Session: B.5 Hydrology
(Convener: )

Title: Land hydrology contributions to sea level rise: quantification of uncertainties in post-processing corrections over land in the JPL mascons
Presenter: Reager, JT
Co-Authors: Gardner, Wiese, Famiglietti, Eicker, Lo

Abstract: Climate-driven changes in land water storage and their contributions to sea level rise have been absent from IPCC sea level budgets owing to observational challenges. Recent advances in the measurement of time variable gravity from space combined with newly reconciled global glacier loss estimates now enable accurate quantification of this term. We find that between 2002 and 2014, climate variability resulted in an additional 2900 +/- 900 Gt of water being stored on land. This gain partially offset water losses from ice sheets, glaciers, and groundwater pumping, slowing the rate of sea level rise by 0.68 +/- 0.30 mm yr-1. These findings highlight the importance of climate-driven changes in land water storage when assigning attribution to decadal changes in sea level.

We apply data from NASA's Gravity Recovery And Climate Experiment (GRACE) satellite mission to assess changes in continental land water storage. We use 140 monthly solutions applying the new Jet Propulsion Laboratory GRACE mascon approach, for the period spanning April 2002 through December 2014. The JPL RL05m mascon solution undergoes several post-processing corrections are applied to the GRACE solutions to correct for known limitations of the GRACE measurements and to remove unwanted signals, including replacing the degree 2, order 0 spherical harmonic coefficients for each month with those estimated from satellite laser ranging, correcting a mean pole trend, adding an estimate of geocenter motion, removing a Glacial Isostatic Adjustment (GIA) signal, removing a glacier change signal, and removing solid earth response to tectonic events. In order to produce a robust estimate of the land hydrology contributions to sea level rise, the uncertainties in each of these corrections much be quantified beyond the formal GRACE error estimates and propagated into the land trend.

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Advances in GRACE Data Assimilation and Related Applications
Presenter: Rodell, Matthew
Co-Authors: S. Kumar, B. Li, A. Getirana, H.K. Beaudoing

Abstract: Here we present recent advances in the assimilation of GRACE data into the Catchment land surface model. We no longer assimilate basin-averaged terrestrial water storage (TWS) anomalies, and instead assimilate 1-degree gridded TWS anomaly fields. This requires accounting for spatially correlated errors, but it preserves the sub-basin scale patterns of TWS variability observed by GRACE. The new results have been incorporated into our weekly drought indicator maps, which concurrently have been upgraded from 0.25 degree to 0.125 degree resolution. We have also tested multi-variate data assimilation, thus integrating GRACE TWS anomalies with satellite derived soil moisture, snow cover, and snow water equivalent. That is the basis for our contributions to the U.S. Global Change Research Program’s National Climate Assessment. Further, we are making progress on global GRACE data assimilation.

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Title: Hydrologic Implications of GRACE Satellite Data in the Colorado River Basin
Presenter: Scanlon, Bridget
Co-Authors: Z. Zhang, H. Save, J. Chen, D. Long, D. Pool, B. Reedy, D. Wolock

Abstract: Use of GRACE (Gravity Recovery and Climate Experiment) satellites for assessing global water resources is rapidly expanding. Here we advance application of GRACE satellites by reconstructing long-term Total Water Storage (TWS) changes from ground-based monitoring and modeling data. We applied the approach to the Colorado River Basin which has experienced multiyear intense droughts at decadal intervals. Estimated TWS declined by 86 km3 during the 1986-1990 drought and by 97 km3 during the 1998-2004 drought, similar to the TWS depletion recorded by GRACE (47 km3) during the 2010-2013 drought. Our analysis indicates that TWS depletion is dominated by reductions in surface reservoir and soil moisture storage in the upper Colorado basin with additional reductions in groundwater storage in the lower basin. Groundwater storage changes are controlled mostly by natural responses to wet and dry cycles and irrigation pumping outside of Colorado River delivery zones based on ground-based water level and gravity data. Water storage changes are controlled primarily by variable water inputs in response to wet and dry cycles rather than increasing water use. Surface reservoir storage evens out supply variability with current reservoir storage representing ~2.5 years of additional water use. This study can be used as a template showing how to extend short-term GRACE TWS records and using all available data on storage components of TWS to interpret GRACE data especially in the context of droughts.

