scholarly journals Quantifying the impacts of human water use and climate variations on recent drying of Lake Urmia basin: the value of different sets of spaceborne and in-situ data for calibrating a hydrological model

2018 ◽  
Author(s):  
Seyed-Mohammad Hosseini-Moghari ◽  
Shahab Araghinejad ◽  
Mohammad J. Tourian ◽  
Kumars Ebrahimi ◽  
Petra Döll
Keyword(s):  
Time Series ◽  
Water Use ◽  
Lake Water ◽  
Water Storage ◽  
Water Volume ◽  
Total Water ◽  
Lake Urmia ◽  
Groundwater Levels ◽  
Lake Volume

Abstract. During the last decades, the endorheic Lake Urmia basin in northwestern Iran has suffered from decreased precipitation, groundwater levels and a very strong reduction in the volume and more recently also in the extent of Lake Urmia. Human water use has exacerbated the desiccating impact of climatic variations. This study quantifies the contribution of human water use to the reduction of inflow into Lake Urmia, to the loss of lake water volume and to the loss of groundwater and total water storage in the entire Lake Urmia basin during 2003–2013. To this end, the WaterGAP Global Hydrology Model (WGHM) was manually calibrated specifically for the basin against multiple in-situ and spaceborne data, and the best-performing calibration variant was run with or without taking into account water use. Observation data encompass remote-sensing based time series of annual irrigated area in the basin from MODIS, monthly total water storage anomaly (TWSA) from GRACE satellites and monthly lake volume. In-situ observations include time series of annual inflow into the lake and basin averages of groundwater level variations based on 284 wells. In addition, local estimates of sectoral water withdrawals in 2009 and return flow fractions were utilized. Four calibration variants were set up in which the number of considered observation types was increased in a stepwise fashion. The best fit to each and all observations is achieved if the maximum amount of observations is used for calibration. Calibration against GRACE TWSA improves simulated inflow into Lake Urmia but still overestimates it by 90 %; it results in an overestimation of lake volume loss, underestimation of groundwater loss and a shifted seasonality of groundwater storage. Lake and groundwater dynamics can only be simulated well if calibration against groundwater levels leads to adjusting the fractions of human water use from groundwater and surface water. According to our study, human water use was the reason for 50 % of the total basin water loss of about 10 km3 during 2003–2013, for 40 % of the Lake Urmia water loss of about 8 km3 and for up to 90 % of the groundwater loss. Lake inflow was 40 % less than it would have been without human water use. We found that even without human water use, Lake Urmia would not have recovered from the significant loss of lake water volume caused by the drought year 2008. These findings may serve to support water management in the basin and more specifically Lake Urmia restoration plans.

scholarly journals Quantifying the impacts of human water use and climate variations on recent drying of Lake Urmia basin: the value of different sets of spaceborne and in situ data for calibrating a global hydrological model

2020 ◽  
Vol 24 (4) ◽  
pp. 1939-1956 ◽  
Author(s):  
Seyed-Mohammad Hosseini-Moghari ◽  
Shahab Araghinejad ◽  
Mohammad J. Tourian ◽  
Kumars Ebrahimi ◽  
Petra Döll
Keyword(s):  
Genetic Algorithm ◽  
Water Use ◽  
Hydrological Model ◽  
Water Storage ◽  
Water Volume ◽  
Climate Variations ◽  
Total Water ◽  
Lake Urmia ◽  
Lake Volume

