HS2.2.1

Many hydrologic modelling groups face similar challenges, with untapped opportunities to share code and concepts across different model development groups. An active community of practice is emerging, where the focus is not so much on developing a community hydrologic model, but more on advancing the science and practice of community hydrologic modeling. This presentation will summarize our recent efforts to develop open-source models, methods, and datasets to enable process-based hydrologic prediction across North America (and beyond). The contributions include (1) developing ensemble meteorological datasets for North America and the globe; (2) developing modular approaches to hydrologic modeling through a hierarchal approach that separates different model sub-domains (vegetation, snow, soil, groundwater) and separates the physical representations from the numerical solution; (3) implementing third-party numerical solvers (sundials) to improve the robustness and efficiency of the numerical solutions; (4) developing agile parallelization methods capable of handling heterogeneous computing loads and bottlenecks in the downstream reaches of large river networks; (5) implementing flexible model configuration toolbox to accelerate the implementation of large-domain hydrologic models; (6) advancing methods for river lake routing, including development of integrated river-lake hydrography datasets and development of large-domain reservoir management models; (7) advancing methods for large-domain parameter estimation; (8) advancing methods for ensemble data assimilation; and (9) advancing methods for probabilistic hydrologic prediction on time scales from seconds to seasons. We will discuss some of the major challenges encountered and the high-priority research that is necessary to advance capabilities in large-domain hydrologic prediction.

How to cite: Clark, M., Arnal, L., Bennett, A., Casson, D., Gharari, S., Hay, J., Freer, J., Knoben, W., Liu, H., Mizukami, N., Nijssen, B., Papalexiou, S., Spiteri, R., Tang, G., Van Beusekom, A., and Wood, A.: Advancing the science and practice of community hydrologic modeling: Development of open-source models, methods, and datasets to enable process-based hydrologic prediction across North America (and beyond), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8451, https://doi.org/10.5194/egusphere-egu22-8451, 2022.

Groundwater-dominated catchments are often critical for nationally-important water resources. Many conceptual rainfall-runoff models used for the simulation of river flows tend to degrade in their model performance in groundwater-dominated catchments as they are rarely designed to simulate spatial groundwater behaviours or interactions with surface waters. Intercatchment groundwater flow is one such neglected variable. Efforts have been made to incorporate this process into existing models, but there is a need for greater emphasis on improving our perceptual models of groundwater-surface water interactions prior to any model edits.

In this study, national meteorological, hydrological, hydrogeological, geological and artificial influence (characterising abstractions and return flows) datasets are used to develop a perceptual model of intercatchment groundwater flow and how it varies spatially and temporally across the River Thames. We characterise the water balance, presence of gaining/losing river reaches and intra-annual dynamics in 80 subcatchments of the River Thames in the UK, taking advantage of its wealth of data, densely gauged river network and geological variability.

We show the prevalence of non-conservative river reaches across the study area, with heterogeneity both between, and within, geological units giving rise to a complex distribution of recharge and discharge points along the river network. We identify where non-conservative reaches can be attributed to intercatchment groundwater flow, and where other processes (e.g. human abstractions and discharge uncertainty) are likely the cause. Escarpments of Chalk and Jurassic Limestone show evidence of intercatchment groundwater flow both from headwater to downstream reaches, and out-of-catchment via springlines. We found temporal as well as spatial variability across the study area, with more seasonality and variability in river catchments on Jurassic Limestone outcrops and less on Chalk and Lower Greensand outcrops. Our results show the need for a degree of local investigation and hydrogeological perceptualisation within regional analysis, which we show to be achievable given relatively simple geological interpretation and data requirements.  We then discuss the inclusion of external flow fluxes within existing models to enable calibration improvements in groundwater-dominated catchments, and, importantly, the characterisation of these fluxes given the temporal and spatial variability of intercatchment groundwater flow that our perceptual model has shown.

How to cite: Oldham, L., Freer, J., Coxon, G., Jackson, C., Bloomfield, J., and Howden, N.: Evidence-based requirements for perceptualising intercatchment groundwater flow in hydrological models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7786, https://doi.org/10.5194/egusphere-egu22-7786, 2022.

