Displays

Storm-induced landslides are a common hazard, but the link between their spatial pattern and rainfall properties is poorly understood, mostly because hillslope stability is modulated by under-constrained, spatially variable topographic, hydrological and mechanical properties.

Here, we use a 26 years long, high spatial resolution rainfall dataset from the Japanese radar network, to analyze the landslide pattern (1900 landslides within ~5000 km2) caused by Typhoon Talas (>1500 mm in 3 days) in 2011 in the Kii Peninsula. We show that it poorly correlates with the rainfall amount accumulated during the event over short to long timescales (1-72h), but agrees well with the rainfall anomaly (i.e., the event rainfall amount over the rainfall amount expected for a 10-year return period rainfall). Normalizing the event rainfall by mean annual or seasonal rainfall does not match as well the landslide pattern. This suggests that the variability in hillslope properties has co-evolved with the recent climate, where slopes exposed to stronger extreme rainfall have experienced higher landslide rates until their properties (e.g., regolith thickness, strength and permeability) have reached an equilibrium. In this framework, the 10-year return rainfall amount would be a proxy for hillslope properties, and we show that it allows an improved prediction of the landslide pattern when coupled with rainfall amount and slope. Finding ways to constrain the spatial variability of these parameters to test this hypothesis is an exciting challenge.

Last we note that rock-types seem to respond to rainfall anomalies at various timescales, favoring specific landslide geometries, and suggesting various hydrological properties in these zones. Specifically, a coastal area underlain by highly weathered volcanic rocks yielded a high landslide density with a high proportion of debris flow, correlating with the 2h anomaly while the rest of the landslides matches best the 48h anomaly.

Although such influence of lithology on hydrological behavior remains hard to predict, we propose the computation of rainfall anomalies for multiple timescales to pave the way towards operational landslide forecasts in case of large storms. More generally, regional landslide susceptibility maps may also be significantly enhanced by considering maps of past extreme rainfall.

How to cite: Marc, O., Gosset, M., Saito, H., Uchida, T., and Malet, J.-P.: Spatial Patterns of Storm-Induced Landslides and Their Relation to Past Extreme Rainfall, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8282, https://doi.org/10.5194/egusphere-egu2020-8282, 2020.

Streamflow distributions represent a powerful tool for water resources and ecological habitat management and have been shown in the past to be predictable with relatively simple analytic models. Such analytic models derive streamflow distributions from fundamental stochastic properties of the rainfall forcing and the filtering effect of the landscape and offer thereby a theoretical basis to compare the hydrologic behavior across climates and landscapes. 

This contribution proposes an extension of the streamflow distribution model originally developed by Botter et al. (2007) to alpine streamflow regimes where the hydrological forcing is strongly influenced by snow and ice melt, i.e. to streamflow regimes that have major relevance for water supply in many world regions. We developed and tested the approach for 10 Swiss high elevation catchments covering a wide range of glacier covers (from 0% to 60%) and obtained good model performances for all test cases, which opens interesting perspectives for the quantification of alpine water resources under climate change. Based on these results, we will also discuss how the presented modeling framework offers new insights into the interplay of snow and ice storage, subsurface storage and precipitation forcing, i.e. into the key drivers of alpine streamflow regimes across elevation gradients

How to cite: Schaefli, B., Santos, A. C., and Rinaldo, A.: Disentangeling key drivers of high alpine hydrology with analytic streamflow distribution models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18074, https://doi.org/10.5194/egusphere-egu2020-18074, 2020.

Intricated variabilities of stream water quality and of stream discharge can provide key insights of integrated processes occurring at the watershed scale. Yet it is difficult to disentangle the effects of hydrologic vs biogeochemical processes occurring in the different compartments of the critical zone, as well as the mixing associated to it. Here we developed a quasi-2D hillslope scale model able to represent the partitioning of precipitation into real evapotranspiration, shallow subsurface lateral flow and deeper groundwater flow circulation. Enhanced with an advective-dispersive particle tracking algorithm, the model delineates the age distributions of the associated flow lines and the resulting transient streamwater transit time distributions (TTDs). To relate geochemical datasets to TTDs, we connected the biogeochemical reactivity, spatially, to the compartment (regolith vs bedrock) and, in time, to the residence time of the different flowpaths.

We hypothesized that streamwater time series datasets (discharge and dissolved silica) and in-situ groundwater age tracers (CFCs) would build minimal but orthogonal information upon these partitioning and tracing processes. Applied to 4 different catchments in Brittany, we were able to represent the seasonal dynamics of evapotranspiration, discharge and dissolved silica (DSi) in rivers as well as CFC concentrations in aquifers once key characteristics of the watershed have been informed (evapotranspiration ratio, amount of water stored in the regolith and in the aquifer, bedrock transmissivity, weathering capacity). We found evapotranspiration ratio (ET/P) in average equal to 54% in agreement with independent, large-scale estimates (derived from the French climate Surfex model). The model also provides estimates for typical bedrock transmissivities around 5.10^-4 m²/s, mean transit times around 10 years with an important spatial and temporal variability, amount of stored water in average equal to 160 mm (resp. 3.10 m) in the regolith (resp. bedrock) and DSi weathering capacity of 0.3 mg/L/yr, which is in accordance with previous studies carried in crystalline contexts like Brittany [Leray et al. 2012, Kolbe et al. 2016, Marçais et al. 2018]. Simplifying the transient behavior of the catchment model with some analytical considerations enabled to directly inform these key characteristics with some properties of the measured datasets (e.g. average low flow rate, mean and standard deviation of the DSi time series, average CFC apparent ages).

This shows that these datasets can be used as standalone tracers and provide powerful indicators of critical zone characteristics described above. This also opens new avenues to spatialize the reactivity in the deep critical zone, and to integrate the information provided by different datasets (e.g. climatic forcing, discharge, solute concentrations, groundwater age tracers) measured in streams and in groundwater. Such modeling exercice paves the way toward an interdisciplinary understanding of the critical zone.

How to cite: Marçais, J., de Dreuzy, J.-R., Derry, L. A., Guillaumot, L., Guillou, A., Vautier, C., Aquilina, L., and Pinay, G.: Streamwater time series coupled to groundwater age tracers informs the hydrologic partitioning of rainfall, the transient age distributions and their associated reactivity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14076, https://doi.org/10.5194/egusphere-egu2020-14076, 2020.

