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Institut
- Fachbereich 6 (8) (entfernen)
Wasserbezogene regulierende und versorgende Ökosystemdienstleistungen (ÖSDL) wurden im Hinblick auf das Abflussregime und die Grundwasserneubildung im Biosphärenreservat Pfälzerwald im Südwesten Deutschlands anhand hydrologischer Modellierung unter Verwendung des Soil and Water Assessment Tool (SWAT+) untersucht. Dabei wurde ein holistischer Ansatz verfolgt, wonach den ÖSDL Indikatoren für funktionale und strukturelle ökologische Prozesse zugeordnet werden. Potenzielle Risikofaktoren für die Verschlechterung von wasserbedingten ÖSDL des Waldes, wie Bodenverdichtung durch Befahren mit schweren Maschinen im Zuge von Holzerntearbeiten, Schadflächen mit Verjüngung, entweder durch waldbauliche Bewirtschaftungspraktiken oder durch Windwurf, Schädlinge und Kalamitäten im Zuge des Klimawandels, sowie der Kli-mawandel selbst als wesentlicher Stressor für Waldökosysteme wurden hinsichtlich ihrer Auswirkungen auf hydrologische Prozesse analysiert. Für jeden dieser Einflussfaktoren wurden separate SWAT+-Modellszenarien erstellt und mit dem kalibrierten Basismodell verglichen, das die aktuellen Wassereinzugsgebietsbedingungen basierend auf Felddaten repräsentierte. Die Simulationen bestätigten günstige Bedingungen für die Grundwasserneubildung im Pfälzerwald. Im Zusammenhang mit der hohen Versickerungskapazität der Bodensubstrate der Buntsandsteinverwitterung, sowie dem verzögernden und puffernden Einfluss der Baumkronen auf das Niederschlagswasser, wurde eine signifikante Minderungswirkung auf die Oberflächenabflussbildung und ein ausgeprägtes räumliches und zeitliches Rückhaltepotential im Einzugsgebiet simuliert. Dabei wurde festgestellt, dass erhöhte Niederschlagsmengen, die die Versickerungskapazität der sandigen Böden übersteigen, zu einer kurz geschlossenen Abflussreaktion mit ausgeprägten Oberflächenabflussspitzen führen. Die Simulationen zeigten Wechselwirkungen zwischen Wald und Wasserkreislauf sowie die hydrologische Wirksamkeit des Klimawandels, verschlechterter Bodenfunktionen und altersbezogener Bestandesstrukturen im Zusammenhang mit Unterschieden in der Baumkronenausprägung. Zukunfts-Klimaprojektionen, die mit BIAS-bereinigten REKLIES- und EURO-CORDEX-Regionalklimamodellen (RCM) simuliert wurden, prognostizierten einen höheren Verdunstungsbedarf und eine Verlängerung der Vegetationsperiode bei gleichzeitig häufiger auftretenden Dürreperioden innerhalb der Vegetationszeit, was eine Verkürzung der Periode für die Grundwasserneubildung induzierte, und folglich zu einem prognostizierten Rückgang der Grundwasserneubildungsrate bis zur Mitte des Jahrhunderts führte. Aufgrund der starken Korrelation mit Niederschlagsintensitäten und der Dauer von Niederschlagsereignissen, bei allen Unsicherheiten in ihrer Vorhersage, wurde für die Oberflächenabflussgenese eine Steigerung bis zum Ende des Jahrhunderts prognostiziert.
Für die Simulation der Bodenverdichtung wurden die Trockenrohdichte des Bodens und die SCS Curve Number in SWAT+ gemäß Daten aus Befahrungsversuchen im Gebiet angepasst. Die günstigen Infiltrationsbedingungen und die relativ geringe Anfälligkeit für Bodenverdichtung der grobkörnigen Buntsandsteinverwitterung dominierten die hydrologischen Auswirkungen auf Wassereinzugsgebietsebene, sodass lediglich moderate Verschlechterungen wasserbezogener ÖSDL angezeigt wurden. Die Simulationen zeigten weiterhin einen deutlichen Einfluss der Bodenart auf die hydrologische Reaktion nach Bodenverdichtung auf Rückegassen und stützen damit die Annahme, dass die Anfälligkeit von Böden gegenüber Verdichtung mit dem Anteil an Schluff- und Tonbodenpartikeln zunimmt. Eine erhöhte Oberflächenabflussgenese ergab sich durch das Wegenetz im Gesamtgebiet.