Abstract. During the last decades, the endorheic Lake Urmia basin in northwestern Iran has suffered from declining groundwater tables and a very strong recent reduction in the volume of Lake Urmia. For the case of Lake Urmia basin, this study explores the value of different locally and globally available observation data for adjusting a global hydrological model such that it can be used for distinguishing the impacts of human water use and climate variations. The WaterGAP Global Hydrology Model (WGHM) was for the first time calibrated against multiple in situ and spaceborne data to analyze the decreasing lake water volume, lake river inflow, loss of groundwater, and total water storage in the entire basin during 2003–2013. The calibration process was done using an automated approach including a genetic algorithm (GA) and non-dominated sorting genetic algorithm II (NSGA-II). Then the best-performing calibrated models were run with and without considering water use to quantify the impact of human water use. Observations encompass remote-sensing-based time series of annual irrigated areas in the basin from MODIS, monthly total water storage anomaly (TWSA) from GRACE satellites, and monthly lake volume anomalies. In situ observations include time series of annual inflow into the lake and basin averages of groundwater level variations based on 284 wells. In addition, local estimates of sectoral water withdrawals in 2009 and return flow fractions were utilized. Calibration against MODIS and GRACE data alone improved simulated inflow into Lake Urmia but inflow and lake volume loss were still overestimated, while groundwater loss was underestimated and seasonality of groundwater storage was shifted as compared to observations. Lake and groundwater dynamics could only be simulated well if calibration against groundwater levels led to an adjustment of the fractions of human water use from groundwater and surface water. Thus, in some basins, globally available satellite-derived observations may not suffice for improving the simulation of human water use. According to WGHM simulations with 18 optimal parameter sets, human water use was the reason for 52 %–57 % of the total basin water loss of about 10 km3 during 2003–2013, for 39 %–43 % of the Lake Urmia water loss of about 8 km3, and for up to 87 %–90 % of the groundwater loss. Lake inflow was 39 %–45 % less than it would have been without human water use. The study shows that even without human water use Lake Urmia would not have recovered from the significant loss of lake water volume caused by the drought year 2008. These findings can support water management in the basin and more specifically Lake Urmia restoration plans.

scholarly journals RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes

2020 ◽  
Author(s):  
Simon Deggim ◽  
Annette Eicker ◽  
Lennart Schawohl ◽  
Helena Gerdener ◽  
Kerstin Schulze ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Water ◽  
Regional Scale ◽  
Water Storage ◽  
Water Volume ◽  
Optical Remote Sensing ◽  
Hydrological Models ◽  
Total Water ◽  
Satellite Mission ◽  
The Impact

Abstract. Observations of changes in terrestrial water storage obtained from the satellite mission GRACE (Gravity Recovery and Climate Experiment) have frequently been used for water cycle studies and for the improvement of hydrological models by means of calibration and data assimilation. However, due to a low spatial resolution of the gravity field models spatially localized water storage changes, such as those occurring in lakes and reservoirs, cannot properly be represented in the GRACE estimates. As surface storage changes can represent a large part of total water storage, this leads to leakage effects and results in surface water signals becoming erroneously assimilated into other water storage compartments of neighboring model grid cells. As a consequence, a simple mass balance at grid/regional scale is not sufficient to deconvolve the impact of surface water on TWS. Furthermore, non-hydrology related phenomena contained in the GRACE time series, such as the mass redistribution caused by major earthquakes, hamper the use of GRACE for hydrological studies in affected regions. In this paper, we present the first release (RL01) of the global correction product RECOG (REgional COrrections for GRACE), which accounts for both the surface water (lakes & reservoirs, RECOG-LR) and earthquake effects (RECOG-EQ). RECOG-LR is computed from forward-modelling surface water volume estimates derived from satellite altimetry and (optical) remote sensing and allows both a removal of these signals from GRACE and a re-location of the mass change to its origin within the outline of the lakes/reservoirs. The earthquake correction RECOG-EQ includes both the co-seismic and post-seismic signals of two major earthquakes with magnitudes above 9 Mw. We can show that applying the correction dataset (1) reduces the GRACE signal variability by up to 75 % around major lakes and explains a large part of GRACE seasonal variations and trends, (2) avoids the introduction of spurious trends caused by leakage signals of nearby lakes when calibrating/assimilating hydrological models with GRACE, even in neighboring river basins, and (3) enables a clearer detection of hydrological droughts in areas affected by earthquakes. A first validation of the corrected GRACE time series using GPS-derived vertical station displacements shows a consistent improvement of the fit between GRACE and GNSS after applying the correction. Data are made available as open access via the Pangea database (RECOG-LR: Deggim et al. (2020a) https://doi.org/10.1594/PANGAEA.921851; RECOG-EQ: Gerdener et al. (2020b, under revision), https://doi.pangaea.de/10.1594/PANGAEA.921923).

