<p>Ecohydrological models are extensively used to evaluate land use, land management and climate change impacts on hydrology and in-stream water quality conditions. The scale at which these models operate influences the complexity of processes incorporated within the models. For instance, a large scale hydrological model such as Soil and Water Assessment Tool (SWAT) that runs on a daily scale may ignore the sub-daily scale in-stream processes. The key processes affecting in-stream solute transport such as advection, dispersion and transient storage (dead zone) exchange can have considerable effect on the predicted stream solute concentrations, especially for localized studies. To represent realistic field conditions, it is therefore required to modify the in-stream water quality algorithms of SWAT by including these additional processes. Existing reach-scale solute transport models like OTIS (One-dimensional Transport with Inflow and Storage) considers these processes but excludes the actual biochemical reactions occurring in the stream and models nutrient uptake using an empirical first-order decay equation. Alternatively, comprehensive stream water quality models like QUAL2E (The Enhanced Stream Water Quality Model) incorporates actual biochemical reactions but neglects the transient storage exchange component which is crucial is predicting the peak and timing of solute concentrations. In this study, these two popular models (OTIS and QUAL2E) are merged to integrate all essential solute transport processes into a single in-stream water quality model known as ‘Enhanced OTIS model’. A generalized model with an improved graphical user interface was developed on MATLAB platform that performed reasonably well for both experimental data and previously published data (R²=0.76). To incorporate this model into large-scale hydrological models, it was necessary to find an alternative to estimate transient storage parameters, which are otherwise derived through calibration using experimental tracer tests. Through a meta-analysis approach, simple regression models were therefore developed for dispersion coefficient (D), storage zone area (A_s) and storage exchange coefficient (α) by relating them to easily obtainable hydraulic characteristics such as discharge, velocity, flow width and flow depth. For experimental data from two study sites, breakthrough curves and storage potential of conservative tracers were predicted with good accuracy (R²>0.5) by using the new regression equations. These equations were hence recommended as a tool for obtaining preliminary and approximate estimates of D, A_s and α when reach-specific calibration is unfeasible. </p> <p> </p> <p>The existing water quality module in SWAT was replaced with the newly developed ‘Enhanced OTIS model’ along with the regression equations for storage parameters. Water quality predictions using the modified SWAT model (Mir-SWAT) for a study catchment in Germany showed that the improvements in process representation yields better results for dissolved oxygen (DO), phosphate and Chlorophyll-a. While the existing model simulated extreme low values of DO, Mir-SWAT improved these values with a 0.11 increase in R² value between modeled and measured values. No major improvement was observed for nitrate loads but modeled phosphate peak loads were reduced to be much closer to measured values with Mir-SWAT model. A qualitative analysis on Chl-<i>a</i> concentrations also indicated that average and maximum monthly Chl-<i>a</i> values were better predicted with Mir-SWAT when compared to SWAT model, especially for winter months. The newly developed in-stream water quality model is expected to act as a stand alone model or coupled with larger models to improve the representation of solute transport processes and nutrient uptake in these models. The improvements made to SWAT model will increase the model confidence and widen its extent of applicability to short-term and localized studies that require understanding of fine-scale solute transport dynamics. </p>

O entendimento da dinâmica hidrossedimentológica em uma bacia hidrográfica pode ser realizado pelo monitoramento das variáveis hidrossedimentológicas e pela modelagem desses processos. Nesse contexto, essa pesquisa analisou a eficiência do modelo Soil and Water Assessment Tool (SWAT) na previsão dos processos hidrossedimentológicos na bacia do Taboão (Pejuçara, RS), considerando as saídas (vazão e produção de sedimentos) em um passo de tempo mensal e diário. Para tal, foram utilizados dados de chuva horária dos anos 2008 a 2016, monitorada em quatro pluviógrafos instalados na bacia (PVGs 34, 40, 43 e 51), e dados climáticos da estação meteorológica de Cruz Alta. As informações de vazão, para os anos de 2011 a 2016, foram obtidas por meio da conversão dos dados de nível de água monitorados no exutório da bacia, utilizando uma curva-chave cota x vazão. A concentração de sedimentos suspensos (CSS), para os anos de 2013 a 2015, foi estimada por meio de modelos de redes neurais artificias (RNAs), empregando como entrada dados de turbidez e de nível de água, monitorados no exutório da bacia. O preenchimento das falhas dos registros de precipitação horária foi executado por meio de modelos de Combinações de RNAs (CRNAs) associados à média simples (MS) ou à média ponderada pelo inverso da distância (MP), utilizando como entrada dados pluviométricos dos postos vizinhos. As falhas nos dados de nível de água foram preenchidas por modelos de RNAs, que usaram como entrada níveis de água monitorados em sub-bacias embutidas ou adjacente à bacia do Taboão (bacias do Donato, Turcato, Alemão e Andorinhas), e dados de precipitação média dos quatro pluviógrafos utilizados nessa pesquisa Foram determinadas as defasagens temporais entre os níveis de água das diferentes bacias, e testados o uso da precipitação média com aplicação de filtro temporal linear e/ou exponencial. Os registros falhos nos dados de turbidez foram preenchidos por modelos de RNAs, que empregaram como entrada informações de nível de água monitoradas, de 10 em 10 minutos, no exutório da bacia. A calibração do modelo SWAT para a previsão dos processos hidrológicos foi realizada usando dados de vazão, diários e mensais, para os anos de 2013, 2014 e 2016 e; a etapa de verificação foi executada para os anos de 2011 e 2015. Considerou-se o Método de Green & Ampt para determinação da infiltração de água no solo e 2 anos (2008-2009) para período de aquecimento do modelo SWAT. A calibração do modelo para a produção de sedimentos foi realizada para os anos de 2013 e 2015 e o processo de verificação foi efetuado para o ano de 2014. A calibração e a análise de sensibilidade dos parâmetros foram realizadas com auxílio do SWAT-CUP, utilizando o algoritmo SUFI-2. O coeficiente de Nash–Sutcliffe (NS) das RNAs para preenchimento das falhas de precipitação variou entre 0,35, classificado como “Insatisfatório”, e 0,86, avaliado como “Muito Bom”, considerando critérios propostos por Moriasi et al. (2007). Das 13 RNAs desenvolvidas para preenchimento das falhas nos níveis de água, apenas uma delas foi classificada