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Terrestrial gravimetry is increasingly used to monitor mass transport processes in geophysics boosted by the ongoing technological development of instruments. Resolving a particular phenomenon of interest, however, requires a set of gravity corrections of which the uncertainties have not been addressed up to now. In this study, we quantify the time domain uncertainty of tide, global atmospheric, large-scale hydrological, and nontidal ocean loading corrections. The uncertainty is assessed by comparing the majority of available global models for a suite of sites worldwide. The average uncertainty expressed as root-mean-square error equals 5.1nm/s(2), discounting local hydrology or air pressure. The correction-induced uncertainty of gravity changes over various time periods of interest ranges from 0.6nm/s(2) for hours up to a maximum of 6.7nm/s(2) for 6months. The corrections are shown to be significant and should be applied for most geophysical applications of terrestrial gravimetry. From a statistical point of view, however, resolving subtle gravity effects in the order of few nanometers per square second is challenged by the uncertainty of the corrections. Plain Language Summary Many scientists are exploring ways to benefit from gravity measurements in fields of high societal relevance such as monitoring of volcanoes or measuring the amount of water in underground. Any application of such new methods, however, requires careful preparation of the gravity measurements. The intention of the preparation process is to ensure that the measurements do not contain information about processes that are not of interest. For that reason, the influence of atmosphere, ocean, tides, and hydrology needs to be reduced from the gravity. In this study, we investigate how this reduction process influences the quality of the measurement. We found that the precision degrades especially owing to the hydrology. The ocean plays an important role at sites close to the coast and the atmosphere at sites located in mountains. The overall errors of the reductions may complicate a reliable use of gravity measurements in certain studies focusing on very small signals. Nevertheless, the precision of gravity reductions alone does not obstruct a meaningful use of gravity measurements in most research fields. Details specifying the reduction precision are provided in this study allowing scientist dealing with gravity measurements to decide if their signal of interest can be reliably resolved.
During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007–2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash–Sutcliffe efficiency of 0.72 and a Kling–Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.
During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007-2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash-Sutcliffe efficiency of 0.72 and a Kling-Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.
Hydrological models are important tools for the simulation and quantification of the water cycle.
They therefore aid in the understanding of hydrological processes, prediction of river discharge, assessment of the impacts of land use and climate changes, or the management of water resources.
However, uncertainties associated with hydrological modelling are still large.
While significant research has been done on the quantification and reduction of uncertainties, there are still fields which have gained little attention so far, such as model structural uncertainties that are related to the process implementations in the models.
This holds especially true for complex process-based models in contrast to simpler conceptual models.
Consequently, the aim of this thesis is to improve the understanding of structural uncertainties with focus on process-based hydrological modelling, including methods for their quantification.
To identify common deficits of frequently used hydrological models and develop further strategies on how to reduce them, a survey among modellers was conducted.
It was found that there is a certain degree of subjectivity in the perception of modellers, for instance with respect to the distinction of hydrological models into conceptual groups.
It was further found that there are ambiguities on how to apply a certain hydrological model, for instance how many parameters should be calibrated, together with a large diversity of opinion regarding the deficits of models.
Nevertheless, evapotranspiration processes are often represented in a more physically based manner, while processes of groundwater and soil water movement are often simplified, which many survey participants saw as a drawback.
A large flexibility, for instance with respect to different alternative process implementations or a small number of parameters that needs to be calibrated, was generally seen as strength of a model.
Flexible and efficient software, which is straightforward to apply, has been increasingly acknowledged by the hydrological community.
This work further elaborated on this topic in a twofold way.
First, a software package for semi-automated landscape discretisation has been developed, which serves as a tool for model initialisation.
This was complemented by a sensitivity analysis of important and commonly used discretisation parameters, of which the size of hydrological sub-catchments as well as the size and number of hydrologically uniform computational units appeared to be more influential than information considered for the characterisation of hillslope profiles.
Second, a process-based hydrological model has been implemented into a flexible simulation environment with several alternative process representations and a number of numerical solvers.
It turned out that, even though computation times were still long, enhanced computational capabilities nowadays in combination with innovative methods for statistical analysis allow for the exploration of structural uncertainties of even complex process-based models, which up to now was often neglected by the modelling community.
In a further study it could be shown that process-based models may even be employed as tools for seasonal operational forecasting.
In contrast to statistical models, which are faster to initialise and to apply, process-based models produce more information in addition to the target variable, even at finer spatial and temporal scales, and provide more insights into process behaviour and catchment functioning.