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Title: High Frequency Hydrological Signal Capture Via a Regularized Sliding Window Mascon Time-Variable Gravity Field from GRACE
Presenter: Sakumura, Carly
Co-Authors: S. Bettadpur, H. Save, C. McCullough

Abstract: The Gravity Recovery and Climate Experiment (GRACE) mission has provided an unprecedented global, homogeneous observational dataset of the time variation in terrestrial water storage since 2002. The data product has evolved over this timeline, and it is now possible to produce daily, regularized fields that resolve higher frequency signals and more accurately capture the location and magnitude of time-variation in TWS. The typical GRACE product uses approximately thirty equally weighted days of data to estimate a monthly mean gravity field with 300+ km resolution. Each regularized sliding window gravity field is composed of twenty-one days of observations differentially weighted to optimize the frequency retention while ensuring sufficient observability for a global solution. Tikonov regularization informed by RL05 error is applied in the estimation process to increase the amplitude and localization of signal retention. The information content of these products will be assessed through comparison with high resolution and high fidelity models, independent in-situ datasets, and assimilation into land surface models.

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Title: Monthly and sub-monthly hydrological variability: In-orbit validation by GRACE level 1B observations
Presenter: Eicker, Annette
Co-Authors: A. Springer

Abstract: In this study, we present an approach to validate hydrological model output directly on the level of GRACE level 1B observations by analyzing K-band range-rate residuals. Modeled water mass variations are converted to simulated satellite observations and reduced from the original measurements. This procedure bypasses the downward continuation and filtering steps generally required for water cycle analysis on the basis of gravity field maps. The goal of the study is twofold: (1) we demonstrate the feasibility of using residuals analysis for hydrological model validation in general and (2) we focus on the potential of the approach to investigate the signal content of temporally high-frequent (daily) modeled hydrological mass variations. In addition to the output of three different hydrological process models, we study mass changes computed from two different daily GRACE products. Aspect (2) is not only interesting for model validation, but it can also be important in the context of improving the GRACE de-aliasing concept. Realistically modeled or observed short-term hydrological mass changes may serve as additional de-aliasing product for GRACE and thus contribute to increasing the accuracy and resolution of future GRACE products.

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Title: Monitoring and Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using GRACE Water Storage, Satellite Soil Moisture Data, and In-situ Observations
Presenter: Geruo A
Co-Authors: I. Velicogna, J. Kimball, Y. Kim, A. Colliander, E. Njoku

Abstract: GRACE terrestrial water storage (TWS) provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture (SM) estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply. We use GRACE TWS together with SM data from AMSR-E and AMSR-2 and in-situ groundwater measurements to investigate the supply changes from water components at different depth in relation to satellite based vegetation metrics, including vegetation greenness (NDVI) measures from MODIS and related higher order productivity (GPP) before, during and following the major drought events observed in the continental US for the past decade. We observe consistent trends and significant correlations between monthly time series of TWS, SM, NDVI and GPP. We study how changes in atmosphere moisture stress and coupling of water storage components at different depth impact on the spatial and temporal correlation between TWS, SM and vegetation metrics. In Texas, we find that surface SM and GRACE TWS agree with each other in general, and both capture the underlying water supply constraints to vegetation growth. Triggered by a transit increase in precipitation following the 2011 hydrological drought, vegetation productivity in Texas shows more sensitivity to surface SM than TWS. In the Great Plains, the correspondence between TWS and vegetation productivity is modulated by temperature-induced atmosphere moisture stress and by the coupling between surface soil moisture and groundwater through irrigation.

