FOR 5288: Fast and invisible: Conquering Subsurface Stormflow
through an Interdisciplinary Multi-Site Approach

Abstract:

In addition to overland flow, subsurface stormflow (SSF) can play a major role for runoff generation during certain events. Even though SSF is a well-recognised process, there is a lack of systematic studies on SSF, partly because it is very difficult to quantify. In hydrological modelling, this can lead to an unclear distinction of SSF from other processes. If parameters that describe SSF processes or thresholds are implemented in hydrological models, they are often used as fitting parameters and can contribute to overall model uncertainty. So far, there has been no systematic benchmarking of SSF routines in hydrological models. This presentation discusses how we plan to address this research gap. In order to address the inconsistency of SSF representation in hydrological models, different existing lumped hydrological models will be set up for four study sites located in the Alps, Ore Mountains, Black Forest and Sauerland. In a first step, different models will be calibrated using only basic data like discharge observations, climate data and readily available geodata. Differences in SSF simulations will be detected and quantified and the models will be benchmarked regarding the simulation of SSF dynamics and associated uncertainties. In a next step, we will include new experimental data on SSF derived at the four study sites in the calibration of the lumped hydrological models by a multi-objective calibration and evaluation framework. In order to consider SSF observations collected at scales different than the scale of model application, new SSF metrics will be developed. Testing different combinations of these metrics for model calibration it will be possible to state which SSF proxies can lead to the most productive improvement of SSF simulations. Identifying current weaknesses in SSF representation of current models, and providing directions for improving them by including the most beneficial SSF metrics, this project will show potential for the improvement of SSF simulations through SSF data collection. In a final application of the most reliable SSF simulations to all study sites, we will show the impact of extreme wet or extreme dry conditions on SSF occurrence and SSF volumes.

Abstract:

Where does water go when it rains? Where are floods generated and how? What controls stream water quality during events? These questions are important to many fields from engineering and flood protection to water and ecosystem management and prediction of impacts of global change. The most elusive processes in the process-ensemble underlying these questions is subsurface stormflow (SSF), the fast event response triggered by lateral subsurface flow. SSF is prevalent and a more important process than generally accounted for because a basic understanding based on systematic studies across scales and sites is still lacking. However, only with systematic studies will it be possible to really advance our understanding by discovering general principles of SSF functioning and to provide protocols and best practices for its assessment, both experimentally and with respect to modelling. In many natural landscapes, SSF, i.e. any subsurface flow that occurs in response to a precipitation event, plays a major role in runoff generation: either by contributing directly to streamflow or by producing saturated areas or return flow, which then is the underlying cause of saturation excess overland flow. Therefore, much of what we see as event response in the hydrograph might be the direct or indirect result of SSF. It is likely that the discharge signal of SSF, including the indirectly triggered response in the stream, is larger than we generally assume. While its importance is probably largest in the headwaters, headwaters make up 70% of the stream network and greatly influence the supply and transport of water and solutes downstream. However, SSF is elusive and poorly accounted for as measurements are difficult for several reasons: the inaccessibility of the subsurface, the large spatial variability and heterogeneity, the variable sources and the fact that it is a threshold-driven process that only occurs during certain events. Thus, systematic studies of SSF are lacking, mainly due to difficulties of quantification. We suggest such a systematic study of SSF in different environments, across scales, and using a well-designed and replicated selection of approaches including novel approaches. This will be followed by a systematic evaluation of methods and possible proxies as well as model intercomparison, evaluation and improvement. Thereby, we will focus on 4 challenges: 1) Development of novel experimental methods,2) Spatial patterns of SSF, 3) Thresholds and cascading effects of SSF, 4) Impacts of SSF. Whereas standard single research projects investigate part of this puzzle at a specific location, this Research Unit provides the unique opportunity of fitting a large number of puzzle pieces together. This Research Unit will have a strong emphasis on experimental work in four contrasting catchments from the low to high mountain ranges (Sauerland, Ore Mountains, Black Forest, Alps) that then directly feeds into a collaborative modelling effort, which in turn influences experimental design in an iterative process.

Abstract:

Environmental tracers have been used to separate streamflow components for many years. They allow us to quantify the contribution of water originating from different sources, such as direct runoff from precipitation, subsurface storm flow, or groundwater to total streamflow at variable flow conditions. Although previous studies have explored the value of incorporating experimentally derived fractions of event and pre-event water into hydrological models, a thorough analysis of the value of incorporating hydrographseparation-derived information on multiple streamflow components at varying flow conditions into model parameter estimation has not yet been performed. This study explores the value of such information to achieve more realistic simulations of catchment discharge. We use a modified version of the process-oriented HBV model that simulates catchment discharge through the interplay of hillslope, riparian-zone discharge, and groundwater discharge at a small forested catchment which is located in the mountainous north of South Korea, subject to a monsoon season between June and August. Applying a Monte-Carlo-based parameter estimation scheme and the Kling–Gupta efficiency (KGE) to compare discharge observations and simulations across two seasons (2013 and 2014), we show that the model is able to provide accurate simulations of catchment discharge (KGE 0.8) but fails to provide robust predictions and realistic estimates of the contribution of the different streamflow components. Using a simple framework that compares simulated and observed contributions of hillslope, riparian zone, and groundwater to total discharge during two sub-periods, we show that the precision of simulated streamflow components can be increased, while remaining with accurate discharge simulations.We further show that the additional information increases the identifiability of all model parameters and results in more robust predictions. Our study shows how tracer-derived information on streamflow contributions can be used to improve the simulation and predictions of streamflow at the catchment scale without adding additional complexity to the model. The complementary use of temporally resolved observations of streamflow components and modeling provides a promising direction to improve discharge prediction by representing model internal dynamics more realistically.

Abstract:

Abstract The simulation of floods with conceptual rainfall-runoff models is a frequently used method for various ap - plications in flood risk management. In mountain areas, the identification of the optimum model parameters during the calibration is often difficult because of the complexity and variability of catchment properties and hydrological processes. Central European mountain ranges are typically covered by Pleistocene periglacial slope deposits. The hydraulic conductivity of the cover beds shows a high degree of anisotropy, so it is impor - tant to understand the role of this effect in flood models of mesoscale mountain watersheds. Based on previ - ous field work, the study analyses the sensitivity of the NASIM modeling system to a variation of vertical and lateral hydraulic conductivity for the Upper Flöha watershed (Ore Mountains, Germany). Depending on the objective function (Nash-Sutcliffe coefficient, peak discharge), two diametric parameter sets were identified both resulting in a high goodness-of-fit for total discharge of the flood events, but only one reflects the hydro- logical process knowledge. In a second step, the knowledge of the spatial distribution of the cover beds is used to investigate the potential for a simplification of the model parameterisation. The soil types commonly used for the spatial discretisation of rainfall-runoff models were aggregated to one main class (periglacial cover beds only). With such a simplified model, the total flood discharge and the runoff components were simulated with the same goodness of fit as with the original model. In general, the results point out that the anisotropy in the unsaturated zone, which is intensified by periglacial cover beds, is an important element of flood models. First, a parameter set corresponding to the hydraulic anisotropy in the cover beds is essential for the optimum reproduction of the flood dynamics. Second, a discretisation of soil types is not necessarily required for flood modeling in Central European mountain areas