como de desempenho “Satisfatório” durante o treinamento e; as demais enquadraram-se como de desempenho “Muito Bom”. Na etapa de verificação, sete RNAs foram consideradas com desempenho “Muito Bom” e cinco com “Bom” desempenho No preenchimento das falhas de turbidez, das cinco RNAs desenvolvidas, quatro mostraram “Bom” desempenho durante o treinamento, e uma rede teve desempenho “Muito Bom”; enquanto que, no processo de verificação, duas RNAs tiveram desempenho “Muito Bom”, uma delas foi classificada com desempenho “Bom” e; duas RNAs foram consideradas com desempenho “Satisfatório”. As estatísticas de desempenho dos modelos de RNAs desenvolvidos para o preenchimento das falhas de nível de água, de turbidez e de precipitação também demonstraram que tais redes representam uma alternativa interessante para a obtenção de séries contínuas desses dados, possibilitando o uso posterior dos registros para a modelagem hidrossedimentológica. A calibração do modelo SWAT para estimativa da vazão mensal mostrou desempenho “Muito Bom” (NS=0,78), e para a determinação da vazão diária foi considerado “Bom” (NS=0,72). Na etapa de verificação, o modelo manteve o “Bom” desempenho (NS=0,68) para estimativa da vazão diária, decaindo para desempenho “Satisfatório” (NS=0,64) para a simulação em escala mensal. Para a estimativa da produção de sedimentos mensal, o desempenho do modelo foi considerado “Bom” tanto na calibração (NS=0,66) quanto na verificação (NS=0,70). Na escala diária o desempenho foi “Satisfatório” para a calibração (NS=0,64) e “Insatisfatório” para a verificação (NS=0,38) Tais resultados indicam que o modelo SWAT é uma ferramenta promissora para aplicações na previsão hidrossedimentológica na bacia do Taboão, especialmente em termos de simulações dos processos hidrológicos. No entanto, existem limitações para aplicações na estimativa da produção de sedimentos, sobretudo quando considerados os processos em escala diária. Essas limitações são consequência da presença de processos erosivos na bacia (voçorocas), que não são simulados pelas rotinas presentes no modelo SWAT, bem como pelo escoamento dominante ser do tipo subsuperficial, com ocorrência de pipping; indicando-se, portanto, adequações nas rotinas do modelo para melhor representatividade desses processos. / The understanding of hydrosedimentological dynamics in a watershed can be obtained by monitoring the hydrossedimentological variables and by modeling these processes. In this context, this research analyzed the efficiency of the Soil and Water Assessment Tool (SWAT) in predicting the hydrosedimentological processes in the Taboão basin (Pejuçara, RS), considering the outputs (flow and sediment production) in a monthly and daily time step. For that, hourly rainfall data from 2008 to 2016 were monitored at four pluviographs installed in the basin (PVGs 34, 40, 43 and 51), and climate data were obtained from the Cruz Alta meteorological station. The flow information for the years 2011 to 2016 was obtained by converting the monitored water level data into flow by using a rating curve. The suspended sediment concentration (SSC), from 2013 to 2015, was estimated using artificial neural network (ANN) models, using as input turbidity and water level data, monitored in the basin. The filling of the hourly rainfall records was performed by models of Combinations of RNAs (CRNAs) associated with the simple mean (MS) or weighted mean to the inverse distance (MP), using as input rainfall data from the neighboring stations. Failures in the water-level data were filled by RNA models, which used as input water levels monitored in sub-basins adjacent or embedded to the Taboão basin (Donato, Turcato, Alemão and Andorinha basins), and mean precipitation data of the four pluviographs used in this research. The temporal lags between the water levels of the different basins were determined and the use of the average precipitation with linear and exponential temporal filters was tested The turbidity data records were filled by RNA models, using water level information monitored at every 10 minutes. The SWAT model calibration for predicting the hydrological processes was performed using daily and monthly flow data for the years 2013, 2014 and 2016 and the verification step was performed for the years 2011 and 2015; considering Green & Ampt Method for infiltration estimation and 2 years of warm-up period (2008-2009). The calibration of the model for sediment yield was performed for the years 2013 and 2015 and the verification process was carried out for the year 2014. The calibration and sensitivity analysis of the parameters were performed with the assistance of SWAT-CUP, using the SUFI-2 algorithm. The Nash-Sutcliffe Coefficient (NS) of the RNAs used to fill precipitation faults varied between 0.35, classified as "Unsatisfactory", and 0.86, evaluated as "Very Good", considering criteria proposed by Moriasi et al. (2007). Of the 13 RNAs developed to fill water level failures, only one of them was classified as a "Satisfactory" performance during training and; the others have been classified as "Very Good" performance. In the verification step, seven RNAs were considered to have "Very Good" performance and five had "Good” performance. In the fulfillment of the turbidity faults, of the five RNAs developed, four showed "Good" performance during the training, and one network had "Very Good" performance; while in the verification process two ANNs performed "Very Good", one of them was classified as "Good" and; two ANNs were considered to have "Satisfactory" performance The performance statistics of the ANN models developed to fill the water level, turbidity and precipitation failures also demonstrated that such networks represent an interesting alternative to obtain continuous series of these data, allowing the later use of the records for hydrossedimentological modeling. In the verification processes, the model maintained a “Good” performance (NS=0.68) to estimate the daily flow, decreasing to "Satisfactory" performance (NS=0.64) for the monthly scale simulation. For the estimation of sediment yield the model performance was considered "Good" for monthly calibration period (NS=0.66) and also for the verification (NS=0.70). In daily scale the performance was "Satisfactory" for calibration (NS=0.64) and “Unsatisfactory” in the verification (NS=0.38). These results indicate that the SWAT model is a promising tool for applications in the hydrosedimentological forecasting in the Taboão basin, especially in terms of hydrological processes simulations. However, there are limitations to applications in the estimation of sediment production, especially when considering daily scale processes. These limitations are due to the presence of erosive processes in the basin (gully erosion), which are not simulated by the routines present in the SWAT model, as well as by the existence of the lateral flow with occurrence of pipping; indicating, therefore, the need for adjustments in the routines of the model to better represent these processes.