O estoque de matéria orgânica de superfície refere-se a todo material orgânico decomposto ou em decomposição sobreposto ao solo mineral, bem como ao material orgânico misturado às partículas minerais do horizonte A. Este serve como indicador da funcionalidade e integridade de ecossistemas florestais quando o analisamos sob a perspectiva das "Formas de Húmus". Nesta perspectiva o material orgânico se presenta como disposto em camadas internas que variam no peso e espessura de acordo com a atuação dos agentes decompositores locais, e expressa a ciclagem de nutrientes que se dá a partir dos dois principais processos que sintetizam e/ou modulam o funcionamento dos ecossistemas, a produção e a decomposição da matéria orgânica. O modelo de formas de húmus segue uma classificação desenvolvida na Europa que não se aplica perfeitamente às áreas tropicais pela alta variabilidade de ambientes. Estima-se que fatores locais e particulares como características edáficas, estrutura e composição da vegetação, relevo e o microclima podem distorcer esta classificação e diferir significativamente do modelo global. Esta pesquisa buscou o refinamento deste modelo, buscando entender de que modo a pluviosidade efetiva (chuva que atravessa a copa das árvores e chega ao solo), como fenômeno de natureza microclimática, se relaciona com o estoque de matéria orgânica de superfície (sob a perspectiva das formas de húmus) em ambiente de floresta ombrófila montanhosa urbana.Para tal foram executadas análises físicas sobre o estoque de matéria orgânica de superfície, monitoramento da pluviosidade efetiva com pluviômetro experimentais adaptados para esta demanda e análises químicas sobre a água da chuva após lixiviação da matéria orgânica. Foi montada uma estrutura composta de quinze pluviômetros experimentais em uma encosta florestada no Parque Nacional da Tijuca (Rio de Janeiro - RJ) e instalação de pluviômetros eletrônicos em ambientes de céu aberto em áreas adjacentes a esta encosta pertencentes à área do parque. Os resultados indicam que da chuva que cai na floresta, cerca de 15% é interceptada pelas copas e o restante, parte é interceptada pela matéria orgânica do solo. A camada MFB (ou H) é a que retém mais água, indicando que, florestas que a decomposição é rápida no processo de fragmentação e lenta na mineralização, terão mais água retida no estoque de matéria orgânica. As diferentes camadas vão nutrir o solo de maneira diferenciada quando este processo deriva da lixiviação, como o cálcio que é liberado em a maior quantidade pelas camadas mais fragmentadas como a F e a MFB, o potássio e magnésio têm maior disponibilização quando deriva da camada L, indicando que durante este processo estes nutrientes são mais consumidos do que liberados. Foi perceptível que o sódio é bastante abundante na chuva antes mesmo de atingir a matéria orgânica, confirmando estudos anteriores. A utilização deste sistema proposto de pluviômetros experimentais possibilitou entender como esta estratificação interna do estoque de matéria orgânica de superfície acumula água, pois os métodos tradicionais não se baseiam no modelo de formas de húmus, e possibilitou ainda, o a análise do processo de lixiviação e liberação de nutrientes para o solo. / The organic matter stocks surface refers to any organic material in decomposition or decomposed superimposed on mineral soil, and the mixed organic material to the mineral particles of the horizon A. This serves as an indicator of the functionality and integrity of forest ecosystems when analyzed from the perspective of "Humus Forms." In this perspective the organic material presents as layered internal ranging in weight and thickness according to the activities of agents decomposers local and express nutrient cycling that occurs from the two main processes that synthesize and / or modulate the functioning of ecosystems, production and decomposition of organic matter. The model forms humus follows a classification developed in Europe that does not apply perfectly to tropical areas by high environmental variability. It is estimated that local and particular factors as soil characteristics, vegetation structure and composition, topography and microclimate can distort this classification and differ significantly from the global model.This study sought to refine this model, seeking to understand how the effective rainfall (rain crossing the canopy and reaches the ground), as a phenomenon of nature microclimate, relates to the stock of organic matter from the surface (from the perspective forms of humus) in an environment of urban mountainous rainforest.For such analyzes were performed on the physical stock of organic matter from the surface, the effective monitoring of rainfall with rain gauges experimental adapted to this demand and chemical analyzes of rain water after leaching of organic matter. Has assembled a structure composed of fifteen experimental gauges on a forested hill in the Tijuca National Park (Rio de Janeiro - RJ) and installation of electronic gauges in environments of open areas adjacent to slopes belonging to this area of ??the park.The results indicate that the rain that falls in the forest, about 15% is intercepted by the canopy and the remaining portion is intercepted by soil organic matter. The MFB layer (or H) is that retains more water, indicating that forests that the decomposition is faster in the process of fragmentation and slow mineralization have more water retained in the stock of organic matter. The different layers will feed the soil differently when this process is derived from the leaching, as the calcium that is released in the greatest quantity by the layers more fragmented as F and MFB, potassium and magnesium are derived from more readily available when the layer L, during this process indicates that these nutrients are consumed more than released. It was noticeable that sodium is quite abundant in the rain before reaching the organic matter, confirming previous studies. The use of this proposed system gauges experimental possible to understand how this internal stratification of the stock of organic matter accumulated water surface, as the traditional methods are not based on the type of humus forms, and possible further analysis of the the leaching process and release nutrients to the soil.

