Frankfurt Hydrology Paper
https://www.uni-frankfurt.de/53949648/FHG
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17
Floodplains and other wetlands depend on seasonal river flooding and play an important role in the terrestrial water cycle. They influence evapotranspiration, water storage and river discharge dynamics, and they are the habitat of a large number of animals and plants. Thus, to assess the Earth’s system and its changes, a robust understanding of the dynamics of floodplain wetlands including inundated areas, water storages, and water flows is required.
This PhD thesis aims at improving the modeling of large floodplains and wetlands within the global-scale hydrological model WaterGAP, in order to better estimate water flows and water storage variations in different storage compartments. Within the scope of this thesis, I have developed a new approach to simulate dynamic floodplain inundation on a global-scale. This approach introduces an algorithm into WaterGAP, which has a spatial resolution of 0.5 degree (longitude and latitude) globally. The new approach uses subgrid-scale topography, based on high-resolution digital elevation models, to describe the floodplain elevation profile within each grid cell by applying a hypsographic curve. The approach comprises the modeling of a two-way river-floodplain interaction, the separate downstream water transport within the river and the floodplain – both with temporally and spatially different variable flow velocities – and the floodplain-groundwater interactions. The WaterGAP version that includes the floodplain algorithm, WaterGAP 2.2b_fpl, estimates floodplain and river water storage, inundated area and water table elevation, and also simulates backwater effects.
WaterGAP 2.2b_fpl was applied to model river discharge, river flow velocity, water storages, water heights and surface water extent on a global-scale. Model results were comprehensively validated against ground observations and remote sensing data. Overall, the modeled and observed data are in agreement. In comparison to the former version WaterGAP 2.2b, the model performance has improved significantly. The improvements are most remarkable in the Amazon River basin. However, the seasonal variation of surface water extent and total water storage anomalies are still too low in many regions on the globe when compared to observations. A detailed analysis of the simulated results suggests that in the Amazon River basin the introduction of backwater effects is important for realistically simulating water storages and surface water extent. Future efforts should focus on the simulation of water levels in order to better model the flow routing according to water slope. To further improve the model performance in specific regions, I recommend that the globally constant model parameters that affect inundation initiation, river-floodplain interaction, DEM correction for vegetation, and backwater amount at basin or subbasin-scale be adjusted.
19
Groundwater is the largest source of accessible freshwater with its dynamics having significantly changed due to human withdrawals, and being projected to continue to as a result of climate change. The pumping of groundwater has led to lowered water tables, decreased base flow, and depletion.
Global hydrological models (GHMs) are used to simulate the global freshwater cycle, assessing impacts of changes in climate and human freshwater use. Currently, groundwater is commonly represented by a bucket-like linear storage component in these models. Bucket models, however, cannot provide information on the location of the groundwater table. Due to this limitation, they can only simulate groundwater discharge to surface water bodies but not recharge from surface water to groundwater and calculate no lateral and vertical groundwater flow whatsoever among grid cells. For instance this may lead to an underestimation of groundwater resources in semiarid areas, where groundwater is often replenished by surface water. In order to overcome these limitations it is necessary to replace the linear groundwater model in GHMs with a hydraulic head gradient-based groundwater flow model
This thesis presents the newly developed global groundwater model G3M and its coupling to the GHM WaterGAP spanning over 70,000 lines of newly developed code. Development and validation of the modeling software are discussed along with numerical challenges. Based on the newly developed software, a global natural equilibrium groundwater model is presented showing better agreements with observations than previous models. Groundwater discharge to rivers is found to be the most dominant flow component globally, compared to flows to other surface water bodies and lateral flows. Furthermore, first global maps of the distribution of gaining and losing surface water bodies are displayed.
For the purpose of determining the uncertainty in model outcomes a sensitivity study is conducted with an innovative approach through applying a global sensitivity analysis for a computationally complex model. First global maps of spatially distributed parameter sensitivities are presented. The results at hand indicate that globally simulated hydraulic heads are equally sensitive to hydraulic conductivity, groundwater recharge and surface water body elevation, even though parameter sensitivities do vary regionally.
A high resolution model of New Zealand is developed to further understand the involved uncertainties connected to the spatial resolution of the global model. This thesis finds that a new understanding is necessary how these models can be evaluated and that a simple increase in spatial resolution is not improving the model performance when compared to observations.
Alongside the assessment of the natural equilibrium, the concept of a fully coupled transient model as integrated storage component replacing the former model in the hydrological model WaterGAP is discussed. First results reveal that the model shows reasonable response to seasonal variability although it contains persistent head trends leading to global overestimates of water table depth due to an incomplete coupling. Nonetheless, WaterGAP-G3M is already able to show plausible long term storage trends for areas that are known to be affected by groundwater depletion. In comparison with two established regional models in the Central Valley the coupled model shows a highly promising simulation of storage declines.