Understanding and representing hydrological processes is the basis for developing and improving hydrological and Earth system models. Modeling and learning is a symbiotic and continuous process through which our understanding of human-natural systems is formulated and tested constantly. As a result, a variety of models are developed and trained by quantitative and qualitative data across desired temporal and spatial scales.
In this session, we welcome contributions on the development of novel data sets and frameworks for model development and evaluation across spatio-temporal scales from catchment to continental scale hydrology. The vision of our session, following the initiative of 23 Unsolved Problems in Hydrology (UPH, https://doi.org/10.1080/02626667.2019.1620507), is to address three questions: What are the hydrologic laws at the catchment scale and how do they change with scale? How can hydrological models be adapted to be able to extrapolate to changing conditions, including changing vegetation dynamics? How can we disentangle and reduce model structural/parameter/input uncertainty in hydrological prediction?
We welcome contributions that (but not limited to):
(1) introduce new global and regional data products into the modeling process;
(2) introduce new approaches for model calibration and evaluation, especially to improve process representation, and/or to improve model predictions under changing conditions;
(3) improve model structure by representing often neglected processes in hydrological models such as human impacts, river regulations, irrigation, as well as vegetation dynamics;
(4) provide novel concepts for improving the characterization of internal and external model fluxes and their spatio-temporal dynamics;
(5) upscale experimentalists' knowledge from smaller to larger scale by identifying driving forces for spatial patterns for a better usage of them in models;
(6) suggest more effective monitoring and seamless modeling of spatial patterns in hydrology and land models using distributed earth observations;
(7) develop novel approaches and performance metrics for evaluating and constraining models in space and time; and
(8) identify model limitations and conceptual improvements that are of general relevance to the geosciences modeling community.
This session is organized as part of the grass-root modelling initiative on "Improving the Theoretical Underpinnings of Hydrologic Models" launched in 2016.
vPICO presentations: Wed, 28 Apr
Land surface models are highly uncertain in estimating evapotranspiration (ET) fluxes, and differ substantially in their projections of how ET will evolve in the future. Biases in estimated ET fluxes will affect the partitioning between sensible and latent heat, and thus alter simulated temperatures and model predictions of droughts and heatwaves. One potential source of bias is the "aggregation bias" that arises whenever nonlinear processes, such as those that regulate ET fluxes, are modeled using averages of heterogeneous inputs. Here we demonstrate that this aggregation bias leads to substantial overestimates in ET fluxes in a typical large-scale land surface model. The proposed methodology can be used to correct for aggregation biases in ET estimates by quantifying the effects of finer-resolution spatiotemporal variability in ET drivers at each modeling time step, without explicitly representing sub-grid heterogeneities in large-scale land surface models.
How to cite: Rouholahnejad Freund, E., Zappa, M., and James, K.: Aggregating over land surface heterogeneity systematically biases evapotranspiration estimates in large-scale evaporation models, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15460, https://doi.org/10.5194/egusphere-egu21-15460, 2021.
Due to the land surface complexity, soil moisture immensely varies both spatially and temporally. However, the combined effects of land surface complexity and key hydrological processes (e.g., subsurface lateral flow) on fine-scale soil moisture heterogeneity remain elusive due to the scarcity of observations. Benefit from improvements in hyper-resolution land surface modeling, it provides an unprecedented opportunity to investigate the fine-scale soil moisture heterogeneity over a large region. Here, we use the Conjunctive Surface-Subsurface Process model version 2 (CSSPv2), which considers subsurface lateral flow, to perform hyperresolution (100-m) simulations over ten selected regions with different climate. We find that the heterogeneities of vegetation, soil texture, precipitation or their combinations increase soil moisture heterogeneity significantly (p<0.01). If only the topography heterogeneity presents, subsurface lateral flow increases the soil moisture heterogeneity significantly (p<0.01). However, the effect of subsurface lateral flow has been reduced by combining topography heterogeneity with other surface heterogeneities, with a few regions showing decreased soil moisture heterogeneity mainly because of the combined effect of subsurface lateral flow and soil texture heterogeneity. This study suggests that soil texture heterogeneity does not necessarily interact synergistically with physical processes (e.g., subsurface lateral flow) for increasing soil moisture heterogeneity, although they can increase the heterogeneity separately.
How to cite: Zeng, J., Yuan, X., and Ji, P.: Effect of surface heterogeneity on hyper-resolution simulation of soil moisture, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9077, https://doi.org/10.5194/egusphere-egu21-9077, 2021.
To clarify rainfall-runoff responses in mountainous areas is essential for disaster prediction as well as water resource management. Runoff is considered to be affected by many factors including evapotranspiration, rainfall, topography, geology, vegetation, and land use. Among them, topography is said to be the most affectable factor. However, previous studies focused on geologies revealed that though catchments in crystalline mountains have less differences among runoffs, catchments in sedimentary rock mountains show great variation in their runoffs. To explain this difference, the geological structures were expected to be the key of runoffs in sedimentary rock mountains. In other words, particularly in headwater catchments located in sedimentary rock mountains, dips and strikes may significantly affect rainwater discharge. Moreover, the groundwater system can significantly be affected by the hydraulic anisotropy originated from geological stratigraphy. Additionally, in sedimentary rock mountains, previous studies suggested convergence of groundwater flows in the direction of strikes, but the effects of dips and strikes on rainfall-runoff responses were not investigated. Furthermore, none of these previous studies focused on the effects of geological structures on storm runoff responses. Therefore, based on the simultaneous observation of twelve catchments that lie radially from a single, isolated mountain peak, this study aims to clarify the effects of dips and strikes, which characterize sedimentary rock mountains, on water discharge.