O estoque de matéria orgânica de superfície refere-se a todo material orgânico decomposto ou em decomposição sobreposto ao solo mineral, bem como ao material orgânico misturado às partículas minerais do horizonte A. Este serve como indicador da funcionalidade e integridade de ecossistemas florestais quando o analisamos sob a perspectiva das "Formas de Húmus". Nesta perspectiva o material orgânico se presenta como disposto em camadas internas que variam no peso e espessura de acordo com a atuação dos agentes decompositores locais, e expressa a ciclagem de nutrientes que se dá a partir dos dois principais processos que sintetizam e/ou modulam o funcionamento dos ecossistemas, a produção e a decomposição da matéria orgânica. O modelo de formas de húmus segue uma classificação desenvolvida na Europa que não se aplica perfeitamente às áreas tropicais pela alta variabilidade de ambientes. Estima-se que fatores locais e particulares como características edáficas, estrutura e composição da vegetação, relevo e o microclima podem distorcer esta classificação e diferir significativamente do modelo global. Esta pesquisa buscou o refinamento deste modelo, buscando entender de que modo a pluviosidade efetiva (chuva que atravessa a copa das árvores e chega ao solo), como fenômeno de natureza microclimática, se relaciona com o estoque de matéria orgânica de superfície (sob a perspectiva das formas de húmus) em ambiente de floresta ombrófila montanhosa urbana.Para tal foram executadas análises físicas sobre o estoque de matéria orgânica de superfície, monitoramento da pluviosidade efetiva com pluviômetro experimentais adaptados para esta demanda e análises químicas sobre a água da chuva após lixiviação da matéria orgânica. Foi montada uma estrutura composta de quinze pluviômetros experimentais em uma encosta florestada no Parque Nacional da Tijuca (Rio de Janeiro - RJ) e instalação de pluviômetros eletrônicos em ambientes de céu aberto em áreas adjacentes a esta encosta pertencentes à área do parque. Os resultados indicam que da chuva que cai na floresta, cerca de 15% é interceptada pelas copas e o restante, parte é interceptada pela matéria orgânica do solo. A camada MFB (ou H) é a que retém mais água, indicando que, florestas que a decomposição é rápida no processo de fragmentação e lenta na mineralização, terão mais água retida no estoque de matéria orgânica. As diferentes camadas vão nutrir o solo de maneira diferenciada quando este processo deriva da lixiviação, como o cálcio que é liberado em a maior quantidade pelas camadas mais fragmentadas como a F e a MFB, o potássio e magnésio têm maior disponibilização quando deriva da camada L, indicando que durante este processo estes nutrientes são mais consumidos do que liberados. Foi perceptível que o sódio é bastante abundante na chuva antes mesmo de atingir a matéria orgânica, confirmando estudos anteriores. A utilização deste sistema proposto de pluviômetros experimentais possibilitou entender como esta estratificação interna do estoque de matéria orgânica de superfície acumula água, pois os métodos tradicionais não se baseiam no modelo de formas de húmus, e possibilitou ainda, o a análise do processo de lixiviação e liberação de nutrientes para o solo. / The organic matter stocks surface refers to any organic material in decomposition or decomposed superimposed on mineral soil, and the mixed organic material to the mineral particles of the horizon A. This serves as an indicator of the functionality and integrity of forest ecosystems when analyzed from the perspective of "Humus Forms." In this perspective the organic material presents as layered internal ranging in weight and thickness according to the activities of agents