Understanding terrestrial water storage variations  in northern latitudes across scales

Trautmann, Tina; Koirala, Sujan; Eicker, Annette; Fink, Manfred; Niemann, Christoph; Jung, Martin

doi:10.5194/hess-22-4061-2018

Cited by 29 publications

(48 citation statements)

References 89 publications

(116 reference statements)

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“…Our findings agree with the results of Trautmann et al (), who compared modeled TWS with GRACE TWS observation in mid‐ to high latitudes. They found that snow mass variations are the main contributor to seasonal TWS variation.…”

Section: Discussionsupporting

confidence: 92%

“…Although the GIA model might not effectively remove the contribution of this background signal from GRACE observations, the inconsistent behaviour of GRACE TWS variabilities, compared with multisource SWEA data, might not only be associated with linear trends. It is worth mentioning that the inter‐annual variations of GRACE TWS in the areas surrounding Hudson Bay are more uncertain and exhibit considerable noises that influence the information content of the observations (Humphrey et al, ; Trautmann et al, ). There might be other factors that influence the correlation results, such as de‐aliasing model (tides are poorly modeled over Hudson Bay) in Arctic coastal regions in Canada and the west coast of Hudson Bay (Humphrey et al, ; Rangelova et al, ).…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, if the contribution of non‐SWE storage compartments is important, it implies that the subtraction of their contributions from the total storage should be taken into account. Trautmann et al () showed that TWS variations in northern latitudes are not only changed by snow variability but also driven by liquid water (soil moisture and retained water) storage changes. Non‐SWE storage anomalies are dominant drivers of inter‐annual (high frequency) TWS changes in mid‐ to high northern latitudes.…”

Section: Discussionmentioning

confidence: 99%

“…They found that snow mass variations are the main contributor to seasonal TWS variation. Furthermore, Trautmann et al () achieved weak correlation values with large uncertainties in the Hudson Bay. We can find an agreement between some of our results and previous research in Western Canada.…”

Section: Discussionmentioning

confidence: 99%

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Analysing the contribution of snow water equivalent to the terrestrial water storage over Canada

Bahrami

Goı̈ta

Magagi

2019

Hydrological Processes

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In this study, the spatial and temporal variabilities of terrestrial water storage anomaly (TWSA) and snow water equivalent anomaly (SWEA) information obtained from the Gravity Recovery and Climate Experiment (GRACE) twin satellites data were analysed in conjunction with multisource snow products over several basins in the Canadian landmass. Snow water equivalent (SWE) data were extracted from three different sources: Global Snow Monitoring for Climate Research version 2 (GlobSnow2), Advanced Microwave Scanning Radiometer‐Earth Observing System (AMSR‐E), and Canadian Meteorological Centre (CMC). The objective of the study was to understand whether SWE variations have a significant contribution to terrestrial water storage anomalies in the Canadian landmass. The period was considered from December 2002 to March 2011. Significant relationships were observed between TWSA and SWEA for most of the 15 basins considered (53% to 80% of the basins, depending on the SWE products considered). The best results were obtained with the CMC SWE products compared with satellite‐based SWE data. Stronger relationships were found in snow‐dominated basins (Rs > = 0.7), such as the Liard [root mean square error (RMSE) = 21.4 mm] and Peace Basins (RMSE = 26.76 mm). However, despite high snow accumulation in the north of Quebec, GRACE showed weak or insignificant correlations with SWEA, regardless of the data sources. The same behaviour was observed in the Western Hudson Bay basin. In both regions, it was found that the contribution of non‐SWE compartments including wetland, surface water, as well as soil water storages has a significant impact on the variations of total storage. These components were estimated using the Water‐Global Assessment and Prognosis Global Hydrology Model (WGHM) simulations and then subtracted from GRACE observations. The GRACE‐derived SWEA correlation results showed improved relationships with three SWEA products. The improvement is particularly important in the sub‐basins of the Hudson Bay, where very weak and insignificant results were previously found with GRACE TWSA data. GRACE‐derived SWEA showed a significant relationship with CMC data in 93% of the basins (13% more than GRACE TWSA). Overall, the results indicated the important role of SWE on terrestrial water storage variations.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Analysing the contribution of snow water equivalent to the terrestrial water storage over Canada