The results obtained were as follows: (1) Even though the topographic wetness index (TWI) distributions of the twelve catchments were similar, there were significant differences in their runoff characteristics; (2) Catchments with average flow direction oriented toward the strike direction (strike-oriented catchments) are characterized by large baseflows; (3) Catchments with average flow direction oriented toward the opposite dip direction (opposite dip-oriented catchments) are steep, and this results in quick storm runoff generation; (4) Catchments with average flow direction oriented toward the dip direction (dip-oriented catchments) are gentle, and this results in delayed storm runoff generation. It was supposed that in strike-oriented catchments, large quantities of groundwater flowing along the bedding planes owing to hydraulic anisotropy, exfiltrate and sustain the large amount of the observed baseflow, i.e., in strike-oriented catchments, runoff is directly controlled by geological structures. On the other hand, in opposite dip-oriented and dip-oriented catchments, runoff is indirectly controlled by geological structures, i.e., geological structures affect slope gradients, which result in differences in storm runoff generation. Thus, this study clearly explains that geological structures significantly affect rainfall-runoff responses in headwater catchments located in sedimentary rock mountains.
How to cite: Inaoka, J., Kosugi, K., Masaoka, N., Itokazu, T., and Nakamura, K.: Effects of Geological Structures on Rainfall-Runoff Processes in Headwater Catchments in a Sedimentary Rock Mountain, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-63, https://doi.org/10.5194/egusphere-egu21-63, 2021.
The Putorana Plateau is located in the North-West of the Central Siberian Plateau in the Krasnoyarsk Territory in permafrost zone. Some mountain peaks reach a height of 1400 - 1700 m. The plateau is composed of stepped canyons formed by the outpouring of a huge mass of red-hot basalts. The Putorana Plateau is the territory that is still unexplored in hydrological terms. Climate change contributes to an increase in the thickness of seasonal thawing, therefore, the conditions of runoff formation change.
The purpose of the work is to study the factors of runoff formation, including the research of geocryological conditions based on short-term expedition data of the State Hydrological Institute (St. Petersburg, Russia) collected in small catchments in 1988-1990.
The object of study is the catchment of the stream Dupkun (an area of 2.75 sq. km), which is located in the basin of the Kureyka river basin, the right tributary of Yenisei River in the southwestern part of the Putorana Plateau. The maximum height of the catchment is 1228 m, and the hydrological gauge is located at an altitude of 923 m. The average slope of the catchment area is 12°. The landscape is a moss-grass mountain tundra, and perennial snowfields are also formed.
The expedition studies in the period from July 19 to September 4, 1990 included the collection of hydrometeorological information, the determination of soil characteristics (moisture content, temperature, structure at different depths and landscapes), and the study of snow cover. The route studies were conducted to determine the characteristics of landscapes, vegetation and soils in the basins of the rivers Kureyka and Khantayka.
The data of the expedition studies were processed, digitized and systematized. Based on the collected material, the water balance of the stream Dupkun was calculated. The presence of perennial snowfields has a significant impact on the formation of runoff. At the beginning of observations, the area of snowfields was 15 %, the average snow height was 2.6 m, and the average density was 0.7 g / cm3. At the end of observations, snowfields occupied 8% of the catchment area. For 20 days, the snowmelt depth was 38 mm, the precipitation reached 140 mm, and the runoff was 167 mm. The runoff coefficient is 0.89. During the entire observation period, the runoff reached 355 mm.
These observations are considerable value due to the lack of knowledge of the geocryological, landscape and hydrological conditions of the Putorana Plateau. Since there are practically no hydrological stations in this region that study the processes of flow formation, the collected data become even more unique. Extremely scarce data allowed to conduct the assessment and verification of the parameters of the hydrological model "Hydrograph". The developed set of the model parameters was used to simulate the river flow of tundra landscapes of the Putorana Plateau and assess its contribution to the formation of the water balance of the territory in the current climate.
The study was supported by the RFBR (project No. 19-55-80028).
How to cite: Zemlianskova, A., Makarieva, O., and Nesterova, N.: Processes of runoff formation at the Putorana Plateau (Central Siberia, Russia), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-208, https://doi.org/10.5194/egusphere-egu21-208, 2021.
A recent initiative by the hydrologic community identified processes that control hillslope-riparian-stream-groundwater interactions as one of the major unsolved scientific problems in Hydrology. It is a long-time argument among hydrologists whether to eliminate the minor details from field-based costing a lot of time, effort, and resources to understand the hydrological process in watershed scale. The modelling approaches are helpful is these cases by focusing on the dominant controllers and might/might'nt bypassing the implications from minor details. In this work, a conceptual semi-distributed rainfall-runoff model for hilly watersheds is used with satellite-based hydrometeorological inputs to parameterize, and thus understand by calibration and validation, at Koshi River Basin, a partly hilly watershed in Himalaya. The semi-distributed model is operated by dividing the river basin into small grids of around 1km2, each representing a micro-watershed. Majority of the model concept is drawn from fill and spill approach from previous literature, observations from plot-scale hillslope experiments, and macropore characterization from dye-tracer experiments, which are upscaled at micro-watershed scale. The parameterization in the rainfall-runoff model includes the daily average variables namely, threshold for runoff generation (T), gradient of runoff generation rate (S), saturated hydraulic conductivity for hillslope aquifers (Ksat), and aquifer thickness limit (D). Variable ranges of these parameters were simulated to find the best values (T = 1±0.25cm; S = 0.6 – 0.1; Ksat ≈ 105 – 1010 times original Ksat; and D = 1m). These ranges resulted in over (NSE = 0.6; R2 = 0.65) during calibration and validation for daily flow volume at the outlet. In these simulations, the Ksat multiplied with factors at several orders higher scale and producing good NSE values shows domination of preferential pathways in runoff generation process. This might represent a flow similar to that of overland flow affecting the surface runoff volume at river basin scale. This model could be used for water budgeting studies in hilly watersheds where several hillslopes dominated by macropores are present.
How to cite: Padhee, S. K. and Dutta, S.: Macropore domination in runoff generation process: A case study by hydrological modelling in Hilly Watersheds of Koshi River Basin, Himalaya, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14425, https://doi.org/10.5194/egusphere-egu21-14425, 2021.
