The knowledge of soil moisture is of pronounced importance in various applications e.g. flood control, agricultural production and effective water resources management. These applications require the knowledge of spatial and temporal variation of the soil moisture in the watershed. There are three approaches of estimating/measuring soil moisture namely,(i) in-situ measurements,(ii) remote sensing, and(iii) hydrological modelling. The in situ techniques of measurement provide relatively accurate information at point scale but are not feasible to gather in large numbers relevant for a watershed. The soil moisture can be simulated by hydrological models at the desired spatial and temporal resolution, but these simulations would often be affected by the uncertainties in the model physics, parameters, forcing, initial and boundary conditions. The remote sensing provides an alternative to retrieve the soil moisture of the surface (top few centimeters ) layer, but even this data is limited by the spatial or temporal resolution, which is satellite dependant. Hydrological models could be improved by assimilating remotely sensed soil moisture, which requires a retrieval algorithm. In order to develop a retrieval algorithm the satellite data need to be calibrated/validated with the in-situ ground measurements. The retrieval of surface soil moisture from microwave remote sensing is sensitive to surface conditions, and hence requires calibration/validation specific to a site/region. The improvement in the hydrological variables/fluxes is sensitive to the framework adopted during the assimilation of remotely sensed data. The main focus of the study was to assess the retrieval algorithm for the surface soil moisture from both active (ENVISAT,RADARSAT-2)and passive(AMSR-E) microwave satellites in a semi-arid tropical watershed of South India. Further, the usefulness of these retrieved remotely sensed products for the estimation of recharge was investigated by developing a coupled hydrological model and an assimilation framework. A brief introduction was made in Chapter 1 on the importance of surface soil moisture and evapotranspiration in hydrology, and the feasible options available for the retrieval from microwave remote sensing. A detailed review of the literature is presented in Chapter 2 to establish the state-of-the-art on the following:(i) retrieval algorithms for the surface soil moisture from active and passive microwave remote sensing,(ii) estimation of actual evapotranspiration from optical remote sensing(MODIS),(iii) coupled surface-ground water hydrological models,(iv) estimation of soil hydraulic properties with their uncertainties, and(v) assimilation framework specific to hydrological modelling. To calibrate/validate the retrieval algorithms and to test the coupled model and the assimilation framework developed, field measurements were carried out in the BerambadI experimental watershed located in the Kabini river basin. The surface soil moisture in 50 field plots, profile soil moisture up to 1m depth in 20 field plots, and ground water level in 200 bore wells were measured. Twelve images of ENVISAT, seven teen images of RADARSAT-2, along with AMSR-E and MODIS data were used. These data pertained to different durations during the period 2008 to 2011,the details of which are given in Chapter 3. The approach for the retrieval of surface soil moisture and the associated uncertainty from active and passive microwave remote sensing is given in Chapter 4. Surface soil moisture was retrieved for six vegetation classes using the linear regression model and copulas. Three types of copulas(Clayton, Frank and Gumbel) were investigated. It was found that the ensemble mean simulated using the linear regression model and three copulas was nearly same. The copulas were found to be superior than the linear regression model when comparing the distributions of the mean of the generated ensemble. Among the copulas it was observed that the Clayton copula performed better in the lower and middle ranges of backscatter coefficient, while the Gumbel and Frank copulas were found to be superior in the upper ranges of backscatter coefficients. The range of RMSE was approximatively 4cm3cm−3 indicating that the retrieval from ENVISAT/RADARSAT-2 was good. ACDF based approach was proposed to retrieve the surface soil moisture map for the watershed with a spatial resolution of 100m x 100m ( i.e one hectare). The map of the uncertainty in the retrieved surface soil moisture was also prepared using the Clayton copula. The AMSR-E surface soil moisture product was calibrated for the watershed during the period 2008 to 2011, using the map generated from the ENVISAT/RADARSAT data. They Clayton copula was used to generate the ensemble of the corrected AMSR-E surface soil moisture. The standard deviation of the generated ensemble varied from 0.01 to 0.03cm3cm−3 ,hence the derived surface soil moisture product for Berambadi was found to be good. In the Chapter 5, a one dimensional soil moisture model was developed based on the numerical solution of the Richards’ equation using finite difference method and inverse modeling was carried out using the Generalized Likelihood Uncertainty Estimation(GLUE) approach for estimating the soil hydraulic parameters of the van Genuchten(VG) model and their uncertainty. The parameters were estimated from the two field sites(Berambadi and Wailapally watershed in South India) and from laboratory evaporation experiment for the Wailapally site. It was found that the GLUE approach was able to provide good uncertainty bounds for the soil hydraulic parameters. The uncertainty in the estimates from the field experiment was found to be higher than from the laboratory evaporation experiment for both water retention and hydraulic conductivity curves. The saturated soil moisture(θs )and shape parameter (n) of VG model estimated from the laboratory evaporation and field experiment were found to be the same, and further more they showed a lower uncertainty from both the experiments. Moreover, the residual soil moisture (θr), inverse of capillary fringe thickness (α) and saturated hydraulic conductivity( KS) showed a relatively higher uncertainty. In the Berambadi watershed ,the inverse modeling was performed in three bare field plots, and it was found that field plots which had higher θs showed a relatively higher actual evapotranspiration (AET) and lower potential recharge. In Chapter 6, the retrieval of profile soil moisture up to 2m by assimilation of surface soil moisture was investigated by performing synthetic experiments on six soil types. The measured surface soil moisture over top 5cm depth was assimilated into the one dimensional soil moisture model to retrieve the profile soil moisture. Even though the assimilation of surface soil moisture helped in improving the profile soil moisture for the six soil types, the bias was observed. To reduce the bias, pseudo observations of profile soil moisture were generated and used in addition to the surface soil moisture in the assimilation altogether. These pseudo observations were generated using the linear relationship existing between the surface and profile soil moisture. A significant bias reduction was found to be feasible by using this method when pseudo observations beyond 75cm depth were used then there was no significant improvement. A coupled surface-ground water model was developed, which had 5 layers for the vadose zone and one layer for the ground water zone, in order to consider the major hydrological processes from ground surface to ground water table in a semi-arid watershed. The details of the coupled model were described in Chapter 7. The major aim of this model was to be able to use remotely sensed data of surface soil moisture and evapotranspiration to simulate recharge. The model was tested by applying in a lumped framework to the field data set in the Berambadi watershed for the year 2010 to 2011. The performance of the model was evaluated with the measured watershed average root zone soil moisture and ground water levels. The watershed average root zone soil moisture was obtained by averaging the field measurements from 20 plots and average ground water level was obtained by averaging the field measurement from 200 bore wells. In order to assimilate the AET into the coupled model, the daily AET at a spatial resolution of 1km was estimated from MODIS data. The AET was validated in one forested and four agricultural sites in the watershed. The validation was based on the comparison with AET simulated from water balance models. For agricultural plots the STICS (crop model) and for the forested site the COMFORT (hydrological) model were used. The AET from the MODIS showed a reasonably good match with both the forested and agricultural plots at the annual scale (for the crop model approximately 4-5 months). Model simulations were carried out with and without assimilating the remotely sensed data and the performance was evaluated. It was found that the assimilation helped in capturing the trends in deeper layer soil moisture and groundwater level. At the end, in Chapter 8 the major conclusions drawn from the various chapters are summarized.