decomposers local and express nutrient cycling that occurs from the two main processes that synthesize and / or modulate the functioning of ecosystems, production and decomposition of organic matter. The model forms humus follows a classification developed in Europe that does not apply perfectly to tropical areas by high environmental variability. It is estimated that local and particular factors as soil characteristics, vegetation structure and composition, topography and microclimate can distort this classification and differ significantly from the global model.This study sought to refine this model, seeking to understand how the effective rainfall (rain crossing the canopy and reaches the ground), as a phenomenon of nature microclimate, relates to the stock of organic matter from the surface (from the perspective forms of humus) in an environment of urban mountainous rainforest.For such analyzes were performed on the physical stock of organic matter from the surface, the effective monitoring of rainfall with rain gauges experimental adapted to this demand and chemical analyzes of rain water after leaching of organic matter. Has assembled a structure composed of fifteen experimental gauges on a forested hill in the Tijuca National Park (Rio de Janeiro - RJ) and installation of electronic gauges in environments of open areas adjacent to slopes belonging to this area of ??the park.The results indicate that the rain that falls in the forest, about 15% is intercepted by the canopy and the remaining portion is intercepted by soil organic matter. The MFB layer (or H) is that retains more water, indicating that forests that the decomposition is faster in the process of fragmentation and slow mineralization have more water retained in the stock of organic matter. The different layers will feed the soil differently when this process is derived from the leaching, as the calcium that is released in the greatest quantity by the layers more fragmented as F and MFB, potassium and magnesium are derived from more readily available when the layer L, during this process indicates that these nutrients are consumed more than released. It was noticeable that sodium is quite abundant in the rain before reaching the organic matter, confirming previous studies. The use of this proposed system gauges experimental possible to understand how this internal stratification of the stock of organic matter accumulated water surface, as the traditional methods are not based on the type of humus forms, and possible further analysis of the the leaching process and release nutrients to the soil.

I denna rapport undersöks hur mängden organiskt kol, TOC (Totalt organiskt kol), varierar i tid och rum i Mälarens avrinningsområde, samt vad det är som styr TOC-halten i Mälaren. Det är viktigt att förstå dynamiken hos TOC i Mälaren och i dess avrinningsområde eftersom ökat TOC i vattnet påverkar vattenkvaliteten och orsakar problem vid beredning av dricksvatten. TOC kan bland annat reagera med klor/UV-ljus och bilda cancerframkallande ämnen. Det kan också öka antal mikrober i vattnets distributionssystem. Arbetet omfattar analys av samband mellan elementen, transportberäkningar per ytenhet av elementen till Mälaren och en modelleringsansats för ett av avrinningsområdena. Rapporten innehåller även en jämförelse mellan de olika vattenföringsmodellerna samt uppmätt vattenföring för analys av eventuella systematiska skillnader mellan dessa som påverkar beräkningen av TOC och de andra elementens transport till Mälaren. Analysen av sambanden mellan variablerna TOC (mg/l), kaliumpermanganat förbrukning (KMnO4, mg/l), absorbans_F (F=filtrerad), järn (mg/l), mangan (mg/l) och SO4_IC (sulfat mätt med hjälp av