A better understanding of hydrological processes in agricultural catchments is not only crucial to hydrologists but also helpful for local farmers. Therefore, we have built the freely-available web-based WALNUD dataset (Water in Agricultural Landscape – NUčice Database) for our experimental catchment Nučice (0.53 km2), the Czech Republic. We have included observed precipitation, air temperature, stream discharge, and soil moisture in the dataset. Furthermore, we have applied numerical modelling techniques to investigate the hydrological processes (e.g. soil moisture variability, water balance) at the experimental catchment using the dataset.
The Nučice catchment, established in 2011, serves for the observation of rainfall-runoff processes, soil erosion and water balance of the cultivated landscape. The average altitude is 401 m a.s.l., the mean land slope is 3.9 %, and the climate is humid continental (mean annual temperature 7.9 °C, average annual precipitation 630 mm). The catchment consists of three fields covering over 95 % of the area. There is a narrow stream which begins as a subsurface drainage pipe in the uppermost field draining the water at catchment. The typical crops are winter wheat, rapeseed, mustard and alfalfa. The installed equipment includes a standard meteorological station, several rain gauges distributed in the area of the basin, and an H flume to monitor the stream discharge, water turbidity and basic water quality indicators. The soil water content (at point scale) and groundwater level are also recorded. Recently, we have installed two cosmic-ray soil moisture sensors (StyX Neutronica) to estimate large-scale topsoil water content at the catchment.
Even though the soil management and soil properties in the fields of Nučice seem to be nearly homogeneous, we have observed variability in the topsoil moisture pattern. The method for the explanation of the soil water regime was the combination of the connectivity indices and numerical modelling. The soil moisture profiles from the point-scale sensors were processed in a 1-D physically-based soil water model (HYDRUS-1D) to optimize the soil hydraulic parameters. Further, the soil hydraulic parameters were used as input into a 3D spatially-distributed model, MIKE-SHE. The MIKE-SHE simulation has been mainly calibrated with rainfall-runoff observations. Meanwhile, the spatial patterns of the soil moisture were assessed from the simulation for both dry and wet catchment conditions. From the MIKE-SHE simulation, the optimized soil hydraulic parameters have improved the estimation of soil moisture dynamics and runoff generation. Also, the correlation between the observed and simulated soil moisture spatial patterns showed different behaviors during the dry and wet catchment conditions.
This study has been supported by the Grant Agency of the Czech Technical University in Prague, grant No. SGS20/156/OHK1/3T/11 and the Project SHui which is co-funded by the European Union Project: 773903 and the Chinese MOST.
How to cite: Li, T., Noreika, N., Jeřábek, J., Dostál, T., and Zumr, D.: Exploring hydrological processes at a small agricultural catchment in the Czech Republic, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4952, https://doi.org/10.5194/egusphere-egu21-4952, 2021.
In agricultural catchments, subsurface runoff is an important process for streamflow generation and the transport of nutrients and pollutants within and out of the catchment. Where and when subsurface runoff occurs is linked to the hydrologic connectivity in the catchment. This study compares spatial patterns of the connectivity between the hillslope and the stream on the event and seasonal scale. We analyse streamflow and groundwater responses to 53 precipitation events and their seasonal dynamics over two years in the Hydrologic Open Air Laboratory (HOAL), a small (66 ha) agricultural headwater catchment in Lower Austria. We quantify the connectivity in terms of Spearman correlation, hysteresis index and peak-to-peak time between streamflow and groundwater dynamics. It shows a clear spatial pattern, i.e. the connectivity is greatest in the riparian zone and diminishes further away from the stream where the groundwater table is deeper. This is reflected in the significant correlation of connectivity to the topographic indices and groundwater depth. Groundwater connectivity to the stream on the seasonal scale is higher than that on the event scale, indicating that groundwater contributes more to the baseflow than event runoff.
How to cite: Pavlin, L., Széles, B., Strauss, P., Blaschke, A. P., and Blöschl, G.: Comparison of the event and seasonal hillslope-stream hydrologic connectivity in an agricultural headwater catchment, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14946, https://doi.org/10.5194/egusphere-egu21-14946, 2021.
Understanding the movement of water in soils is important for estimating subsurface water reserves. Despite the advances made in understanding water movement, very few tools can directly ‘follow the water’. Tritium, a tracer that decays with time and resides within individual water molecules, is one such tool. Some tritium is produced naturally, others result from the nuclear bomb test era of the 1960s. Since the atmospheric nuclear tests ended following the Partial Nuclear Test Ban Treaty in 1963, however, the amount of tritium in soil water has declined, putting into question the usefulness of the environmental tritium method for tracking water movement in future studies. Our study explores the usefulness of the tritium method. Our results highlight the narrow window of time, over the next 20 years depending on the model used, within which the tritium method may still be applicable. We call on scientists to now take full advantage of the environmental tritium method in places where the tool may still be applicable. A richer understanding of water movement in soils is ultimately critical for ecosystem services and water resources management, particularly in semi-arid environments with deep soils.
How to cite: Evaristo, J., Huang, Y., Li, Z., Chun, K. P., Sutanudjaja, E. H., and Bierkens, M. F. P.: The nature and extent of bomb tritium remaining in deep soils, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12504, https://doi.org/10.5194/egusphere-egu21-12504, 2021.
Hydrological models are often calibrated with respect to flow observations at the basin outlet. As a result, flow predictions may seem reliable but this is not necessarily the case for the spatiotemporal variability of system-internal processes, especially in large river basins. Satellite observations contain valuable information not only for poorly gauged basins with limited ground observations and spatiotemporal model calibration, but also for stepwise model development. This study explored the value of satellite observations to improve our understanding of hydrological processes through stepwise model structure adaption and to calibrate models both temporally and spatially. More specifically, satellite-based evaporation and total water storage anomaly observations were used to diagnose model deficiencies and to subsequently improve the hydrological model structure and the selection of feasible parameter sets. A distributed, process based hydrological model was developed for the Luangwa river basin in Zambia and calibrated with respect to discharge as benchmark. This model was modified stepwise by testing five alternative hypotheses related to the process of upwelling groundwater in wetlands, which was assumed to be negligible in the benchmark model, and the spatial discretization of the groundwater reservoir. Each model hypothesis was calibrated with respect to 1) discharge and 2) multiple variables simultaneously including discharge and the spatiotemporal variability in the evaporation and total water storage anomalies. The benchmark model calibrated with respect to discharge reproduced this variable well, as also the basin-averaged evaporation and total water storage anomalies. However, the evaporation in wetland dominated areas and the spatial variability in the evaporation and total water storage anomalies were poorly modelled. The model improved the most when introducing upwelling groundwater flow from a distributed groundwater reservoir and calibrating it with respect to multiple variables simultaneously. This study showed satellite-based evaporation and total water storage anomaly observations provide valuable information for improved understanding of hydrological processes through stepwise model development and spatiotemporal model calibration.