Aux Antilles, la disponibilité limitée des ressources en contexte insulaire et l'activité agricole à aux niveaux d'intrants fragilisent les ressources en eau. Dans les zones bananières à forts niveaux d'intrants, des phénomènes de pollution des eaux sont particulièrement marqués, notamment du fait de l'usage d'un pesticide, la chlordécone. La connaissance du fonctionnement des systèmes hydrologiques à l'échelle du bassin versant représente un enjeu primordial pour pouvoir estimer l'exposition de l'écosystème aux pollutions et pour prévoir l'évolution des contaminations dans le temps. L'objectif de la thèse a été de développer une modélisation mécaniste représentant les processus hydrologiques de surface et souterrains à l'échelle d'un bassin versant sur substrat volcanique, sous climat tropical humide, situé en zone bananière en Guadeloupe. En premier a été développé un modèle parcellaire de bilan hydrique adapté au cas des cultures bananières. Il a pour originalité de prendre en compte l'importante redistribution de pluie opérée par le couvert bananier et d'en simuler les effets en matière d'intensité et d'hétérogénéité intra-parcellaire sur les termes du bilan hydrique. Les résultats d'analyse de sensibilité montrent que la redistribution de la pluie augmente le ruissellement de surface ainsi que la percolation, en cohérence avec les observations de terrain, mais impacte peu ou temporairement l'évapotranspiration et l'humidité du sol. Le calage du modèle sur des données expérimentales indiquent une performance améliorée de la simulation du ruissellement par rapport à un modèle ignorant le mécanisme de redistribution. En second, le bassin versant expérimental de Féfé (17.8 ha) a fait l'objet d'une approche de modélisation intégrant processus hydrologiques de surface et souterrains basée sur un chaînage itératif des modèles MHYDAS et MODFLOW. Confrontée à une année hydrologique de mesures de débits à l'exutoire et de piézométries, l'approche de chaînage de modèles de surface et souterrain apparaît pertinente. Une limite majeure est toutefois la non prise en compte de la zone non saturée dans le processus de recharge des aquifères. L'analyse des simulations et de leurs écarts avec les données observées conforte plusieurs hypothèses issues des analyses expérimentales : un ruissellement de surface fortement hortonien, une contribution majeure des écoulement souterrains au débit à l'exutoire. Elle indique toutefois également une indétermination des processus majeurs lors des périodes de fortes pluies. Différentes hypothèses sont proposées qu'il conviendra d'évaluer dans des travaux futurs. Ce travail constitue une première étape pour évaluer les chemins d'écoulement majeurs et les dynamiques des contaminations par les produits phytosanitaires dans un milieu volcanique tropical sous culture bananière. / In the French West Indies (FWI), limited resources supply on island and farming with extensive uses of pesticides have damaged water resources. In environments under intensive banana production, water pollution can be of particular concern, with regards to the use of chlordecone, an insecticide to control the banana weevil. Understanding the hydrological behaviour of a catchment is a challenge in assessing the exposure of the ecosystem to pollutions and in predicting the long-term contamination dynamics. This thesis aimed at developing a model to simulate de surface and underground hydrological processes at the catchment scale on volcanic deposits in a humid tropical area covered by banana plantations in Guadeloupe. First, we developed an original water budget model at the plot scale, adapted to the banana canopy. It takes into account the high rainfall redistribution by banana cover and simulates the effects of modified rainfall intensities and within-plot heterogeneities on the water balance components. The sensitivity analysis showed that rainfall redistribution promotes surface runoff and percolation, in accordance with the field observations, but influences little or only temporarily the average field evapotranspiration and soil moisture. The model calibration tested on experimental data indicated improved runoff production performances compared to a model without rainfall redistribution. Secondly, the Féfé experimental catchment (17.8 ha) was studied with a linked iterative modelling approach (of MHYDAS and MODFLOW) that includes surface and underground hydrological processes. Tested against a year of outlet discharge and water table depth measurements, the linked modelling approach seems appropriate. However, the main limit of this approach was that it does not consider the transfer through the unsaturated zone when simulating the aquifers' recharge. The analysis of the results and of the differences between measured and simulated variables supported the hypothesis, from experimental analyses, that: the surface runoff is mainly Hortonian, groundwater flow is the main contributor to runoff at the catchment outlet. However, there was still uncertainty concerning the main processes during wet periods. Various hypotheses were suggested and should be investigated in future studies. This work represents a first step towards the evaluation of the major flow paths and contamination dynamics of pesticides on volcanic deposits in a humid tropical area covered by banana plantations.

Ziel der Arbeit war die Beurteilung der räumlichen Verteilung und Struktur von Feldhecken hinsichtlich ihrer Wirkung für Hochwasser- und Naturschutz, sowie die Analyse von agrarökonomischen Faktoren, welche die Anlage von Hecken fördern beziehungsweise behindern. Folgende Fragen standen bei den Untersuchungen im Mittelpunkt: Wie muss eine Hecke sowohl aus naturschutzfachlicher als auch hydrologischer Sicht aufgebaut sein, um eine optimale Wirkung zu erzielen, und wie müssen die Rahmenbedingungen für Landwirte aussehen, damit Heckenstrukturen nicht nur erhalten, sondern auch neu angelegt werden können? Um diese komplexen Fragen zu beantworten, wurden verschiedene methodische Ansätze zur Analyse ökologischer, hydrologischer und entscheidungsbildender Prozesse gewählt. Um die Ergebnisse der verschiedenen Skalenarten (ordinal / kardinal) zu vergleichen und dabei aus verschiedenen Optionen eine für alle Ziele optimale Vorzugsvariante zu ermitteln, wurde am Ende eine Nutzwertanalyse durchgeführt. / There were two main purposes of the study; the evaluation of the spatial distribution and structural patterns of hedgerows in regard to their impact on flood prevention and nature conservation, and the investigation of factors facilitating or constraining the establishment of hedgerows. On the basis of this assessment, knowledge based recommendations were developed for the facilitation of hedgerows in agricultural landscapes in mountainous areas such as the Erzgebirge. The following questions were the main focus of the investigation: how should a hedgerow be composed to obtain the optimal effect from the nature conservation as well as the flood prevention point of view, and how should the general requirements for farmers be constructed so that hedgerows are not only maintained but also newly established. To answer these complex questions different methodologies were applied for analysing ecological, hydrological and decision-forming processes. In order to compare the results and hedgerow alternatives to determine the optimal choice, a value-benefit analysis was performed.