Designing a distributed rainfall-runoff model requires many not obvious decisions, such as whether to include regional groundwater flow, whether to account for the spatial variability of topography, geology, soils and vegetation, and at which spatial resolution to resolve model inputs. Typically, the effect of such decisions is determined a posteriori, for example based on sensitivity analyses, with the disadvantage that if a decision is poorly made, it is necessary to restart the model development from the conceptualization stage, which is a time consuming process. We here show that a more effective strategy is to base such decisions on a preliminary analysis of the available data, hence by “looking at data first”. In particular, similarly to what done in catchment classification studies, we start by identifying potential climatic and landscape controls on streamflow signatures. These insights are subsequently used to inform model decisions such as the ones above described. This approach is illustrated in the Thur catchment in Switzerland (1702 km²), with 10 sub-catchments. The catchment shows a large variability in streamflow, climatic, and landscape characteristics. Results demonstrate that precipitation (quantity and type) is the main control of the water balance and of streamflow seasonality; geological features control the partition of the fluxes between baseflow and quick flow; other catchment characteristics are not of primary importance in determining streamflow variability. The present study, that conjugates some aspects of catchment classification with hydrological modelling, represents a step forward in understanding catchment dominant processes at the large scale and in designing a procedure for constructing distributed hydrological models with limited complexity.

How to cite: Fenicia, F. and Dal Molin, M.: Understanding what to account for and what to ignore in the design of distributed hydrological models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7467, https://doi.org/10.5194/egusphere-egu2020-7467, 2020.

The Budyko framework is a widely used empirical concept in hydrology and climatology. However, catchment water balances that plot along the curve are often noisy and scattered, with some catchments plotting above the curve and some below the curve. Here we examine one of the possible causes for such scatter: subsurface storage. We bring together data from 38 experimental catchments in Luxembourg where all climate and landuse factors are roughly constant, except for subsurface storage.

We leverage diverse catchment geology represented by the large differences in bedrock porosity and permeability with resulting large differences in storage and streamwater transit times across our set of nested catchments. This setting enables us to test the null hypothesis that departures (offset) from the Budyko line along the evaporative index (i.e. actual evapotranspiration / potential evapotranspiration) axis has no relation to below ground storage. We then ask the following questions:

1. Where do the 38 Luxembourg catchments plot in the Budyko space?
2. How do subsurface storage metrics vary across the 38 Luxembourg catchments?
3. How are these subsurface storage metrics related to the Budyko offset?

And secondarily,

1. What might explain scatter on the precipitation / PET axis in the Luxembourg catchments and how is this related to catchment area?

Our main finding is that subsurface storage—driven by differences in catchment geology—explains approximately 60% of the departure from the Budyko curve. Furthermore, scatter along the aridity index axis (i.e. precipitation / potential evapo-transpiration) is explained by an east-west gradient in precipitation amount within an otherwise low seasonality environment.

How to cite: Pfister, L., Schymanski, S., Nijzink, R., and McDonnell, J.: The role of subsurface storage on departures from the Budyko curve, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9746, https://doi.org/10.5194/egusphere-egu2020-9746, 2020.

Dry spells and heat waves control the frequency and duration of streamflow drought events. Groundwater storage and release in catchments can modulate their timing and severities in terms of deficit volume and persistence. To better understand the role of recharge and groundwater storage for catchment sensitivity to droughts we investigate the effect of recharge scenarios on streamflow drought characteristics and baseflow for 50 mesoscale catchments with different hydrogeological characteristics in southwestern Germany. In model experiments, we simulate daily recharge on a 1 km resolution with the water balance model TRAIN reflecting the most dominant soil-vegetation processes. Then we calibrate long-term reference simulations, fitting the outflow of different conceptual groundwater box models with varying model structure to hydrograph-separated baseflow. After calibration, we define probabilistic stress tests as scenarios of reduced pre-drought recharge. The tolerance of catchments to different drought intensities is analyzed based on the concepts of resistance, resilience, and recovery to drought situations. Results suggest that catchments with higher resistance and resilience are less sensitive to recharge stress, but recovery is often much slower. However, by comparing the events of e.g. 2003 and 2018 specifically, we show that the sensitivity is also a function of the intensity and duration of the stress test simulation, the drought event characteristics, and the storage memory of catchments. Additionally, the performance ranking of all groundwater models in each catchment allows to link the variability in model structure to catchment properties (e.g. geology). The analysis shows that catchments with short-term or long-term storage memory react differently under different stress tests. Stress test simulations may help to answer planning-relevant questions such as which preconditions make a drought intensification or prolongation more likely and how long does it take for the system to recover to the reference condition. Catchment-specific stress tests with historical worst-case pre-conditions before extreme drought events may thus be a way forward to constrain relevant timescales of drought management and drought early warning.

How to cite: Stoelzle, M., Hellwig, J., Stahl, K., Weiler, M., Tijdeman, E., and Menzel, L.: Stress test modelling to assess catchment drought resistance and recovery, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5046, https://doi.org/10.5194/egusphere-egu2020-5046, 2020.

Today there are tens of thousands of storage structures in the US ranging from Hoover Dam, with a capacity more than 34 million cubic meters, to small structures less than 2 m tall.  While there exists a myriad of water management tools that capture storage operations for local to regional systems, national and global scale hydrologic models struggle to incorporate this storage. Large scale earth system simulations generally exclude management operations or rely on generic operating policies due to lack of data.  Reservoir storage capacity is much more easily obtained and can tell us about the potential for regulation of a system, but without evaluating actual operations we can’t capture the actual influence of human storage on catchment dynamics.  Here we use the National Inventory of Dams to evaluate the evolution of total storage capacity across the US over the last century. Consistent with previous work we show spatial trends in storage volume relative to streamflow and storage purpose (i.e. flood control as opposed to water supply). To quantify the actual impact of operations on hydrologic regimes though, reservoir capacity is not sufficient. Therefore, we also assemble a dataset of reservoir inflows, outflows and changes in storage focusing on large reservoirs in the western US.  Using these timeseries we can isolate the historical regulation imposed by reservoirs and their impact catchment memory. Furthermore, we compare our historical observations to generic operating policies to evaluate how well storage dynamics are captured by existing models and the potential for these tools to over or underestimate reservoir impacts.

How to cite: Condon, L., Steyaert, J., and Spinti, R.: Evaluating Historical Impacts of Surface Reservoir Storage on Catchment Memory Across the US, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11875, https://doi.org/10.5194/egusphere-egu2020-11875, 2020.