Abstract: Parametrization is an important step to construct a reasonable hydrologic model for a catchment. However, selecting appropriate model parameters can be challenging, particularly in data scarce regions. Conventionally, hydrologic model parameters are selected through calibration assuming that catchment processes and model parameters are stationary over time. However, the assumption of stationarity may not be valid all the time due to temporal changes in the behaviors of catchments. Therefore, the purpose of this study is to investigate the influence of temporal variability on the SWAT model parametrization using different calibration periods. To this end, we calibrated the SWAT model based on daily and monthly streamflow data in the Adyar catchment, Chennai. Results showed that the SWAT model performance and parameter values differed when the calibration periods were shifted by one year. This is reflected in the KGE (Kling Gupta Efficiency) values that varied between 0.38 to 0.68 for calibration periods of 2004-2007,2005-2008, 2006-2009, 2007-2010, 2008-2011, 2009-2012 and 2010-2013. Likewise, the selection of values for sensitive model parameters varied even though the parameter values were chosen in the same ranges. Moreover, independent model evaluation for wet and dry years showed significantly different performance indices and model parameter values. The model efficiency of wet years (NSE = 0.59 and KGE= 0.68) was by far better than the model efficiency of dry years (NSE = -0.59 and KGE = 0.1). In general, this study provides a good insight into hydrologic model calibration under non-stationarity conditions.

How to cite: Tigabu, T., Wagner, P., Narasimhan, B., and Fohrer, N.: Influences of temporal variability on the calibration of a hydrologic model , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6534, https://doi.org/10.5194/egusphere-egu22-6534, 2022.

The accurate simulation and partitioning of the water balance components is important for the simulation of hydrological processes and the interaction between the land and the atmosphere. The objective of this study is to identify the model parameters and parameterization options that impact the most the water balance components modelled with the Noah-MP land surface model coupled to the WRF-Hydro hydrological model. The water balance components are runoff and total evapotranspiration (ET), comprised of evaporation, transpiration and interception. Three types of different parameterization options and 12 model parameters were tested and the sensitivity of the model output was investigated for two consecutive hydrological years and for 31 watersheds in the Troodos mountains of Cyprus, in the Eastern Mediterranean. A baseline configuration, based on initial estimates of model parameters from previous literature and suggested default values, of the Noah-MP and WRF-Hydro model system was found to systematically overestimate the total streamflow of the 31 watersheds, with the median runoff coefficient equal to 0.4 compared to the observed value of 0.2. Consistent with the streamflow overestimation, the ratio of total ET to total precipitation was underestimated, with a value of 0.5 compared to the value of 0.8 from local observations. The sensitivity analysis revealed that specific parameters can substantially modify the amount of simulated streamflow and ET. The bedrock drainage parameter, hydraulic conductivity and soil porosity can each reduce or increase streamflow and ET up to 20% on average. Among the vegetation parameters and model parameterization options, the change of the dynamic vegetation option, the use of the Jarvis-based stomatal conductance model, instead of the Ball-Berry model, and the simulation of nocturnal transpiration can each increase ET by about 20%, and thus reduce the overestimation of total streamflow. The findings of this sensitivity analysis can be used to configure the Noah-MP and WRF-Hydro models in order to improve the simulation of the water balance of the studied area and other areas with similar hydroclimatic characteristics.

How to cite: Sofokleous, I., Bruggeman, A., Eliades, M., and Camera, C.: Sensitivity analysis of water balance components with the Noah-MP and WRF-Hydro models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6003, https://doi.org/10.5194/egusphere-egu22-6003, 2022.

Dryland regions cover around one-third of the global land surface and are naturally prone to water scarcity. Drylands typically experience highly variable precipitation, both spatially and temporally, with potential evapotranspiration (PET) greatly exceeding annual rates of precipitation. However, our ability to accurately quantify the key components of the water partitioning in these regions is hampered by the scarcity of data and the highly dynamic nature of the hydrological processes. In this context, assessing the ability of models to represent the key hydrological processes at different spatial and temporal scales is of key importance to enhance our understanding and quantification of the water balance in dryland regions. Here, we have assessed the impact of the model grid size and the temporal scale of climatic forcing in combination with variations in model structure in the description and representation of key hydrological processes that influence the water partitioning in dryland regions. The analysis was performed in the Walnut Gulch Experimental Watershed where a dense network of hydrological measurements is readily available for model evaluation. We show that our parsimonious model, DRYP, can describe well the water partitioning across a range of different temporal and spatial scales. However, we find that sub-daily time steps of precipitation and PET, combined with a fine spatial resolution of less than or equal to 1km grid size, are needed for robust quantification of the water partitioning, which is also very sensitive to the choice of infiltration model. The results highlight the important role of channel losses through the streambed of ephemeral streams (~7% of the precipitation), and the impact of the underlying alluvial riparian area in the partitioning of water fluxes between riparian vegetation evapotranspiration (~60 % of transmission losses) and the production of focused groundwater recharge (~3 % of the precipitation). These results have important implications for the potential for improving the performance of large scale models in dryland regions by indicating the appropriate temporal and spatial scales required for the proper representation of dryland hydrological processes.