Bahrami

Goı̈ta

Magagi

2019

Hydrological Processes

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“…In fact, a very recent implementation of lateral flow in a global-scale LSM (Zeng et al, 2018), at a resolution similar to this study, shows similar bias with shallower WTD compared to that from Fan et al (2013). These discrepancies in global WTD estimates also suggests a need for better treatment of other global data sets, such as the Gravity Recovery and Climate Experiment terrestrial water storage variations (Tapley et al, 2004), in constraining global-scale model simulations of soil moisture-GW dynamics, as demonstrated previously in regional-scale studies (Lo et al, 2008;Trautmann et al, 2018).…”

Section: Summary Discussion and Limitationssupporting

confidence: 82%

Sensitivity of Global Hydrological Simulations to Groundwater Capillary Flux Parameterizations

Koirala

Kim

Hirabayashi

et al. 2019

Water Resources Research

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Global land surface and hydrologic models, used to quantify the influence of groundwater (GW) dynamics on land surface hydrology, vary in parameterizations of the GW capillary flux and depth of moisture flux exchange between GW and unsaturated soil column (interaction depth). In this study, we demonstrate that the parameterization of capillary flux significantly affects the magnitude of GW‐supported ET (±15%) and GW recharge (±25%). The largest sensitivities are associated with a strong dependence of the capillary flux parameterization on water table depth (WTD) with further controls by soil hydraulic properties. Under shallow WTD condition, the finer soils show a larger GW‐supported ET for parameterization that depends only on WTD. Further, GW‐supported ET reduces by 7–13% per meter increase in interaction depth used in simulation compared to simulation in which the interaction depth varies in space and time with WTD. The simulations of runoff, soil moisture, and WTD are even more sensitive to the difference in parameterization and interaction depth. Moreover, these sensitivities vary largely in both space and time. Evaluations against observation‐based data and previous modeling simulations reveal that simulations with capillary flux perform better than that the one without it in regions with large GW‐supported ET. We concur that capillary flux has a large and nonnegligible influence in global hydrologic simulation. But, the spatiotemporal variabilities of sensitivities of hydrological fluxes and storages demonstrate that different parameterization of GW capillary flux may also lead to a substantial uncertainty in global hydrologic simulations and subsequent water resources assessments.

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A Robust Light Use Efficiency Model Parameterization Method Based on Ecosystem Properties

Bao

Alonso

Wang

et al. 2022

Preprint

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In a model simulating the dynamics of a system, parameters can represent system properties and unresolved processes, therefore affecting the model accuracy and uncertainties. For a light use efficiency (LUE) model, which is a typical tool to estimate gross primary productivity (GPP), the plant-functional-type (PFT)-dependent parameterization method was widely used to extrapolate parameters to larger spatial scales. However, the method cannot capture the spatial variability within PFT and introduces misclassification errors. To overcome the shortage, here we proposed an ecosystem-property-based parameterization method (mNN-GPP) for an LUE model. This method refers to predicting model parameters using the multi-output artificial neural network based on collected variables including PFT, climate types, bioclimatic variables, vegetation features, atmospheric deposition and soil properties at 196 FLLUXNET eddy covariance flux sites. The neural network was optimized according to GPP errors and constraints on sensitivity functions of the LUE model. We compared mNN-GPP with eleven other typical parameter extrapolating methods, including PFT-, climate-specific parameterization, global and PFT-based parameter optimization, site-similarity-based, and regression methods. These twelve methods were assessed using Nash-Sutcliffe model efficiency (NSE), determination coefficient and normalized root mean squared error of the simulated GPP. The simulated results were also contrasted with those of site-specific calibration based on full-time-series GPP estimated from observational net ecosystem exchange. The N-fold cross-validated results showed that mNN-GPP had the best performance across various temporal and spatial scales (e.g., NSE=0.62 at the daily scale). No extrapolated parameters reached the same performance as the calibrated parameters (NSE=0.82), but the ranges of predicted parameters were constrained. Furthermore, the Shapley values, layer-wise relevance and partial dependence of the input features showed that bioclimatic variables, PFT, and vegetation features are the key variables determining parameters. We recommend using the parameterization method considering both ecosystem properties and prediction errors to other GPP models and across spatio-temporal scales.

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Understanding terrestrial water storage variations in northern latitudes across scales

Cited by 29 publications

References 89 publications

Analysing the contribution of snow water equivalent to the terrestrial water storage over Canada

Analysing the contribution of snow water equivalent to the terrestrial water storage over Canada

Sensitivity of Global Hydrological Simulations to Groundwater Capillary Flux Parameterizations

A Robust Light Use Efficiency Model Parameterization Method Based on Ecosystem Properties

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