The operation of multireservoir systems is a challenging decision-making problem due to (i) multiple, often conflicting, objectives (e.g. hydropower generation versus irrigated agriculture), (ii) stochastic variables (e.g. inflows, water demands, commodity prices), (iii) nonlinear relationships, (e.g. hydropower production function) and (iv) trade-offs between immediate and future consequences. Properly capturing the properties of the hydrologic processes responsible for the inflows is of paramount importance to enhance the performance of water resources systems. This becomes all the more relevant since low-frequency climate signals, which affect the hydrology in numerous regions around the globe, has increased in recent years. If traditional time series models generally fail to reproduce this regime-like behavior, so are the optimization models that are used to support multireservoir operation. Hidden Markov Model (HMM) is a class of hydrological models that can accommodate both overdispersion and serial dependence in historical time series, two essential hydrological properties that must be captured when modeling a system where the climate is switching between different states (e.g., dry, normal, wet). In terms of reservoir operation, Stochastic Dual Dynamic Programming (SDDP) is one of the few optimization techniques that can accomodate both system and hydrologic complexity. In SDDP, the hydrologic uncertainty is often captured by a multi-site periodic autoregressive (MPAR) model. However, MPAR models are unable to represent the long-term persistence of the streamflow process found in some regions, which may lead to suboptimal reservoir operating policies. We present an extension of the SDDP algorithm that can handle the long-term persistence and provide reservoir operating policies that explicitly capture regime shifts. To achieve this, the state-space vector now includes a climate variable whose transition is governed by a HMM. The Senegal River Basin (SRB), whose flow regime is characterized by multiyear dry/wet periods, is used as a case study.

How to cite: Tilmant, A. and Espanmanesh, V.: Optimizing the management of complex water resources systems taking into account the long-term persistence in streamflow, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11779, https://doi.org/10.5194/egusphere-egu2020-11779, 2020.

The 2019 major drought in northern France highlighted the necessity to design an efficient and reliable low-flow forecasting system. Most forecasting tools, based on rainfall-runoff surface models, could benefit from an utilization of piezometric data, broadly available over the French metropolitan territory: obviously, surface water/groundwater interaction are a key process to explain low-flow dynamics.

Indeed, aquifers carry most of the hydroclimatic memory of a catchment, which determines the intensity and duration of droughts: a catchment beginning summer with empty aquifers will not have the same trajectory as the same catchment with higher than average piezometric levels. However, the piezometric data itself is not straightforward to use in a hydrological model, since aquifer-river connexions are often equivocal. Thus, a prior analysis of available data is necessary.

In this work, using 100 catchments of the national French hydroclimatic database and available piezometric data from the national aquifer monitoring network, we performed a comparative memory analysis of piezometry and streamflow, through a simple convolution function. The results were then compared to the behaviour of GR6J, a conceptual lumped rainfall-runoff model. For each catchment of the dataset, a selection of relevant piezometers was made, in the perspective of developing a model incorporating their levels as input data.

How to cite: Pelletier, A. and Andréassian, V.: From aquifers’ and rivers’ memory to a better low-flow forecasting model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5701, https://doi.org/10.5194/egusphere-egu2020-5701, 2020.

The long-term memory of catchments (carried by their hydrogeological characteristics) has a considerable impact on low-flow dynamics. Here, we present an exploratory study on a large French dataset to characterize the climate elasticity of low-flows and understand its long-term dependency. The climate elasticity of catchments is a simple concept (almost model-free) that allows analyzing the linear dependency of streamflow anomalies to climate anomalies (Andréassian et al., 2016). Widely-used for average annual streamflow, we propose to extend this concept to annual minimum monthly flow anomalies (QMNA) in order to characterize the climate dependency of QMNAs. By introducing progressively the linear dependency to the climatic anomalies of previous years, we further characterize the long-term memory of low-flows for the catchments of our set.

References

Andréassian, V., Coron, L., Lerat, J., and Le Moine, N. 2016. Climate elasticity of streamflow revisited – an elasticity index based on long-term hydrometeorological records, Hydrol. Earth Syst. Sci., 20, 4503-4524.

How to cite: Andréassian, V. and de Lavenne, A.: Climate elasticity of low-flows: the long-term impact of droughts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19661, https://doi.org/10.5194/egusphere-egu2020-19661, 2020.

Long-term memory in hydrological systems is usually ascribed to extensive catchment water storage that builds up in wet periods and empties in dry periods. Besides, additional memory effects can result from plants responding to changing boundary conditions, from swelling or shrinking of clayey soils, etc. However, another fundamental effect is widely ignored. The second law of thermodynamics is often understood as an argument that the effects of external disturbances of natural systems fade off in the long term, resulting in basically stationary systems. However, this falls short of the mark and ignores that the damping of external triggers depends on the frequency of the signal: High frequency signals are much more damped during propagation through the same medium compared to low-frequency signals. This holds for electro-magnetic waves as well as for pressure waves. For example, low-frequency ground-penetrating radar exhibits larger penetration depth compared to higher frequencies, although at the cost of spatial resolution. Music is not only less loud but sounds more muffled on the other side of a concrete wall due to the overproportional loss of higher frequencies. The same holds, e.g., for time series of soil matrix potential or groundwater head that are nothing but irregular pressure waves. Consequently, the high frequency part of the signal of infiltrating rain or snowmelt is much more efficiently attenuated in the vadose zone, resulting in increasingly more smooth time series at greater depth. The low-frequency part of the signal is attenuated as well, but to a lesser degree. Thus, in the long-term only low-frequency signals remain, in some cases exhibiting period lengths of decades and more, which are often mistaken as trends, without any corresponding low-frequency input signal. As much of the catchment hydrology research has been done in small catchments and for shallow groundwater systems, and mostly based on short time series, these effects have been widely and systematically underrated so far. However, at larger spatial and temporal scales they become more evident and need more attention. Often power spectrum analysis is used to assess these effects. Another and even more efficient approach especially for complex systems is provided by principal component analysis of sets of hydrological time series. Some examples will be shown from a lowland region in Northeast Germany with extensive groundwater storage.

How to cite: Lischeid, G.: Long-term catchment memory: The underrated thermodynamic dimension, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5422, https://doi.org/10.5194/egusphere-egu2020-5422, 2020.