Land and water resources degradation are the major problems on the Ethiopian highlands. Poor land use practices and improper management systems have played a significant role in causing high soil erosion rates, sediment transport and loss of agricultural nutrients. So far limited meas-ures have been taken to combat the problems. In this study a physically based watershed model, SWAT2005 was applied to the Northern Highlands of Ethiopia for modelling of the hydrology and sediment yield. The main objective of this study was to test the performance and feasibility of SWAT2005 model to examine the influence of topography, land use, soil and climatic condi-tion on streamflows, soil erosion and sediment yield. The model was calibrated and validated on four tributaries of Lake Tana as well as Anjeni watershed using SUFI-2, GLUE and ParaSol algo-rithms. SWAT and GIS based decision support system (MCE analysis) were also used to identify the most erosion prone areas in the Lake Tana Basin. Streamflows are more sensitive to the hy-drological response unites definition thresholds than subbasin discretization. Prediction of sedi-ment yield is highly sensitive to subbasin size and slope discretization. Baseflow is an important component of the total discharge within the study area that contributes more than the surface runoff. There is a good agreement between the measured and simulated flows and sediment yields with higher values of coefficients of determination and Nash Sutcliffe efficiency. The an-nual average measured sediment yield in Anjeni watershed was 24.6 tonnes/ha. The annual aver-age simulated sediment yield was 27.8 and 29.5 tonnes/ha for calibration and validation periods, respectively. The SWAT model indicated that 18.5 % of the Lake Tana Basin is erosion potential areas. Whereas the MCE result indicated that 25.5 % of the basin are erosion potential areas. The calibrated model can be used for further analysis of the effect of climate and land use change as well as other different management scenarios on streamflows and soil erosion. The result of the study could help different stakeholders to plan and implement appropriate soil and water conser-vation strategies. / QC 20101123

Applications of the Soil and Water Assessment Tool (SWAT) are common. However, few attempts have focused on the tropics like in the Yen Bai province, Vietnam. Annual water-induced soil erosion (WSE) rates and surface runoff (SR) were estimated. The Nam Kim and Ngoi Hut watersheds were calibrated with accepted agreement between simulated and observed discharge. Correlations between precipitation, land covers, surface runoff and WSE were indicated. Although the estimated average WSE 4.1 t ha−1 year−1 (t ha−1 y−1) was moderate, some steep-bare areas were suffering serious soil loss of 26 t ha−1 y−1 and 15% of the province was calculated at the rate of 8.5 t ha−1 y−1. We found that the changes in WSE significantly correlated with land use changes. As calibrated SR matched closely with the measured data, we recommend SWAT applications for long-term soil erosion assessments in the tropics. / Những ứng dụng của mô hình công cụ đánh giá đất và nước (SWAT) đã được sử dụng phổ biến. Tuy nhiên có rất ít nghiên cứu tập trung vào khu vực nhiệt đới như tỉnh Yên Bái của Việt Nam. Trong nghiên cứu này, giá trị trung bình năm (2001-2012) nước chảy bề mặt (NCM) và xói mòn đất do nước (XM) đã được đánh giá trên cơ sở mô hình SWAT. Các thông số thủy văn của hai lưu vực sông là Nậm Kim và Ngòi Hút được tính toán và kiểm nghiệm với sự trùng hợp tương đối tốt giữa kết quả mô hình và số liệu thực đo. Mối liên hệ giữa lượng mưa, phủ bề mặt, NCM và XM cũng được phân tích và trình bầy chi tiết. Mặc dù giá trị XM năm được ước lượng ở mức trung bình cho toàn Tỉnh (4,1 tấn/ha/năm) nhưng ở một số khu vực nơi có độ dốc lớn và phủ mặt ít lại có lượng XM năm ở mức cao, 26 tấn/ha/năm và 15% tổng diện tích của Tỉnh có giá trị XM là 8,5 tấn/ha/năn. Kết quả nghiên cứu cho thấy sự liên hệ mật thiết giữa sự thay đổi phủ mặt tới giá trị XM. Trên cơ sở kết quả kiểm nghiệm mô hình khả quan, chúng tôi đề xuất sử dụng mô hình SWAT để đánh giá XM trong thời gian dài cho vùng nhiệt đới.

The Penman-Monteith (PM) equation is a state-of-the-art modelling approach to simulate evapotranspiration (ET) at site and local scale. However, its practical application is often restricted by the availability and quality of required parameters. One of these parameters is the canopy conductance. Long term measurements of evapotranspiration by the eddy-covariance method provide an improved data basis to determine this parameter by inverse modelling. Because this approach may also include evaporation from the soil, not only the ‘actual’ canopy conductance but the whole surface conductance (gc) is addressed. Two full cycles of crop rotation with five different crop types (winter barley, winter rape seed, winter wheat, silage maize, and spring barley) have been continuously monitored for 10 years. These data form the basis for this study. As estimates of gc are obtained on basis of measurements, we investigated the impact of measurements uncertainties on obtained values of gc. Here, two different foci were inspected more in detail. Firstly, the effect of the energy balance closure gap (EBCG) on obtained values of gc was analysed. Secondly, the common hydrological practice to use vegetation height (hc) to determine the period of highest plant activity (i.e., times with maximum gc concerning CO2-exchange and transpiration) was critically reviewed. The results showed that hc and gc do only agree at the beginning of the growing season but increasingly differ during the rest of the growing season. Thus, the utilisation of hc as a proxy to assess maximum gc (gc,max) can lead to inaccurate estimates of gc,max which in turn can cause serious shortcomings in simulated ET. The light use efficiency (LUE) is superior to hc as a proxy to determine periods with maximum gc. Based on this proxy, crop specific estimates of gc,maxcould be determined for the first (and the second) cycle of crop rotation: winter barley, 19.2 mm s−1 (16.0 mm s−1); winter rape seed, 12.3 mm s−1 (13.1 mm s−1); winter wheat, 16.5 mm s−1 (11.2 mm s−1); silage maize, 7.4 mm s−1 (8.5 mm s−1); and spring barley, 7.0 mm s−1 (6.2 mm s−1).