jonkromatografi, mg/l), visade att vissa av dessa variabler är korrelerade med varandra. TOC mot KMnO4 och TOC mot absorbans_F hade de bästa anpassningarna med respektive R2- värden 0,65 och 0,59 och p-värden <0,001. Årsnederbörd är positivt korrelerad med TOC per ytenhet för Kolbäcksån med R2-värde 0,63 och p-värde <0,01, vilket innebär att sambandet är signifikant. Ökad årsnederbörd leder till ökad tillförsel av TOC till Mälaren. Det finns däremot inget signifikant samband mellan TOC-transport per ytenhet och årsmedeltemperatur. Arealflödesberäkningar tyder på att den största tillförseln av TOC- transport per ytenhet kommer från den nordöstra delen av Mälaren. Fyrisån står för den största tillförseln av TOC. Hydrologiska, kemiska och meteorologiska data inkluderades i modeller för att kunna skatta TOC-halten i Mälaren. Temperatur-, evapotranspirations- och nederbördsdata användes i en hydrologisk modell, HBV- modellen, för att simulera vattenföringen från avrinningsområdet. Sedan användes en processbaserad modell, INCA- C, som drivs av hydrologisk data och beräknade grundvattenbildning och markfuktighet för att simulera tidsmässiga mönster i TOC. Invariablerna till INCA-modellen, markfuktigheten och HER (grundvattenbildning), simulerades med hjälp av HBV- modellen. Dessa modeller tillämpades i Kolbäcksån (ett av Mälarens största avrinningsområden). Modelleringen av Kolbäcksåns TOC- halt resulterade i en modell som anpassade dynamiken mellan 1996 och 2009, men missar den mellan 2009 och juni 2010, med bäst anpassning mellan 2006 och 2008. R2- och NS värden som erhölls för modellen var 0,086 och -0,059. / In this report, it has been investigated how the amount of organic carbon, TOC, varies in time and space in the basin of Mälaren, and what controls the TOC content in the lake. It is important to understand the dynamics of the TOC in the lake and its catchment because increased TOC in the water affects water quality and causes problems in the preparation of drinking water. Particularly, it can react with chlorine / UV- light and form carcinogenic substances. It can also increase the number of microbes in water distribution systems. In addition the work includes analysis of the relation between water chemistry variables, annual fluxes calculations (g/m2/year) of element flows to the lake and a modeling approach to a watershed. Annual fluxes calculations (g/m2/year) indicate that the largest supply of TOC to the lake comes from the northeast of the lake. Fyrisån accounts for the largest input of TOC to the lake. The high TOC-flux is due to a small proportion of open water in the catchment. Hydrological, chemical and meteorological data have been included in models to estimate the TOC content in the Mälaren. Input data processing, especially precipitation data, has been an important part of the work as it affects the whole model. Temperature, evapotranspiration and precipitation data were used in a hydrological model, HBV model, to simulate the flow from the catchment area. Then a process-based model, INCA-C, operated by the hydrological data and soil moisture, has been used to simulate the temporal patterns in TOC. The input variables to INCA-C- model, soil moisture and HER (Hydrological effective rainfall), have been simulated using the HBV- model. Those models were applied in Kolbäcksån, one of the lake's largest catchments. The modeling of Kolbäcksån resulted in a model that captured the dynamics of a few periods of the whole time series. The modeling of Kolbäcksån TOC-concentration resulted in a model that captured the dynamics between 1996 and 2009, but misses it between 2009 and June 2010. R2 and NS values obtained for the model were 0.086 and -0.059, respectively.