However, the process-based model was much more dependent on reliable rainfall forecasts.
It seems unlikely that there exists a single best formulation for hydrological processes, even for a specific catchment.
This supports the use of flexible model environments with alternative process representations instead of a single model structure.
However, correlation and compensation effects between process formulations, their parametrisation, and other aspects such as numerical solver and model resolution, may lead to surprising results and potentially misleading conclusions.
In future studies, such effects should be more explicitly addressed and quantified.
Moreover, model functioning appeared to be highly dependent on the meteorological conditions and rainfall input generally was the most important source of uncertainty.
It is still unclear, how this could be addressed, especially in the light of the aforementioned correlations.
The use of innovative data products, e.g.\ remote sensing data in combination with station measurements, and efficient processing methods for the improvement of rainfall input and explicit consideration of associated uncertainties is advisable to bring more insights and make hydrological simulations and predictions more reliable.
The Central Asian Pamir Mountains (Pamirs) are a high-altitude region sensitive to climatic change, with only few paleoclimatic records available. To examine the glacial-interglacial hydrological changes in the region, we analyzed the geochemical parameters of a 31-kyr record from Lake Karakul and performed a set of experiments with climate models to interpret the results. delta D values of terrestrial biomarkers showed insolation-driven trends reflecting major shifts of water vapor sources. For aquatic biomarkers, positive delta D shifts driven by changes in precipitation seasonality were observed at ca. 31-30, 28-26, and 17-14 kyr BP. Multiproxy paleoecological data and modelling results suggest that increased water availability, induced by decreased summer evaporation, triggered higher lake levels during those episodes, possibly synchronous to northern hemispheric rapid climate events. We conclude that seasonal changes in precipitation-evaporation balance significantly influenced the hydrological state of a large waterbody such as Lake Karakul, while annual precipitation amount and inflows remained fairly constant.
Flooding is an imminent natural hazard threatening most river deltas, e.g. the Mekong Delta. An appropriate flood management is thus required for a sustainable development of the often densely populated regions. Recently, the traditional event-based hazard control shifted towards a risk management approach in many regions, driven by intensive research leading to new legal regulation on flood management. However, a large-scale flood risk assessment does not exist for the Mekong Delta. Particularly, flood risk to paddy rice cultivation, the most important economic activity in the delta, has not been performed yet. Therefore, the present study was developed to provide the very first insight into delta-scale flood damages and risks to rice cultivation. The flood hazard was quantified by probabilistic flood hazard maps of the whole delta using a bivariate extreme value statistics, synthetic flood hydrographs, and a large-scale hydraulic model. The flood risk to paddy rice was then quantified considering cropping calendars, rice phenology, and harvest times based on a time series of enhanced vegetation index (EVI) derived from MODIS satellite data, and a published rice flood damage function. The proposed concept provided flood risk maps to paddy rice for the Mekong Delta in terms of expected annual damage. The presented concept can be used as a blueprint for regions facing similar problems due to its generic approach. Furthermore, the changes in flood risk to paddy rice caused by changes in land use currently under discussion in the Mekong Delta were estimated. Two land-use scenarios either intensifying or reducing rice cropping were considered, and the changes in risk were presented in spatially explicit flood risk maps. The basic risk maps could serve as guidance for the authorities to develop spatially explicit flood management and mitigation plans for the delta. The land-use change risk maps could further be used for adaptive risk management plans and as a basis for a cost-benefit of the discussed land-use change scenarios. Additionally, the damage and risks maps may support the recently initiated agricultural insurance programme in Vietnam.
Water scarcity, adaption on climate change, and risk assessment of droughts and floods are critical topics for science and society these days. Monitoring and modeling of the hydrological cycle are a prerequisite to understand and predict the consequences for weather and agriculture. As soil water storage plays a key role for partitioning of water fluxes between the atmosphere, biosphere, and lithosphere, measurement techniques are required to estimate soil moisture states from small to large scales.
The method of cosmic-ray neutron sensing (CRNS) promises to close the gap between point-scale and remote-sensing observations, as its footprint was reported to be 30 ha. However, the methodology is rather young and requires highly interdisciplinary research to understand and interpret the response of neutrons to soil moisture. In this work, the signal of nine detectors has been systematically compared, and correction approaches have been revised to account for meteorological and geomagnetic variations. Neutron transport simulations have been consulted to precisely characterize the sensitive footprint area, which turned out to be 6--18 ha, highly local, and temporally dynamic. These results have been experimentally confirmed by the significant influence of water bodies and dry roads. Furthermore, mobile measurements on agricultural fields and across different land use types were able to accurately capture the various soil moisture states. It has been further demonstrated that the corresponding spatial and temporal neutron data can be beneficial for mesoscale hydrological modeling. Finally, first tests with a gyrocopter have proven the concept of airborne neutron sensing, where increased footprints are able to overcome local effects.
