scholarly journals A global water cycle reanalysis (2003–2012) reconciling satellite gravimetry and altimetry observations with a hydrological model ensemble

2013 ◽  
Vol 10 (12) ◽  
pp. 15475-15523 ◽  
Author(s):  
A. I. J. M. van Dijk ◽  
L. J. Renzullo ◽  
Y. Wada ◽  
P. Tregoning

Abstract. We present a global water cycle reanalysis that reconciles water balance estimates derived from the GRACE satellite mission, satellite water level altimetry and off-line estimates from several hydrological models. Error estimates for the sequential data assimilation scheme were derived from available uncertainty information and the triple collocation technique. Errors in four GRACE storage products were estimated to be 11–12 mm over land areas, while errors in monthly storage changes derived from five global hydrological models were estimated to be 17–28 mm. Prior and posterior estimates were evaluated against independent observations of river water level and discharge, snow water storage and glacier mass loss. Data assimilation improved or maintained agreement overall, although results varied regionally. Uncertainties were greatest in regions where glacier mass loss and sub-surface storage decline are both plausible but poorly constrained. We calculated a global water budget for 2003–2012. The main changes were a net loss of polar ice (−341 Gt yr−1) and mountain glaciers (−185 Gt yr−1), with an additional decrease in seasonal snow pack (−19 Gt yr−1). Storage in lakes increased by +77 Gt yr−1, due to new reservoir impoundments (+87 Gt yr−1), water level change in the Caspian Sea (−27 Gt yr−1) and net increases in the remaining lakes combined (+17 Gt yr−1). There was no change in subsurface storage, because groundwater depletion (−90 Gt yr−1) was offset by increased water storage in the seasonally wet tropics of South America and southern Africa (+87 Gt yr−1), which agrees with observed and predicted changes in the tropical monsoon.

2014 ◽  
Vol 18 (8) ◽  
pp. 2955-2973 ◽  
Author(s):  
A. I. J. M. van Dijk ◽  
L. J. Renzullo ◽  
Y. Wada ◽  
P. Tregoning

Abstract. We present a global water cycle reanalysis that merges water balance estimates derived from the Gravity Recovery And Climate Experiment (GRACE) satellite mission, satellite water level altimetry and off-line estimates from several hydrological models. Error estimates for the sequential data assimilation scheme were derived from available uncertainty information and the triple collocation technique. Errors in four GRACE storage products were estimated to be 11–12 mm over land areas, while errors in monthly storage changes derived from five global hydrological models were estimated to be 17–28 mm. Prior and posterior water storage estimates were evaluated against independent observations of river water level and discharge, snow water storage and glacier mass loss. Data assimilation improved or maintained agreement overall, although results varied regionally. Uncertainties were greatest in regions where glacier mass loss and subsurface storage decline are both plausible but poorly constrained. We calculated a global water budget for 2003–2012. The main changes were a net loss of polar ice caps (−342 Gt yr−1) and mountain glaciers (−230 Gt yr−1), with an additional decrease in seasonal snowpack (−18 Gt yr−1). Storage increased due to new impoundments (+16 Gt yr−1), but this was compensated by decreases in other surface water bodies (−10 Gt yr−1). If the effect of groundwater depletion (−92 Gt yr−1) is considered separately, subsurface water storage increased by +202 Gt yr−1 due particularly to increased wetness in northern temperate regions and in the seasonally wet tropics of South America and southern Africa. The reanalysis results are publicly available via www.wenfo.org/wald/.


2021 ◽  
Author(s):  
Stephan Dietrich ◽  
Valentin Aich ◽  
Wouter Dorigo ◽  
Thomas Recknagel ◽  
Harald Koethe ◽  
...  

<p>Life on earth is closely linked to the availability of water and its variability. However, global change means that the demands placed on water resources are constantly increasing. According to the conclusions of the IPCC's 5th Assessment Report, it is likely that human activities have influenced the global water cycle since 1960. Satellite-based remote sensing of water-related parameters and operational data-assimilation services are becoming increasingly important to assess changes of the global water cycle as part of the essential climate variables (gcos.wmo.int). However, particularly over land or in the deep ocean where space-borne monitoring is not possible, in-situ data provide long-term records of changes in the various components of the hydrological cycle.</p><p>Global data centres, often operating under the auspices of UN agencies, collect and harmonise water data worldwide and make the global data sets available to the public again. Most of these relevant Global Data Centres are members of the Global Terrestrial Network of Hydrology (GTN-H) that operates under auspices of WMO and the Terrestrial observation Panel of Climate (TOPC) of the Global Climate Observing System GCOS. GTN-H links existing networks and systems for integrated observations of the global water cycle. The network was established in 2001 as a „network of networks“ to support a range of climate and water resource objectives, building on existing networks and data centres, and producing value-added products through enhanced communications and shared development. Since 2017 the GTN-H coordination is held by the International Centre for Water Resources and Global change (ICWRGC, operating under auspices of the UNESCO) aiming for a data and knowledge transfer between data providers, scientists and decision makers as well as between the different institutional bodies on UN-level inter alia the WMO, UNESCO, FAO, UNEP or GCOS.</p><p>We will demonstrate the state-of-the art of the global in-situ terrestrial water resources monitoring and draw a picture of a global water observation architecture. <br>As a major outcome we will share the most recent evaluation of global water storage and water cycle fluxes. Here, we assess the relevant land, atmosphere, and ocean water storage and the fluxes between them, including anthropogenic water use. Based on the assessment, we discuss gaps in existing observation systems and formulate guidelines for future water cycle observation strategies.</p>