This thesis describes the conception and implementation of the hydrological model ArcEGMO-URBAN and its application to the basin of the Havel river in north-eastern Germany. The model has been developed in order to make up the balance of nitrogen and phosphorus inputs from point sources in urban areas on the scale of river basins. The nutrient input can be calculated with a high spatial resolution and according to its seasonal variation. At the same time, the impact of the rainfall on the nutrient input is being focused on in this project. ArcEGMO-URBAN models rainfall-runoff processes and pollution-transport processes in urban areas taking natural, technological and social parameters into consideration. Input data are meteorological and terrestrial data with a high spatiotemporal resolution as well as statistic data on the scale of municipalities. The digitally available spatial data are being analysed with GIS functions before the actual modelling and later merged to areas with similar attributes. Technological and social parameters are assigned to these areas which were derived from statistic data. The diversity of the input data and their high spatial resolution allow for the description of relevant processes differentiated on the scale of urban patches. The model considers different urban water technologies and their determined matter fluxes as well as different sewer systems. With regard to rainfall-runoff processes the following sub-processes are considered for this model: the runoff-generation and runoff-concentration on sealed surfaces, the runoff-transformation and combination with the dry weather flow in the sewer system, and the split-up of the runoff in retention tanks and waste water treatment plants. Referring to pollution-transport processes the following sub-processes are taken into account: the atmospheric pollution and surface pollution dependent on the type of land use, and the matter transport in the sewer system. The sub-processes of matter accumulation and matter erosion on the land surface can be calculated by using mean values of pollution or, more detailed, by using special functions for processes of accumulation as well as erosion. In order to guarantee an easy application, the model's conception allows the use of input data and parameters of varying accuracy. Both, either measurements or statistical data can be used for the calculation dependent on the available data. The model is programmed in "C" and, therefore, usable on every established computer system. The model's validation succeeds for several sub-processes as well as sub catchments. Results of the model's application in the basin of the Havel river illustrate that the model calculates similar annual matter loads when compared to established other models. Furthermore, the results show the potential of the model to calculate the seasonal variation of matter loads and to calculate scenarios by using GIS based parameters. ArcEGMO-URBAN therefore is a capable tool for the identification of nutrient input from point sources on the scale of river catchments. / Diese Arbeit beschreibt die Konzeption und Realisierung des Modells ArcEGMO-URBAN sowie die Modellanwendung im Flussgebiet der Havel. ArcEGMO-URBAN wurde entwickelt um die punktuell in Gewässer eingetragenen Frachten von Gesamtstickstoff und Gesamtphosphor aus urbanen Räumen auf der Ebene von Flussgebieten zu bilanzieren. Die Nährstoffeinträge werden mit einer hohen räumlichen Auflösung und in ihrer innerjährlichen Dynamik berechnet, wobei der Einfluss des Niederschlagsgeschehens auf die Stoffeinträge besonders thematisiert wird. ArcEGMO-URBAN modelliert die Niederschlags-Abfluss- und die Schmutz-Transport-Prozesse in urbanen Räumen unter Berücksichtigung von naturräumlichen, technologischen und sozialen Parametern. Eingangsgrößen sind meteorologische und terrestrische Daten mit einer hohen zeitlichen und räumlichen Auflösung sowie statistische Angaben auf Gemeindeebene. Die digital vorliegenden Flächendaten werden vor der Modellierung mittels GIS-Funktionen ausgewertet und zu Flächen mit gleichen Eigenschaften zusammengefasst. Diesen Flächen werden technologische und soziale Parameter zugeordnet, welche aus den statistischen Angaben abgeleitet wurden. Durch die hohe inhaltliche und räumliche Auflösung der Eingangsdaten können relevante Prozesse teilflächendifferenziert beschrieben werden. Es können sowohl unterschiedliche Wasserver- und -entsorgungstechnologien und die durch sie induzierten Stoffströme als auch unterschiedliche Kanalisationsverfahren berücksichtigt werden. Bezogen auf den Niederschlags-Abfluss-Prozess werden die Abflussbildung und Abflusskonzentration auf befestigten Flächen, die Abflusstransformation und Überlagerung mit dem Trockenwetterabfluss im Kanalnetz und die Abflussaufteilung an Sonderbauwerken bzw. Kläranlagen berechnet. Für die Berücksichtigung der Stoff-Transport-Prozesse werden die durch die Atmosphäre und spezifische Nutzungen bedingten Stoffeinträge sowie der durch die Kanalisation bestimmte Stofftransport berechnet. Die auf der Oberfläche stattfindenden Teilprozesse von Stoffakkumulation und -abtrag können über mittlere Verschmutzungswerte oder detailliert über Akkumulations- und Abtragsfunktionen berechnet werden. Um ein weites Anwendungsspektrum zu gewährleisten, ist das Modell so konzipiert, dass eine Parametrisierung mit Eingangsdaten unterschiedlicher Qualität möglich ist. Abhängig von der verfügbaren Datenbasis werden entweder konkrete Messwerte oder statistische Größen verwendet. Das Programm ist in "C" programmiert und damit auf jeder Rechnerarchitektur lauffähig. Die Validierung des Modells gelingt für einzelne Teilprozesse aber auch für Teilgebiete gut. Die Ergebnisse im Flussgebiet der Havel belegen, dass das Modell ähnliche jährliche Nährstofffrachten wie bereits eingeführte Modelle berechnet. Darüber hinaus zeigen die Ergebnisse das Potenzial des Modells, die innerjährliche Dynamik punktueller Stoffeinträge abzubilden und durch die GIS-gestützte Parametrisierung aufwandsarm Szenarien zu berechnen. Damit ist ArcEGMO-URBAN ein geeignetes Modell zur Bestimmung von Nährstoffeinträgen aus punktuellen Quellen auf der Ebene von Flussgebieten.