How to cite: Quichimbo, E. A., Singer, M. B., Michaelides, K., Rosolem, R., and Cuthbert, M.: Sensitivity to spatial and temporal resolution in the performance of a parsimonious hydrological model for quantifying water balance partitioning in dryland regions., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3264, https://doi.org/10.5194/egusphere-egu22-3264, 2022.

Runoff generation in semi-humid regions is always characterized by a complex nonlinear process influenced by both saturation excess mechanism and infiltration excess mechanism. A hybrid runoff generation module is proposed in this study to delineate the mixed rainfall-runoff process by integrating an infiltration module, based on a modified Horton equation, with the saturation excess runoff generation module of Xinanjiang model at grid scale. A new distributed hydrological model, termed grid-Xinanjiang-infiltration-excess (GXAJ-IE) model, is subsequently developed in the context of grid-Xinanjiang model. Not only in semi-humid regions, but GXAJ-IE model is also expected to achieve acceptable performance in other hydrometeorological zones due to its superimposed runoff generation structure. Thus GXAJ-IE model is tested in four watersheds across different hydrometeorological zones (humid, semi-humid, semi-arid and arid) of China, and two models with single runoff generation mode, grid-Xinanjiang (GXAJ) model and grid-infiltration-excess (GIE) model, are set as benchmarks for comparison purpose. The results indicate that compared with the two benchmark models, GXAJ-IE model has higher flexibility and robustness in reproducing the flood hydrographs, especially the flood peaks, driven by various rainfall patterns in the semi-humid Dongwan and Maduwang watersheds. Furthermore, GXAJ-IE model could well capture the spatiotemporal characteristic of the saturation and infiltration excess runoff components, and delineate the evolution of their contributing areas within a flood event. Yet rainfall input with low spatiotemporal resolution still remains a limitation to give full play to the advantage of GXAJ-IE model. None of the models performs well in the arid and semi-arid Suide watershed, even though, GXAJ-IE model shows comparable simulation accuracy with GIE model whereas GXAJ model absolutely loses its edge. In the humid Tunxi watershed, GXAJ-IE model produces comparably good performance with GXAJ model while GIE model is slightly inferior. Overall, GXAJ-IE model is fairly adaptable to different hydrometeorological regions in China and shows great potential for universal application, with an especially promising prospect in improving the flood forecasting accuracy for the semi-humid watersheds.

How to cite: Zhang, Q., Zhang, K., Chao, L., Chen, X., Wang, J., and Wu, N.: Testing a new hybrid runoff generation module in four typical watersheds across different hydrometeorological zones in China, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13237, https://doi.org/10.5194/egusphere-egu22-13237, 2022.

As part of the International Geoscience IGCP-715 project, we present the core objective and preliminary analyses on the karst development of the study areas. Our aim is to further characterize the geomorphologic features of the extended karst of Koiliaris Critical Zone Observatory (KCZO), Crete, Greece. Simultaneously to better understand the main drivers of karst development we compare the CKZO karst system with other areas in different tectonic contexts such as Oman (Salma Plateau), the northern UAE and southern China (Guilin karst area).