How to cite: Hrachowitz, M., Hulsman, P., and Savenije, H.: Stepwise improvement of hydrological models using satellite-based evaporation and total water storage estimations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-796, https://doi.org/10.5194/egusphere-egu21-796, 2021.
Most lumped hydrological models are focused on the rainfall-runoff relationship, since climatic conditions are the driving force of the hydrological behaviour of a catchment. Many hydrological models, like the ones used by the French national PREMHYCE platform, only take climatic variables as inputs – daily rainfall and potential evaporation – to simulate and forecast low-flows. Yet, a hydrological drought is generally a medium- to long-term phenomenon, which is the consequence of long records of dry climatic conditions. Daily lumped hydrological models often struggle to integrate these records to reproduce catchment memory.
In many French catchments, it was observed that this memory of past hydroclimatic conditions is well represented in piezometric signals that are broadly available over the national territory. Indeed, aquifers, especially the large ones, do store water on the long, feeding rivers during droughts: aquifers are not only water carriers – the etymology for the word aquifer – they are also memory carriers. A dataset of 108 catchments, each of them being associated with one or several piezometers, was used to investigate whether the GR6J daily lumped rainfall-runoff model could be constrained by piezometric time series to improve low-flow simulations. We found that a particular state of the model, the exponential store, is particularly well correlated with piezometry in most studied catchments.
In order to get a univocal relationship between the exponential store and piezometry, a multi-objective calibration approach was implemented, optimising both (i) flow simulation with a criterion focused on low-flows and (ii) affine correspondence between the exponential store level and piezometry. For that purpose, a new parameter was added to the model. The modified calibration was then evaluated through a split-sample test and the performance in simulating particular drought events. The calibrated store-piezometry relationship can now be used for data assimilation to improve low-flow forecasting.
How to cite: Pelletier, A. and Andréassian, V.: Constraining a lumped rainfall-runoff model with piezometry to improve low-flow simulation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4402, https://doi.org/10.5194/egusphere-egu21-4402, 2021.
Hydrological models are increasingly used under evolving climatic conditions. They should thus be evaluated regarding their temporal transferability (application in different time periods) and extrapolation capacity (application beyond the range of known past conditions). In theory, parameters of hydrological models are independent of climate. In practice, however, many published studies based on the Split-Sample Test (Klemeš, 1986), have shown that model performances decrease systematically when it is used out of its calibration period. The RAT test proposed here aims at evaluating model robustness to a changing climate by assessing potential undesirable dependencies of hydrological model performances to climate variables. The test compares, over a long data period, the annual value of several climate variables (temperature, precipitation and aridity index) and the bias of the model over each year. If a significant relation exists between the climatic variable and the bias, the model is not considered to be robust to climate change on the catchment. The test has been compared to the Generalized Split-Sample Test (Coron et al., 2012) and showed similar results.
Here, we report on a large scale application of the test for three hydrological models with different level of complexity (GR6J, HYPE, MIKE-SHE) on a data set of 352 catchments in Denmark, France and Sweden. The results show that the test behaves differently given the evaluated variable (be temperature, precipitation or aridity) and the hydrological characteristics of each catchment. They also show that, although of different level of complexity, the robustness of the three models is similar on the overall data set. However, they are not robust on the same catchments and, then, are not sensitive to the same hydrological characteristics. This example highlights the applicability of the RAT test regardless of the model set-up and calibration procedure and its ability to provide a first evaluation of the model robustness to climate change.
Coron, L., V. Andréassian, C. Perrin, J. Lerat, J. Vaze, M. Bourqui, and F. Hendrickx, 2012. Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments, Water Resour. Res., 48, W05552, doi:10.1029/2011WR011721
Klemeš, V., 1986. Operational testing of hydrological simulation models, Hydrol. Sci. J., 31, 13–24, doi:10.1080/02626668609491024
How to cite: Andréassian, V., Santos, L., Sonnenborg, T., de Lavenne, A., Lindström, G., Nicolle, P., and Thirel, G.: RAT (Robustness Assessment Test): a straightforward evaluation of hydrological model robustness to a changing climate, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8403, https://doi.org/10.5194/egusphere-egu21-8403, 2021.
Development of robust approaches for calibrating daily rainfall-runoff models to monthly streamflow data enable modelling platforms that operate at daily time step to be applied in practical situations. Here precipitation is available at the daily scale, but observed streamflow is available only at the monthly scale (e.g. predicting inflows into large dams). This study compares the performance of the daily GR4J hydrological model when calibrated against (1) daily and (2) monthly streamflow data. The performance comparison relies on a wide range of metrics and is undertaken for 508 Australian catchments. Two evaluation periods (1975–1992 and 1992–2015) and four objective functions (including sum-of-squared-errors of Box-Cox transformed streamflow and the Kling-Gupta efficiency) were tested.
Monthly calibration performs similar to or better than daily calibration in most sites and both periods in terms of bias and fit of the flow duration curve. This result remains the same when the flow duration curve is computed at the daily time step, which constitutes a significant finding of this study.
However, the performance of monthly calibration is worse than daily calibration for daily pattern metrics such as Nash-Sutcliffe efficiency in most sites and both periods. Significant improvement can be achieved if the flow-timing parameter of GR4J is regionalised, effectively reducing the number of calibrated parameters. Similar results are obtained for other pattern metrics and all objective functions.