Within the frame work of the International Water Research Alliance Saxony (IWAS), project “Middle East” a complex integrated water management system is developed and tested in the project region of Middle East (Oman and Saudi-Arabia). Hence, new solutions for a sustainable management of the scarce water resources in (semi-) arid regions are explored within IWAS in the sultanate of Oman on which this study work is carried out. Rainfall runoff models are established to estimate the “water yield” of the catchments in the project region. Modeling is a very important tool that enables hydrologists to make more comprehensive use of rainfall time series. Rainfall-runoff modeling is also useful for water resources assessment as these models can generate a long representative time series of stream flow volumes from which water supply schemes can be designed (D.A. Hughes, 1995). Therefore, this study project mainly focuses on the following main tasks such as data analysis, data processing and statistical evaluation; Model selection and model setup; Model adaptation test and verification. As part of the common modeling protocol, sensitivity analysis of a Rainfall-Runoff Modeling Toolbox (RRMT) is carried out in this study with the aim to identify sensitive model parameters. RRMT has been developed in order to produce parsimonious, lumped model structures with a high level of parameter identifiability. Such identifiability is crucial if relationships between the model parameters representing the system and catchment characteristics are to be established. RRMT is a modular framework that allows its user to implement different model structures to find a suitable balance between model performance and parameter identifiability. The study is carried out in the upper catchment part of Wadi Ma’wil (gauge near to Afi’), Batinah Region of the Sultanate of Oman. Arid and semi-arid zones are characterized by rainfall which is highly variable in space, time, quantity and duration (Noy-Meir, 1973). The Sultanate of Oman is characterized by hyper-arid (<100 mm rainfall), through the arid (100–250 mm rainfall) and semi-arid (250–500 mm rainfall) environments that are experienced in different parts of the country. Furthermore, arid areas have distinctive hydrological features substantially different from those of humid areas. The high temporal and spatial distribution of the rainfall, flash floods, absence of base flow, sparsity of plant cover, high transmission losses, high amounts of evaporation and evapotranspiration and the general climatologies are examples of such differences.:Acknowledgments i Abstract ii List of Figures and Photos v List of Tables and Plots v 1. Description of Study Area 1 1.1 General characteristics of arid regions 1 1.2 Study area (Batinah Region and Ma’awil catchment of gauge ‘Afi’) 2 1.2.1 Overview of Study area 2 1.2.2 Wadi Ma’awil and Gauge near to Afi’ 3 2. Data Processing and Evaluation 6 2.1 Rainfall data 6 2.1.1 Monthly and Annual Mean Rainfall Analyses 6 2.1.2 Estimation of Missing Precipitation Data 6 2.1.3 Annual and monthly average rainfall 6 2.2 Runoff data 9 2.2.1Rainfall-Runoff events – Processing and Analysis 9 2.2.2 Wadi Ma’awil Runoff Analysis 9 2.3 Areal Precipitation 11 2.3.1 Area 11 2.3.2 Summary of Calculated Results of Mean Annual Areal Precipitation 12 2.4 Evapotranspiration 13 2.4.1 Evaporation and Potential Evapotranspiration 13 2.4.2 Calculation of Evapotranspiration by FAO Penman-Monteith Equation 13 2.4.3 Sample Calculation for Daily ET using FAO Penman-Monteith Equation 14 2.4.4 Comparisons of Evapotranspiration Calculation Results 16 3. Rainfall-Runoff Modeling 16 3.1 Modeling approach – selection of modules 16 3.1.1 Basic Principle 16 3.1.2 Classification of models 16 3.1.3 Modeling Process 17 3.2 Rainfall-Runoff Modeling Toolbox 19 3.2.1 Introduction 19 3.2.2 Data Needs and Model Structure 20 3.3 Provision of input data 20 3.4 Calibration and Validation 20 3.4.1 Model Calibration and Validation 21 3.5 Sensitivity Analysis 22 3.6 Discussions of Results 23 3.6.1 Optimization Modules 23 3.6.2 Soil Moisture Accounting (SMA) Modules 24 3.6.3 Routing (R) Modules 25 3.6.4 The objective functions 26 3.6.5 Visualization Modules Results 27 3.7 Conclusions and Recommendations 35 3.7.1 Conclusions 35 3.7.2 Limitations and Recommendations 35 References 37 Appendix 38 Appendix A: Daily extraterrestrial radiation (Ra) for different latitudes for the 15th day of the month 38 Appendix B: Mean daylight hours (N) for different latitudes for the 15th of the month 38 Annexes 39 Annex - A: Mean Rainfall for the Gauge Afi’ from 1995 – 2005 39 Annex A-1: Annual Mean Rainfall for Gauge Afi’ for the time period 1995-2005 39 Annex A-2: Monthly Mean Rainfall for Gauge Afi’ for the time period 1995-2005 39 Annex A-3: Monthly Mean Rainfall for each Rain Gauge within the Wadi Ma’awil Catchment area for the time period 1995-2005 40 Annex - B: Rainfall - Runoff events for the Gauge Afi’ 41 Annex B-1: Annual Rainfall Vs Runoff events for the Gauge Afi’ from 1995 – 2005 42 Annex B-2: Monthly Rainfall Vs Runoff events for the Gauge Afi’ from 1995 – 2005 44 Annex B-3: Daily Rainfall Vs Runoff events for the Gauge Afi’ sample graphs with the time period from 1995to 2005 46