Schadflächen mit Bestandesverjüngung wurden anhand eines artifiziellen Modells innerhalb eines Teileinzugsgebiets unter der Annahme von 3-jährigen Baumsetzlingen in einem Entwicklungszeitraum von 10 Jahren simuliert und hinsichtlich spezifischer Was-serhaushaltskomponenten mit Altbeständen (30 bis 80 Jahre) verglichen. Die Simulation ließ darauf schließen, dass bei fehlender Kronenüberschirmung die hydrologisch verzögernde Wirkung der Bestände beeinträchtigt wird, was die Entstehung von Oberflächenabfluss begünstigt und eine quantitativ geringfügig höhere Tiefensickerung fördert. Hydrologische Unterschiede zwischen dem geschlossenem Kronendach der Altbestände und Jungbeständen mit annähernden Freilandniederschlagsbedingungen wurden durch die dominierenden Faktoren atmosphärischer Verdunstungsanstoß, Niederschlagsmengen und Kronenüberschirmungsgrad bestimmt. Je weniger entwickelt das Kronendach von verjüngten Waldbeständen im Vergleich zu Altbeständen, je höher der atmosphärische Verdunstungsanstoß und je geringer die eingetragenen Niederschlagsmengen, desto größer war der hydrologische Unterschied zwischen den Bestandestypen.
Verbesserungsmaßnahmen für den dezentralen Hochwasserschutz sollten folglich kritische Bereiche für die Abflussbildung im Wald (CSA) berücksichtigen. Die hohe Sensibilität und Anfälligkeit der Wälder gegenüber Verschlechterungen der Ökosystembedingungen legen nahe, dass die Erhaltung des komplexen Gefüges und von intakten Wechselbeziehungen, insbesondere unter der gegebenen Herausforderung des Klimawandels, sorgfältig angepasste Schutzmaßnahmen, Anstrengungen bei der Identifizierung von CSA sowie die Erhaltung und Wiederherstellung der hydrologischen Kontinuität in Waldbeständen erfordern.
Forest inventories provide significant monitoring information on forest health, biodiversity,
resilience against disturbance, as well as its biomass and timber harvesting potential. For this
purpose, modern inventories increasingly exploit the advantages of airborne laser scanning (ALS)
and terrestrial laser scanning (TLS).
Although tree crown detection and delineation using ALS can be seen as a mature discipline, the
identification of individual stems is a rarely addressed task. In particular, the informative value of
the stem attributes—especially the inclination characteristics—is hardly known. In addition, a lack
of tools for the processing and fusion of forest-related data sources can be identified. The given
thesis addresses these research gaps in four peer-reviewed papers, while a focus is set on the
suitability of ALS data for the detection and analysis of tree stems.
In addition to providing a novel post-processing strategy for geo-referencing forest inventory plots,
the thesis could show that ALS-based stem detections are very reliable and their positions are
accurate. In particular, the stems have shown to be suited to study prevailing trunk inclination
angles and orientations, while a species-specific down-slope inclination of the tree stems and a
leeward orientation of conifers could be observed.
Agricultural monitoring is necessary. Since the beginning of the Holocene, human agricultural
practices have been shaping the face of the earth, and today around one third of the ice-free land
mass consists of cropland and pastures. While agriculture is necessary for our survival, the
intensity has caused many negative externalities, such as enormous freshwater consumption, the
loss of forests and biodiversity, greenhouse gas emissions as well as soil erosion and degradation.