Extensive deforestations, particularly in the (sub)tropics, have led to intense soil degradation and erosion with concomitant reduction in soil fertility. Reforestations or plantations on those degraded sites may provide effective measures to mitigate further soil degradation and erosion, and can lead to improved soil quality. However, a change in land use from, e.g., grassland to forest may have a crucial impact on water balance. This may affect water availability even under humid tropical climate conditions where water is normally not a limiting factor. In this context, it should also be considered that according to climate change projections rainfall may decrease in some of these regions. To mitigate climate change related problems (e.g. increases in erosion and drought), reforestations are often carried out. Unfortunately, those measures are seldom completely successful, because the environmental conditions and the plant specific requirements are not appropriately taken into account. This is often due to data-scarcity and limited financial resources in tropical regions. For this reason, innovative approaches are required that are able to measure environmental conditions quasi-continuously in a cost-effective manner. Simultaneously, reforestation measures should be accompanied by monitoring in order to evaluate reforestation success and to mitigate, or at least to reduce, potential problems associated with reforestation (e.g. water scarcity). To avoid reforestation failure and negative implications on ecosystem services, it is crucial to get insights into the water balance of the actual ecosystem, and potential changes resulting from reforestation. The identification and prediction of water balance changes as a result of reforestation under climate change requires the consideration of the complex feedback system of processes in the soil-vegetation-atmosphere continuum. Models that account for those feedback system are Soil-Vegetation-Atmosphere-Transfer (SVAT) models. For the before-mentioned reasons, this study targeted two main objectives: (i) to develop and test a method combination for site evaluation under data scarcity (i.e. study requirements) (Part I) and (ii) to investigate the consequences of prediction uncertainty of the SVAT model input parameters, which were derived using geophysical methods, on SVAT modeling (Part II). A water balance modeling approach was set at the center of the site evaluation approach. This study used the one-dimensional CoupModel, which is a SVAT model. CoupModel requires detailed spatial soil information for (i) model parameterization, (ii) upscaling of model results and accounting for local to regional-scale soil heterogeneity, and (iii) monitoring of changes in soil properties and plant characteristics over time. Since traditional approaches to soil and vegetation sampling and monitoring are time consuming and expensive (and therefore often limited to point information), geophysical methods were used to overcome this spatial limitation. For this reason, vis-NIR spectroscopy (visible to near-infrared wavelength range) was applied for the measurement of soil properties (physical and chemical), and remote sensing to derive vegetation characteristics (i.e. leaf area index (LAI)). Since the estimated soil properties (mainly texture) could be used to parameterize a SVAT model, this study investigated the whole processing chain and related prediction uncertainty of soil texture and LAI, and their impact on CoupModel water balance prediction uncertainty. A greenhouse experiment with bamboo plants was carried out to determine plant-physiological characteristics needed for CoupModel parameterization. Geoelectrics was used to investigate soil layering, with the intent of determining site-representative soil profiles for model parameterization. Soil structure was investigated using image analysis techniques that allow the quantitative assessment and comparability of structural features. In order to meet the requirements of the selected study approach, the developed methodology was applied and tested for a site in NE-Brazil (which has low data availability) with a bamboo plantation as the test site and a secondary forest as the reference (reference site). Nevertheless, the objective of the thesis was not the concrete modeling of the case study site, but rather the evaluation of the suitability of the selected methods to evaluate sites for reforestations and to monitor their influence on the water balance as well as soil properties. The results (Part III) highlight that one needs to be aware of the measurement uncertainty related to SVAT model input parameters, so for instance the uncertainty of model input parameters such as soil texture and leaf area index influences meaningfully the simulated model water balance output. Furthermore, this work indicates that vis-NIR spectroscopy is a fast and cost-efficient method for soil measurement, mapping, and monitoring of soil physical (texture) and chemical (N, TOC, TIC, TC) properties, where the quality of soil prediction depends on the instrument (e.g. sensor resolution), the sample properties (i.e. chemistry), and the site characteristics (i.e. climate). Additionally, also the sensitivity of the CoupModel with respect to texture prediction uncertainty with respect to surface runoff, transpiration, evaporation, evapotranspiration, and soil water content depends on site conditions (i.e. climate and soil type). For this reason, it is recommended that SVAT model sensitivity analysis be carried out prior to field spectroscopic measurements to account for site specific climate and soil conditions. Nevertheless, mapping of the soil properties estimated via spectroscopy using kriging resulted in poor interpolation (i.e. weak variograms) results as a consequence of a summation of uncertainty arising from the method of field measurement to mapping (i.e. spectroscopic soil prediction, kriging error) and site-specific ‘small-scale’ heterogeneity. The selected soil evaluation method (vis-NIR spectroscopy, structure comparison using image analysis, traditional laboratory analysis) showed that there are significant differences between the bamboo soil and the adjacent secondary forest soil established on the same soil type (Vertisol). Reflecting on the major study results, it can be stated that the selected method combination is a way forward to a more detailed and efficient way to evaluate the suitability of a specific site for reforestation. The results of this study provide insights into where and when during soil and vegetation measurements a high measurement accuracy is required to minimize uncertainties in SVAT modeling. / Umfangreiche Abholzungen, besonders in den (Sub-)Tropen, habe zu intensiver Bodendegradierung und Erosion mit einhergehendem Verlust der Bodenfruchtbarkeit geführt. Eine wirksame Maßnahme zur Vermeidung fortschreitender Bodendegradierung und Erosion sind Aufforstungen auf diesen Flächen, die bisweilen zu einer verbesserten Bodenqualität führen können. Eine Umwandlung von Grünland zu Wald kann jedoch einen entscheidenden Einfluss auf den Wasserhaushalt haben. Selbst unter humid-tropischen