scholarly journals Supplementary material to "Understanding terrestrial water storage variations in northern latitudes across scales"

2017 ◽  
Author(s):  
Tina Trautmann ◽  
Sujan Koirala ◽  
Nuno Carvalhais ◽  
Annette Eicker ◽  
Manfred Fink ◽  
...  
Keyword(s):  
Water Storage ◽  
Terrestrial Water Storage ◽  
Northern Latitudes ◽  
Terrestrial Water ◽  
Supplementary Material

scholarly journals Understanding terrestrial water storage variations in northern latitudes across scales

2018 ◽  
Vol 22 (7) ◽  
pp. 4061-4082 ◽  
Author(s):  
Tina Trautmann ◽  
Sujan Koirala ◽  
Nuno Carvalhais ◽  
Annette Eicker ◽  
Manfred Fink ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Liquid Water ◽  
Spatial Scales ◽  
Water Storage ◽  
Earth Observation ◽  
High Latitudes ◽  
Terrestrial Water Storage ◽  
Northern Latitudes ◽  
Terrestrial Water ◽  
Spatio Temporal

Abstract. The GRACE satellites provide signals of total terrestrial water storage (TWS) variations over large spatial domains at seasonal to inter-annual timescales. While the GRACE data have been extensively and successfully used to assess spatio-temporal changes in TWS, little effort has been made to quantify the relative contributions of snowpacks, soil moisture, and other components to the integrated TWS signal across northern latitudes, which is essential to gain a better insight into the underlying hydrological processes. Therefore, this study aims to assess which storage component dominates the spatio-temporal patterns of TWS variations in the humid regions of northern mid- to high latitudes. To do so, we constrained a rather parsimonious hydrological model with multiple state-of-the-art Earth observation products including GRACE TWS anomalies, estimates of snow water equivalent, evapotranspiration fluxes, and gridded runoff estimates. The optimized model demonstrates good agreement with observed hydrological spatio-temporal patterns and was used to assess the relative contributions of solid (snowpack) versus liquid (soil moisture, retained water) storage components to total TWS variations. In particular, we analysed whether the same storage component dominates TWS variations at seasonal and inter-annual temporal scales, and whether the dominating component is consistent across small to large spatial scales. Consistent with previous studies, we show that snow dynamics control seasonal TWS variations across all spatial scales in the northern mid- to high latitudes. In contrast, we find that inter-annual variations of TWS are dominated by liquid water storages at all spatial scales. The relative contribution of snow to inter-annual TWS variations, though, increases when the spatial domain over which the storages are averaged becomes larger. This is due to a stronger spatial coherence of snow dynamics that are mainly driven by temperature, as opposed to spatially more heterogeneous liquid water anomalies, that cancel out when averaged over a larger spatial domain. The findings first highlight the effectiveness of our model–data fusion approach that jointly interprets multiple Earth observation data streams with a simple model. Secondly, they reveal that the determinants of TWS variations in snow-affected northern latitudes are scale-dependent. In particular, they seem to be not merely driven by snow variability, but rather are determined by liquid water storages on inter-annual timescales. We conclude that inferred driving mechanisms of TWS cannot simply be transferred from one scale to another, which is of particular relevance for understanding the short- and long-term variability of water resources.

scholarly journals Understanding terrestrial water storage variations in northern latitudes across scales

2017 ◽  
Author(s):  
Tina Trautmann ◽  
Sujan Koirala ◽  
Nuno Carvalhais ◽  
Annette Eicker ◽  
Manfred Fink ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Scales ◽  
Water Storage ◽  
Earth Observation ◽  
Snow Pack ◽  
Terrestrial Water Storage ◽  
Northern Latitudes ◽  
Terrestrial Water ◽  
Spatial Domains ◽  
Spatio Temporal