Groundwater is the largest store of freshwater on Earth after the cryosphere and provides a substantial proportion of the water used for domestic, irrigation and industrial purposes. Knowledge of the relationship between groundwater and climate is limited and undermined by the scale, duration, and accessibility of observations. Here we examine a 14-year period (2002-2016) of GRACE observations to investigate climate-groundwater dynamics of 14 tropical and sub-tropical aquifers selected from WHYMAP’s 37 large aquifer systems of the world. GRACE-derived changes in groundwater storage resolved using GRACE JPL Mascons and the CLM Land Surface Model are related to precipitation time series and regional-scale hydrogeology. We show that aquifers in dryland environments exhibit long-term hydraulic memory through a strong correlation between groundwater storage changes and annual precipitation anomalies integrated over the time series; aquifers in humid environments show short-term memory through strong correlation with monthly precipitation. This classification is consistent with estimates of Groundwater Response Times calculated from the hydrogeological properties of each system, with long (short) hydraulic memory associated with slow (rapid) response times. The results suggest that groundwater systems in dryland environments may be less sensitive to seasonal climate variability but vulnerable to long-term trends from which they will be slow to recover. In contrast, aquifers in humid regions may be more sensitive to seasonal climate disturbances such as ENSO-related drought but may also be relatively quick to recover. Exceptions to this general pattern are traced to human interventions through groundwater abstraction. Hydraulic memory is an important factor in the management of groundwater resources, particularly under climate change. 

How to cite: Taylor, R., Opie, S., Brierley, C., Shamsudduha, M., and Cuthbert, M.: Climate-groundwater dynamics inferred from GRACE and the role of hydraulic memory, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20485, https://doi.org/10.5194/egusphere-egu2020-20485, 2020.

The English Lake District has experienced a number of recent devastating flood events (2005, 2009, 2015), without precedent in terms of magnitude during recent centuries. Climate projections for Northwest England have forecast intensification in frequency and magnitude of extreme precipitation, calling for a review of current catchment management practices. Flood hazard management requires precise estimates of extreme flood magnitude and frequency to better inform estimates of future risk, but are challenged by the short duration of river gauging data that often fails to capture the rarer, high magnitude events.

Methodological developments increasingly permit the high-resolution analysis of palaeoflood frequency and magnitude from lake sediments; but development of a regional database is challenged by the variable distribution of lakes. Conversely reservoirs were built extensively across the British uplands from the mid-eighteenth century and are more ubiquitous in their distribution. Attempts to reconstruct flood chronologies from reservoir sediments are limited, despite this broad distribution and there is a growing need to capture reservoir catchment histories to guide management of upland water resources. Better histories for reservoir catchment is needed, because though dam failures are rare recent examples (e.g. Whaley Bridge, Derbyshire, August 2019) highlight a paucity of hydrological data associated with these often aging structures.

Here, we investigate the sediment records from Thirlmere reservoir (Cumbria) and assess their value as indicators for flood history. A 200-year flood chronology has been interpreted from high-resolution particle size analyses and geochemical ratios diagnostic of variations in sediment grain size alongside historical documentary evidence, and a chronology has been developed through 210Pb dating. We address the following questions:

1) Is it possible to create a high-resolution flood chronology of a centennial timescale from reservoir sediments to better inform reservoir catchment management practices?

2) How similar are reservoir-based flood reconstructions to data from nearby lakes and historical records?

3) Do catchment landuse practices, for example mining activity, affect sediment delivery to the reservoir basins perturbing flood reconstruction?

How to cite: Phillips, H., Chiverrell, R., and Macdonald, N.: Developing a 200-year flood chronology from reservoir sediments at Thirlmere, Northwest England, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20047, https://doi.org/10.5194/egusphere-egu2020-20047, 2020.

The Mediterranean region is very vulnerable to both water shortage and flooding. Hence, the study of the hydrological response characteristics of Mediterranean catchments is of a great importance especially that the region is one of the most densely populated on the planet. Numerous Mediterranean catchment hydrological studies exist in the literature, however, mostly concentrated in the European part of the Mediterranean, especially the north-western part of the basin. The eastern Mediterranean have fewer studies and this is indeed the case of Lebanon, a small mountainous country on the eastern shore of the Mediterranean. The objective of this work is to present a state of the art assessment of the hydrology of Lebanon in the largest Mediterranean context and to present a first classification attempt for the Lebanese catchments. Twenty-eight Lebanese basins where data are available are studied. Spatial data consist of Digital Elevation Model, land cover map, soil and geological maps of the country. Temporal hydro-meteorological data exist at a monthly and daily timescale for the period 2001-2011. The methodology is threefold: (1) a synthesis of the previous hydrological studies in Lebanon, (2) an analysis of the hydrological response characteristics of the Lebanese catchments and a comparison with other Mediterranean catchments, and (3) the classification of the Lebanese catchments according to their physical and hydrological response characteristics. After extracting physical descriptors and runoff signatures for the available data, using Agglomerative Hierarchical Clustering. The results of the synthesis of previous studies in Lebanon assert that indeed hydrological studies in Lebanon are scarce and when exist focus mostly on groundwater hydrology and water quality. Nevertheless. The Lebanese literature suggest that even though rainfall and physical characteristics are highly variable across the country, a certain regional pattern do exist. This is corroborated by the analysis of the Lebanese catchments temporal data. Indeed, mean annual runoff and runoff ratio across the country show regional tendencies with the highest values in the central part of mount Lebanon. Moreover, intra-annual variation of runoff also shows geographical pattern and can be divided into three main regimes: rainfall dominated, snow dominated and a mixed snow-rainfall regime. This is also true at the event scale, where unit maximum daily discharge and runoff depth and ratio, all show regional pattern with the highest values in the central part of Lebanon which receive the highest precipitation amount. In addition, the Lebanese catchments, and despite a high reference evapotranspiration, exhibit hydrological response characteristics that are similar to catchments in the wetter north-western Mediterranean than other catchments in the Eastern Mediterranean. Finally, the classification of the Lebanese catchments yielded five groups of catchments. This grouping is well in range with the regional pattern discussed in the literature and the data analysis of the Lebanese catchments.

How to cite: Merheb, M., Abdallah, C., Moussa, R., and Baghdadi, N.: Hydrological response characteristics and classification of Lebanese catchments , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-636, https://doi.org/10.5194/egusphere-egu2020-636, 2020.