This dissertation not only bridges the gap between scales of soil moisture measurements. It also establishes a close connection between the two worlds of observers and modelers, and further aims to combine the disciplines of particle physics, geophysics, and soil hydrology to thoroughly explore the potential and limits of the CRNS method.
Large-scale soy agriculture in the southern Brazilian Amazon now rivals deforestation for pasture as the region's predominant form of land use change. Such landscape-level change can have substantial consequences for local and regional hydrology, but these effects remain relatively unstudied in this ecologically and economically important region. We examined how the conversion to soy agriculture influences water balances and stormflows using stream discharge (water yields) and the timing of discharge (stream hydrographs) in small (2.5-13.5 km2) forested and soy headwater watersheds in the Upper Xingu Watershed in the state of Mato Grosso, Brazil. We monitored water yield for 1 year in three forested and four soy watersheds. Mean daily water yields were approximately four times higher in soy than forested watersheds, and soy watersheds showed greater seasonal variability in discharge. The contribution of stormflows to annual streamflow in all streams was low (< 13% of annual streamflow), and the contribution of stormflow to streamflow did not differ between land uses. If the increases in water yield observed in this study are typical, landscape-scale conversion to soy substantially alters water-balance, potentially altering the regional hydrology over large areas of the southern Amazon.
The humid tropics are the region with the highest rate of land-cover change worldwide. Especially prevalent is the deforestation of old-growth tropical forests to create space for cattle pastures and soybean fields.
The regional water cycle is influenced by vegetation cover in various ways. Especially evapotranspiration considerably contributes to water vapor content in the lower atmosphere. Besides active transpiration by plants, evaporation from wetted plant surfaces further known as interception loss is an important supply of water vapor. Changes in interception loss due to change in land cover and the related consequences on the regional water cycle in the humid tropics of Latin America are the research focus of my thesis. (1) In an experimental setup I assess differences in interception loss between an old-growth tropical forest and a soybean plantation. (2) In a modeling study, I examine interception losses of these two vegetation types compared to a younger secondary forest with the use of the Gash interception model, including an uncertainty analysis for the estimation of the necessary model parameters. (3) Studying the water balance of a 192-km² catchment I disentangle the influences of changes in land cover and climatic factors on interception loss.
The three different research sites in my thesis represent a currently typical spectrum for land-cover changes in Latin America. In the first example I study the consequences of deforestation of transitional forest, which forms the transition from the Brazilian tree savanna (cerrado) to tropical rain forest, for the establishment of soybean fields in the southern Amazon basin. The second study site is a young secondary forest within the “Agua Salud” project area in Panama as an example of reforestation of former pastures. The third study site is the Cirí Grande river catchment which comprises a mixture of young and old forests as well as pastures, which is typical for the southern sub-catchments of the Panama Canal.
The experimental approach consists of the indirect estimation of interception loss by measuring throughfall and stem flow. For the first experimental study I measured throughfall as well as stem flow manually. Measurements of the leaf area index of the two land covers do not show distinct differences; hence it could not serve as an explanation for the differences in the measured interception loss. The considerably higher interception loss at the soybean field is attributed to a possible underestimation of stemflow but also to the stronger ventilation within the well-structured plant rows causing higher evaporation rates. This situation is valid only for two months of the rainy season, when soybean plants are fully developed. In the annual balance evapotranspiration at the soybean site is clearly less than at the forest site, accelerating the development of fast runoff components and consequently discharge. In the medium term, a reduction of water availability in the study area can be expected.
For the modeling study, throughfall in a young secondary forest is sampled automatically. The resulting temporally high-resolution dataset allows the distinction between different precipitation and interception events. The core of this study is the sensitivity and uncertainty analysis of the Gash interception model parameters and the consequences for its results. Canopy storage capacity plays a key role for the model and parameter uncertainty. With increasing storage capacity uncertainty in parameter delineation also increases. Evaporation rate as the driving component of the interception process incorporates in this context the largest parameter uncertainty. Depending on the selected method for parameter estimation, parameter values may vary tremendously.