Abstract. The GRACE satellites provide signals of total terrestrial water storage (TWS) variations over large spatial domains at seasonal to inter-annual time scales. While the GRACE data have been extensively and successfully used to assess spatio-temporal changes in TWS, little effort has been made to quantify the relative contributions of snow pack, soil moisture and other components to the integrated TWS signal across northern latitudes, which is essential to gain a better insight into the underlying hydrological processes. Therefore, this study aims to assess which storage component dominates the spatio-temporal patterns of TWS variations in the humid regions of northern mid-to-high latitudes. To do so, we constrained a rather parsimonious hydrological model with multiple state-of-the-art Earth observation products including GRACE TWS anomalies, estimates of snow water equivalent, evapotranspiration fluxes, and gridded runoff estimates. The optimized model demonstrates good agreement with observed hydrological patterns, and was used to assess the relative contributions of solid (snow pack) versus liquid (soil moisture, retained water) storage components to total TWS variations. In particular, we analysed whether the same storage component dominates TWS variations at seasonal and inter-annual temporal scales, and whether the dominating component is consistent across small to large spatial scales. Consistent with previous studies, we show that snow dynamics control seasonal TWS variations across spatial scales in the northern mid-to-high latitudes. In contrast, we find that inter-annual variations of TWS are dominated by liquid water storages, comprising mainly of soil moisture. However, as the spatial domain over which the storages are averaged becomes larger, the relative contribution of snow to inter-annual TWS variations increases. This is due to a stronger spatial coherence of snow anomalies as opposed to spatially more heterogeneous liquid water anomalies that cancel out over large spatial domains. The findings first highlight the effectiveness of our model-data fusion approach that jointly interprets multiple Earth observation data streams with a simple model. Secondly, they reveal that the determinants of TWS variations in snow-affected northern latitudes are scale dependent. We conclude that inferred driving mechanisms of TWS cannot simply be transferred from one scale to another, which is of particular relevance for understanding the short and long-term variability of water resources.

scholarly journals A time series assessment of terrestrial water storage and its relationship with hydro-meteorological factors in Gilgit-Baltistan region using GRACE observation and GLDAS-Noah model

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Dostdar Hussain ◽  
Aftab Ahmed Khan ◽  
Syed Najam Ul Hassan ◽  
Syed Ali Asad Naqvi ◽  
Akhtar Jamil
Keyword(s):  
Snow Water Equivalent ◽  
Gravity Data ◽  
Water Storage ◽  
Indus Basin ◽  
Flood Hazards ◽  
Terrestrial Water Storage ◽  
Satellite Gravity ◽  
Terrestrial Water ◽  
Gilgit Baltistan

AbstractMountains regions like Gilgit-Baltistan (GB) province of Pakistan are solely dependent on seasonal snow and glacier melt. In Indus basin which forms in GB, there is a need to manage water in a sustainable way for the livelihood and economic activities of the downstream population. It is important to monitor water resources that include glaciers, snow-covered area, lakes, etc., besides traditional hydrological (point-based measurements by using the gauging station) and remote sensing-based studies (traditional satellite-based observations provide terrestrial water storage (TWS) change within few centimeters from the earth’s surface); the TWS anomalies (TWSA) for the GB region are not investigated. In this study, the TWSA in GB region is considered for the period of 13 years (from January 2003 to December 2016). Gravity Recovery and Climate Experiment (GRACE) level 2 monthly data from three processing centers, namely Centre for Space Research (CSR), German Research Center for Geosciences (GFZ), and Jet Propulsion Laboratory (JPL), System Global Land Data Assimilation System (GLDAS)-driven Noah model, and in situ precipitation data from weather stations, were used for the study investigation. GRACE can help to forecast the possible trends of increasing or decreasing TWS with high accuracy as compared to the past studies, which do not use satellite gravity data. Our results indicate that TWS shows a decreasing trend estimated by GRACE (CSR, GFZ, and JPL) and GLDAS-Noah model, but the trend is not significant statistically. The annual amplitude of GLDAS-Noah is greater than GRACE signal. Mean monthly analysis of TWSA indicates that TWS reaches its maximum in April, while it reaches its minimum in October. Furthermore, Spearman’s rank correlation is determined between GRACE estimated TWS with precipitation, soil moisture (SM) and snow water equivalent (SWE). We also assess the factors, SM and SWE which are the most efficient parameters producing GRACE TWS signal in the study area. In future, our results with the support of more in situ data can be helpful for conservation of natural resources and to manage flood hazards, droughts, and water distribution for the mountain regions.

Sign in / Sign up

Export Citation Format

Share Document