The aim of the study is the spatial analysis of the structure of the river basin in identifying anthropogenic-transformed landscapes. The object of the study is the water catchment basin of the «Yayva» river, which is a left, mountain-taiga tributary of the «Kama» river and flows in the Perm region, in the Russian Federation. The river basin covers an area of km² 6502, long main river, 304 km, the average slope of the basin 1,85⁰, height difference is significant and is 687 meters. the Catchment has a high degree of ruggedness of 0.91 km/km2. The sharp asymmetry of the catchment basin is expressed, so the left part of the basin is more pronounced.

With the use of remote sensing satellite images with high spatial resolution Landsat – 8 and Sentinel – 2, based on digital elevation model and GIS tools identify the types of land cover of the basin. In the ArcGis 10.4 software environment, morphometric indicators of the river basin at the level of small rivers are determined. The map of the basin territorial structure is developed on the basis of a vector relief model with a section height of 25 meters. The areas of morphological elements of river basins are unevenly distributed over the absolute height and slope of the terrain, causing spatial heterogeneity of landscape structures.

In the zones of the sources of watercourses, water-collecting funnels of a rounded shape are formed, the boundaries of which are clearly deciphered from space images. In the direction from the mouth to the source along the main river, the average absolute height of the terrain increases from 170 to 540 meters, the height differences also increase, while the area of the catchment funnels increases from 0.04 km² to 13.4 km².

On well-drained slopes with average humidity, fern spruce-fir forests are represented, and on wet slopes and areas with temporary watercourses, sparse high-forest taiga and raw horsetail spruce forests are developed. Also, waterlogging is manifested in flat areas with poorly developed river network, where drainage is insufficient, so in the lower reaches of the basin, the wide valley of the river is swamped.

For each morphological element of the catchment area, a characteristic type of vegetation is determined. The most common wetland landscapes are confined to catchment funnels (37%), which is especially pronounced in mountainous conditions (upper reaches of the basin at an altitude of 500 meters or more); less wetlands (17%) occur in inland river valleys.

Transformed landscapes (cuttings and secondary forests) are confined to the upper parts of the slopes of the catchment surface (14%) and arcs of the watershed system (10%). The largest share of urbanized areas corresponds to inland river valleys (3%). Areal dynamics of anthropogenically transformed landscapes is determined. As a result of the analysis of the dynamics of vegetation cover, the growth of the area of cuttings, secondary forests and anthropogenic objects that form the basins of river systems was established.

The work was carried out with the financial support of The Russian Foundation for basic research No. 19-05-00363 A.

How to cite: Shutov, P.: Spatial analysis of the landscape structure of the river basin on the basis of remote sensing data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-428, https://doi.org/10.5194/egusphere-egu2020-428, 2020.

The National Hydrometric Program, operated by the Water Survey of Canada, is the primary source of surface water quantity data in Canada. The network is cost-shared between the federal and provincial governments, and decisions relating to station placement are made according to both federal and provincial interests. Nova Scotia is a small maritime province in Atlantic Canada that is roughly one third the size of England and Wales and has a diverse climate and geology. The Nova Scotia hydrometric monitoring network currently consists of just 31 stations. The overall objective of this study was to determine how well the current network captures the level of hydrologic variability expected in the province using a regional catchment classification scheme. To accomplish this, we developed a combined inductive-deductive catchment classification system and applied it to the province’s active monitoring network and ungauged major watersheds. Initially, hydrologic signatures were used to quantify the catchment function of 47 long-term gauged catchments and to cluster similarly behaving catchments. We identified five generalized flow classes and then attempted to replicate this classification using a deductive-based decision tree framework with physiographic and meteorological explanatory variables. The validated decision tree was used to classify the active hydrometric network and 250+ major watersheds in the province. The network was assessed to determine how well it covered the expected hydrologic variability in the major watersheds across the province. The decision tree proved to be a useful tool for understanding the current network’s coverage and could also be easily applied by practitioners to identify appropriate donor catchments for ungauged watersheds.

How to cite: Johnston, L., Dunnington, D., Greenwood, M., Kurylyk, B., and Jamieson, R.: Hydrologic assessment of a small maritime hydrometric monitoring network using a combined inductive-deductive process-informed catchment classification system, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11968, https://doi.org/10.5194/egusphere-egu2020-11968, 2020.

We present the Catchments Attributes for Brazil (CABra) dataset. This is the first large-scale dataset for Brazilian catchments and includes data for 1,252 catchments in seven main classes of catchment attributes (CA: streamflow, groundwater, geology, soil, topography, climate, and land-use and land-cover). We have collected and synthetized data from multi-sources (ground stations data, remote sensed data, and gridded data. CABra contains catchments over the six Brazilian biomes: Amazon, Atlantic Forest, Caatinga, Cerrado, Pampa, and Pantanal. We delineated all catchments using the coordinates of each streamflow station provided by the Brazilian Water Agency (ANA, in Portuguese). We only considered stations with more than 10 years of data records and less than 20% of missing data. Catchment areas range from 9 to 4,670,000 km² and the mean daily streamflow varies from 0.006 to 170,271 m³ s^-1. We also calculated several hydrological signatures – based on distribution, frequency and duration, and dynamics of daily streamflow – and climate indices. Additionally, this dataset includes  boundary shapefiles, centroids latitude and longitude, and drainage area for each catchment, aside from more than 50 attributes within each CA class. The CABra intends to fill a huge gap of multisource data collection in Brazil. This dataset plays an important role towards a better understanding of the climate-landscape-hydrology related drivers in a country of continental dimensions and heterogeneous landscape characteristics. Moreover, we described the collection and processing methods and discussed the limitations of each of our multiple data sources. Aside from being a potential tool for large-scale studies in hydrology, our extensive dataset is of main importance for the development of high-quality hydrologic studies in Brazil.

How to cite: Oliveira, P. T., Almagro, A., Pitaluga, F., Meira Neto, A., Durcik, M., and Troch, P.: CABra: a novel large-scale dataset for Brazilian catchments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12138, https://doi.org/10.5194/egusphere-egu2020-12138, 2020.