These findings suggest that monthly calibration of rainfall-runoff models using daily-rainfall and monthly-streamflow data is a viable alternative to daily calibration when no daily streamflow data are available.
How to cite: Lerat, J., Thyer, M., McInerney, D., and Kavetski, D.: Advantages of calibrating a daily rainfall-runoff model to monthly streamflow data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6913, https://doi.org/10.5194/egusphere-egu21-6913, 2021.
Ephemeral pools are seasonally flooded geographically isolated wetlands with distinct hydrology i.e., they are filled in winter and spring with inflow from snowmelt, and precipitation and dry out during summer. Ephemeral pools offer a variety of biodiversity benefits notably providing breeding habitat for several amphibian and invertebrate species. The quality of their ecosystem services is mainly controlled by their hydroperiod which is regulated by hydrology i.e., inflow /outflow of the pools. The classic water budget modeling approach with a simplified representation of the flow exchange between the pool and surface-subsurface zones may not adequately reveal their sensitivity to anthropogenic interventions and climatic changes. On the other hand, the generic volume-area-depth relationship of isolated wetlands in deterministic hydrologic models may not adequately reveal their dynamic water level fluctuations. The objective of this study, in the first place, is to improve the representation of ephemeral pools in the semi-distributed SWAT hydrological model, notably in the pothole module which is used for modeling isolated wetlands. The developed model will then be used to analyze the impact of land use and climate changes on dynamics of hydroperiods of ephemeral pools of the Saumon River watershed (68 km2) in the Canadian Shield of the Outaouais region (Quebec, Canada). A detailed bathymetry survey along with a long series (one to five years) of daily water level measurements available at ten pools allowed to replace the simplified linear volume-area relationship with the measured rating curve for the ephemeral pools in this region. The calibration process of the revised model is performed using the standard SWAT calibration code (SWAT-CUP) coupled to a Particle Swarm Optimization (PSO) algorithm adjusting evaporation and seepage coefficients of the revised module for all isolated wetlands of the region. This double calibration ensures representation of both the watershed hydrology (10 years of river flow rates) and the water level fluctuations in the pools. The simulation results show that the revised SWAT version can adequately reproduce the dynamic water level behavior of the monitored pools as well as streamflow discharges. The model is currently used with scenarios of human and climatic disturbances to understand their impact on the filling-drying cycle of ephemeral pools and on the integrated hydrologic system at the watershed scale.
How to cite: Bizhanimanzar, M., Larocque, M., and Roux, M.: An improved representation of ephemeral pool hydrology in a semi-distributed hydrologic model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12833, https://doi.org/10.5194/egusphere-egu21-12833, 2021.
Digital Elevation Models (DEMs) are approximations used for hydrological simulations and flood mapping. Usually, DEMs have sinks corresponding to actual landscape depressions and/or engineered structures such as bridges, road embankments, overhangs, dams... over or near to water bodies. These sinks often result from interpolation errors or measurement inaccuracies. Regardless of the source, sinks usually cause issues in hydrological simulations.
Classical filling and breaching methods have shown performance limitations. On one hand, a breaching method cannot deal with big sinks such as sinkholes and lakes in a fair manner as it may yield a long and deeply incised breach channel (lindsay 2016) . On the other hand, even though favored among practitioners, filling a sink may yield a flat area whose altitude is the same as its outlet. Therefore, hybrid methods combining breaching and filling were introduced. Lindsay (2016) presented a hybrid method called “Selective breaching” where a threshold sink depth is defined. As noted in Martz and Garbrecht (1999), a flat area near to the drainage basin outlet impacts the computation of flow direction and the subsequent hydrological simulation.
A watershed partition into hydrological sub-units, e.g. (Hariri 2019) allows for the parallelization of hydrological simulations. However, the larger the number of drainage basins and outlets, the more opportunities of having flat areas near outlets are met.
As an automatic mitigation, we propose a hybrid method blending a carved DEM and a filled DEM based on the distance to the outlet to take advantage of both methods.
The impact of the different methods to deal with sinks are evaluated for the Moderbach watershed (89 km², Région Grand-Est, France) chosen for its numerous engineering structures (5 big reservoirs, 6 large dams, 3 flood detention areas, roads and highway) comparing the results produced by a mixed-hybrid finite element code for surface flow simulation (Younes 1999) and HEC-RAS (Brunner 1994). The results show that the hybrid method we proposed overcomes the limitations of the classic filling and breaching and it is well adapted for parallel computing.
Brunner GW. HEC river analysis system (HEC-RAS). US Army Corps of Engineers, Hydrologic Engineering Center. 1994.
Hariri S, Weill S, Gustedt J, Charpentier I. Pairing GIS and distributed hydrological models using Matlab 2. CAJG - 2nd Conference of the Arabian Journal of Geosiences. 2019 Nov.
Lindsay JB. Efficient hybrid breaching‐filling sink removal methods for flow path enforcement in digital elevation models. Hydrological Processes. 2016 Mar 15;30(6):846-57.
Martz LW, Garbrecht J. An outlet breaching algorithm for the treatment of closed depressions in a raster DEM. Computers & Geosciences. 1999 Aug 1;25(7):835-44.
Younes A, Mose R, Ackerer P, Chavent G. A new formulation of the mixed finite element method for solving elliptic and parabolic PDE with triangular elements. Journal of Computational Physics. 1999 Feb 10;149(1):148-67.
How to cite: hariri, S., Gustedt, J., Weill, S., and Charpentier, I.: A Hybrid Breaching-Filling method for sink removal adapted to parallel hydrological simulations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7849, https://doi.org/10.5194/egusphere-egu21-7849, 2021.