Hydrological studies and previous geomorphologic analysis of KCZO suggest that 27% of the total water budget is coming from the adjacent watershed in the east where an extensive karst system with two explored super-deep caves is situated (Liontari Cave - 1100 m, Gourgouthakas Cave - 1200 m). The area is build up by a continuous carbonate succession exceeding 5 km in depth, lying on top of the Hellenic subduction zone. Field work and Google Earth mapping show two dominantly striking directions of failures (fault, fracture surfaces), trending E-W to ESE-WNW (90-120°) and N-S to NNE-SSE (0-22.5°). The N-S surfaces are mainly fractures while the E-W ones are mainly thrusts and/or strike-slip faults with obvious large displacements of hundreds of meters. The karst development in a subduction zone with dramatic thrusting on the overriding plate has created super-deep caves which are controlled by the vertical bedding and a series of faults and fractures. The area exhibits two layers with different hydraulic properties, a fast water-transferring zone and a slower one which is consistent and supports the hypothesis of the hydrologic model.  

At the Salma Plateau, in Oman, the karstic system is related to rapid uplifted Eocene limestones that overlay the Semail Ophiolite. There is a large cave (Majilis Al Jinn) at an area of interconnected fractures (and/or faults?). It is the only karstic system presented inhere which has similarities with the karstic system in the KCZO.

At the UAE and northern Oman (Musandam) is an active collision zone between Arabia and Eurasia with 2000-m-thick allochthonous Mesozoic limestones. The area lacks a subsurface karst system, and the only karst has developed in steep wadis.

Finally, the Guilin area in China represents a former passive margin with a Devonian limestone. It features a spectacular karst of conical peaks (fengcong) and tower peaks (fenglin). Caves exhibit mainly a horizontal development and there is no similarities to the KCZO.

How to cite: Moraetis, D., Palvopoulos, K., Fassoulas, C., Scharf, A., Mattern, F., Yu, X., Pennos, C., Adamopoulos, K., Zacharias, S., Hamdan, H., and Nikolaidis, N.: Karst development in different tectonic settings (Middle East, Greece, South China), concept analysis and first findings towards hydrology modeling reconsideration, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5206, https://doi.org/10.5194/egusphere-egu22-5206, 2022.

Natural streamflow of most mountain catchments worldwide is altered as a consequence of hydropower exploitation and other water uses. Hydrological modelling in these watersheds represents a challenging task, as the streamflow alteration caused by hydropower production is linked to operational schedules as well as to geometrical and technical constraints, which are system specific. Key parameters controlling hydropower functioning are difficult to acquire, because protected by producers, hence modelling hydropower systems in large domains often resorts to simplified (and less realistic) approaches, in order to cope with the lack of information. However, the accuracy of the simulations depends critically on the reliability of the simplified assumptions, which varies among the proposed approaches. In this work we analyzed the impact of the simplifications typically introduced in modelling hydropower at the catchment and larger scales by assuming as reference HYPERstreamHS, a coupled hydrological and hydraulic model exploiting the information publicly available on single hydropower systems. We present an application of the proposed framework to the Adige river basin, a large watershed located in the south-eastern portion of the Alps, in which the presence of 39 large hydropower systems characterized by complex infrastructures, 22 of which connected to storage reservoirs, causes significant alterations of streamflow timing and magnitude. We demonstrate the benefit of accurately representing hydropower-related water diversions by analyzing how the model represents the observed streamflows at impacted sites and hydropower production at the regional scale. We also provide insights on how a simplified representation of large hydropower systems can lead to a biased evaluation of streamflow alterations at impacted sections and of hydropower production at several sites. Our results show that the effects of different simplifications that may be adopted in the modelling framework combine in a non-linear manner, thus complicating the overall evaluation of the associated impacts.

How to cite: Galletti, A., Avesani, D., Bellin, A., and Majone, B.: On the accurate representation of hydropower systems in large-scale hydrological models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7813, https://doi.org/10.5194/egusphere-egu22-7813, 2022.

For many decades, sediment yield (SY) observations have been collected around the world to analyze, monitor, and better understand the state and dynamics of various Earth system processes. These records are highly relevant for a wide variety of research applications, yet they remain poorly accessible, especially for large-scale studies. A main reason for this is the fact that many of these measurements are collected on an isolated basis, leading to inconsistencies across data sets. SY observations also suffer from large uncertainties in data quality: key factors such as location accuracy, sampling method and frequency, measuring period, and others vary greatly but are not systematically reported.