scholarly journals RECOG RL01: correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes

2021 ◽  
Vol 13 (5) ◽  
pp. 2227-2244
Author(s):  
Simon Deggim ◽  
Annette Eicker ◽  
Lennart Schawohl ◽  
Helena Gerdener ◽  
Kerstin Schulze ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Water ◽  
Regional Scale ◽  
Water Storage ◽  
Water Volume ◽  
Optical Remote Sensing ◽  
Hydrological Models ◽  
Total Water ◽  
Lakes And Reservoirs ◽  
The Impact

Abstract. Observations of changes in terrestrial water storage (TWS) obtained from the satellite mission GRACE (Gravity Recovery and Climate Experiment) have frequently been used for water cycle studies and for the improvement of hydrological models by means of calibration and data assimilation. However, due to a low spatial resolution of the gravity field models, spatially localized water storage changes, such as those occurring in lakes and reservoirs, cannot properly be represented in the GRACE estimates. As surface storage changes can represent a large part of total water storage, this leads to leakage effects and results in surface water signals becoming erroneously assimilated into other water storage compartments of neighbouring model grid cells. As a consequence, a simple mass balance at grid/regional scale is not sufficient to deconvolve the impact of surface water on TWS. Furthermore, non-hydrology-related phenomena contained in the GRACE time series, such as the mass redistribution caused by major earthquakes, hamper the use of GRACE for hydrological studies in affected regions. In this paper, we present the first release (RL01) of the global correction product RECOG (REgional COrrections for GRACE), which accounts for both the surface water (lakes and reservoirs, RECOG-LR) and earthquake effects (RECOG-EQ). RECOG-LR is computed from forward-modelling surface water volume estimates derived from satellite altimetry and (optical) remote sensing and allows both a removal of these signals from GRACE and a relocation of the mass change to its origin within the outline of the lakes/reservoirs. The earthquake correction, RECOG-EQ, includes both the co-seismic and post-seismic signals of two major earthquakes with magnitudes above Mw9. We discuss that applying the correction dataset (1) reduces the GRACE signal variability by up to 75 % around major lakes and explains a large part of GRACE seasonal variations and trends, (2) avoids the introduction of spurious trends caused by leakage signals of nearby lakes when calibrating/assimilating hydrological models with GRACE, and (3) enables a clearer detection of hydrological droughts in areas affected by earthquakes. A first validation of the corrected GRACE time series using GPS-derived vertical station displacements shows a consistent improvement of the fit between GRACE and GNSS after applying the correction. Data are made available on an open-access basis via the Pangaea database (RECOG-LR: Deggim et al., 2020a, https://doi.org/10.1594/PANGAEA.921851; RECOG-EQ: Gerdener et al., 2020b, https://doi.org/10.1594/PANGAEA.921923).

scholarly journals Learning from satellite observations: increased understanding of catchment processes through stepwise model improvement

2021 ◽  
Vol 25 (2) ◽  
pp. 957-982 ◽  
Author(s):  
Petra Hulsman ◽  
Hubert H. G. Savenije ◽  
Markus Hrachowitz
Keyword(s):  
Time Series ◽  
Spatial Patterns ◽  
Temporal Dynamics ◽  
Water Storage ◽  
Remotely Sensed ◽  
Satellite Observations ◽  
Model Structure ◽  
Total Water ◽  
Groundwater Reservoir ◽  
Spatio Temporal