Klimabedingungen, wo Wasser in der Regel kein begrenzender Faktor ist, können sich Aufforstungen negativ auf die Wasserverfügbarkeit auswirken. In diesem Zusammenhang muss auch berücksichtigt werden, dass Klimamodelle eine Abnahme der Niederschläge in einigen dieser Regionen prognostizieren. Um die Probleme, die mit dem Klimawandel in Verbindung stehen zu mildern (z.B. Zunahme von Erosion und Dürreperioden), wurden und werden bereits umfangreiche Aufforstungsmaßnahmen durchgeführt. Viele dieser Maßnahmen waren nicht immer umfassend erfolgreich, weil die Umgebungsbedingungen sowie die pflanzenspezifischen Anforderungen nicht angemessen berücksichtigt wurden. Dies liegt häufig an der schlechten Datengrundlage sowie an den in vielen Entwicklungs- und Schwellenländern begrenzter verfügbarer finanzieller Mittel. Aus diesem Grund werden innovative Ansätze benötigt, die in der Lage sind quasi-kontinuierlich und kostengünstig die Standortbedingungen zu erfassen und zu bewerten. Gleichzeitig sollte eine Überwachung der Wiederaufforstungsmaßnahme erfolgen, um deren Erfolg zu bewerten und potentielle negative Effekte (z.B. Wasserknappheit) zu erkennen und diesen entgegenzuwirken bzw. reduzieren zu können. Um zu vermeiden, dass Wiederaufforstungen fehlschlagen oder negative Auswirkungen auf die Ökosystemdienstleistungen haben, ist es entscheidend, Kenntnisse vom tatsächlichen Wasserhaushalt des Ökosystems zu erhalten und Änderungen des Wasserhaushalts durch Wiederaufforstungen vorhersagen zu können. Die Ermittlung und Vorhersage von Wasserhaushaltsänderungen infolge einer Aufforstung unter Berücksichtigung des Klimawandels erfordert die Berücksichtigung komplex-verzahnter Rückkopplungsprozesse im Boden-Vegetations-Atmosphären Kontinuum. Hydrologische Modelle, die explizit den Einfluss der Vegetation auf den Wasserhaushalt untersuchen sind Soil-Vegetation-Atmosphere-Transfer (SVAT) Modelle. Die vorliegende Studie verfolgte zwei Hauptziele: (i) die Entwicklung und Erprobung einer Methodenkombination zur Standortbewertung unter Datenknappheit (d.h. Grundanforderung des Ansatzes) (Teil I) und (ii) die Untersuchung des Einflusses der mit geophysikalischen Methoden vorhergesagten SVAT-Modeleingangsparameter (d.h. Vorhersageunsicherheiten) auf die Modellierung (Teil II). Eine Wasserhaushaltsmodellierung wurde in den Mittelpunkt der Methodenkombination gesetzt. In dieser Studie wurde das 1D SVAT Model CoupModel verwendet. CoupModel benötigen detaillierte räumliche Bodeninformationen (i) zur Modellparametrisierung, (ii) zum Hochskalierung von Modellergebnissen unter Berücksichtigung lokaler und regionaler Bodenheterogenität, und (iii) zur Beobachtung (Monitoring) der zeitlichen Veränderungen des Bodens und der Vegetation. Traditionelle Ansätze zur Messung von Boden- und Vegetationseigenschaften und deren Monitoring sind jedoch zeitaufwendig, teuer und beschränken sich daher oft auf Punktinformationen. Ein vielversprechender Ansatz zur Überwindung der räumlichen Einschränkung sind die Nutzung geophysikalischer Methoden. Aus diesem Grund wurden vis-NIR Spektroskopie (sichtbarer bis nah-infraroter Wellenlängenbereich) zur quasi-kontinuierlichen Messung von physikalischer und chemischer Bodeneigenschaften und Satelliten-basierte Fernerkundung zur Ableitung von Vegetationscharakteristika (d.h. Blattflächenindex (BFI)) eingesetzt. Da die mit geophysikalisch hergeleiteten Bodenparameter (hier Bodenart) und Pflanzenparameter zur Parametrisierung eines SVAT Models verwendet werden können, wurde die gesamte Prozessierungskette und die damit verbundenen Unsicherheiten und deren potentiellen Auswirkungen auf die Wasserhaushaltsmodellierung mit CoupModel untersucht. Ein Gewächshausexperiment mit Bambuspflanzen wurde durchgeführt, um die zur CoupModel Parametrisierung notwendigen pflanzenphysio- logischen Parameter zu bestimmen. Geoelektrik wurde eingesetzt, um die Bodenschichtung der Untersuchungsfläche zu untersuchen und ein repräsentatives Bodenprofil zur Modellierung zu definieren. Die Bodenstruktur wurde unter Verwendung einer Bildanalysetechnik ausgewertet, die die qualitativen Bewertung und Vergleichbarkeit struktureller Merkmale ermöglicht. Um den Anforderungen des gewählten Standortbewertungsansatzes gerecht zu werden, wurde die Methodik auf einem Standort mit einer Bambusplantage und einem Sekundärregenwald (als Referenzfläche) in NO-Brasilien (d.h. geringe Datenverfügbarkeit) entwickelt und getestet. Das Ziel dieser Arbeit war jedoch nicht die Modellierung dieses konkreten Standortes, sondern die Bewertung der Eignung des gewählten Methodenansatzes zur Standortbewertung für Aufforstungen und deren zeitliche Beobachtung, als auch die Bewertung des Einfluss von Aufforstungen auf den Wasserhaushalt und die Bodenqualität. Die Ergebnisse (Teil III) verdeutlichen, dass es notwendig ist, sich den potentiellen Einfluss der Messunsicherheiten der SVAT Modelleingangsparameter auf die Modellierung bewusst zu sein. Beispielsweise zeigte sich, dass die Vorhersageunsicherheiten der Bodentextur und des BFI einen bedeutenden Einfluss auf die Wasserhaushaltsmodellierung mit CoupModel hatte. Die Arbeit zeigt weiterhin, dass vis-NIR Spektroskopie zur schnellen und kostengünstigen Messung, Kartierung und Überwachung boden-physikalischer (Bodenart) und -chemischer (N, TOC, TIC, TC) Eigenschaften geeignet ist. Die Qualität der Bodenvorhersage hängt vom Instrument (z.B. Sensorauflösung), den Probeneigenschaften (z.B. chemische Zusammensetzung) und den Standortmerkmalen (z.B. Klima) ab. Die Sensitivitätsanalyse mit CoupModel zeigte, dass der Einfluss der spektralen Bodenartvorhersageunsicherheiten auf den mit CoupModel simulierten Oberflächenabfluss, Evaporation, Transpiration und Evapotranspiration ebenfalls von den Standortbedingungen (z.B. Klima, Bodentyp) abhängt. Aus diesem Grund wird empfohlen eine SVAT Model Sensitivitätsanalyse vor der spektroskopischen Feldmessung von Bodenparametern durchzuführen, um die Standort-spezifischen Boden- und Klimabedingungen angemessen zu berücksichtigen. Die Anfertigung einer Bodenkarte unter Verwendung von Kriging führte zu schlechten Interpolationsergebnissen in Folge der Aufsummierung von Mess- und Schätzunsicherheiten (d.h. bei spektroskopischer Feldmessung, Kriging-Fehler) und der kleinskaligen Bodenheterogenität. Anhand des gewählten Bodenbewertungsansatzes (vis-NIR Spektroskopie, Strukturvergleich mit Bildanalysetechnik, traditionelle Laboranalysen) konnte gezeigt werden, dass es bei gleichem Bodentyp (Vertisol) signifikante Unterschiede zwischen den Böden unter Bambus und Sekundärwald gibt. Anhand der wichtigsten Ergebnisse kann festgehalten werden, dass die gewählte Methodenkombination zur detailreicheren und effizienteren Standortuntersuchung und -bewertung für Aufforstungen beitragen kann. Die Ergebnisse dieser Studie geben einen Einblick darauf, wo und wann bei Boden- und Vegetationsmessungen eine besonders hohe Messgenauigkeit erforderlich ist, um Unsicherheiten bei der SVAT Modellierung zu minimieren. / Extensos desmatamentos que estão sendo feitos especialmente nos trópicos e sub-trópicos resultam em uma intensa degradação do solo e num aumento da erosão gerando