In the third study, I analyze the influence of interception loss on the water balance of the Cirí Grande catchment, incorporating the interlinked effects of temperature, precipitation and changes of the land use mosaic using the SWAT (soil water assessment tool) model. Constructing several land-cover scenarios I assess their influence on the catchment’s discharge. The results show that land-cover change exerts only a small influence on annual discharge in the Cirí Grande catchment whereas an increase in temperature markedly influences evapotranspiration. The temperature-induced larger transpiration and interception loss balances the simultaneous increase in annual precipitation, such that the resulting changes in annual discharge are negligible.
The results of the three studies show the considerable effect of land cover on interception. However, the magnitude of this effect can be masked by changes in local conditions, especially by an increase in temperature. Hence, the results cannot be transferred easily between the different study sites. For modeling purposes, this means that measurements of vegetation characteristics as well as interception loss at the respective sites are indispensable.
Logging and large earthquakes are disturbances that may significantly affect hydrological and erosional processes and process rates, although in decisively different ways. Despite numerous studies that have documented the impacts of both deforestation and earthquakes on water and sediment fluxes, a number of details regarding the timing and type of de- and reforestation; seismic impacts on subsurface water fluxes; or the overall geomorphic work involved have remained unresolved. The main objective of this thesis is to address these shortcomings and to better understand and compare the hydrological and erosional process responses to such natural and man-made disturbances. To this end, south-central Chile provides an excellent natural laboratory owing to its high seismicity and the ongoing conversion of land into highly productive plantation forests. In this dissertation I combine paired catchment experiments, data analysis techniques, and physics-based modelling to investigate: 1) the effect of plantation forests on water resources, 2) the source and sink behavior of timber harvest areas in terms of overland flow generation and sediment fluxes, 3) geomorphic work and its efficiency as a function of seasonal logging, 4) possible hydrologic responses of the saturated zone to the 2010 Maule earthquake and 5) responses of the vadose zone to this earthquake. Re 1) In order to quantify the hydrologic impact of plantation forests, it is fundamental to first establish their water balances. I show that tree species is not significant in this regard, i.e. Pinus radiata and Eucalyptus globulus do not trigger any decisive different hydrologic response. Instead, water consumption is more sensitive to soil-water supply for the local hydro-climatic conditions. Re 2) Contradictory opinions exist about whether timber harvest areas (THA) generate or capture overland flow and sediment. Although THAs contribute significantly to hydrology and sediment transport because of their spatial extent, little is known about the hydrological and erosional processes occurring on them. I show that THAs may act as both sources and sinks for overland flow, which in turn intensifies surface erosion. Above a rainfall intensity of ~20 mm/h, which corresponds to <10% of all rainfall, THAs may generate runoff whereas below that threshold they remain sinks. The overall contribution of Hortonian runoff is thus secondary considering the local rainfall regime. The bulk of both runoff and sediment is generated by Dunne, saturation excess, overland flow. I also show that logging may increase infiltrability on THAs which may cause an initial decrease in streamflow followed by an increase after the groundwater storage has been refilled. Re 3) I present changes in frequency-magnitude distributions following seasonal logging by applying Quantile Regression Forests at hitherto unprecedented detail. It is clearly the season that controls the hydro-geomorphic work efficiency of clear cutting. Logging, particularly dry seasonal logging, caused a shift of work efficiency towards less flashy and mere but more frequent moderate rainfall-runoff events. The sediment transport is dominated by Dunne overland flow which is consistent with physics-based modelling using WASA-SED. Re 4) It is well accepted that earthquakes may affect hydrological processes in the saturated zone. Assuming such flow conditions, consolidation of saturated saprolitic material is one possible response. Consolidation raises the hydraulic gradients which may explain the observed increase in discharge following earthquakes. By doing so, squeezed water saturates the soil which in turn increases the water accessible for plant transpiration. Post-seismic enhanced transpiration is reflected in the intensification of diurnal cycling. Re 5) Assuming unsaturated conditions, I present the first evidence that the vadose zone may also respond to seismic waves by releasing pore water which in turn feeds groundwater reservoirs. By doing so, water tables along the valley bottoms are elevated thus providing additional water resources to the riparian vegetation. By inverse modelling, the transient increase in transpiration is found to be 30-60%. Based on the data available, both hypotheses, are not testable. Finally, when comparing the hydrological and erosional effects of the Maule earthquake with the impact of planting exotic plantation forests, the overall observed earthquake effects are comparably small, and limited to short time scales.