Hydrological processes import across scales is known to constitute a key challenge to improve their representation in large-scale land surface models. Since these models describe continental hydrology with vertical one dimensional infiltration and evapotranspiration, the challenge mainly resides in the dimensionality reduction of the processes. Departing from the catchment three-dimensional scale, previous work has shown that an equivalent two-dimensional hillslope model is able to simulate long term watershed water balance with good accuracy. This work has been done on the Little Washita basin (Ok, USA) using the integrated code HydroGeoSphere. Following this framework, we show that hillslope hydrology can be described by using realistic simplifying assumptions, such as linear water table profile. These assumptions allow the writing of an analytical model relying on two hydrological variables: the seepage face extension, which describe the intersection length between the water table and the land surface, and the water table slope. The last step of the work will be to use these key variables and this simplified description of the driving processes for importing small-scale hydrological processes into large-scale models.
How to cite: Picourlat, F., Mouche, E., and Mugler, C.: Capturing watershed water balance with a physically-based two-hydrological-variable model: Application to the Little Washita basin, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8443, https://doi.org/10.5194/egusphere-egu21-8443, 2021.
Modelers often make different decisions in building hydrologic models based on their experience and modeling philosophy. Consequently, a wide range of models is developed, which differ in many aspects of conceptualization and implementation. This diversity of models has been useful to explore a myriad of scientiﬁc and applied questions, but it has also led to great confusion on choosing the appropriate model configurations in compliance with the dominant processes in the study area. Also, modeling decisions during model configuration introduce subjectivity from the modeler. To provide guidance to select the best-suited model configuration for a catchment it is required to examine and evaluate the different model representations of hydrological processes and their impact on model simulations. In this study, we show that modeling decisions during the model configuration, beyond the model choice, also impact the model results. The framework, Structure for Unifying Multiple Modeling Alternatives (SUMMA; Clark et al., 2015a, b) is used in this study to disentangle the model components which helps to have a controlled and systematic evaluation of multiple models representations. The area chosen for the study is the Malaprabha catchment in the Karnataka state of India. The impact of the choice of parameterizations and parameter values on the model simulations are shown. To improve upon the traditional model evaluation methods, hydrological signatures are made use to have a hydrologically meaningful evaluation of model simulations. This study helped to identify the suitable model configuration for the Malaprabha catchment. Multiple working hypotheses during model configuration which is possible with the help of such flexible framework like SUMMA can provide insights on the impact of subjective modeling decisions.
How to cite: Ann Alexander, A. and Nagesh Kumar, D.: Impact of subjective modeling decisions on hydrological modeling, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6548, https://doi.org/10.5194/egusphere-egu21-6548, 2021.
airGR (Coron et al., 2017, 2020) is an R package that offers the possibility to use the GR rainfall-runoff models developed in the Hydrology Research Group at INRAE (formerly at Irstea). It allows running seven hydrological models (including GR4J) dedicated to different time steps (hourly to annual) that can be combined to a snow accumulation and melt model (CemaNeige).
Thanks to the success of the airGR package, that was downloaded 45,000 times so far among 50 countries in the world and was used in dozen of publications since its release, its development team carries on its efforts to offer new features and improve the computer codes. This is how after offering a first add-on, the airGRteaching package, expressly developed for educational purposes, the team now offers tools dedicated to semi-distribution and data assimilation.
Using (semi-)distributed models is often necessary to explicitly represent spatial climatic and physiographic heterogeneities and to allow an analysis of their impact on the watershed response. Consequently, in the latest version of the airGR package, we introduced the semi-distribution of GR models, which are traditionally lumped, on a sub-basin basis. This development will also ultimately enable possibilities of implementing on a modular way different transfer functions as well as integrated water resource management (see package airGRiwrm in Abstract EGU21-2190).
In addition, a new package, called airGRdatassim, was recently proposed (Piazzi et al., 2021a, b) as an add-on to the airGR package. airGRdatassim enables the user to assimilate discharge observations via both Ensemble Kalman filter (EnKF) and particle filter (PF) schemes. Besides improving the simulations of GR models, this new package extends the potential applications of airGR to forecasting purposes by allowing for a reliable assessment of the initial conditions of streamflow forecasts.
Coron L., Thirel G., Delaigue O., Perrin C., Andréassian V. (2017). The Suite of Lumped GR Hydrological Models in an R package, Environmental Modelling & Software, 94, 166-171. DOI: 10.1016/j.envsoft.2017.05.002.
Coron, L., Delaigue, O., Thirel, G., Perrin, C. and Michel, C. (2020). airGR: Suite of GR Hydrological Models for Precipitation-Runoff Modelling. R package version 220.127.116.11. URL: https://CRAN.R-project.org/package=airGR.
Piazzi, G., Delaigue, O. (2021a). airGRdatassim: Suite of Tools to Perform Ensemble-Based Data Assimilation in GR Hydrological Models. R package version 0.0.3.13. URL: https://gitlab.irstea.fr/HYCAR-Hydro/airgrdatassim.
Piazzi, G., Thirel, G., Perrin, C., Delaigue, O. (2021b, accepted). Sequential data assimilation for streamflow forecasting: assessing the sensitivity to uncertainties and updated variables of a conceptual hydrological model. Water Resources Research.
How to cite: Thirel, G., Delaigue, O., Dorchies, D., and Piazzi, G.: New airGR developments: semi-distribution and data assimilation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1371, https://doi.org/10.5194/egusphere-egu21-1371, 2021.
IWRM modeling aims at representing interactions between humans and their environment (Badham et al. 2019), which can involve hydrological, surface-hydraulic, and groundwater models. Semi-distributed models implementing a simplified hydraulic propagation between sub-catchments are often used as IWRM model (Ficchi et al. 2014, Dorchies et al. 2016) because of the good trade-off they offer between simplification and result relevancy.
The R-package airGR (Coron et al., 2017, 2020) is widely used in the R language hydrology community and its recent development with semi-distributive (see Abstract EGU21-1371) capabilities allows to use it for IWRM modeling. The R-package airGRiwrm has been developed for multiple purposes linked to IWRM. First, it proposes a simplified network description for building semi-distributed models containing several sub-basins with diverse connections, which greatly simplifies the calibration and modeling steps. Then, it allows to easily integrate predefined flows (feedforward control) into the model, namely local flow injections or withdrawals. Finally, it integrates controllers that apply user-defined decision algorithms given model outputs during simulation (feedback control). The controllers allows for example to apply withdrawal restriction in case of drought, or to simulate a reservoir behaviour with complex management rules.