assim uma redução na sua fertilidade. Reflorestamentos ou plantações nestas áreas degradadas podem ser medidas eficazes para atenuar esses problemas e levar a uma melhoria da qualidade do mesmo. No entanto, uma mudança no uso da terra, por exemplo de pastagem para floresta pode ter um impacto crucial no balanço hídrico e isso pode afetar a disponibilidade de água, mesmo sob condições de clima tropical úmido, onde a água normalmente não é um fator limitante. Devemos levar também em consideração que de acordo com projeções de mudanças climáticas, as precipitações em algumas dessas regiões também diminuirão agravando assim, ainda mais o quadro apresentado. Para mitigar esses problemas relacionados com as alterações climáticas, reflorestamentos são frequentemente realizados mas raramente são bem-sucedidos, pois condições ambientais como os requisitos específicos de cada espécie de planta, não são devidamente levados em consideração. Isso é muitas vezes devido, não só pela falta de dados, como também por recursos financeiros limitados, que são problemas comuns em regiões tropicais. Por esses motivos, são necessárias abordagens inovadoras que devam ser capazes de medir as condições ambientais quase continuamente e de maneira rentável. Simultaneamente com o reflorestamento, deve ser feita uma monitoração a fim de avaliar o sucesso da atividade e para prevenir, ou pelo menos, reduzir os problemas potenciais associados com o mesmo (por exemplo, a escassez de água). Para se evitar falhas e reduzir implicações negativas sobre os ecossistemas, é crucial obter percepções sobre o real balanço hídrico e as mudanças que seriam geradas por esse reflorestamento. Por este motivo, esta tese teve como objetivo desenvolver e testar uma combinação de métodos para avaliação de áreas adequadas para reflorestamento. Com esse intuito, foi colocada no centro da abordagem de avaliação a modelagem do balanço hídrico local, que permite a identificação e estimação de possíveis alterações causadas pelo reflorestamento sob mudança climática considerando o sistema complexo de realimentação e a interação de processos do continuum solo-vegetação-atmosfera. Esses modelos hidrológicos que investigam explicitamente a influência da vegetação no equilíbrio da água são conhecidos como modelos Solo-Vegetação-Atmosfera (SVAT). Esta pesquisa focou em dois objetivos principais: (i) desenvolvimento e teste de uma combinação de métodos para avaliação de áreas que sofrem com a escassez de dados (pré-requisito do estudo) (Parte I), e (ii) a investigação das consequências da incerteza nos parâmetros de entrada do modelo SVAT, provenientes de dados geofísicos, para modelagem hídrica (Parte II). A fim de satisfazer esses objetivos, o estudo foi feito no nordeste brasileiro,por representar uma área de grande escassez de dados, utilizando como base uma plantação de bambu e uma área de floresta secundária. Uma modelagem do balanço hídrico foi disposta no centro da metodologia para a avaliação de áreas. Este estudo utilizou o CoupModel que é um modelo SVAT unidimensional e que requer informações espaciais detalhadas do solo para (i) a parametrização do modelo, (ii) aumento da escala dos resultados da modelagem, considerando a heterogeneidade do solo de escala local para regional e (iii) o monitoramento de mudanças nas propriedades do solo e características da vegetação ao longo do tempo. Entretanto, as abordagens tradicionais para amostragem de solo e de vegetação e o monitoramento são demorados e caros e portanto muitas vezes limitadas a informações pontuais. Por esta razão, métodos geofísicos como a espectroscopia visível e infravermelho próximo (vis-NIR) e sensoriamento remoto foram utilizados respectivamente para a medição de propriedades físicas e químicas do solo e para derivar as características da vegetação baseado no índice da área foliar (IAF). Como as propriedades estimadas de solo (principalmente a textura) poderiam ser usadas para parametrizar um modelo SVAT, este estudo investigou toda a cadeia de processamento e as incertezas de previsão relacionadas à textura de solo e ao IAF. Além disso explorou o impacto destas incertezas criadas sobre a previsão do balanço hídrico simulado por CoupModel. O método geoelétrico foi aplicado para investigar a estratificação do solo visando a determinação de um perfil representante. Já a sua estrutura foi explorada usando uma técnica de análise de imagens que permitiu a avaliação quantitativa e a comparabilidade dos aspectos estruturais. Um experimento realizado em uma estufa com plantas de bambu (Bambusa vulgaris) foi criado a fim de determinar as caraterísticas fisiológicas desta espécie que posteriormente seriam utilizadas como parâmetros para o CoupModel. Os resultados do estudo (Parte III) destacam que é preciso estar consciente das incertezas relacionadas à medição de parâmetros de entrada do modelo SVAT. A incerteza presente em alguns parâmetros de entrada como por exemplo, textura de solo e o IAF influencia significantemente a modelagem do balanço hídrico. Mesmo assim, esta pesquisa indica que vis-NIR espectroscopia é um método rápido e economicamente viável para medir, mapear e monitorar as propriedades físicas (textura) e químicas (N, TOC, TIC, TC) do solo. A precisão da previsão dessas propriedades depende do tipo de instrumento (por exemplo da resolução do sensor), da propriedade da amostra (a composição química por exemplo) e das características das condições climáticas da área. Os resultados apontam também que a sensitividade do CoupModel à incerteza da previsão da textura de solo em respeito ao escoamento superficial, transpiração, evaporação, evapotranspiração e ao conteúdo de água no solo depende das condições gerais da área (por exemplo condições climáticas e tipo de solo). Por isso, é recomendado realizar uma análise de sensitividade do modelo SVAT prior a medição espectral do solo no campo, para poder considerar adequadamente as condições especificas do área em relação ao clima e ao solo. Além disso, o mapeamento de propriedades de solo previstas pela espectroscopia usando o kriging, resultou em interpolações de baixa qualidade (variogramas fracos) como consequência da acumulação de incertezas surgidas desde a medição no campo até o seu mapeamento (ou seja, previsão do solo via espectroscopia, erro do kriging) e heterogeneidade especifica de uma pequena escala. Osmétodos selecionados para avaliação das áreas (vis-NIR espectroscopia, comparação da estrutura de solo por meio de análise de imagens, análise de laboratório tradicionais) revelou a existência de diferenças significativas entre o solo sob bambu e o sob floresta secundária, apesar de ambas terem sido estabelecidas no mesmo tipo de solo (vertissolo). Refletindo sobre os principais resultados do estudo, pode-se afirmar que a combinação dos métodos escolhidos e aplicados representam uma forma mais detalhada e eficaz de avaliar se uma determinada área é adequada para ser reflorestada. Os resultados apresentados fornecem percepções sobre onde e quando, durante a medição do solo e da vegetação, é necessário se ter uma precisão mais alta a fim de minimizar incertezas potenciais na modelagem com o modelo SVAT.