To address these shortcomings and provide a standardized global reference for SY data, we are developing an extensive, coherent and georeferenced global database of contemporary SY observations. Through an extensive review of (grey) literature and contacts with numerous research groups, we already compiled SY observations for >8,000 catchments worldwide (comprising a total of >80,000 catchment years of observations). These observations are either derived from gauging station measurements or reservoir sedimentation rates. We assess the reliability of SY records and provide data quality indices based on available information such as measuring location, reported catchment area, sampling method and frequency, and measuring period. We further link the SY observations to the HydroSHEDS global river network, making them readily accessible and consistent with a wide array of hydro-environmental catchment variables also connected to the HydroSHEDS network. 

This new global SY database creates untouched opportunities for large-scale model development and statistical analyses of sediment-related factors and processes, such as soil erosion, sediment budgets, land cover and land use change impacts, or hydrological and sediment connectivity. Here we present a first overview of the data collected so far, its spatial patterns and its research potential. 

How to cite: Tan, F., Borrelli, P., Verstraeten, G., Tsyplenkov, A., Campforts, B., Golosov, V., Lehner, B., Poesen, J., and Vanmaercke, M.: Developing a global database of contemporary sediment yield observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11728, https://doi.org/10.5194/egusphere-egu22-11728, 2022.

The flow conditions (e.g., river network) for rivers and open channels are often forced into hydrogeological models that use a constant horizontal grid resolution without correction for grid mismatching. As a result, the flow velocity will be significantly underestimated if the width of rivers is substantially narrower than the grid size of these models. Furthermore, the exchange between the river and the subsurface is overestimated, resulting in an erroneously large vertical exchange.

In response to this challenge, in this work, the subscale channel flow is approximated in the kinematic wave equation by a scaled roughness coefficient. A relationship between grid cell size and river width is used for this purpose, which follows a simplified modification of the Manning-Strickler equation. In addition, the exchange between the subsurface and the river, as well as the rate of ex- and in-filtration, are scaled across river beds based on grid resolution. As a result, even though the grid size is relatively large, the exchange rates are corrected across river beds. The effectiveness of the scaling of river parametrization is validated against groundwater gauges and remote sensing-based surface soil moisture in a fully coupled subsurface-land surface ParFlow-CLM at a spatial resolution of 0.055° (~6 km) over the Upper Rhine Basin. The validity of the results is examined through an innovative application of the First Order Reliability Method (FORM) for the time period 2012-2014. Results indicate that the scaling approach improves the estimates of soil moisture, particularly in the summer and autumn seasons when cross-validated with independent CCI-SM observations. This improvement is achieved (SM RMSE reduction from 0.03 to 0.005) due to the effective impacts of the scaling river parametrization on SM estimation. FORM results show that the accuracy of ParFlow-CLM soil moisture simulations by using scaling approach is more than 95, 89, 85 and 92 percent for Autumn, Winter, April and Summer, respectively. The scaling river parametrization also shows overall improvements in groundwater level estimation, particularly over the central and northern regions where the groundwater level is shallow.

How to cite: Soltani, S. S., Fahs, M., Al Bitar, A., and Ataie-Ashtiani, B.: Fully coupled subsurface-land surface hydrological models: A scaling approach to improve subsurface storage predictions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2828, https://doi.org/10.5194/egusphere-egu22-2828, 2022.

Integrated hydrological models (IHM) are often used for a better understanding of the hydrological fluxes at the surface and in the subsurface. IHMs can also be coupled to land surface models to study the interactions between vegetation and hydrological processes. At our study site, the Weierbach catchment (43 ha), Luxembourg, sap flux observations showed high spatial variability in observed transpiration due to many factors such as DBH, landscape characteristics and position, and tree species. However, this spatial variability is often not captured by land surface models at small scale and transpiration fluxes are usually treated as an integrated flux. In our study, we employ the coupled integrated surface-subsurface hydrological model Parflow coupled with the land surface model (CLM) to simulate water and energy fluxes in the forested Weierbach catchment in Luxembourg. Our objectives are twofold. First, we evaluate the coupled physically-based model and land surface model with discharge, groundwater level and soil moisture, and spatiotemporal sap flow data. In addition to that, we are exploring whether simulated and observed transpiration for three different hillslope positions (plateau, midslope, hillfoot) are driven by atmospheric demand or water availability in the subsurface. Our main result was that model has captured discharge, groundwater fluxes and the average transpiration well. However, the modelled transpiration showed a much smaller spatial variability compared to the spatial variability derived from sapflow observation. For the three different hillslope positions, we found that the fluxes were mainly driven by atmospheric demand and the model captured this dominance well. Our results demonstrate that there is a limitation of the model in reproducing the spatial variability of transpiration in the heterogeneous forest and future modelling work at small scale needs to better parameterize the spatial characteristics of vegetation.