Some of these externalities can potentially be ameliorated by careful allocation of crops and
cropping practices, while at the same time the state of these crops has to be monitored in order
to assess food security. Modern day satellite-based earth observation can be an adequate tool to
quantify abundance of crop types, i.e., produce spatially explicit crop type maps. The resources to
do so, in terms of input data, reference data and classification algorithms have been constantly
improving over the past 60 years, and we live now in a time where fully operational satellites
produce freely available imagery with often less than monthly revisit times at high spatial
resolution. At the same time, classification models have been constantly evolving from
distribution based statistical algorithms, over machine learning to the now ubiquitous deep
learning.
In this environment, we used an explorative approach to advance the state of the art of crop
classification. We conducted regional case studies, focused on the study region of the Eifelkreis
Bitburg-Prüm, aiming to develop validated crop classification toolchains. Because of their unique
role in the regional agricultural system and because of their specific phenologic characteristics
we focused solely on maize fields.
In the first case study, we generated reference data for the years 2009 and 2016 in the study
region by drawing polygons based on high resolution aerial imagery, and used these in
conjunction with RapidEye imagery to produce high resolution maize maps with a random forest
classifier and a gaussian blur filter. We were able to highlight the importance of careful residual
analysis, especially in terms of autocorrelation. As an end result, we were able to prove that, in
spite of the severe limitations introduced by the restricted acquisition windows due to cloud
coverage, high quality maps could be produced for two years, and the regional development of
maize cultivation could be quantified.
In the second case study, we used these spatially explicit datasets to link the expansion of biogas
producing units with the extended maize cultivation in the area. In a next step, we overlayed the
maize maps with soil and slope rasters in order to assess spatially explicit risks of soil compaction
and erosion. Thus, we were able to highlight the potential role of remote sensing-based crop type
classification in environmental protection, by producing maps of potential soil hazards, which can
be used by local stakeholders to reallocate certain crop types to locations with less associated
risk.
In our third case study, we used Sentinel-1 data as input imagery, and official statistical records
as maize reference data, and were able to produce consistent modeling input data for four
consecutive years. Using these datasets, we could train and validate different models in spatially
iv
and temporally independent random subsets, with the goal of assessing model transferability. We
were able to show that state-of-the-art deep learning models such as UNET performed
significantly superior to conventional models like random forests, if the model was validated in a
different year or a different regional subset. We highlighted and discussed the implications on
modeling robustness, and the potential usefulness of deep learning models in building fully
operational global crop classification models.
We were able to conclude that the first major barrier for global classification models is the
reference data. Since most research in this area is still conducted with local field surveys, and only
few countries have access to official agricultural records, more global cooperation is necessary to
build harmonized and regionally stratified datasets. The second major barrier is the classification
algorithm. While a lot of progress has been made in this area, the current trend of many appearing
new types of deep learning models shows great promise, but has not yet consolidated. There is
still a lot of research necessary, to determine which models perform the best and most robust,
and are at the same time transparent and usable by non-experts such that they can be applied
and used effortlessly by local and global stakeholders.
Soils in forest ecosystems bear a high potential as carbon (C) sinks in the mitigation of climate change. The amount and characteristics of soil organic matter (SOM) are driven by inputs, transformation, degradation and stabilization of organic substances. While tree species fuel the C cycle by producing aboveground and belowground litter, soil microorganisms are crucial for litter degradation as well as the formation and stabilization of SOM. Nonetheless, our knowledge about the tree species effect on the SOM status is limited, inconsistent and blurred. The investigation of tree species effects on SOM is challenging because in long-established forest ecosystems the spatial distribution of tree species is a result of the interplay of environmental factors including climate, geomorphology and soil chemistry. Moreover, tree distribution can further vary with forest successional stage and silvicultural management. Since these factors also directly affect the soil C-status, it is difficult to identify a pure “tree species effect” on the SOM status at regular forested sites. It therefore remains unclear in how far tree species-specific litter with different quality influences the microbial driven turnover and formation of SOM.