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Areas under intensive tobacco crop cultivation have been impacting the water balance and increasing soil erosion in Southern Brazil. Application of large amounts of mineral fertilizers, higher than the tobacco requirement, contributes to excessive phosphorus loads in soil and water bodies. The assessment of potential environmental impacts due to changes in land use and management practices is necessary to achieve the sustainable management of natural resources such as soil and water. In this study the hydrological processes, the sediment yield and the phosphorus transfer in the Arroio Lino watershed were evaluated by using the Soil and Water Assessment Tool (SWAT) model. The small watershed (4.18 km2 ) is located in Southern Brazil and its main land use is tobacco crop under conventional tillage. Measured streamflow and sediment yield at the watershed outlet were used for model streamflow sensitivity analysis, calibration and validation. Phosphorus loads at four sub-watersheds (A1, A2, B, C) and at the watershed outlet were used for model sensitivity analysis and calibration. A Latin Hypercube (LH) and One-factor- At-a-Time (OAT) sensitivity analysis was performed on input variables. Model calibration was performed with the Shuffled Complex Evolution Algorithm-Uncertainty Analysis (SCE-UA). Time series plots and standard statistical measures were used to verify model predictions. Adaptations of the model parameters for the reality of the region in which the watershed is located were made during the calibration and validation of the model. The predicted monthly streamflow matched the observed values, with a Nash Sutcliffe coefficient (NSE) of 0.87 for calibration and 0.76 for validation. In an attempt to account for sediment transport and deposition processes across the landscape, the SWAT model was modified to simulate landscape sediment transport capacity. The new deposition routine performed better during calibration (NSE of 0.70) than SWAT standard version (NSE of -0.14) in the studied watershed. The modified model provided reasonable simulations of sediment transport across the landscape positions. The results suggest that the integration of the sediment deposition routine in SWAT increases model predictions accuracy in steeper areas, while at the same time significantly improves the ability to predict spatial distribution of sediment deposition areas. The predicted P loads are in the order of magnitude of the measured ones, however, the model failed to predict the P loads in three sub-watersheds (A1, A2 and B). Although occupying only 29% of the total land cover, cropland is the primary source of nutrients in the watershed (80%). After calibration of streamflow, sediment yield and phosphorus loads, the simulation of distinct management scenarios was done for the Arroio Lino watershed. Three scenarios of management practices: conventional tillage (CT), minimum tillage (MT) and no-tillage cultivation (NT) with reduction of 50% of fertilizer rate application were tested over a period of 30 years. No-tillage practices did not significantly affect water yield, but greatly affected sediment yield due to reduction of soil erosion. The soluble phosphorus losses decreased mainly when the fertilizer doses decreased. The simulation results suggest that conventional tillage practices should be replaced by less intensive tillage practices in order to minimize environmental impacts caused by a single land use. / Áreas com culturas de tabaco cultivadas intensivamente, no sul do Brasil, vêm afetando a qualidade da água e aumentando a erosão do solo nesta região. A aplicação de grandes quantidades de fertilizantes minerais, maiores do que a exigência da cultura, contribui para a excessiva carga de fósforo nos solos e corpos d'água. A avaliação dos impactos potenciais das mudanças no uso e manejo do solo é fundamental para propiciar uma gestão sustentável dos recursos naturais como solo e água. Neste estudo foram avaliados os processos hidrológicos, a produção de sedimentos e a transferência de fósforo na bacia hidrográfica do Arroio Lino, por meio do modelo Soil and Water Assessment Tool (SWAT). A pequena bacia (4,18 km2 ) localiza-se no sul do Brasil e seu principal uso da terra é a cultura de fumo sob plantio convencional. As vazões e a produção de sedimentos medidos no exutório da bacia foram utilizadas para análise de sensibilidade, calibração e validação dos parâmetros do modelo. Cargas de fósforo em quatro sub-bacias (A1, A2, B, C) e no exutório foram utilizados para a análise de sensibilidade e calibração do modelo. A análise de sensibilidade foi feita com o uso de um algoritmo que combina as técnicas de Hipercubo Latino (LH) e One-factor-At-a-Time (OAT). A calibração foi realizada com o algoritmo Shuffled Complex Evolution (SCE-UA). Análises gráficas e medidas estatísticas foram utilizadas para verificar as previsões do modelo. Adaptações nos parâmetros do modelo foram feitas durante as etapas de calibração e validação, tendo em vista a realidade da região em que a bacia está localizada. Na simulação de vazões mensais obtiveram-se valores do índice de eficiência de Nash e Sutcliffe (NSE) de 0,87 na calibração e 0,76 na validação. Com o intuito de representar melhor os processos de deposição de sedimentos nas encostas, o modelo SWAT foi modificado com a incorporação de um termo de capacidade de transporte de sedimentos na paisagem. Com a nova rotina de sedimentos obteve-se um melhor desempenho durante a calibração (NSE de 0,70) em relação ao modelo SWAT original (NSE de -0,14). As simulações com o modelo modificado foram satisfatórias para o transporte de sedimentos em diferentes posições da paisagem. Os resultados sugerem que a integração da rotina de deposição de sedimentos no SWAT aumenta a precisão do modelo de previsões em áreas mais íngremes e, ao mesmo tempo, melhora significativamente a capacidade de prever a distribuição espacial das áreas de deposição de sedimentos. As previsões de cargas de fósforo foram na ordem de grandeza das cargas medidas; no entanto, o modelo não conseguiu prever satisfatoriamente as cargas de fósforo em três sub-bacias (A1, A2 e B). Apesar das lavouras ocuparem apenas 29% da área total da bacia, de acordo com a simulação elas são a principal fonte de nutrientes na bacia hidrográfica (80%). Após a calibração da vazão, da produção de sedimentos e de fósforo, foi realizada a simulação de cenários de manejo do solo na bacia hidrográfica do Arroio Lino. Três cenários de práticas de manejo: preparo convencional (PC), cultivo mínimo (CM) e plantio direto de cultivo (NT) com redução de 50% da taxa de aplicação de fertilizantes foram testados durante um período de 30 anos. A prática de plantio direto não afetou significativamente o escoamento, no entanto afetou fortemente a produção de sedimentos devido à redução da erosão do solo. Houve redução das perdas de fósforo principalmente devido à redução das doses de fertilizantes. Os resultados indicam que as práticas de preparo convencional do solo deveriam ser substituídas por práticas de cultivo mínimo ou direto, a fim de minimizar os impactos ambientais causados por um determinado uso do solo.