Abstract. Satellite observations can provide valuable information for a better understanding of hydrological processes and thus serve as valuable tools for model structure development and improvement. While model calibration and evaluation have in recent years started to make increasing use of spatial, mostly remotely sensed information, model structural development largely remains to rely on discharge observations at basin outlets only. Due to the ill-posed inverse nature and the related equifinality issues in the modelling process, this frequently results in poor representations of the spatio-temporal heterogeneity of system-internal processes, in particular for large river basins. The objective of this study is thus to explore the value of remotely sensed, gridded data to improve our understanding of the processes underlying this heterogeneity and, as a consequence, their quantitative representation in models through a stepwise adaptation of model structures and parameters. For this purpose, a distributed, process-based hydrological model was developed for the study region, the poorly gauged Luangwa River basin. As a first step, this benchmark model was calibrated to discharge data only and, in a post-calibration evaluation procedure, tested for its ability to simultaneously reproduce (1) the basin-average temporal dynamics of remotely sensed evaporation and total water storage anomalies and (2) their temporally averaged spatial patterns. This allowed for the diagnosis of model structural deficiencies in reproducing these temporal dynamics and spatial patterns. Subsequently, the model structure was adapted in a stepwise procedure, testing five additional alternative process hypotheses that could potentially better describe the observed dynamics and pattern. These included, on the one hand, the addition and testing of alternative formulations of groundwater upwelling into wetlands as a function of the water storage and, on the other hand, alternative spatial discretizations of the groundwater reservoir. Similar to the benchmark, each alternative model hypothesis was, in a next step, calibrated to discharge only and tested against its ability to reproduce the observed spatio-temporal pattern in evaporation and water storage anomalies. In a final step, all models were re-calibrated to discharge, evaporation and water storage anomalies simultaneously. The results indicated that (1) the benchmark model (Model A) could reproduce the time series of observed discharge, basin-average evaporation and total water storage reasonably well. In contrast, it poorly represented time series of evaporation in wetland-dominated areas as well as the spatial pattern of evaporation and total water storage. (2) Stepwise adjustment of the model structure (Models B–F) suggested that Model F, allowing for upwelling groundwater from a distributed representation of the groundwater reservoir and (3) simultaneously calibrating the model with respect to multiple variables, i.e. discharge, evaporation and total water storage anomalies, provided the best representation of all these variables with respect to their temporal dynamics and spatial patterns, except for the basin-average temporal dynamics in the total water storage anomalies. It was shown that satellite-based evaporation and total water storage anomaly data are not only valuable for multi-criteria calibration, but can also play an important role in improving our understanding of hydrological processes through the diagnosis of model deficiencies and stepwise model structural improvement.

scholarly journals Analysis of Groundwater and Total Water Storage Changes in Poland Using GRACE Observations, In-situ Data, and Various Assimilation and Climate Models

2019 ◽  
Vol 11 (24) ◽  
pp. 2949 ◽  
Author(s):  
Justyna Śliwińska ◽  
Monika Birylo ◽  
Zofia Rzepecka ◽  
Jolanta Nastula
Keyword(s):  
Climate Models ◽  
Water Storage ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Climate Data ◽  
Total Water ◽  
In Situ Data ◽  
Grace Data ◽  
Land Data Assimilation System