Tree species effects on SOM and related soil microbial properties were investigated by examining soil profiles (comprising organic forest floor horizons and mineral soil layers) in different forest stands at the recultivated spoil heap ‘Sophienhöhe’ located at the lignite open-cast mine Hambach near Jülich, Germany. The afforested sites comprised monocultural stands of Douglas fir (Pseudotsuga menziesii), black pine (Pinus nigra), European beech (Fagus sylvatica) and red oak (Quercus rubra) as well as a mixed deciduous stand site planted mainly with hornbeam (Carpinus betulus), lime (Tilia cordata) and common oak (Quercus robur) that were grown for 35 years under identical soil and geomorphological conditions. Because the parent material used for site recultivation was free from organic matter or coal material, the SOM accumulation is entirely the result of in situ soil development due to the impact of tree species.
The first study revealed that tree species had a significant effect on soil organic carbon (SOC) stocks, stoichiometric patterns of C, nitrogen (N), sulfur (S), hydrogen (H) and oxygen (O) as well as the microbial biomass carbon (MBC) content in the forest floor and the top mineral soil layers (0-5 cm, 5-10 cm, 10-30 cm). In general, forest floor SOC stocks were significantly higher at coniferous forest stands compared to deciduous tree species, whereas in mineral soil layers the differences were smaller. Thus, the impact of tree species decreased with increasing soil depth. By investigating the linkage of the natural abundance of 13C and 15N in the soil depth gradients with C:N and O:C stoichiometry, the second study showed that differences in SOC stocks and SOM quality resulted from a tree species-dependent turnover of SOM. Significantly higher turnover of organic matter in soils under deciduous tree species depended to 46 % on the quality of litterfall and root inputs (N content, C:N, O:C ratio), and on the initial isotopic signatures of litterfall. Hence, SOM composition and turnover also depends on additional – presumably microbially driven – factors. The subsequent results of the third study revealed that differences in SOM composition and related soil microbial properties were linked to different microbial communities. Phospholipid fatty acid (PLFA) patterns in the soil profiles indicated that the supply and availability of C and nutrient-rich substrates drive the distribution of fungi, Gram-positive (G+) bacteria and Gram-negative (G−) bacteria between tree species and along the soil depth gradients. The fourth study investigated the molecular composition of extractable soil microbial biomass-derived (SMB) and SOM-derived compounds by electrospray ionization Fourier transformation ion cyclotron resonance mass spectrometry (ESI-FT-ICR-MS). This was complemented by the analysis of nine monosaccharides representing microbial or plant origin. Microbially derived compounds substantially contributed to SOM and the contribution increased with soil depth. The supply of tree species-specific substrates resulted in different chemical composition of SMB with largest differences between deciduous and coniferous stands. At the same time, microorganisms contributed to SOM resulting in a strong similarity in the composition of SOM and SMB.
Overall, the complex interplay of tree species-specific litter inputs and the ability, activity and efficiency of the associated soil fauna and microbial community in metabolizing the organic substrates leads to significant differences in the amount, distribution, quality and consequently, the stability of SOM. These findings are useful for a targeted cultivation of tree species to optimize soil C sequestration and other forest ecosystems services.
Climate fluctuations and the pyroclastic depositions from volcanic activity both influence ecosystem functioning and biogeochemical cycling in terrestrial and marine environments globally. These controlling factors are crucial for the evolution and fate of the pristine but fragile fjord ecosystem in the Magellanic moorlands (~53°S) of southernmost Patagonia, which is considered a critical hotspot for organic carbon burial and marine bioproductivity. At this active continental margin in the core zone of the southern westerly wind belt (SWW), frequent Plinian eruptions and the extremely variable, hyper-humid climate should have efficiently shaped ecosystem functioning and land-to-fjord mass transfer throughout the Late Holocene. However, a better understanding of the complex process network defining the biogeochemical cycling at this land-to-fjord continuum principally requires a detailed knowledge of substrate weathering and pedogenesis in the context of the extreme climate. Yet, research on soils, the ubiquitous presence of tephra and the associated chemical weathering, secondary mineral (trans)formation and organic matter (OM) turnover processes is rare in this remote region. This complicates an accurate reconstruction of the ecosystem´s potentially sensitive response to past environmental impacts, including the dynamics of Late Holocene land-to-fjord fluxes as a function of volcanic activity and strong hydroclimate variability.