O entendimento da dinâmica hidrossedimentológica em uma bacia hidrográfica pode ser realizado pelo monitoramento das variáveis hidrossedimentológicas e pela modelagem desses processos. Nesse contexto, essa pesquisa analisou a eficiência do modelo Soil and Water Assessment Tool (SWAT) na previsão dos processos hidrossedimentológicos na bacia do Taboão (Pejuçara, RS), considerando as saídas (vazão e produção de sedimentos) em um passo de tempo mensal e diário. Para tal, foram utilizados dados de chuva horária dos anos 2008 a 2016, monitorada em quatro pluviógrafos instalados na bacia (PVGs 34, 40, 43 e 51), e dados climáticos da estação meteorológica de Cruz Alta. As informações de vazão, para os anos de 2011 a 2016, foram obtidas por meio da conversão dos dados de nível de água monitorados no exutório da bacia, utilizando uma curva-chave cota x vazão. A concentração de sedimentos suspensos (CSS), para os anos de 2013 a 2015, foi estimada por meio de modelos de redes neurais artificias (RNAs), empregando como entrada dados de turbidez e de nível de água, monitorados no exutório da bacia. O preenchimento das falhas dos registros de precipitação horária foi executado por meio de modelos de Combinações de RNAs (CRNAs) associados à média simples (MS) ou à média ponderada pelo inverso da distância (MP), utilizando como entrada dados pluviométricos dos postos vizinhos. As falhas nos dados de nível de água foram preenchidas por modelos de RNAs, que usaram como entrada níveis de água monitorados em sub-bacias embutidas ou adjacente à bacia do Taboão (bacias do Donato, Turcato, Alemão e Andorinhas), e dados de precipitação média dos quatro pluviógrafos utilizados nessa pesquisa Foram determinadas as defasagens temporais entre os níveis de água das diferentes bacias, e testados o uso da precipitação média com aplicação de filtro temporal linear e/ou exponencial. Os registros falhos nos dados de turbidez foram preenchidos por modelos de RNAs, que empregaram como entrada informações de nível de água monitoradas, de 10 em 10 minutos, no exutório da bacia. A calibração do modelo SWAT para a previsão dos processos hidrológicos foi realizada usando dados de vazão, diários e mensais, para os anos de 2013, 2014 e 2016 e; a etapa de verificação foi executada para os anos de 2011 e 2015. Considerou-se o Método de Green & Ampt para determinação da infiltração de água no solo e 2 anos (2008-2009) para período de aquecimento do modelo SWAT. A calibração do modelo para a produção de sedimentos foi realizada para os anos de 2013 e 2015 e o processo de verificação foi efetuado para o ano de 2014. A calibração e a análise de sensibilidade dos parâmetros foram realizadas com auxílio do SWAT-CUP, utilizando o algoritmo SUFI-2. O coeficiente de Nash–Sutcliffe (NS) das RNAs para preenchimento das falhas de precipitação variou entre 0,35, classificado como “Insatisfatório”, e 0,86, avaliado como “Muito Bom”, considerando critérios propostos por Moriasi et al. (2007). Das 13 RNAs desenvolvidas para preenchimento das falhas nos níveis de água, apenas uma delas foi classificada como de desempenho “Satisfatório” durante o treinamento e; as demais enquadraram-se como de desempenho “Muito Bom”. Na etapa de verificação, sete RNAs foram consideradas com desempenho “Muito Bom” e cinco com “Bom” desempenho No preenchimento das falhas de turbidez, das cinco RNAs desenvolvidas, quatro mostraram “Bom” desempenho durante o treinamento, e uma rede teve desempenho “Muito Bom”; enquanto que, no processo de verificação, duas RNAs tiveram desempenho “Muito Bom”, uma delas foi classificada com desempenho “Bom” e; duas RNAs foram consideradas com desempenho “Satisfatório”. As estatísticas de desempenho dos modelos de RNAs desenvolvidos para o preenchimento das falhas de nível de água, de turbidez e de precipitação também demonstraram que tais redes representam uma alternativa interessante para a obtenção de séries contínuas desses dados, possibilitando o uso posterior dos registros para a modelagem hidrossedimentológica. A calibração do modelo SWAT para estimativa da vazão mensal mostrou desempenho “Muito Bom” (NS=0,78), e para a determinação da vazão diária foi considerado “Bom” (NS=0,72). Na etapa de verificação, o modelo manteve o “Bom” desempenho (NS=0,68) para estimativa da vazão diária, decaindo para desempenho “Satisfatório” (NS=0,64) para a simulação em escala mensal. Para a estimativa da produção de sedimentos mensal, o desempenho do modelo foi considerado “Bom” tanto na calibração (NS=0,66) quanto na verificação (NS=0,70). Na escala diária o desempenho foi “Satisfatório” para a calibração (NS=0,64) e “Insatisfatório” para a verificação (NS=0,38) Tais resultados indicam que o modelo SWAT é uma ferramenta promissora para aplicações na previsão hidrossedimentológica na bacia do Taboão, especialmente em termos de simulações dos processos hidrológicos. No entanto, existem limitações para aplicações na estimativa da produção de sedimentos, sobretudo quando considerados os processos em escala diária. Essas limitações são consequência da presença de processos erosivos na bacia (voçorocas), que não são simulados pelas rotinas presentes no modelo SWAT, bem como pelo escoamento dominante ser do tipo subsuperficial, com ocorrência de pipping; indicando-se, portanto, adequações nas rotinas do modelo para melhor representatividade desses processos. / The understanding of hydrosedimentological dynamics in a watershed can be obtained by monitoring the hydrossedimentological variables and by modeling these processes. In this context, this research analyzed the efficiency of the Soil and Water Assessment Tool (SWAT) in predicting the hydrosedimentological processes in the Taboão basin (Pejuçara, RS), considering the outputs (flow and sediment production) in a monthly and daily time step. For that, hourly rainfall data from 2008 to 2016 were monitored at four pluviographs installed in the basin (PVGs 34, 40, 43 and 51), and climate data were obtained from the Cruz Alta meteorological station. The flow information for the years 2011 to 2016 was obtained by converting the monitored water level data into flow by using a rating curve. The suspended sediment concentration (SSC), from 2013 to 2015, was estimated using artificial neural network (ANN) models, using as input turbidity and water level data, monitored in the basin. The filling of the hourly rainfall records was performed by models of Combinations of RNAs (CRNAs) associated with the simple mean (MS) or weighted mean to the inverse distance (MP), using as input rainfall data from the neighboring stations. Failures in the water-level data were filled by RNA models, which used as input water levels monitored in sub-basins adjacent or embedded to the Taboão basin (Donato, Turcato, Alemão and Andorinha basins), and mean precipitation data of the four pluviographs used in this research. The temporal lags between the water levels of the different basins were determined and the use of the average precipitation with linear and exponential temporal filters was tested The turbidity data records were filled by RNA models, using water level information monitored at every 10 minutes. The SWAT model calibration for predicting the hydrological processes was performed using daily and monthly flow data for the years 2013, 2014 and 2016 and the verification step was performed for the years 2011 and 2015; considering Green & Ampt Method for infiltration estimation and 2 years of warm-up period (2008-2009). The calibration of the model for sediment yield was performed for the years 2013 and 2015 and the verification process was carried out for the year 2014. The calibration and sensitivity analysis of the parameters were performed with the assistance of SWAT-CUP, using the SUFI-2 algorithm. The Nash-Sutcliffe Coefficient (NS) of the RNAs used to fill precipitation faults varied between 0.35, classified as "Unsatisfactory", and 0.86, evaluated as "Very Good", considering criteria proposed by Moriasi et al. (2007). Of the 13 RNAs developed to fill water level failures, only one of them was classified as a "Satisfactory" performance during training and; the others have been classified as "Very Good" performance. In the verification step, seven RNAs were considered to have "Very Good" performance and five had "Good” performance. In the fulfillment of the turbidity faults, of the five RNAs developed, four showed "Good" performance during the training, and one network had "Very Good" performance; while in the verification process two ANNs performed "Very Good", one of them was classified as "Good" and; two ANNs were considered to have "Satisfactory" performance The performance statistics of the ANN models developed to fill the water level, turbidity and precipitation failures also demonstrated that such networks represent an interesting alternative to obtain continuous series of these data, allowing the later use of the records for hydrossedimentological modeling. In the verification processes, the model maintained a “Good” performance (NS=0.68) to estimate the daily flow, decreasing to "Satisfactory" performance (NS=0.64) for the monthly scale simulation. For the estimation of sediment yield the model performance was considered "Good" for monthly calibration period (NS=0.66) and also for the verification (NS=0.70). In daily scale the performance was "Satisfactory" for calibration (NS=0.64) and “Unsatisfactory” in the verification (NS=0.38). These results indicate that the SWAT model is a promising tool for applications in the hydrosedimentological forecasting in the Taboão basin, especially in terms of hydrological processes simulations. However, there are limitations to applications in the estimation of sediment production, especially when considering daily scale processes. These limitations are due to the presence of erosive processes in the basin (gully erosion), which are not simulated by the routines present in the SWAT model, as well as by the existence of the lateral flow with occurrence of pipping; indicating, therefore, the need for adjustments in the routines of the model to better represent these processes.

Submitted by Emanuel Varela Cardoso (emanuel.varela@ufcg.edu.br) on 2018-09-19T19:31:31Z No. of bitstreams: 1 EDIVALDO AFONSO DE OLIVEIRA SERRÃO – DISSERTAÇÃO (PPGMet) 2018.pdf: 5221512 bytes, checksum: 0bb1b4ee7c18b4cae80a1e0ca7a742f9 (MD5) / Made available in DSpace on 2018-09-19T19:31:31Z (GMT). No. of bitstreams: 1 EDIVALDO AFONSO DE OLIVEIRA SERRÃO – DISSERTAÇÃO (PPGMet) 2018.pdf: 5221512 bytes, checksum: 0bb1b4ee7c18b4cae80a1e0ca7a742f9 (MD5) Previous issue date: 2018-02-23 / CNPq / A bacia amazônica representa a maior extensão de florestas tropicais da Terra, exercendo significativa influência no clima local e global devido aos fluxos de energia e água na atmosfera. Exerce um papel importante no sequestro de carbono, bem como na emissão de água para a atmosfera que é fundamental na manutenção da própria floresta. Vários modelos hidrológicos têm sido aplicados para os biomas do Brasil, desde bases conceituais até a inserção dos SIG’s desenvolvendo os modelos distribuídos de base física. Dentre estes, o Soil and Water Assessment Tool – SWAT é um modelo hidrológico para grandes bacias e foi desenvolvido para simular processos que ocorrem em uma bacia hidrográfica. O objetivo desse trabalho foi utilizar o modelo SWAT para simular a vazão fluvial, alguns processos hidrológicos e risco de erosão da bacia hidrográfica do rio Itacaiúnas, sudeste do Estado do Pará, bem como sua calibração e validação do modelo para a bacia de estudo. Para isto foram necessários dados de uso e ocupação do solo, tipos de solo, declividade. Bem como dados climáticos e fluviométricos de precipitação, temperatura, vento, umidade relativa, radiação solar e vazão fluvial. Os resultados demostraram que para a análise do risco de erosão para a bacia hidrográfica do rio Itacaiúnas foi constatado que ás áreas de maior risco para erosão, foram ás regiões de maior altitude com solos de fácil degradação e com uma dinâmica de uso de solo elevada, sendo estas na jusante da bacia e na porção sul do município de Marabá. Na validação da vazão obtida através do modelo SWAT, foi observado que todos os índices estatísticos aplicados mostraram que a vazão simulada tive um bom desempenho, em relação a vazão observada na estação fluviométrica da ANA. Foi validado ainda a evapotranspiração potencial simulada pelo SWAT, a partir de outros dois métodos, Linacre e Turc e observou-se que todos os índices estatísticos aplicados a evapotranspiração simulada com SWAT tive um bom desempenho em relação aos outros dois métodos de estimar evapotranspiração. Já na comparação dos métodos de Linacre teve um menor desempenho, em relação ao método de Turc, haja visto que na estimativa feita por Turc é levado em consideração radiação solar, o que torna o método mais robusto em relação a Linacre. Logo o modelo SWAT teve um bom desempenho em simular a vazão, evapotranspiração e outros processos hidrológicos para a bacia hidrográfica do rio Itacaiúnas e pode ser uma fundamental ferramenta no monitoramento hidrológico dessa bacia, além de auxiliar os tomadores de decisões em uma boa gestão dos seus recursos. / The Amazon basin represents the largest expanse of tropical rainforests on Earth, exerting significant influence on the local and global climate due to the energy and water fluxes in the atmosphere. It plays an important role in carbon sequestration as well as in the emission of water into the atmosphere that is essential in maintaining the forest itself. Several hydrological models have been applied to the biomes of Brazil, from conceptual bases to the insertion of the GIS, developing the distributed models of physical base. Among these, the Soil and Water Assessment Tool - SWAT is a hydrological model for large basins and was developed to simulate processes that occur in a watershed. The objective of this work was to use the SWAT model to simulate river flow, some hydrological processes and risk of erosion of the Itacaiúnas river basin, southeast of the State of Pará, as well as its calibration and validation of the model for the study basin. For this, data on land use and occupation, soil types and slope were required. As well as climatic and fluviometric data of precipitation, temperature, wind, relative humidity, solar radiation and river flow. The results showed that for the analysis of the erosion risk for the Itacaiúnas river basin, it was found that the areas with the highest risk for erosion were the highest altitude areas with easily degraded soils and a high soil use dynamics, being these downstream of the basin and in the southern portion of the municipality of Marabá. In the validation of the flow obtained through the SWAT model, it was observed that all the applied statistical indices showed that the simulated flow had a good performance, in relation to the flow observed in the fluviometric station of the ANA. It was also validated the potential evapotranspiration simulated by SWAT, from two other methods, Linacre and Turc, and it was observed that all the statistical indices applied to simulated evapotranspiration with SWAT performed well in relation to the other two methods of estimating evapotranspiration. In the comparison of the methods of Linacre had a lower performance, in relation to the method of Turc, since in the estimation made by Turc is taken into consideration solar radiation, which makes the method more robust in relation to Linacre. The SWAT model performed well in simulating flow, evapotranspiration and other hydrological processes for the Itacaiúnas river basin and can be a fundamental tool in the hydrological monitoring of this basin, besides helping decision-makers in a good way. management of its resources.