The Gravity Recovery and Climate Experiment (GRACE) observations have provided global observations of total water storage (TWS) changes at monthly intervals for over 15 years, which can be useful for estimating changes in GWS after extracting other water storage components. In this study, we analyzed the TWS and groundwater storage (GWS) variations of the main Polish basins, the Vistula and the Odra, using GRACE observations, in-situ data, GLDAS (Global Land Data Assimilation System) hydrological models, and CMIP5 (the World Climate Research Programme’s Coupled Model Intercomparison Project Phase 5) climate data. The research was conducted for the period between September 2006 and October 2015. The TWS data were taken directly from GRACE measurements and also computed from four GLDAS (VIC, CLM, MOSAIC, and NOAH) and six CMIP5 (FGOALS-g2, GFDL-ESM2G, GISS-E2-H, inmcm4, MIROC5, and MPI-ESM-LR) models. The GWS data were obtained by subtracting the model TWS from the GRACE TWS. The resulting GWS values were compared with in-situ well measurements calibrated using porosity coefficients. For each time series, the trends, spectra, amplitudes, and seasonal components were computed and analyzed. The results suggest that in Poland there has been generally no major TWS or GWS depletion. Our results indicate that when comparing TWS values, better compliance with GRACE data was obtained for GLDAS than for CMIP5 models. However, the GWS analysis showed better consistency of climate models with the well results. The results can contribute toward selection of an appropriate model that, in combination with global GRACE observations, would provide information on groundwater changes in regions with limited or inaccurate ground measurements.

Assessing Impacts of Climate Extremes and Human Water Use on GRACE Total Water Storage Trends in Major U.S. Aquifers

2020 ◽  
Author(s):  
Bridget Scanlon ◽  
Ashraf Rateb ◽  
Alexander Sun ◽  
Himanshu Save
Keyword(s):  
Surface Water ◽  
Water Use ◽  
Groundwater Level ◽  
Water Storage ◽  
Climate Extremes ◽  
High Plains ◽  
Total Water ◽  
Groundwater Storage ◽  
Grace Data ◽  
The U.S

<p>There is considerable concern about water depletion caused by climate extremes (e.g., drought) and human water use in the U.S. and globally. Major U.S. aquifers provide an ideal laboratory to assess water storage changes from GRACE satellites because the aquifers are intensively monitored and modeled. The objective of this study was to assess the relative importance of climate extremes and human water use on GRACE Total Water Storage Anomalies in 14 major U.S. aquifers and to evaluate the reliability of the GRACE data by comparing with groundwater level monitoring (~-23,000 wells) and regional and global models. We quantified total water and groundwater storage anomalies over 2002 – 2017 from GRACE satellites and compared GRACE data with groundwater level monitoring and regional and global modeling results.  </p> <p>The results show that water storage changes were controlled primarily by climate extremes and amplified or dampened by human water use, primarily irrigation. The results were somewhat surprising, with stable or rising long-term trends in the majority of aquifers with large scale depletion limited to agricultural areas in the semi-arid southwest and southcentral U.S. GRACE total water storage in the California Central Valley and Central/Southern High Plains aquifers was depleted by drought and amplified by groundwater irrigation, totaling ~70 km<sup>3</sup> (2002–2017), about 2× the capacity of Lake Mead, the largest surface reservoir in the U.S. In the Pacific Northwest and Northern High Plains aquifers, lower drought intensities were partially dampened by conjunctive use of surface water and groundwater for irrigation and managed aquifer recharge, increasing water storage by up to 22 km<sup>3</sup> in the Northern High Plains over the 15 yr period. GRACE-derived total water storage changes in the remaining aquifers were stable or slightly rising throughout the rest of the U.S.</p> <p>GRACE data compared favorably with composite groundwater level hydrographs for most aquifers except for those with very low signals, indicating that GRACE tracks groundwater storage dynamics. Comparison with regional models was restricted to the limited overlap periods but showed good correspondence for modeled aquifers with the exception of the Mississippi Embayment, where the modeled trend is 4x the GRACE trend. The discrepancy is attributed to uncertainties in model storage parameters and groundwater/surface water interactions. Global hydrologic models (WGHM-2d and PCR-GLOBWB-5.0 overestimated trends in groundwater storage in heavily exploited aquifers in the southwestern and southcentral U.S. Land surface models (CLSM-F2.5 and NOAH-MP) seem to track GRACE TWSAs better than global hydrologic models but underestimated TWS trends in aquifers dominated by irrigation.</p> <p>Intercomparing GRACE, traditional hydrologic monitoring, and modeling data underscore the importance of considering all data sources to constrain water storage changes.  GRACE satellite data have critical implications for many nationally important aquifers, highlighting the importance of conjunctively using surface-water and groundwater and managed aquifer recharge to enhance sustainable development.</p>

scholarly journals Satellite altimetry over small reservoirs in the Brazilian semiarid region