Against this background, this PhD thesis aims to disentangle the controlling factors that modulate the terrigenous element mobilization and export mechanisms in the hyper-humid Patagonian Andes and assesses their significance for fjord primary productivity over the past 4.5 kyrs BP. For the first time, distinct biogeochemical characteristics of the regional weathering system serve as major criterion in paleoenvironmental reconstruction in the area. This approach includes broad-scale mineralogical and geochemical analyses of basement lithologies, four soil profiles, volcanic ash deposits, the non-karst stalagmite MA1 and two lacustrine sediment cores. In order to pay special attention to the possibly important temporal variations of pedosphere-atmosphere interaction and ecological consequences initiated by volcanic eruptions, the novel data were evaluated together with previously published reconstructions of paleoclimate and paleoenvironmental conditions.
The devastative high-tephra loading of a single eruption from Mt. Burney volcano (MB2 at 4.216 kyrs BP) sustainably transformed this vulnerable fjord ecosystem, while acidic peaty Andosols developed from ~2.5 kyrs BP onwards after the recovery from millennium-scale acidification. The special setting is dominated by most variable redox-pH conditions, profound volcanic ash weathering and intense OM turnover processes, which are closely linked and ultimately regulated by SWW-induced water-level fluctuations. Constant nutrient supply though sea spray deposition represents a further important control on peat accumulation and OM turnover dynamics. These extreme environmental conditions constrain the biogeochemical framework for an extended land-to-fjord export of leachates comprising various organic and inorganic colloids (i.e., Al-humus complexes and Fe-(hydr)oxides). Such tephra- and/or Andosol-sourced flux contains high proportions of terrigenous organic carbon (OCterr) and mobilized essential (micro)nutrients, e.g., bio-available Fe, that are beneficial for fjord bioproductivity. It can be assumed that this supply of bio-available Fe produced by specific Fe-(hydr)oxide (trans)formation processes from tephra components may outlast more than 6 kyrs and surpasses the contribution from basement rock weathering and glacial meltwaters. However, the land-to-fjord exports of OCterr and bio-available Fe occur mostly asynchronous and are determined by the frequency and duration of redox cycles in soils or are initiated by SWW-induced extreme weather events.
The verification of (crypto)tephra layers embedded stalagmite MA1 enabled the accurate dating of three smaller Late Holocene eruptions from Mt. Burney (MB3 at 2.291 kyrs BP and MB4 at 0.853 kyrs BP) and Aguilera (A1 at 2.978 kyrs BP) volcanoes. Irrespective of the improvement of the regional tephrochronology, the obtained precise 230Th/U-ages allowed constraints on the ecological consequences caused by these Plinian eruptions. The deposition of these thin tephra layers should have entailed a very beneficial short-term stimulation of fjord bioproductivity with bio-available Fe and other (micro)nutrients, which affected the entire area between 52°S and 53°S 30´, respectively. For such beneficial effects, the thickness of tephra deposited to this highly vulnerable peatland ecosystem should be below a threshold of 1 cm.
The Late Holocene element mobilization and land-to-fjord transport was mainly controlled by (i) volcanic activity and tephra thickness, (ii) SWW-induced and southern hemispheric climate variability and (iii) the current state of the ecosystem. The influence of cascading climate and environmental impacts on OCterr and Fe-(hydr)oxide fluxes to can be categorized by four individual, in part overlapping scenarios. These different scenarios take into account the previously specified fundamental biogeochemical mechanisms and define frequently recurring patterns of ecosystem feedbacks governing the land-to-fjord mass transfer in the hyper-humid Patagonian Andes on the centennial-scale. This PhD thesis provides first evidence for a primarily tephra-sourced, continuous and long-lasting (micro)nutrient fertilization for phytoplankton growth in South Patagonian fjords, which is ultimately modulated by variations in SWW-intensity. It highlights the climate sensitivity of such critical land-to-fjord element transport and particularly emphasizes the important but so far underappreciated significance of volcanic ash inputs for biogeochemical cycles at active continental margins.