O entendimento da dinâmica hidrossedimentológica em uma bacia hidrográfica pode ser realizado pelo monitoramento das variáveis hidrossedimentológicas e pela modelagem desses processos. Nesse contexto, essa pesquisa analisou a eficiência do modelo Soil and Water Assessment Tool (SWAT) na previsão dos processos hidrossedimentológicos na bacia do Taboão (Pejuçara, RS), considerando as saídas (vazão e produção de sedimentos) em um passo de tempo mensal e diário. Para tal, foram utilizados dados de chuva horária dos anos 2008 a 2016, monitorada em quatro pluviógrafos instalados na bacia (PVGs 34, 40, 43 e 51), e dados climáticos da estação meteorológica de Cruz Alta. As informações de vazão, para os anos de 2011 a 2016, foram obtidas por meio da conversão dos dados de nível de água monitorados no exutório da bacia, utilizando uma curva-chave cota x vazão. A concentração de sedimentos suspensos (CSS), para os anos de 2013 a 2015, foi estimada por meio de modelos de redes neurais artificias (RNAs), empregando como entrada dados de turbidez e de nível de água, monitorados no exutório da bacia. O preenchimento das falhas dos registros de precipitação horária foi executado por meio de modelos de Combinações de RNAs (CRNAs) associados à média simples (MS) ou à média ponderada pelo inverso da distância (MP), utilizando como entrada dados pluviométricos dos postos vizinhos. As falhas nos dados de nível de água foram preenchidas por modelos de RNAs, que usaram como entrada níveis de água monitorados em sub-bacias embutidas ou adjacente à bacia do Taboão (bacias do Donato, Turcato, Alemão e Andorinhas), e dados de precipitação média dos quatro pluviógrafos utilizados nessa pesquisa Foram determinadas as defasagens temporais entre os níveis de água das diferentes bacias, e testados o uso da precipitação média com aplicação de filtro temporal linear e/ou exponencial. Os registros falhos nos dados de turbidez foram preenchidos por modelos de RNAs, que empregaram como entrada informações de nível de água monitoradas, de 10 em 10 minutos, no exutório da bacia. A calibração do modelo SWAT para a previsão dos processos hidrológicos foi realizada usando dados de vazão, diários e mensais, para os anos de 2013, 2014 e 2016 e; a etapa de verificação foi executada para os anos de 2011 e 2015. Considerou-se o Método de Green & Ampt para determinação da infiltração de água no solo e 2 anos (2008-2009) para período de aquecimento do modelo SWAT. A calibração do modelo para a produção de sedimentos foi realizada para os anos de 2013 e 2015 e o processo de verificação foi efetuado para o ano de 2014. A calibração e a análise de sensibilidade dos parâmetros foram realizadas com auxílio do SWAT-CUP, utilizando o algoritmo SUFI-2. O coeficiente de Nash–Sutcliffe (NS) das RNAs para preenchimento das falhas de precipitação variou entre 0,35, classificado como “Insatisfatório”, e 0,86, avaliado como “Muito Bom”, considerando critérios propostos por Moriasi et al. (2007). Das 13 RNAs desenvolvidas para preenchimento das falhas nos níveis de água, apenas uma delas foi classificada como de desempenho “Satisfatório” durante o treinamento e; as demais enquadraram-se como de desempenho “Muito Bom”. Na etapa de verificação, sete RNAs foram consideradas com desempenho “Muito Bom” e cinco com “Bom” desempenho No preenchimento das falhas de turbidez, das cinco RNAs desenvolvidas, quatro mostraram “Bom” desempenho durante o treinamento, e uma rede teve desempenho “Muito Bom”; enquanto que, no processo de verificação, duas RNAs tiveram desempenho “Muito Bom”, uma delas foi classificada com desempenho “Bom” e; duas RNAs foram consideradas com desempenho “Satisfatório”. As estatísticas de desempenho dos modelos de RNAs desenvolvidos para o preenchimento das falhas de nível de água, de turbidez e de precipitação também demonstraram que tais redes representam uma alternativa interessante para a obtenção de séries contínuas desses dados, possibilitando o uso posterior dos registros para a modelagem hidrossedimentológica. A calibração do modelo SWAT para estimativa da vazão mensal mostrou desempenho “Muito Bom” (NS=0,78), e para a determinação da vazão diária foi considerado “Bom” (NS=0,72). Na etapa de verificação, o modelo manteve o “Bom” desempenho (NS=0,68) para estimativa da vazão diária, decaindo para desempenho “Satisfatório” (NS=0,64) para a simulação em escala mensal. Para a estimativa da produção de sedimentos mensal, o desempenho do modelo foi considerado “Bom” tanto na calibração (NS=0,66) quanto na verificação (NS=0,70). Na escala diária o desempenho foi “Satisfatório” para a calibração (NS=0,64) e “Insatisfatório” para a verificação (NS=0,38) Tais resultados indicam que o modelo SWAT é uma ferramenta promissora para aplicações na previsão hidrossedimentológica na bacia do Taboão, especialmente em termos de simulações dos processos hidrológicos. No entanto, existem limitações para aplicações na estimativa da produção de sedimentos, sobretudo quando considerados os processos em escala diária. Essas limitações são consequência da presença de processos erosivos na bacia (voçorocas), que não são simulados pelas rotinas presentes no modelo SWAT, bem como pelo escoamento dominante ser do tipo subsuperficial, com ocorrência de pipping; indicando-se, portanto, adequações nas rotinas do modelo para melhor representatividade desses processos. / The understanding of hydrosedimentological dynamics in a watershed can be obtained by monitoring the hydrossedimentological variables and by modeling these processes. In this context, this research analyzed the efficiency of the Soil and Water Assessment Tool (SWAT) in predicting the hydrosedimentological processes in the Taboão basin (Pejuçara, RS), considering the outputs (flow and sediment production) in a monthly and daily time step. For that, hourly rainfall data from 2008 to 2016 were monitored at four pluviographs installed in the basin (PVGs 34, 40, 43 and 51), and climate data were obtained from the Cruz Alta meteorological station. The flow information for the years 2011 to 2016 was obtained by converting the monitored water level data into flow by using a rating curve. The suspended sediment concentration (SSC), from 2013 to 2015, was estimated using artificial neural network (ANN) models, using as input turbidity and water level data, monitored in the basin. The filling of the hourly rainfall records was performed by models of Combinations of RNAs (CRNAs) associated with the simple mean (MS) or weighted mean to the inverse distance (MP), using as input rainfall data from the neighboring stations. Failures in the water-level data were filled by RNA models, which used as input water levels monitored in sub-basins adjacent or embedded to the Taboão basin (Donato, Turcato, Alemão and Andorinha basins), and mean precipitation data of the four pluviographs used in this research. The temporal lags between the water levels of the different basins were determined and the use of the average precipitation with linear and exponential temporal filters was tested The turbidity data records were filled by RNA models, using water level information monitored at every 10 minutes. The SWAT model calibration for predicting the hydrological processes was performed using daily and monthly flow data for the years 2013, 2014 and 2016 and the verification step was performed for the years 2011 and 2015; considering Green & Ampt Method for infiltration estimation and 2 years of warm-up period (2008-2009). The calibration of the model for sediment yield was performed