The Penman-Monteith (PM) equation is a state-of-the-art modelling approach to simulate evapotranspiration (ET) at site and local scale. However, its practical application is often restricted by the availability and quality of required parameters. One of these parameters is the canopy conductance. Long term measurements of evapotranspiration by the eddy-covariance method provide an improved data basis to determine this parameter by inverse modelling. Because this approach may also include evaporation from the soil, not only the ‘actual’ canopy conductance but the whole surface conductance (gc) is addressed. Two full cycles of crop rotation with five different crop types (winter barley, winter rape seed, winter wheat, silage maize, and spring barley) have been continuously monitored for 10 years. These data form the basis for this study. As estimates of gc are obtained on basis of measurements, we investigated the impact of measurements uncertainties on obtained values of gc. Here, two different foci were inspected more in detail. Firstly, the effect of the energy balance closure gap (EBCG) on obtained values of gc was analysed. Secondly, the common hydrological practice to use vegetation height (hc) to determine the period of highest plant activity (i.e., times with maximum gc concerning CO2-exchange and transpiration) was critically reviewed. The results showed that hc and gc do only agree at the beginning of the growing season but increasingly differ during the rest of the growing season. Thus, the utilisation of hc as a proxy to assess maximum gc (gc,max) can lead to inaccurate estimates of gc,max which in turn can cause serious shortcomings in simulated ET. The light use efficiency (LUE) is superior to hc as a proxy to determine periods with maximum gc. Based on this proxy, crop specific estimates of gc,maxcould be determined for the first (and the second) cycle of crop rotation: winter barley, 19.2 mm s−1 (16.0 mm s−1); winter rape seed, 12.3 mm s−1 (13.1 mm s−1); winter wheat, 16.5 mm s−1 (11.2 mm s−1); silage maize, 7.4 mm s−1 (8.5 mm s−1); and spring barley, 7.0 mm s−1 (6.2 mm s−1).

This thesis describes the conception and implementation of the hydrological model ArcEGMO-URBAN and its application to the basin of the Havel river in north-eastern Germany. The model has been developed in order to make up the balance of nitrogen and phosphorus inputs from point sources in urban areas on the scale of river basins. The nutrient input can be calculated with a high spatial resolution and according to its seasonal variation. At the same time, the impact of the rainfall on the nutrient input is being focused on in this project. ArcEGMO-URBAN models rainfall-runoff processes and pollution-transport processes in urban areas taking natural, technological and social parameters into consideration. Input data are meteorological and terrestrial data with a high spatiotemporal resolution as well as statistic data on the scale of municipalities. The digitally available spatial data are being analysed with GIS functions before the actual modelling and later merged to areas with similar attributes. Technological and social parameters are assigned to these areas which were derived from statistic data. The diversity of the input data and their high spatial resolution allow for the description of relevant processes differentiated on the scale of urban patches. The model considers different urban water technologies and their determined matter fluxes as well as different sewer systems. With regard to rainfall-runoff processes the following sub-processes are considered for this model: the runoff-generation and runoff-concentration on sealed surfaces, the runoff-transformation and combination with the dry weather flow in the sewer system, and the split-up of the runoff in retention tanks and waste water treatment plants. Referring to pollution-transport processes the following sub-processes are taken into account: the atmospheric pollution and surface pollution dependent on the type of land use, and the matter transport in the sewer system. The sub-processes of matter accumulation and matter erosion on the land surface can be calculated by using mean values of pollution or, more detailed, by using special functions for processes of accumulation as well as erosion. In order to guarantee an easy application, the model's conception allows the use of input data and parameters of varying accuracy. Both, either measurements or statistical data can be used for the calculation dependent on the available data. The model is programmed in "C" and, therefore, usable on every established computer system. The model's validation succeeds for several sub-processes as well as sub catchments. Results of the model's application in the basin of the Havel river illustrate that the model calculates similar annual matter loads when compared to established other models. Furthermore, the results show the potential of the model to calculate the seasonal variation of matter loads and to calculate scenarios by using GIS based parameters. ArcEGMO-URBAN therefore is a capable tool for the identification of nutrient input from point sources on the scale of river catchments. / Diese Arbeit beschreibt die Konzeption und Realisierung des Modells ArcEGMO-URBAN sowie die Modellanwendung im Flussgebiet der Havel. ArcEGMO-URBAN wurde entwickelt um die punktuell in Gewässer eingetragenen Frachten von Gesamtstickstoff und Gesamtphosphor aus urbanen Räumen auf der Ebene von Flussgebieten zu bilanzieren. Die Nährstoffeinträge werden mit einer hohen räumlichen Auflösung und in ihrer innerjährlichen Dynamik berechnet, wobei der Einfluss des Niederschlagsgeschehens auf die Stoffeinträge besonders thematisiert wird. ArcEGMO-URBAN modelliert die Niederschlags-Abfluss- und die Schmutz-Transport-Prozesse in urbanen Räumen unter Berücksichtigung von naturräumlichen, technologischen und sozialen Parametern. Eingangsgrößen sind meteorologische und terrestrische Daten mit einer hohen zeitlichen und räumlichen Auflösung sowie statistische Angaben auf Gemeindeebene. Die digital vorliegenden Flächendaten werden vor der Modellierung mittels GIS-Funktionen ausgewertet und zu Flächen mit gleichen Eigenschaften zusammengefasst. Diesen Flächen werden technologische und soziale Parameter zugeordnet, welche aus den statistischen Angaben abgeleitet wurden. Durch die hohe inhaltliche und räumliche Auflösung der Eingangsdaten können relevante Prozesse teilflächendifferenziert beschrieben werden. Es können sowohl unterschiedliche Wasserver- und -entsorgungstechnologien und die durch sie induzierten Stoffströme als auch unterschiedliche Kanalisationsverfahren berücksichtigt werden. Bezogen auf den Niederschlags-Abfluss-Prozess werden die Abflussbildung und Abflusskonzentration auf befestigten Flächen, die Abflusstransformation und Überlagerung mit dem Trockenwetterabfluss im Kanalnetz und die Abflussaufteilung an Sonderbauwerken bzw. Kläranlagen berechnet. Für die Berücksichtigung der Stoff-Transport-Prozesse werden die durch die Atmosphäre und spezifische Nutzungen bedingten Stoffeinträge sowie der durch die Kanalisation bestimmte Stofftransport berechnet. Die auf der Oberfläche stattfindenden Teilprozesse von Stoffakkumulation und -abtrag können über mittlere Verschmutzungswerte oder detailliert über Akkumulations- und Abtragsfunktionen berechnet werden. Um ein weites Anwendungsspektrum zu gewährleisten, ist das Modell so konzipiert, dass eine Parametrisierung mit Eingangsdaten unterschiedlicher Qualität möglich ist. Abhängig von der verfügbaren Datenbasis werden entweder konkrete Messwerte oder statistische Größen verwendet. Das Programm ist in "C" programmiert und damit auf jeder Rechnerarchitektur lauffähig. Die Validierung des Modells gelingt für einzelne Teilprozesse aber auch für Teilgebiete gut. Die Ergebnisse im Flussgebiet der Havel belegen, dass das Modell ähnliche jährliche Nährstofffrachten wie bereits eingeführte Modelle berechnet. Darüber hinaus zeigen die Ergebnisse das Potenzial des Modells, die innerjährliche Dynamik punktueller Stoffeinträge abzubilden und durch die GIS-gestützte Parametrisierung aufwandsarm Szenarien zu berechnen. Damit ist ArcEGMO-URBAN ein geeignetes Modell zur Bestimmung von Nährstoffeinträgen aus punktuellen Quellen auf der Ebene von Flussgebieten.