Reptiles belong to a taxonomic group characterized by increasing worldwide population declines. However, it has not been until comparatively recent years that public interest in these taxa has increased, and conservation measures are starting to show results. While many factors contribute to these declines, environmental pollution, especially in form of pesticides, has seen a strong increase in the last few decades, and is nowadays considered a main driver for reptile diversity loss. In light of the above, and given that reptiles are extremely underrepresented in ecotoxicological studies regarding the effects of plant protection products, this thesis aims at studying the impacts of pesticide exposure in reptiles, by using the Common wall lizard (Podarcis muralis) as model species. In a first approach, I evaluated the risk of pesticide exposure for reptile species within the European Union, as a means to detect species with above average exposure probabilities and to detect especially sensitive reptile orders. While helpful to detect species at risk, a risk evaluation is only the first step towards addressing this problem. It is thus indispensable to identify effects of pesticide exposure in wildlife. For this, the use of enzymatic biomarkers has become a popular method to study sub-individual responses, and gain information regarding the mode of action of chemicals. However, current methodologies are very invasive. Thus, in a second step, I explored the use of buccal swabs as a minimally invasive method to detect changes in enzymatic biomarker activity in reptiles, as an indicator for pesticide uptake and effects at the sub-individual level. Finally, the last part of this thesis focuses on field data regarding pesticide exposure and its effects on reptile wildlife. Here, a method to determine pesticide residues in food items of the Common wall lizard was established, as a means to generate data for future dietary risk assessments. Subsequently, a field study was conducted with the aim to describe actual effects of pesticide exposure on reptile populations at different levels.
Global food security poses large challenges to a fast changing human society and has been a key topic for scientists, agriculturist, and policy makers in the 21st century. The United Nation predicts a total world population of 9.15 billion in 2050 and defines the provision of food security as the second major point in the UN Sustainable Development Goals. As the capacities of both, land and water resources, are finite and locally heavily overused, reducing agriculture’s environmental impact while meeting an increasing demand for food of a constantly growing population is one of the greatest challenges of our century. Therefore, a multifaceted solution is required, including approaches using geospatial data to optimize agricultural food production.
The availability of precise and up-to-date information on vegetation parameters is mandatory to fulfill the requirements of agricultural applications. Direct field measurements of such vegetation parameters are expensive and time-consuming. On the contrary, remote sensing offers a variety of techniques for a cost-effective and non-destructive retrieval of vegetation parameters. Although not widely used, hyperspectral thermal infrared (TIR) remote sensing has demonstrated being a valuable addition to existing remote sensing techniques for the retrieval of vegetation parameters.
This thesis examined the potential of TIR imaging spectroscopy as an important contribution to the growing need of food security. The main scientific question dealt with the extraction of vegetation parameters from imaging TIR spectroscopy. To this end, two studies impressively demonstrated the ability of extracting vegetation related parameters from leaf emissivity spectra: (i) the discrimination of eight plant species based on their emissivity spectra and (ii) the detection of drought stress in potato plants using temperature measures and emissivity spectra.
The datasets used in these studies were collected using the Telops Hyper-Cam LW, a novel imaging spectrometer. Since this FTIR spectrometer presents some particularities, special attention was paid on the development of dedicated experimental data acquisition setups and on data processing chains. The latter include data preprocessing and the development of algorithms for extracting precise surface temperatures, reproducible emissivity spectra and, in the end, vegetation parameters.