for the years 2013 and 2015 and the verification process was carried out for the year 2014. The calibration and sensitivity analysis of the parameters were performed with the assistance of SWAT-CUP, using the SUFI-2 algorithm. The Nash-Sutcliffe Coefficient (NS) of the RNAs used to fill precipitation faults varied between 0.35, classified as "Unsatisfactory", and 0.86, evaluated as "Very Good", considering criteria proposed by Moriasi et al. (2007). Of the 13 RNAs developed to fill water level failures, only one of them was classified as a "Satisfactory" performance during training and; the others have been classified as "Very Good" performance. In the verification step, seven RNAs were considered to have "Very Good" performance and five had "Good” performance. In the fulfillment of the turbidity faults, of the five RNAs developed, four showed "Good" performance during the training, and one network had "Very Good" performance; while in the verification process two ANNs performed "Very Good", one of them was classified as "Good" and; two ANNs were considered to have "Satisfactory" performance The performance statistics of the ANN models developed to fill the water level, turbidity and precipitation failures also demonstrated that such networks represent an interesting alternative to obtain continuous series of these data, allowing the later use of the records for hydrossedimentological modeling. In the verification processes, the model maintained a “Good” performance (NS=0.68) to estimate the daily flow, decreasing to "Satisfactory" performance (NS=0.64) for the monthly scale simulation. For the estimation of sediment yield the model performance was considered "Good" for monthly calibration period (NS=0.66) and also for the verification (NS=0.70). In daily scale the performance was "Satisfactory" for calibration (NS=0.64) and “Unsatisfactory” in the verification (NS=0.38). These results indicate that the SWAT model is a promising tool for applications in the hydrosedimentological forecasting in the Taboão basin, especially in terms of hydrological processes simulations. However, there are limitations to applications in the estimation of sediment production, especially when considering daily scale processes. These limitations are due to the presence of erosive processes in the basin (gully erosion), which are not simulated by the routines present in the SWAT model, as well as by the existence of the lateral flow with occurrence of pipping; indicating, therefore, the need for adjustments in the routines of the model to better represent these processes.

<p></p><p></p><p>Land use alteration and climate change are major contributors to the hydrological cycle within watersheds. They can influence the quantity and quality of water resources, the ecosystem and environmental sustainability. Urban areas have expanded in recent decades, accompanied by a noticeable increase in energy and water use. Such changes in land use have many implications for humans to meet the increasing share of the planet’s resources and water issues. Hence, distinguishing the effects of land use change from concurrent climate variability is a particular challenge for studies on operational management processes. In this work, some shortcomings related to climate variability and land use change have been addressed, as applied to land surface temperature (LST) and groundwater resources. Thus, the main goal of this study is to evaluate the impacts of land use change on surface temperature and the impact of urbanization and climate variation on hydrology. The research methodology included modeling approaches that were used to estimate the land surface temperature and the responses of hydrology to climate change and urbanization.</p> <p>Land use maps derived from Landsat datasets were analyzed using several classification techniques to evaluate the intensity and pattern of urbanization and land surface temperature in the Greater Cairo Region (GCR), Egypt. Accuracy of Landsat derived land use data were relatively high and up to 96.5%. Findings indicated that the GCR land use alteration was dynamic and that vegetation loss was the main contributor to urban expansion in the GCR. Consequently, this led to increased LST and modified urban microclimate. The results showed that vegetation cover decreased by 7.73% within a 26-year timespan (1990-2016).</p> <p>Land use alteration impacted not only land surface temperature, but also, combined with variation in climate, affected watershed hydrology, specifically streamflow and baseflow. Changes in streamflow and filtered baseflow in three watersheds: Little Eagle Creek (LEC), Upper West Branch DuPage River (UWBDR) and Walzem Creek watershed, from 1980 to 2017, caused by climate alteration and land use change were separated and accessed using the SWAT (Soil and Water Assessment Tool) model. Results showed that SWAT performed well in capturing the streamflow and baseflow in urban catchments. SWAT model calibration and validation was within acceptable levels for streamflow and baseflow. About 30%, 30% and 12% of the LEC, UWBDR and Walzem Creek watershed areas changed from agricultural to urban areas. Findings for the LEC watershed indicated that the variability in the baseflow and streamflow appeared to be heavily driven by the response to climate change in comparison to the variability due to altered land use. The contribution of both land use alteration and climate variability on the flow variation was higher in the UWBDR watershed. In Walzem Creek, the alteration in streamflow and baseflow appeared to be driven by the effect of climate variability more than that of urbanization.</p> <p>Finally, the impacts of basin lithology and physical properties on baseflow were examined using multiple regression models. Results suggest that the baseflow index (BFI) can be predicted using the basin’s physical and geological characteristics. This included different land uses and climate variables with high accuracy and low relative errors. BFI was found to be highly driven by precipitation and fractional areas of different lithologies in the basins in various regions. These could be estimated with a high accuracy, as opposed to evapotranspiration that caused lower model accuracy.</p> <p>Information gleaned from these outputs can help in understanding the dynamics of land use change and climate variation, in order to help policy-makers predict and plan for future expansion in developing countries and across the globe, in achieving long-term sustainability of soil and water resources and their impact on climate change. Increasing efforts to prevent further urbanization and vegetation loss should be regarded as a practical management strategy and are of vital significance to many communities. In addition, the regression models developed in this study can be easily exploited in other areas with poor hydrological data quality and ungauged sites in order to estimate the amount of groundwater discharge.</p><p></p><p></p>