Catchments are complex self-organizing environmental systems for which the form, drainage network, channel geometries, soil and vegetation, are all an outcome of co-evolution and adaptation to the ecological, geomorphologic and land-forming processes. Quantification of hydrological signatures provides vital information about the complex system properties and the functional behaviour of catchments. This work aims at evaluating catchment similarity with respect to geomorphology and hydrological signatures such as runoff ratio, flow duration curves and peak flows for calibrating and upscaling model parameters. The study is carried out on the sub-catchments of Cauvery river basin which is a major river basin in Peninsular India. The basin is characterized by extensive regional variability in surface and groundwater availability and large-scale shift in land use patterns in recent decades. With a significant number of anthropogenic interventions such as check dams and reservoirs, the basin faces water management challenges at the local, regional and basin scales. Hydrological signatures derived from elevation, streamflow and meteorological data are used to evaluate geomorphologic and hydrological similarity between the sub-catchments. We employ the physically based macroscale Variable Infiltration Capacity (VIC) model coupled with a routing model to simulate the streamflow. Streamflow simulations are carried out for various sub-catchments delineated based on discharge gauging stations. Model parameters are estimated and hydrological signatures are assessed for effective model calibration. Impact of interventions on flow signatures at the catchment scale is also assessed. This work can significantly improve the scientific understanding of variability of hydrological processes at various scales and provide useful insights for development of scaling relationships. It can also aid in examining the model parameter transferability across scales.

How to cite: Reghunath, G. and Mujumdar, P.: Evaluating hydrological signatures and catchment similarities to estimate model parameters in Cauvery river basin, India, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12756, https://doi.org/10.5194/egusphere-egu2020-12756, 2020.

Hydrological signatures aim at extracting information about certain aspects of hydrological behaviour. They can be used to quantify hydrological similarity, to explore catchment functioning and to evaluate hydrological models. Relating hydrological signatures to hydrological processes is, however, still a challenge and many signatures remain poorly understood.

We propose a flexible approach for linking hydrological signatures to hydrological processes, which might help to improve our understanding and hence the usefulness of certain hydrological signatures. As a first step, we should build a perceptual model describing the hydrological process of interest. We should then try to find or create relevant – and ideally widely available – catchment attributes that target the process of interest, and hence have the potential to explain the signature in a process-based way. We should control for climate by either incorporating it into our perceptual model or by analysing sub-climates individually, to disentangle the influences of forcing and catchment form. Lastly, simple conceptual models might be a useful tool to systematically explore the controlling factors (parameters, forcing) of a signature. Focusing on hydrological processes and explaining hydrological signatures in a process-based way will make hydrological signatures more meaningful, useful and robust.

The proposed approach is tested on signatures related to baseflow and groundwater processes, such as the baseflow index. Baseflow generation has been studied extensively, and while many regional studies could identify landscape controls on baseflow generation (e.g. soils and geology), continental or global studies have resulted in a less clear picture, partially because of the masking influence of climate at these scales. Furthermore, the relationship between controls, such as climate and catchment form, and baseflow response has often been only described statistically (e.g. by means of regression-type approaches).  A mechanistic theory based on widely available catchment attributes (e.g. soils, geology, topography) would thus be a major step towards improved understanding and transferability.

How to cite: Gnann, S., Howden, N., Woods, R., and McMillan, H.: Linking hydrological signatures to hydrological processes and catchment attributes: a flexible approach applied to baseflow signatures, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3569, https://doi.org/10.5194/egusphere-egu2020-3569, 2020.

In the past decades, climate change has been leading to non-stationarity in hydrological variables. Therefore, a simple framework within the Budyko framework is proposed to estimate the annual runoff frequency distribution and provide a new method for hydrological design under non-stationarity conditions. In this framework, the mean and standard deviation of annual runoff are derived by the Choudhury-Yang equation. Furthermore, the P-Ш type frequency curve is selected to calculate the annual runoff on a design return period. Based on this framework, the change in water resources in 207 three-level basins across China during 2020-2050 are estimated according to the Coupled Model Inter-comparison Project Phase 5. The results show that the mean annual runoff will decrease by 2.7% for all basins, and the regional difference will decline, i.e., the mean annual runoff will increase in the north of China and decrease in the south of China. However, the inter-annual variability of annual runoff will increase in more than 70% of basins. Additionally, in the wet year, approximately half of the total basins show decreased runoff change, and in the dry year, decreased change appears in ~65% basins. These findings offer a simple and effective way to re-examine the effects of non-stationarity in hydrological design.

How to cite: Yang, H. and Liu, Z.: Estimation of the annual runoff frequency distribution under a non-stationarity condition within the Budyko framework, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21024, https://doi.org/10.5194/egusphere-egu2020-21024, 2020.

We employed a physically-based spatially explicit 3D model to investigate how certain catchment parameters influence water ages and water transport dynamics in low-order catchments. The parameters we explored were catchment shape, porosity, bedrock conductivity, soil conductivity decay with depth, water retention curve, precipitation frequency, precipitation sequence and precipitation event amount. Each one of the parameters has its own specific influence on water ages and transport. Some of the results were expected (higher porosity = longer transit times), some were surprising to us. For example, we found that bedrock conductivity does not have a simple straightforward relationship with catchment transit time (i.e. an increase in conductivity causing a decrease in transit time). Instead, an increase in bedrock conductivity can also result in the overall increase in catchment transit time – e.g., when this increase allows a larger proportion of water to infiltrate into the comparatively less conductive bedrock instead of flowing towards the outlet in the more conductive soil. Also, the sequence of precipitation events that constitute the atmospheric forcing does play a less important role than we expected, i.e. it does not matter how the differently-sized precipitation events driving the water flow through the catchment are arranged – as long as the precipitation event frequency is high (≤3 days) and the event amounts are Poisson-distributed. We conclude that the multitude of influences from the different parameters makes it very challenging to find rules and underlying principles in the integrated catchment response, therefore it is necessary to look at the individual parameters and their potential interactions and interdependencies in a bottom-up approach.

How to cite: Heidbüchel, I., Yang, J., Musolff, A., and Fleckenstein, J.: How certain physical and meteorological catchment parameters influence water ages and transit times, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8238, https://doi.org/10.5194/egusphere-egu2020-8238, 2020.