How to cite: Moussa, A., Sulis, M., and Klaus, J.: On the value of benchmarking a fully coupled surface-subsurface model with spatially distributed sap flow measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8452, https://doi.org/10.5194/egusphere-egu22-8452, 2022.

Pedotransferfunctions (PTF) play a major role in physically based hydrological modeling, as they establish the relationship between soil properties and the water stress curve. The selection of the PTF thus has a great influence on the water balance of a catchment in general, as well as on the spatial distribution and intensity of runoff processes. In this study, these very influences of PTF's on the runoff processes will be investigated. The hydrological model "WaSiM-ETH", which was calibrated and validated, is used for the investigations. On the basis of this modeling, 11 further scenarios were created, which differ only in their PTFs. In all scenarios an artificial weather event is applied, which includes a constant heavy precipitation of 100 mm as well as input data, which excludes the generation of interfering processes e.g., evaporation or snowfall. In addition, these scenarios will be applied to different system conditions to determine the differences of dry, humid, and wet system preconditions. Ultimately, the precipitation intensity but not the amount of the artificial weather event will also be varied to be able to determine any change in the dominant runoff processes due to precipitation intensity. The results of the modeling will then be compared using the generated surface runoff, interflow, and deep infiltration. In addition, a check of the modeling with a runoff process map available for the catchment area as well as a pattern comparison using the spatial efficiency metric (SPEAF) will be performed. It is expected that the different PTF´s per se, as well as depending on the system precondition and precipitation intensity, will result in very different spatial distributions and dominance of the individual runoff processes. Thus, one goal is to find the PTF´s that provide comprehensible distributions and intensities of the considered runoff processes.

How to cite: Jackel, M., Casper, M., and Mohajerani, H.: The effect of different pedotransferfunctions on the spatial distribution and intensity of runoff processes using the hydrological model WaSiM-ETH., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8027, https://doi.org/10.5194/egusphere-egu22-8027, 2022.

Flood forecasting agencies and hydropower companies require cost effective approaches for accurate estimation of snow water equivalent (SWE) to improve spring flow forecast and to make informed decision about reservoir operation.  The lack of accurate SWE estimation at the watershed scale is an issue in northern watersheds, as snow surveys are either absent, or sparsely distributed and infrequent (monthly to bi-weekly). Remotely sensed SWE data sets retrieved from passive microwave satellites, such as GlobSnow, offers the advantage of high frequent coverage of the Northern Hemisphere at the watershed scale.  The main issue is that SWE is typically underestimated because of vegetation. Also, the signal saturates for deep snowpacks.  An approach is therefore required to correct GlobSnow which does not resort to local SWE measurements.

A correction factor approach which focuses on improving the Maximum Snow Water Equivalent (MSWE) estimate for a watershed produced by publicly available regional databases, such as GlobSnow, has been developed. The method does not require point SWE measurements and assumes that the spring runoff volume calculated from historical streamflow observations equals the total snow melt volume retrieved from GlobSnow’s MSWE, less infiltration into frozen ground. The latter is calculated from freely available hydro-meteorological information. The method presented below introduces a cost-effective approach which can bridge the temporal and spatial sparsity that is often associated with the snow survey programs.

The results from applying this approach to the regional GlobSnow database to northern watersheds in Quebec show that the Corrected GlobSnow (C-Glob) more accurately correlates to the manual snow surveys, compared to the uncorrected GlobSnow data source. The corrected database may prove especially useful for watersheds where no SWE measurements are available, may serve as a supplementary source of information to better understand what takes place over the entire watershed by filling gaps of manual surveys.

How to cite: Whittaker, C. and Leconte, R.: A novel watershed scale Snow Water Equivalent (SWE) correction approach, using stream flow and remote sensing data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1570, https://doi.org/10.5194/egusphere-egu22-1570, 2022.