In this presentation, we will introduce the airGRiwrm possibilities and we will demonstrate its use on the case of the Seine River basin in France.
Badham, J., et al., 2019. Effective modeling for Integrated Water Resource Management: A guide to contextual practices by phases and steps and future opportunities. Environmental Modelling & Software 116, 40–56. https://doi.org/10.1016/j.envsoft.2019.02.013
Coron, L., Delaigue, O., Thirel, G., Perrin, C., Michel, C., 2020. airGR: Suite of GR Hydrological Models for Precipitation-Runoff Modelling. R package version 18.104.22.168. https://doi.org/10.15454/EX11NA
Coron, L., Thirel, G., Delaigue, O., Perrin, C., Andréassian, V., 2017. The suite of lumped GR hydrological models in an R package. Environmental Modelling & Software 94, 166–171. https://doi.org/10.1016/j.envsoft.2017.05.002
Dorchies, D., Thirel, G., Perrin, C., Bader, J.-C., Thepot, R., Rizzoli, J.-L., Jost, C., Demerliac, S., 2016. Climate change impacts on water resources and reservoir management in the Seine river basin (France). La Houille Blanche 32–37. https://doi.org/10.1051/lhb/2016047
Ficchi, A., Raso, L., Malaterre, P.-O., Dorchies, D., Jay-Allemand, M., 2014. Short Term Reservoirs Operation On The Seine River: Performance Analysis Of Tree-Based Model Predictive Control. Presented at the International Conference on Hydroinformatics, New York.
How to cite: Dorchies, D., Delaigue, O., and Thirel, G.: airGRiwrm: an extension of the airGR R-package for handling Integrated Water Resources Management modeling, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2190, https://doi.org/10.5194/egusphere-egu21-2190, 2021.
Hydrological models exhibit great complexity and diversity in the exact methodologies applied, competing for hypotheses of hydrologic behaviour, technology stacks, and programming languages used in those models. The preprocessing of forcing (meteorological) data is often performed by various sets of scripts that may or may not be included with model source codes, making it hard to reproduce results. Moreover, forcing data can be retrieved from a wide variety of forcing products with discrepant variable names and frequencies, spatial and temporal resolutions, and spatial coverage. Even though there is an infinite amount of preprocessing scripts for different models, these preprocessing scripts use only a limited set of operations, mainly re-gridding, temporal and spatial manipulations, variable derivation, and unit conversion. Also, these exact same preprocessing functions are used in analysis and evaluation of output from Earth system models in climate science.
Within the context of the eWaterCycle II project (https://www.ewatercycle.org/), a common preprocessing system has been created for hydrological modelling based on ESMValTool (Earth System Model Evaluation Tool). ESMValTool is a community-driven diagnostic and performance metrics tool that supports a broad range of preprocessing functions. Using a YAML script called a recipe, instructions are provided to ESMValTool: the datasets which need to be analyzed, the preprocessors that need to be applied, and the model-specific analysis (i.e. diagnostic script) which need to be run on data. ESMValTool is modular and flexible so all preprocessing functions can also be used directly in a Python script and additional analyses can easily be added.
The current preprocessing pipeline of the eWaterCycle using ESMValTool consists of hydrological model-specific scripts and supports ERA5 and ERA-Interim data provided by the ECMWF (European Centre for Medium-Range Weather Forecasts), as well as CMIP5 and CMIP6 climate model data. The pipeline starts with the downloading and CMORization (Climate Model Output Rewriter) of input data. Then a recipe is prepared to find the data and run the preprocessors. When ESMValTool runs a recipe, it produces preprocessed data that can be passed as input to a hydrological model. It will also store provenance and citation information to ensure transparency and reproducibility. This leads to less time spent on building custom preprocessing, more reproducible and comparable hydrological science.
In this presentation, we will give an overview of the current preprocessing pipeline of the eWaterCycle, outline ESMValTool preprocessing functions, and introduce available hydrological recipes and diagnostic scripts for the PCRGLOB, WFLOW, HYPE, MARRMOT and LISFLOOD models.
How to cite: Alidoost, F., Aerts, J., Andela, B., Camphuijsen, J., van De Giesen, N., van Den Oord, G., Drost, N., Hut, R., Kalverla, P., Pelupessy, I., van Werkhoven, B., Smeets, S., and Verhoeven, S.: Preprocessing of hydrological models’ input in eWaterCycle with ESMValTool, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6051, https://doi.org/10.5194/egusphere-egu21-6051, 2021.
How water and solute are transported in catchments is the foundation for sustainable water management. The flow and transport processes can be described through the travel time of water summarizing the catchment functions of storage, mixing, and release. For a catchment scale, travel time is defined as the time a water particle needs to travel from when it hits the ground surface until it leaves the catchment as discharge or evapotranspiration. Recent studies treated travel time distributions as time-variant in order to reflect the temporal and spatial variability of atmospheric forcing and corresponding hydrologic dynamics through the Master Equation and StorAge selection functions (SAS functions). A challenge is that travel times cannot be directly estimated from data but are inferred from either conceptual or physically based hydrological models. In our study, we employ the integrated surface-subsurface hydrological model Parflow to simulate water fluxes in the forested Weierbach catchment in Luxembourg. However, there are challenges on model parametrization and optimization to build a robust model that is representative of the catchments processes. Our objective here is to setup a robust model for Weierbach catchment based on available catchment parameters. We will evaluate the model against observed streamflow at several sites and soil moisture data. Nevertheless, such model can be used to reveal the spatio-temporal heterogeneity of the hydrological processes at our catchment once it is constrained with the available field data. Future work will consist of directly estimating the travel time of both discharge and evapotranspiration using Parflow and particle tracking (such as EcoSLIM) and will be constrained with the observed stable isotope data.
How to cite: Moussa, A., Klaus, J., and Sulis, M.: Simulating hydrological processes with a fully coupled surface-subsurface model for estimating catchment travel times, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10577, https://doi.org/10.5194/egusphere-egu21-10577, 2021.