High nitrate concentrations in groundwater and surface water are a long-known but still widespread problem. To most efficiently reduce nitrate pollution, a detailed understanding of catchment organization and the catchment internal processes that drive nitrate mobilization, transport and storage across time scales is needed. Especially in mesoscale catchments (10¹ – 10³ km²), spatial heterogeneity adds another layer of complexity to these processes compared to headwater catchments. To address this issue, we analyzed seasonal long-term trends (1983 – 2016) and high frequency event dynamics (2010 – 2016) of nitrate concentrations, loads and the concentration-discharge relationship (CQ-slope) in three nested catchments within the Selke catchment (Germany). Transit time distributions (TTDs) were calculated for each nested catchment to analyze the response of nitrate export to changes in nitrogen surplus. The upper part of the Selke catchment is dominated by forests with only little agriculture and an overall lower nitrogen surplus, while the lower Selke is dominated by agriculture and a higher nitrogen surplus. Surprisingly, we found a disproportionally high contribution to nitrate loads from the forest-dominated upper Selke (64% of average annual load at the Selke outlet), caused by high nitrate concentrations during wet seasons ( average of 2.5 mg-N L^-1 during winter and spring) while dry season nitrate concentrations are relatively low (average of 1.1 mg-N L^-1 during summer and autumn). These seasonally high concentrations can be explained by the sub-catchment characteristics such as shallow soils and steeper slopes that lead to a low retention capacity and short effective transit times (peak of TTD after 2 years, indicating a fast response to changes in nitrogen surplus). The increase of nitrate concentrations with discharge resulted in a positive CQ-slope that was consistently observed in long-term dynamics and during events. In the lower Selke, nitrate concentrations are relatively constant across seasons (around 3.1 mg-N L^-1). This dynamic is caused by deeper aquifers, long effective transit times (peak of TTD at the Selke outlet after 14 years, indicating a delayed response to changes in nitrogen surplus) and legacy stores of nitrate that constantly release into the Selke River. Consequently, the lower Selke dominates nitrate concentrations and loads exported during dry seasons and is characterized by lower CQ-slopes compared to the upper Selke. Our study shows that the contribution of different sub-catchments to elevated nitrate concentrations can vary greatly between seasons, flow conditions and in their response to changes in nitrogen surplus. It is, therefore, not enough to focus on areas of highest nitrogen surplus – such as the upper Selke; instead, an assessment of all characteristic sub-catchments, their temporally variable contribution to nitrate export and their specific TTDs is needed to place reduction measures most effectively and to estimate realistic time scales for their success.

How to cite: Winter, C., Lutz, S., Musolff, A., Weber, M., and Fleckenstein, J. H.: Disentangling the impact of catchment heterogeneity in a meso-scale catchment on nitrate export dynamics across time scales, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13677, https://doi.org/10.5194/egusphere-egu2020-13677, 2020.

The water age is a lumped descriptor of the complex dynamics taking place in hillslope and catchments, allowing a synthetic description of mechanisms by which the hillslopes and the channel network transport water and solute at the outlet. Nevertheless, the assessment of the water age is still a challenging problem due to i-technical limitation in the data acquisition and ii- modeling simplification in the data interpretation.

In this study, we present a general physically based framework for the description of the water age in catchments. The water age at the catchment outlet is considered as collection of the different ages of the water particles moving through the outlet at a given time. The water age of each particle results from two main processes: the first one is the transport through the hillslope the second one is the transport thorough the channel. The interplay of those dynamics, which depends on hydrological and geometrical parameters, is of paramount importance in the water age and solute transport study.

Following the previous approach, we develop an analytical framework embedding: i- a Boussinesq model for the description of the flow and the assessment of the water ageing processes in hillslope, and ii- a geomorphological model for the assessment of the water transport and ageing in the channel network.  Besides introducing the model, we provide some relevant examples exploring the impacts of the hillslope and channel dynamics on the water age.

How to cite: Zarlenga, A. and Fiori, A.: How hillslopes and channels impact the water age in catchments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9871, https://doi.org/10.5194/egusphere-egu2020-9871, 2020.

The Anthropocene is an epoch in Earth’s history that has been proposed to characterise the global impact of human activities on the Earth's atmosphere, biosphere, hydrosphere, geosphere, i.e. the Critical Zone.

Just as for past climates, the signature of these anthropogenic impacts are recorded by environmental tracers dissolved in groundwater that could provide a better understanding of groundwater flows, residence time and mixing thus providing information on this major water resource both in terms of quantity and quality.

In this study, we use dissolved gases (CFCs, SF₆, ⁴He, ¹⁴C, noble gases and VOCs) and groundwater chemical composition as environmental tracers to unveil insights of the Anthropocene in a fractured aquifer in the northwest of France. We analyse the impact of groundwater abstraction on residence time and excess air composition. We evidence the influence of climate change through recharge temperature. We also quantify the appearance of anthropogenic compounds over the last decades.

These observations enable us to define precisely the anthropogenic limits and distribution within groundwater and thus to gain a better picture of the groundwater resource resilience potential in the future.

How to cite: Chatton, E., Labasque, T., Aeschbach, W., Vergnaud, V., Guillou, A., and Aquilina, L.: A glimpse of the Anthropocene captured by environmental tracers in the groundwater of a fractured aquifer, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13812, https://doi.org/10.5194/egusphere-egu2020-13812, 2020.

Residence and travel times of water in headwater catchments and hillslopes represent important descriptors of hydrological regime. In this study, travel time distributions were evaluated for a montane forest hillslope site using a two-dimensional dual-continuum model. The model was used to simulate the seasonal soil water regime and selected major rainfall–runoff events observed at the hillslope site. In particular, it was used to generate hillslope breakthrough curves of a fictitious conservative tracer applied at the hillslope surface in the form of the Dirac impulse. The simulated tracer breakthroughs allowed us to estimate the travel time distributions of soil water associated with the episodic subsurface stormflow, deep percolation and transpiration, yielding partial travel time distributions for the individual discharge processes. The travel time distributions determined for stormflow were dominated by the lateral component of preferential flow. The event-based stormflow median travel times ranged from 1 to 17 days. The estimated travel times were significantly affected by the temporal rainfall patterns and antecedent soil moisture distributions. The applied modeling methodology can be used for the evaluation of runoff dynamics at the hillslope and catchment scales as well as for the quantification of biogeochemical transformations of dissolved chemicals.

How to cite: Dusek, J. and Vogel, T.: Evaluating travel time distributions of macroporous hillslope, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17660, https://doi.org/10.5194/egusphere-egu2020-17660, 2020.

At a very general level most surface and subsurface hydrologist would surely agree that their systems usually exhibit an enormous spatial heterogeneity. Jim Dooge was probably one of the first hydrologists who distinguished different types of heterogeneity namely stochastic and structured variability and to reflect about how these affect predictability of hydrological dynamics. He concluded that most hydrological systems drop into Weinberg’s category of organized complexity – they are too heterogeneous for a purely deterministic handling, but they exhibit too much organization for a pure statistical treatment.