RBRH ◽  
2021 ◽  
Vol 26 ◽  
Author(s):  
Alfredo Ribeiro Neto ◽  
Sajedeh Behnia ◽  
Mohammad J. Tourian ◽  
Fábio Araújo da Costa ◽  
Nico Sneeuw
Keyword(s):  
Time Series ◽  
Water Level ◽  
Satellite Altimetry ◽  
Water Storage ◽  
Semiarid Region ◽  
Northeast Brazil ◽  
Drought Period ◽  
Small Reservoirs ◽  
Brazilian Semiarid

ABSTRACT Northeast Brazil is one of the most populated semiarid regions in the world. The region is highly dependent on reservoirs for human water supply, irrigation, industry, and livestock. The objective of this study was to validate water level time series from the satellites Envisat, SARAL, Sentinel-3A/-3B, Jason-2/-3 in small reservoirs in Northeast Brazil. In total, we evaluated the water level time series of 20 reservoirs. The Sentinel-3B outperforms the other altimeters with a maximum RMSE of 0.21 m. In seven reservoirs with updated depth-area-volume curves, the altimetric water level was used to calculate the corresponding volume. The obtained volume was then compared to the volume given by the same curve by using in situ stage. Our investigations showed that, in the case of small reservoirs, the precision of water level time series derived from satellite altimetry is mainly governed by the seasonal variability of the water storage especially at the end of the 2012-2017 drought period.

scholarly journals Long-term Total Water Storage Change from a SAtellite Water Cycle (SAWC) reconstruction over large south Asian basins

2019 ◽  
Author(s):  
Victor Pellet ◽  
Filipe Aires ◽  
Fabrice Papa ◽  
Simon Munier ◽  
Bertrand Decharme
Keyword(s):  
Water Resources ◽  
Climate Variability ◽  
Water Cycle ◽  
Water Storage ◽  
Anthropogenic Pressure ◽  
Total Water ◽  
Storage Change ◽  
Discharge Measurements

Abstract. The Total Water Storage Change (TWSC) over land is a major component of the global water cycle, with a large influence on climate variability, sea level budget and water resources availability for human life. Its first estimates at large-scale were made available with GRACE observations for the 2002–2016 period, followed since 2018 by the launch of GRACE-FO mission. In this paper, using an approach based on the water mass conservation rule, we proposed to merge satellite-based observations of precipitation and evapotranspiration along with in situ river discharge measurements to estimate TWSC over longer time periods (typically from 1980 to 2016), compatible with climate studies. We performed this task over five major Asian basins, subject to both large climate variability and strong anthropogenic pressure for water resources, and for which long term record of in situ discharge measurements are available. Our SAtellite Water Cycle (SAWC) reconstruction provides TWSC estimates very coherent in terms of seasonal and interannual variations with independent sources of information such as (1) TWSC GRACE-derived observations (over the 2002–2015 period), (2) ISBA-CTRIP model simulations (1980–2015), and (3) multi-satellite inundation extent (1993–2007). This analysis shows the advantages of the use of multiple satellite-derived data sets along with in situ data to perform hydrologically coherent reconstruction of missing water component estimate. It provides a new critical source of information for long term monitoring of TWSC and to better understand their critical role in the global and terrestrial water cycle.

scholarly journals Long-term total water storage change from a Satellite Water Cycle reconstruction over large southern Asian basins

