är nödvändiga för att förutsäga vattenbalansen för tidsperioder och områden utan data, men påverkas av observationsosäkerheter. Metoder för att hantera sådana osäkerheter i vattenresursmodellering är av stor betydelse i regioner såsom Centralamerika. Observationsosäkerheter hanterades på tre olika sätt i denna avhandling; kvalitetskontroll, kvantitativ uppskattning och utveckling av modellutvärderingsmetoder för beaktande av icke kvantifierbara osäkerheter. Ett viktigt första steg är kvalitetskontroll och samtidig analys av datas representativitet. Vid karaktäriseringen av nederbördsregimen i Cholutecaflodens avrinningsområde i Honduras identifierades fyra olika kvalitetsproblem och 22 % av data sorterades bort. Stationsnätet var otillräckligt för en fullödig karaktärisering av nederbördsregimens variationer i tid och rum. Dessa var mycket stora som ett resultat av komplexiteten hos de nederbördsgenererande mekanismerna. Kvantitativ uppskattning av observerade datas osäkerhet kan göras när tillräcklig information är tillgänglig. Osäkerheter i vattenföringsdata uppskattades dels vid beräkning av vattenföring med en oskarp regression för en tidsvariabel avbördningskurva, dels från en analys av officiella avbördningskurvor från 35 stationer i Honduras. Osäkerheten var i båda fallen högst vid låga flöden som ett resultat av högre mätosäkerheter samt större naturlig variabilitet än vid höga flöden. En metod för modellkalibrering med varaktighetskurvor utvecklades och gjorde det möjligt att kalibrera för hela flödesintervallet samtidigt, ta hänsyn till osäkerheter i vattenföringsdata samt kalibrera med icke överlappande driv- och utvärderingsdata. Metoden testades med två olika modeller i två avrinningsområden med olika avrinningsbildningsprocesser, och visade goda resultat jämfört med traditionell modellkalibrering. En post hoc-analys gjorde det möjligt att identifiera troliga modellstrukturfel och perioder med disinformativa data. Varaktighetskurvor regionaliserades och användes för kalibrering av en regional vattenbalansmodell för Centralamerika, varvid den initiala modellosäkerheten minskades med 70 %. Icke representativa nederbördsdata identifierades som det största hindret för regional vattenresursmodellering i Centralamerika. De metoder som utvecklades i detta arbete gör det möjligt att överbrygga ett flertal problem orsakade av bristfällig tillgänglighet och kvalitet av data och leder därmed till en förbättrad uppskattning av osäkerheten i vattenbalanssimuleringar. Sådana osäkerhetsskattningar är ett viktigt underlag vid alla typer av förvaltningsbeslut som rör vattenresurser.