A straightforward way for defining spatial organization of a system is through its deviation from the state of maximum entropy, where all gradients are depleted. In this light the persistence of a smooth topography is probably the most obvious form of landscape organization; and catchment systems reflect the interplay of tectonic uplift and the amount of work water and biota have performed to weather and erode solid materials, to form soils and create flow paths. Despite of the fact these processes are strongly dissipative and produce entropy, they nevertheless leave signatures of self-organization in catchment systems. These are for instance manifested through the soil a catena and even stronger through all kinds of preferential flow paths veining the subsurface, to rill and river networks connecting across multiple scales. These networks exhibit similar topological characteristics and they commonly increase the efficiency in transporting water, chemicals, sediments/ colloids and energy across driving gradients across scales and compartments.

In line with these thoughts, joint research within the CAOS project has been guided by the postulate that self-organization in catchments leads to hydrological similarity and simplicity. This was deemed to manifest through the existence of a hierarchy of functional units, which act similarly either with respect to the controls of land-surface-atmosphere energy exchange and evaporation during radiation driven conditions or with respect to the controls of rainfall driven stream flow generation and water driven transport . This study will present model and experimental evidence from multiple catchments that functional units for stream flow generation exist and that the complexity of catchment functioning is indeed changing at its own pulse. The key to define these functional units is to acknowledge that runoff is jointly controlled by driving potential energy differences and dissipative losses along the flow paths and that a similar combination of both will create cause runoff generation. While potential energy differences largely relate to catchment topography, dissipative losses increase with flow path length and the length specific energy loss. The latter is on one hand controlled by local textural properties, depending on either surface roughness or subsurface hydraulic conductivity and wetness, while on the other hand either rills or subsurface preferential flow paths reduce dissipative losses. Based on this evidence we suggest functional units exist, that they allow a simplification of hydrological models without loosing the physical basis and without loosing predict performance. If catchments are spatially organised, we expect that their dynamic functioning is less than the sum of their elements.

How to cite: Zehe, E., Loritz, R., Ehret, U., Westhoff, M., Kleidon, A., and Mälicke, M.: From catchment organization to dynamic functional similarity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19632, https://doi.org/10.5194/egusphere-egu2020-19632, 2020.

The catchment hydrologic behavior is the result of a complex interaction between its physical characteristics, such as bedrock lithology, superficial geology, soil type and depth, vegetation type, topography, and drainage network. It has been known for a long time that, in addition to climate characteristics, the variations in the geomorphological and lithological features inside the basin originate specifics surface hydrodynamics, particularly in terms of runoff velocity, runoff amount and lag time. Understanding the hydrological functioning of the different sectors in a basin is essential to its spatial planning and management under the present scenario of climate uncertainty.

The Arunca river catchment is situated in the center-west of Portugal and occupies an area of about 550 km². One of the main characteristics is its geomorphological and lithological diversity, which is responsible for the existence of two different hydrological dynamics: (i) a karstic hydrodynamic where the cryptoreic drainage is absolutely dominant, and (ii) a fluvial hydrodynamic, characterized totally by surface runoff (exorheic drainage). The overall aim of this empirical study is to investigate and quantify the geomorphological and lithological influence on the hydrological behavior of these areas, which present very different physical characteristics.

Methodologically, we have adopted an empirical approach based on the analysis of spring and river hydrographs for simultaneous hydrometeorological events. Daily and hourly datasets of rainfall and spring and river flow were performed from 2009/2010 to 2014/2015. The data of the outflow from the karst area were collected by a gauge station at the main spring of the Degracias-Sicó karst aquifer. A second gauge station registered the data of river flow at the Arunca river sub-catchment, a non-karstic area, where only surface hydrodynamic is observed. Both gauge stations recorded data with an acquisition time interval of 20 minutes. The rainfall data were registered every 0.2 mm by two rain gauges installed, one in each studied sector of the catchment. An intra-annual period of analysis was established from October to May in order to understand the hydrodynamic functioning under diverse underground hydraulic conditions in different moments along the hydrological year. For every hydrometeorological event in both study areas of the basin, the hydrograph analysis focused on the calculation of the lag time, the time lag between the hydrological response of spring and river. The shape of the rising limb and the recession curve also was examined.

The results display a similar reaction of both sectors to a rainfall event. However, the lag time is shorter in the river than in spring, and the hydrograph of the river presents a more pronounced peak flow.  The main difference stands in the recession curve, particularly in the falling limb, much steeper in the river hydrograph, which shows the return to pre-event conditions only some hours after the peak flow. Basing on the simple analysis of the hydrograph, it is clear the effects of geomorphology and lithology in catchment hydrodynamic behavior.

How to cite: Paiva, I. and Cunha, L.: The influence of geomorphological and lithological diversity in catchment hydrodynamic behavior. The case of Arunca river catchment, Portugal, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22210, https://doi.org/10.5194/egusphere-egu2020-22210, 2020.

In many areas of the world, the surface of the earth is changing rapidly. Surface runoff is one of the processes that can dramatically modify the shape of our landscapes but is also affected by the land surface characteristics. However, our understanding of the evolution of overland flow characteristics and the feedback mechanisms between hydrological, pedological, biological and geormorphological processes that affect surface runoff is limited.

We used a space-for-time approach and studied 3 plots (4m x 6m each) on four different aged moraines (several decades to ~13.500 years) on the Sustenpass near the Steinglacier and in the karstic glacier foreland of the Griessfirn near Klausenpass (total of 24 plots) to determine how surface runoff generation changes during landscape evolution. We used artificial rainfall experiments with three different intensities to determine the surface flow ratio, peak flow rate, timing and duration of surface runoff. The addition of tracers (²H and salt) to the sprinkling water and sampling of soil water allowed identification of the mixing of the water within the slopes and the interaction of overland flow pathways with the subsurface. In addition, the runoff samples and sensor-based turbidity measurements provide an estimate of the erosion rates during extreme events. In order to link the differences in surface runoff generation with the pedological and biological characteristics of the slopes, soil and vegetation samples were taken on each plot to determine soil texture and root characteristics and the saturated hydraulic conductivity was measured in situ at three different depths.

The results show that the surface runoff amount and related erosion rates, response times and mixing of surface runoff and soil water change during landscape development and can largely be explained by related changes in soil surface and near surface characteristics. However, the rate of these changes during landscape evolution depends on the geology.

How to cite: Maier, F. and van Meerveld, I.: Surface runoff evolution on moraines in silicate and carbonate proglacial areas of the Swiss Alps, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20296, https://doi.org/10.5194/egusphere-egu2020-20296, 2020.