2020 ◽  
Vol 24 (6) ◽  
pp. 3033-3055
Author(s):  
Victor Pellet ◽  
Filipe Aires ◽  
Fabrice Papa ◽  
Simon Munier ◽  
Bertrand Decharme
Keyword(s):  
Climate Variability ◽  
Water Cycle ◽  
Critical Role ◽  
Water Storage ◽  
Anthropogenic Pressure ◽  
Total Water ◽  
Storage Change ◽  
Discharge Measurements

Abstract. The total water storage change (TWSC) over land is a major component of the global water cycle, with a large influence on the climate variability, sea level budget and water resource availability for human life. Its first estimates at a large scale were made available with GRACE (Gravity Recovery and Climate Experiment) observations for the 2002–2016 period, followed since 2018 by the launch of the GRACE-FO (Follow-On) mission. In this paper, using an approach based on the water mass conservation rule, we propose to merge satellite-based observations of precipitation and evapotranspiration with in situ river discharge measurements to estimate TWSC over longer time periods (typically from 1980 to 2016), compatible with climate studies. We performed this task over five major Asian basins, subject to both large climate variability and strong anthropogenic pressure for water resources and for which long-term records of in situ discharge measurements are available. Our Satellite Water Cycle (SAWC) reconstruction provides TWSC estimates very coherent in terms of seasonal and interannual variations with independent sources of information such as (1) TWSC GRACE-derived observations (over the 2002–2015 period), (2) ISBA-CTRIP (Interactions between Soil, Biosphere and Atmosphere CNRM – Centre National de Recherches Météorologiques – Total Runoff Integrating Pathways) model simulations (1980–2015) and (3) the multi-satellite inundation extent (1993–2007). This analysis shows the advantages of the use of multiple satellite-derived datasets along with in situ data to perform a hydrologically coherent reconstruction of a missing water component estimate. It provides a new critical source of information for the long-term monitoring of TWSC and to better understand its critical role in the global and terrestrial water cycle.

Data-driven and physically informed modelling of the Terrestrial Water Storage dynamics 

2021 ◽  
Author(s):  
Karim Douch ◽  
Peyman Saemian ◽  
Nico Sneeuw
Keyword(s):  
Transition Matrix ◽  
Amazon Basin ◽  
Stochastic Matrix ◽  
Water Storage ◽  
Water Volume ◽  
Terrestrial Water Storage ◽  
Total Water ◽  
Monthly Basis ◽  
Terrestrial Water ◽  
Volume Anomaly

<p>The Gravity Recovery and Climate Experiment (GRACE) mission, and its successor GRACE Follow-On, have enabled to map on a monthly basis the Terrestrial Water Storage Anomaly (TWSA) since 2002. This unprecedented capability has provided hydrologists with new observations of the spatiotemporal evolution of TWSA, which have been used, among others, to better constrain numerical runoff models, to characterize empirically the relations between runoff and TWSA, or to simply monitor and quantify groundwater depletions. In this study, we explore the possibility to infer from GRACE observations a physically informed and linear dynamical system that models the intrinsic dynamics of TWSA at sub-basin scales.</p><p>First, we apply a hexagonal binning over the study area and aggregate the total water volume anomaly derived from GRACE data for each bin. Assuming that each bin exchanges water with the others in proportion to its water content, we then reformulate the mass balance equation of the whole basin as a first order matrix differential equation. All the proportionality coefficients encoding the bin exchanges are gathered in an unknown transition matrix to be determined.  Such a transition matrix must satisfy different algebraic properties to be physically consistent and interpretable. In particular, we show that this matrix is necessarily a left stochastic matrix. Finally, we used the time series of total water volume anomaly to estimate this transition matrix by solving an optimization problem on the manifold defined by the aforementioned matrix constraint. This method is applied to the Amazon basin and to mainland Australia respectively, and the predictive performances of the derived dynamical systems are quantified and discussed.</p>

Sign in / Sign up

Export Citation Format

Share Document