The contamination of rivers with nitrate from agricultural diffuse sources is not just a risk for ecosystems and their services, but also a health risk for water users. The Great Lakes (USA and Canada) are suffering from eutrophication problems. The Midwest is one of the richest farming land and one of the most productive areas on the planet. Thus, agriculture is one of the biggest drivers of local economies, accounting for billions of dollars of exports and thousands of jobs. The Midwest encompasses the Corn Belt region, a specialised system in corn production. Many of its agricultural basins drain into the Great Lakes. Corn requires a heavy amount of fertilizer to keep the best-yielding varieties. Some of the soils also require artificial drainage due to their low permeability, and to enable agriculture. The Cedar Creek watershed (CCW) in northeastern Indiana in the Corn Belt region is used as a case study area in this dissertation. Intensive agriculture in the CCW is characterised mainly by corn and soybean production. Tile drains are used, ejecting nitrate directly into the water. To find hotspots of nitrate is, then, crucial to avoid water quality deterioration. Identification of critical source areas of nitrate (CSAs) impairing waters is challenging. There are, mainly, two methodologies to identify hotspots of nitrate for the implementation of Best Management Practices (BMP): the targeting technique and the optimization approach. The targeting technique tends to identify hotspots based on loads of nitrate, omitting geomorphological watershed characteristics, costs for BMP implementation, and their spatial interactions. On the other hand, the parsimonious strategy does contemplate the trade-off of the economic and environmental contribution but requires sophisticated computational resources and it is more data-intense. This research presents a new framework based on the synergistic combination of both methodologies for the identification of CSAs in agricultural watersheds. Changes in watershed response due to alternative BMP applications were assessed using the model Soil and Water Assessment Tool (SWAT). Outputs in SWAT (nitrate export rates and nitrate concentration at the subbasin level) were used to evaluate the changes in water quality for the CCW. The newly developed targeting technique (HosNIT) considers SWAT outputs and intrinsic watershed parameters such as stream order, crop distance to the draining stream, and downstream nitrate enrichment/dilution effects within the river network. HosNIT establishes a workflow, based on a threshold system for the parameters considered, in order to spatially identify priority areas from where nitrate is reaching water. The more precise hotspots of nitrate are identified, the more improved the allocation of limited resources for conservation practices will be. HosNIT allows for a more spatially accurate CSAs identification, which enables a parsimonious optimization for BMP implementation. This parsimonious strategy will test BMP’s performance based on the environmental contribution and cost at the hotspots determined by HosNIT. The optimised solution for the CCW comes from the environmental contribution (decrease percentage of nitrate concentration at outlets) per dollar spent. For this case study means a year average of 3.7% of nitrate reduction with the optimised selection of scenarios for the studied period.

Pollution of surface and groundwater, due to improper land management, has become a major problem worldwide. Integrated watershed modelling provides a tool for the understanding of the processes governing water and matter transport at different scales within the watershed. The Soil Water Assessment Tool (SWAT) has been successfully utilized for the combined modelling of water fluxes and quality within a large range of scales and environmental conditions across the world. For suitable assessments integrated watershed models require large data sets of measured information for both model parameterization as for model calibration and validation. Data scarcity represents a serious limitation to the use of hydrologic models for supporting decision making processes, and may lead unsupported statements, poor statistics, misrepresentations, and, ultimately, to inappropriate measures for integrated water resources management efforts. In particular, the importance of spatially distributed soil information is often overlooked. In this thesis the eco-hydrological SWAT model was been applied to assess the water balance and diffuse pollution loadings of two rivers within a rural context at the mesoscale watershed level: 1) the Western Bug River, Ukraine, 2) the Águeda River, Portugal. Both watersheds in focus serve as examples for areas where the amount and quality of the measured data hinders a strait forward hydrologic modelling assessment. The Dobrotvir watershed (Western Bug River, Ukriane) is an example of such a region. In the former Soviet Union, soil classification primarily focused on soils of agricultural importance, whereas, forested, urban, industrial, and shallow soil territories were left underrepresented in the classification systems and resulting soil maps. Similarly the forest-dominated Águeda watershed in North-Central Portugal is a second example of a region with serious soil data availability limitations. Through the use of pedotransfer functions (PTFs) and the construction of soil-landscape models the data gaps could be successfully diminished, allowing a subsequent integrated watershed modelling approach. A valuable tool for the data gap closure was the fuzzy logic Soil Land Inference Model (SoLIM) which, combined with information from several soil surveys, was used to create improved maps. In the Dobrotvir watershed the fuzzy approach was used to close the gaps of the existing soil map, while in the Águeda watershed a new soil properties map, based upon the effective soil depths of the landscape, was constructed. While the water balance simulation in both study areas was successful, a calibration parameter ensemble approach was tested for the Águeda watershed. In the common modelling practice the individual best simulation and best parameter set is considered, the tested approach involved merging individual model outputs from numerous acceptable parameter sets, tackling the problematic of parameter equifinality. This procedure was tested for both original soil map and the newly derived soil map with differentiation of soil properties. It was noticeable that a better model set-up, with a better representation of the soil spatial distribution, was reflected in tighter model output spreads and narrower parameter distances. A further challenge was the calibration of water quality parameters, namely nitrate-N in the Dobrotvir watershed and sediment loads in the Águeda watershed. The limited amount of water quality observations were handled by assessing and by process verification at the smallest modelling unit, the hydrological response unit (HRU). The ruling hydrological processes could be depicted by combining own measured data and modelling outputs. The management scenario simulations showed the anticipated response to changes in management and reflected the rational spatial variation within the watershed reasonably well. The impacts of the different intervention options were evaluated on water balance, nitrate-N export and sediment yield at the watershed, sub-watershed and, when feasible, HRU level. This thesis covers two regional case studies with particular data limitations and specific processes of water and matter fluxes. Still, data reliability is a problem across the globe. This thesis demonstrates how relevant it is to tackle shortages of spatially differentiated soil information. The considered approaches contribute toward more reliable model predictions. Furthermore, the tested methods are transferable to other regions with differing landscape and climate conditions with similar problems of data scarcity, particularly soil spatially differentiated information.

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