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Title: Estimating Fine-Resolution Terrestrial Water Storage Changes Over Central Congo Basin By Integrating GRACE, PALSAR, and Altimetry
Presenter: Hyongki, Lee
Co-Authors: H. Jung, T. Yuan, E. Beighley

Abstract: Several studies have been conducted to quantify and characterize terrestrial water storage changes over the Congo’s wetlands, especially focusing on the central Congo Basin, or Cuvette Centrale, where vast wetlands can be found. The annual variations of the surface water storage changes over the wetlands were estimated to range between ~20 km3 to ~30 km3 by multiplying changes of inundated areas from PALSAR ScanSAR with changes of water level changes from Envisat altimetry. By comparison with total storage changes from GRACE, it was revealed that the coarse-resolution (~300 km) GRACE signal is mostly governed by the surface water storage changes. Based on this finding, we then, for the first time, attempted to generate finer-resolution storage change maps by integrating coarse-resolution GRACE data and fine-resolution (~100 m) ScanSAR data. The downscaled storage change maps were then validated with a few upscaled water depth maps (~100 m) which were generated based on spatial variations of water level changes from altimetry, backscattering coefficients from ScanSAR, and vegetation density from MODIS. The comparison indicates that reasonable downscaling can be done up to 40 km by 40 km. The maps were further compared with estimated storage changes from the Hillsope River Routing (HRR) model. Our finer-scale storage change maps revealed significant annual changes of water storages around the proximal floodplains of the Congo mainstem up to 1 km3 over a 40 km by 40 km grid.

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Title: Improving the Performance of Land Surface Models over Varying Hydrologic and Climatic Settings Using GRACE and Remote Sensing Data: Advances and Limitations
Presenter: Ahmed, Mohamed
Co-Authors: M. Sultan (Second), E. Yan (Third)

Abstract: The Gravity Recovery and Climate Experiment (GRACE), along with other relevant field and remote sensing datasets, was used to evaluate the performance of two land surface models (LSMs): CLM4.5-SP and GLDAS-Noah over varying hydrologic and climatic settings in Africa (e.g., arid, semiarid, tropical, subtropical, and Mediterranean). Spatial and temporal analysis of monthly (January 2003 to December 2010) terrestrial water storage (TWS) estimates extracted from GRACE [TWS(GRACE)], CLM4.5-SP [TWS(CLM4.5)], and GLDAS-Noah [TWS(GLDAS)] over the African climatic zones indicates the following: (1) compared to GRACE, LSMs overestimate TWS in winter months and underestimate them in summer months; (2) the amplitude of annual cycle (AAC) of TWS(GRACE) is always higher than that of TWSLSM [AAC: TWS(GRACE) > TWS(GLDAS) > TWS(CLM4.5)]; (3) higher, and statistically significant correlations were observed between TWS(GRACE) and TWS(GLDAS) compared to those between TWS(GRACE) and TWS(CLM4.5); (4) differences in forcing precipitation and temperature datasets for GLDAS-Noah and CLM4.5-SP models are unlikely to be the main cause for the observed discrepancies between TWS(GRACE) and TWS(LSM); and (5) the CLM4.5-SP model overestimates evapotranspiration (ET) values in summer months and underestimates them in winter months compared to ET estimates extracted from field-based (FLUXNET-MTE) and satellite-based (MOD16 and GLEAM) ET measurements. A first-order bias correction was developed and applied to correct the bias in CLM4.5-derived ET, soil moisture, groundwater, and TWS. The bias correction improved the correspondence (i.e., higher correlation and comparable AAC) between TWS(CLM4.5) and TWS(GRACE) over all of the African climatic settings. Current investigations concentrates on testing the performance of the developed methodology over similar hydrologic and climatic settings in Asia, and over additional settings that are absent in Africa (i.e., temperate, polar) and adjusting the adopted methodology accordingly.