2021 ◽  
Author(s):  
Basil Kraft ◽  
Martin Jung ◽  
Marco Körner ◽  
Sujan Koirala ◽  
Markus Reichstein

Abstract. Progress in machine learning in conjunction with the increasing availability of relevant Earth observation data streams may help to overcome uncertainties of global hydrological models due to the complexity of the processes, diversity, and heterogeneity of the land surface and subsurface, as well as scale-dependency of processes and parameters. In this study, we exemplify a hybrid approach to global hydrological modeling that exploits the data-adaptiveness of machine learning for representing uncertain processes within a model structure based on physical principles like mass conservation. Our H2M model simulates the dynamics of snow, soil moisture, and groundwater pools globally at 1º spatial resolution and daily time step where simulated water fluxes depend on an embedded recurrent neural network. We trained the model simultaneously against observational products of terrestrial water storage variations (TWS), runoff, evapotranspiration, and snow water equivalent with a multi-task learning approach. We find that H2M is capable of reproducing the key patterns of global water cycle components with model performances being at least on par with four state-of-the-art global hydrological models. The neural network learned hydrological responses of evapotranspiration and runoff generation to antecedent soil moisture state that are qualitatively consistent with our understanding and theory. Simulated contributions of groundwater, soil moisture, and snowpack variability to TWS variations are plausible and within the large range of traditional GHMs. H2M indicates a somewhat stronger role of soil moisture for TWS variations in transitional and tropical regions compared to GHMs. Overall, we present a proof of concept for global hybrid hydrological modeling in providing a new, complementary, and data-driven perspective on global water cycle variations. With further increasing Earth observations, hybrid modeling has a large potential to advance our capability to monitor and understand the Earth system by facilitating a data-adaptive yet physically consistent, joint interpretation of heterogeneous data streams.


2021 ◽  
Author(s):  
Mohammad J. Tourian ◽  
Omid Elmi ◽  
Yasin Shafaghi ◽  
Sajedeh Behnia ◽  
Peyman Saemian ◽  
...  

Abstract. Against the backdrop of global change, both in terms of climate and demography, there is a pressing need for monitoring the global water cycle. The publicly available global database is very limited in its spatial and temporal coverage worldwide. Moreover, the acquisition of in situ data and their delivery to the database are in decline since the late 1970s, be it for economical or political reasons. Given the insufficient monitoring from in situ gauge networks, and with no outlook for improvement, spaceborne approaches have been under investigation for some years now. Satellite-based Earth observation with its global coverage and homogeneous accuracy has been demonstrated to be a potential alternative to in situ measurements. This paper presents HydroSat as a repository of global water cycle products from spaceborne geodetic sensors. HydroSat provides time series and their uncertainty of: water level from satellite altimetry, surface water extent from satellite imagery, terrestrial water storage anomaly from satellite gravimetry, lake and reservoir water storage anomaly from a combination of satellite altimetry and imagery, and river discharge from either satellite altimetry or imagery. These products can contribute to understanding the global water cycle within the Earth system in several ways. They can act as inputs to hydrological models, they can play a complementary role to current and future spaceborne observations, and they can define indicators of the past and future state of the global freshwater system. The repository is publicly available through http://hydrosat.gis.uni-stuttgart.de.


2021 ◽  
Vol 13 (5) ◽  
pp. 915
Author(s):  
Elias C. Massoud ◽  
Zhen Liu ◽  
Amin Shaban ◽  
Mhamad Hage

Regions with high productivity of agriculture, such as the Beqaa Plain, Lebanon, often rely on groundwater supplies for irrigation demand. Recent reports have indicated that groundwater consumption in this region has been unsustainable, and quantifying rates of groundwater depletion has remained a challenge. Here, we utilize 15 years of data (June 2002–April 2017) from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to show Total Water Storage (TWS) changes in Lebanon’s Beqaa Plain. We then obtain complimentary information on various hydrologic cycle variables, such as soil moisture storage, snow water equivalent, and canopy water storage from the Global Land Data Assimilation System (GLDAS) model, and surface water data from the largest body of water in this region, the Qaraaoun Reservoir, to disentangle the TWS signal and calculate groundwater storage changes. After combining the information from the remaining hydrologic cycle variables, we determine that the majority of the losses in TWS are due to groundwater depletion in the Beqaa Plain. Results show that the rate of groundwater storage change in the West Beqaa is nearly +0.08 cm/year, in the Rashaya District is −0.01 cm/year, and in the Zahle District the level of depletion is roughly −1.10 cm/year. Results are confirmed using Sentinel-1 interferometric synthetic aperture radar (InSAR) data, which provide high-precision measurements of land subsidence changes caused by intense groundwater usage. Furthermore, data from local monitoring wells are utilized to further showcase the significant drop in groundwater level that is occurring through much of the region. For monitoring groundwater storage changes, our recommendation is to combine various data sources, and in areas where groundwater measurements are lacking, we especially recommend the use of data from remote sensing.


1989 ◽  
Vol 289 (4) ◽  
pp. 455-483 ◽  
Author(s):  
Y. Tardy ◽  
R. N'Kounkou ◽  
J.-L. Probst

2007 ◽  
Vol 88 (3) ◽  
pp. 375-384 ◽  
Author(s):  
E. S. Takle ◽  
J. Roads ◽  
B. Rockel ◽  
W. J. Gutowski ◽  
R. W. Arritt ◽  
...  

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.


Science ◽  
2012 ◽  
Vol 336 (6080) ◽  
pp. 455-458 ◽  
Author(s):  
P. J. Durack ◽  
S. E. Wijffels ◽  
R. J. Matear

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