The spectrometer’s versatility allows the collection of airborne imaging spectroscopy datasets. Since the general availability of airborne TIR spectrometers is limited, the preprocessing and
data extraction methods are underexplored compared to reflective remote sensing. This counts especially for atmospheric correction (AC) and temperature and emissivity separation (TES) algorithms. Therefore, we implemented a powerful simulation environment for the development of preprocessing algorithms for airborne hyperspectral TIR image data. This simulation tool is designed in a modular way and includes the image data acquisition and processing chain from surface temperature and emissivity to the final at-sensor radiance data. It includes a series of available algorithms for TES, AC as well as combined AC and TES approaches. Using this simulator, one of the most promising algorithms for the preprocessing of airborne TIR data – ARTEMISS – was significantly optimized. The retrieval error of the atmospheric water vapor during the atmospheric characterization was reduced. As a result, this improvement in atmospheric characterization accuracy enhanced the subsequent retrieval of surface temperatures and surface emissivities intensely.
Although, the potential of hyperspectral TIR applications in ecology, agriculture, and biodiversity has been impressively demonstrated, a serious contribution to a global provision of food security requires the retrieval of vegetation related parameters with global coverage, high spatial resolution and at high revisit frequencies.
Emerging from the findings in this thesis, the spectral configuration of a spaceborne TIR spectrometer concept was developed. The sensors spectral configuration aims at the retrieval of precise land surface temperatures and land surface emissivity spectra. Complemented with additional characteristics, i.e. short revisit times and a high spatial resolution, this sensor potentially allows the retrieval of valuable vegetation parameters needed for agricultural optimizations. The technical feasibility of such a sensor concept underlines the potential contribution to the multifaceted solution required for achieving the challenging goal of guaranteeing global food security in a world of increasing population.
In conclusion, thermal remote sensing and more precisely hyperspectral thermal remote sensing has been presented as a valuable technique for a variety of applications contributing to the final goal of a global food security.
Physically-based distributed rainfall-runoff models as the standard analysis tools for hydro-logical processes have been used to simulate the water system in detail, which includes spa-tial patterns and temporal dynamics of hydrological variables and processes (Davison et al., 2015; Ek and Holtslag, 2004). In general, catchment models are parameterized with spatial information on soil, vegetation and topography. However, traditional approaches for eval-uation of the hydrological model performance are usually motivated with respect to dis-charge data alone. This may thus cloud model realism and hamper understanding of the catchment behavior. It is necessary to evaluate the model performance with respect to in-ternal hydrological processes within the catchment area as well as other components of wa-ter balance rather than runoff discharge at the catchment outlet only. In particular, a consid-erable amount of dynamics in a catchment occurs in the processes related to interactions of the water, soil and vegetation. Evapotranspiration process, for instance, is one of those key interactive elements, and the parameterization of soil and vegetation in water balance mod-eling strongly influences the simulation of evapotranspiration. Specifically, to parameterize the water flow in unsaturated soil zone, the functional relationships that describe the soil water retention and hydraulic conductivity characteristics are important. To define these functional relationships, Pedo-Transfer Functions (PTFs) are common to use in hydrologi-cal modeling. Opting the appropriate PTFs for the region under investigation is a crucial task in estimating the soil hydraulic parameters, but this choice in a hydrological model is often made arbitrary and without evaluating the spatial and temporal patterns of evapotran-spiration, soil moisture, and distribution and intensity of runoff processes. This may ulti-mately lead to implausible modeling results and possibly to incorrect decisions in regional water management. Therefore, the use of reliable evaluation approaches is continually re-quired to analyze the dynamics of the current interactive hydrological processes and predict the future changes in the water cycle, which eventually contributes to sustainable environ-mental planning and decisions in water management.
Remarkable endeavors have been made in development of modelling tools that provide insights into the current and future of hydrological patterns in different scales and their im-pacts on the water resources and climate changes (Doell et al., 2014; Wood et al., 2011). Although, there is a need to consider a proper balance between parameter identifiability and the model's ability to realistically represent the response of the natural system. Neverthe-less, tackling this issue entails investigation of additional information, which usually has to be elaborately assembled, for instance, by mapping the dominant runoff generation pro-cesses in the intended area, or retrieving the spatial patterns of soil moisture and evapotran-spiration by using remote sensing methods, and evaluation at a scale commensurate with hydrological model (Koch et al., 2022; Zink et al., 2018). The present work therefore aims to give insights into the modeling approaches to simulate water balance and to improve the soil and vegetation parameterization scheme in the hydrological model subject to producing more reliable spatial and temporal patterns of evapotranspiration and runoff processes in the catchment.