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Title: Forecasting GRACE Data Over Africa
Presenter: Sultan, Mohamed
Co-Authors: M. Ahmed (Second), T. Elbayoumi (Third)

Abstract: We adopted a statistical approach that could potentially advance GRACE’s applications and benefits to the GRACE user community at large. The proposed methodology accomplishes the following: (1) fills gaps in GRACE temporal records, (2) minimizes the lag in GRACE data release time by providing near-real time reliable estimates of GRACE data, and (3) forecasts GRACE data six months in advance. Seven African watersheds (Niger, Okavango, Zambezi, Limpopo, Lake Chad, Volta, and East Central Coast) were selected as test sites. Artificial Neural Networks (ANNs) were used to derive relationships between the GRACE data and controlling factors (precipitation, temperature, evapotranspiration, and NDVI) over the selected test sites. ANN is a powerful tool for pattern recognition that does not require a complete understanding of the underlying physical processes. A nonlinear autoregressive model with external input (NARX) was applied. The trained ANNs model (training period: 04/2002 to 10/2013) successfully predicted GRACE data for the period from 05/2015 through 10/2015. The Pearson correlation coefficient (r) throughout the testing period (11/2013 to 04/2015) was found to be 0.98, 0.96, 0.91, 0.79, 0.98, 0.97, and 0.90 for the Niger, Zambezi, Okavango, Limpopo, Lake Chad, Volta, and East Central Coast basins, respectively. Ongoing research activities are concentrated on: (1) applying the developed methodologies to the remaining African watersheds, (2) understanding the capabilities and the limitations of the advanced methodology, (3) incorporating additional relevant inputs (e.g., climatic indices), and (4) investigating the potential of the developed methodologies for forecasting drought and flooding events.

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Title: Connections between Eco-hydrologic variability and water storage within the Sacramento and San Joaquin river basins
Presenter: Ukasha, Muhammad
Co-Authors: J.A. Ramirez

Abstract: In order to estimate groundwater depletion rates at high spatial and temporal resolution, GRACE Terrestrial Water Storage Anomalies (TWSA) and their time derivative (i.e. dTWSA/dt) must be downscaled to the appropriate spatial and temporal scales. A potential approach for such downscaling is to determine relationships between the variability of eco-hydrological variables (e.g., NDVI, LAI, etc.) and water storage. Observations of monthly Terrestrial Water Storage Anomalies (TWSA) monitored by the GRACE satellite mission and their time derivate (i.e. dTWSA/dt) were correlated with monthly NDVI and LAI at time lags from -6 months to +6 months for the combined Sacramento and San Joaquin river basins. Linear correlation analysis shows that both TWSA and dTWSA/dt are better correlated with LAI than with NDVI. TWSA shows a maximum correlation of 0.48 with NDVI at the lag of +1 month (i.e. current month TWSA shows a correlation of 0.48 with next month’s NDVI). On the other hand, TWSA shows a maximum correlation of 0.69 with LAI at the lag of +3 months. NDVI and dTWSA/dt have their strongest mutual correlation at +4 month lag having a value of 0.53. However, the strongest correlation of dTWSA/dt with LAI occurs at a lag of -1 month (i.e. previous month LAI and current month TWSA) having a correlation strength of -0.75. Additionally, results of non-linear correlation analysis at different time lags will be presented. The results of this analysis will help to identify the best eco-hydrological variable to downscale TWSA and/or dTWSA/dt.

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Title: The influence of GRACE on Community Land Model version 5 development
Presenter: Swenson, Sean
Co-Authors:

Abstract: As part of the development of version 5 of the Community Land Model (CLM), multiple parameterization changes have been implemented in CLM that have improved the agreement between CLM and GRACE total water storage (TWS) estimates. In this talk I will compare CLM TWS to GRACE TWS in a number of regions around the world, and discuss some of the model changes responsible for the decreased model bias. In addition, I will discuss the sensitivity of simulated water storage to parameter perturbations, and implications for uncertainty in applications that synthesize GRACE data and model simulations.

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