Reservoir sedimentation represents a significant threat to the reliability of global water and energy supplies. Over the life of a reservoir, storage capacity is gradually lost due to the deposition of sediments. Hydrological models represent a valuable method to study and evaluate the effects of reservoir storage losses on issues such as energy production, discharge capacity, and flood attenuation. The Hydrological Predictions for the Environment (HYPE) model is a semi-distributed, catchment-based hydrology model that has been used to quantify sediment fluxes across a variety of catchment, country, continent, and global modeling domains. In this study, several methods to estimate reservoir storage capacity losses due to sedimentation were added to HYPE, and their impact on sediment simulations and resulting model performance was tested in multiple landscapes in various parts of the world. Selected methods consider the texture and size of deposited sediment particles, the compaction of deposited sediments over time, and the manner in which reservoirs are operated. Results from the study will be used to inform future model development and improve modeling of sediment fluxes at the global scale.
How to cite: Brendel, C., Bartosova, A., Strömqvist, J., Pers, C., Capell, R., and Arheimer, B.: Modelling losses of reservoir storage capacity from sedimentation in different landscapes, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14251, https://doi.org/10.5194/egusphere-egu21-14251, 2021.
Present regional and global scale hydrology has to account for man-made reservoirs that impart significant regulation signature into the downstream streamflow regime. Optimization of domains with large number of reservoirs would incur multitude of reservoir regulation parameters. Such parameter-set-per-reservoir approach not only results in excessive computational costs but also, by principle, lacks effective constraining of the parameter space. We propose an approach to derive single set of parameters for all the reservoirs and lakes in the modelling domain. The hypothesis is that reservoir regulation parameters can be regionalized using physiography and climatology at lakes and their catchments.
To test this hypothesis, we setup a modeling domain for the São Francisco basin of Northeast Brazil in the mesoscale hydrological model (mHM, www.ufz.de/mhm). The domain consists of climatology ranging from tropical (As) to semi-arid (BSh) and reservoirs with catchment area varying from less than 500 km2 to greater than 500,000 km2. We carried out correlation analysis between selected physiographical and climatological predictors and the reservoir parameters of the multiscale lake module, mLM, of the mHM model (https://presentations.copernicus.org/EGU2020/EGU2020-6047_presentation.pdf). For an instance, the reservoir rule curves in mLM are estimated based on inflow and position of water level. The predictors here are inflow and water level which are normalized using catchment area and the shape of the reservoir, respectively. Similarly, the timing and shape parameters of rule curves were plotted against the climatological characteristics of the upstream catchment. The preliminary results reveal significant trends between the mLM parameters and the normalized predictors. These mathematical relationships, better known as transfer functions, can now be used to generate a single global reservoir parameter set.
The demonstrated hypothesis helps to optimize regulated hydrology using a single parameter set, irrespective of size, location and inherent climatology of reservoirs involved. This is inline with the pre-existing paradigm of multiscale parameter regionalization (MPR) of mHM. The findings contribute to the contemporary effort of hydrological modeling society towards improved global scale hydrological modeling.
How to cite: Shrestha, P. K., Thober, S., and Samaniego, L.: Regionalization of Reservoir regulation parameters using physiographic and climatological predictors, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5030, https://doi.org/10.5194/egusphere-egu21-5030, 2021.
For decades, lumped rainfall-runoff models have been used for hydrological analysis and forecasting such as operational flood forecasting. However, the accuracy of model forecasts depends on the ability of the model to approximate the dominant hydrological processes of the catchment under consideration. These processes are site specific and, therefore, the choice of a particular model is challenging.
A large number of hydrological models has been developed and applied in various regions of the world. Model choice has often been hampered in the past by technical problems such as different programming languages, different software platforms, and different input formats and requirements.
The Modular Assessment of Rainfall Runoff Model Toolbox (MARRMoT) unites 46 lumped models from around the world within the same Matlab® framework with standardized inputs. The model equations have been simplified and adapted for this purpose. As a result, it is possible to test a large number of different models with comparatively little effort. The models implemented in MARRMoT vary in their structural complexity and have between 1-24 parameters and between 1-8 storages.
Here MARRMoT was used in order to find a model or model ensemble suitable for the simulation of precipitation-runoff relationships in the Wairau River catchment, New Zealand. The catchment area is assumed to have predominantly homogeneous runoff-generating properties. Model input data (precipitation and potential evapotranspiration) was derived from the Virtual Climate Station Network by National Institute of Water and Atmospheric Research, NZ.
In a first scenario, 42 selected models from MARRMoT were calibrated for the Wairau River catchment using 45 years of Wairau River flow data, an in-built nonlinear unconstrained optimization algorithm and the model fitness criteria Kling-Gupta-Efficiency (KGE). In two further scenarios, calibrations using the KGE with inversely transformed flows (KGEi) as well as a mixed form of the two criteria (KGEm) were realized.
Model performance was further evaluated based on different performance criteria such as NSE, RMSE and R². It was demonstrated that the model ranking depends on the choice of the performance.
Evaluating the model performance for the different calibration scenarios showed that a few models with very different structures performed well to reproduce the flow data. No decisive structural feature could be identified which all models have in common and which led to a good representation of the rainfall-runoff processes in the Wairau River catchment. However, the differentiated consideration of flow routing and a high degree of flexibility seem to benefit model performance. Deficits in the modeling can be seen in the discharge peaks, which are not correctly simulated by many models. The simulation of fast direct runoff with lumped models seems to be less accurate for the relatively large catchment area of the Wairau River (3430 km²).
Eventually, three models (GR4J, FLEX-I and HBV-96) demonstrated a high performance in all three calibration scenarios and were identified as suitable for further use in the Wairau River catchment.
How to cite: Peesel, A. and Wöhling, T.: Evaluation of 42 lumped rainfall-runoff models for the Wairau River catchment, New Zealand, using the MARRMoT toolbox, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6977, https://doi.org/10.5194/egusphere-egu21-6977, 2021.
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