An important contribution to the overall body of work is a book chapter included among publications. The book chapter provides a comprehensive overview of the topic and valua-ble insights into the understanding the water balance and its estimation methods.
Moreover, the first paper aimed to evaluate the hydrological model behavior with re-spect to contribution of various sources of information. To do so, a multi-criteria evaluation metric including soft and hard data was used to define constraints on outputs of the 1-D hydrological model WaSiM-ETH. Applying this evaluation metric, we could identify the optimal soil and vegetation parameter sets that resulted in a “behavioral” forest stand water balance model. It was found out that even if simulations of transpiration and soil water con-tent are consistent with measured data, but still the dominant runoff generation processes or total water balance might be wrongly calculated. Therefore, only using an evaluation scheme which looks over different sources of data and embraces an understanding of the local controls of water loss through soil and plant, allowed us to exclude the unrealistic modeling outputs. The results suggested that we may need to question the generally accept-ed soil parameterization procedures that apply default parameter sets.
The second paper attempts to tackle the pointed model evaluation hindrance by getting down to the small-scale catchment (in Bavaria). Here, a methodology was introduced to analyze the sensitivity of the catchment water balance model to the choice of the Pedo-Transfer Functions (PTF). By varying the underlying PTFs in a calibrated and validated model, we could determine the resulting effects on the spatial distribution of soil hydraulic properties, total water balance in catchment outlet, and the spatial and temporal variation of the runoff components. Results revealed that the water distribution in the hydrologic system significantly differs amongst various PTFs. Moreover, the simulations of water balance components showed high sensitivity to the spatial distribution of soil hydraulic properties. Therefore, it was suggested that opting the PTFs in hydrological modeling should be care-fully tested by looking over the spatio-temporal distribution of simulated evapotranspira-tion and runoff generation processes, whether they are reasonably represented.
To fulfill the previous studies’ suggestions, the third paper then aims to focus on evalu-ating the hydrological model through improving the spatial representation of dominant run-off processes. It was implemented in a mesoscale catchment in southwestern Germany us-ing the hydrological model WaSiM-ETH. Dealing with the issues of inadequate spatial ob-servations for rigorous spatial model evaluation, we made use of a reference soil hydrologic map available for the study area to discern the expected dominant runoff processes across a wide range of hydrological conditions. The model was parameterized by applying 11 PTFs and run by multiple synthetic rainfall events. To compare the simulated spatial patterns to the patterns derived by digital soil map, a multiple-component spatial performance metric (SPAEF) was applied. The simulated DRPs showed a large variability with regard to land use, topography, applied rainfall rates, and the different PTFs, which highly influence the rapid runoff generation under wet conditions.
The three published manuscripts proceeded towards the model evaluation viewpoints that ultimately attain the behavioral model outputs. It was performed through obtaining information about internal hydrological processes that lead to certain model behaviors, and also about the function and sensitivity of some of the soil and vegetation parameters that may primarily influence those internal processes in a catchment. Accordingly, using this understanding on model reactions, and by setting multiple evaluation criteria, it was possi-ble to identify which parameterization could lead to behavioral model realization. This work, in fact, will contribute to solving some of the issues (e.g., spatial variability and modeling methods) identified as the 23 unsolved problems in hydrology in the 21st century (Blöschl et al., 2019). The results obtained in the present work encourage the further inves-tigations toward a comprehensive model calibration procedure considering multiple data sources simultaneously. This will enable developing the new perspectives to the current parameter estimation methods, which in essence, focus on reproducing the plausible dy-namics (spatio-temporal) of the other hydrological processes within the watershed.