ALBERT

Description: 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 94 km 3 during 1986–1990 and by 102 km 3 during 1998–2004, similar to the TWS depletion recorded by GRACE (47 km 3 ) during 2010–2013. 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 buffers supply variability with current reservoir storage representing ∼2.5 years of available 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 within the context of droughts. This article is protected by copyright. All rights reserved.

Description: Abstract The scarcity of groundwater storage change data at the global scale hinders our ability to monitor groundwater resources effectively. In this study, we assimilate a state‐of‐the‐art terrestrial water storage (TWS) product derived from Gravity Recovery and Climate Experiment (GRACE) satellite observations into NASA's Catchment land surface model (CLSM) at the global scale, with the goal of generating groundwater storage time series that are useful for drought monitoring and other applications. Evaluation using in situ data from nearly 4,000 wells shows that GRACE data assimilation improves the simulation of groundwater, with estimation errors reduced by 36% and 10% and correlation improved by 16% and 22% at the regional and point scales, respectively. The biggest improvements are observed in regions with large interannual variability in precipitation, where simulated groundwater responds too strongly to changes in atmospheric forcing. The positive impacts of GRACE data assimilation are further demonstrated using observed low flow data. CLSM and GRACE data assimilation performance is also examined across different permeability categories. The evaluation reveals that GRACE data assimilation fails to compensate for the lack of a groundwater withdrawal scheme in CLSM when it comes to simulating realistic groundwater variations in regions with intensive groundwater abstraction. CLSM simulated groundwater correlates strongly with 12‐month precipitation anomalies in low and mid‐latitude areas. A groundwater drought indicator based on GRACE data assimilation generally agrees with other regional‐scale drought indicators, with discrepancies mainly in their estimated drought severity.

Description: Increasing interest in use of GRACE satellites and a variety of new products to monitor changes in total water storage (TWS) underscores the need to assess the reliability of output from different products. The objective of this study was to assess skills and uncertainties of different approaches for processing GRACE data to restore signal losses caused by spatial filtering based on analysis of 1°×1° grid scale data and in 60 river basins globally. Results indicate that scaling factors from six LSMs, including GLDAS-1 four models (Noah2.7, Mosaic, VIC, and CLM 2.0), CLM 4.0, and WGHM, are similar over most of humid, sub-humid, and high-latitude regions but can differ by up to 100% over arid and semi-arid basins and areas with intensive irrigation. Temporal variability in scaling factors is generally minor at the basin scale except in arid and semi-arid regions, but can be appreciable at the 1°×1° grid scale. Large differences in TWS anomalies from three processing approaches (scaling factor, additive, and multiplicative corrections) were found in arid and semi-arid regions, areas with intensive irrigation, and relatively small basins (e.g., ≤ 200,000km 2 ). Furthermore, TWS anomaly products from gridded data with CLM4.0 scaling factors and the additive correction approach more closely agree with WGHM output than the multiplicative correction approach. This comprehensive evaluation of GRACE processing approaches should provide valuable guidance on applicability of different processing approaches with different climate settings and varying levels of irrigation. This article is protected by copyright. All rights reserved.

Description: Various remote sensing-based terrestrial evapotranspiration (ET) models have been developed during the past four decades. These models vary in conceptual and mathematical representations of the physics, consequently leading to different performances. Examination of uncertainties associated with limitations in model physics will be useful for model selection and improvement. Here, three dual-source remote sensing ET models (i.e. the Hybrid dual-source scheme and Trapezoid framework-based ET Model (HTEM), the Two-Source Energy Balance (TSEB) model and the MOD16 ET algorithm) using ASTER images were compared during the MUSOEXE-12 campaign in the Heihe River Basin in Northwest China, aiming to better understand the differences in model physics that potentially lead to differences in model performance. Model results were firstly compared against observations from a dense network of eddy covariance towers and isotope-based evaporation (E) and transpiration (T) partitioning. Results show that HTEM outperformed the other two models in simulating ET and its partitioning, whereas MOD16 performed worst (i.e. ET root-mean-square errors are 42.3 W/m 2 (HTEM), 49.8 W/m 2 (TSEB), and 95.3 W/m 2 (HTEM)). On to model limitations, HTEM tends to underestimate ET under high advection due mostly to the underestimation of temperatures for the wet edge in its trapezoidal space. For TSEB, large uncertainties occur in determining the initial Priestley-Taylor coefficient and the iteration procedure for ET partitioning, leading to overestimation/underestimation of T/E in most cases, particularly over sparse vegetation. Primary use of meteorological data for MOD16 does not effectively capture the soil moisture restriction on ET, and therefore results in unreasonable spatial ET patterns. This article is protected by copyright. All rights reserved.

Description: There is increasing interest in using Gravity Recovery and Climate Experiment (GRACE) satellite data to remotely monitor groundwater storage variations; however, comparisons with ground-based well data are limited but necessary to validate satellite data processing, especially when the study area is close to or below the GRACE footprint. The Central Valley is a heavily irrigated region with large-scale groundwater depletion during droughts. Here we compare updated estimates of groundwater storage changes in the California Central Valley using GRACE satellites with storage changes from groundwater level data. A new processing approach was applied that optimally uses available GRACE and water balance component data to extract changes in groundwater storage. GRACE satellites show that groundwater depletion totaled ∼31.0 ± 3.0 km3 for Groupe de Recherche de Geodesie Spatiale (GRGS) satellite data during the drought from October 2006 through March 2010. Groundwater storage changes from GRACE agreed with those from well data for the overlap period (April 2006 through September 2009) (27 km3 for both). General correspondence between GRACE and groundwater level data validates the methodology and increases confidence in use of GRACE satellites to monitor groundwater storage changes.

Description: A tracer test was performed at the Rifle Integrated Field Research Challenge site to assess the effect of addition of bicarbonate on U(VI) desorption from contaminated sediments in the aquifer and to compare equilibrium and rate-limited reactive transport model descriptions of mass transfer limitations on desorption. The tracer test consisted of injection of a 37 mM NaHCO3 solution containing conservative tracers followed by down-gradient sampling of groundwater at various elevations and distances from the point of injection. Breakthrough curves show that dissolved U(VI) concentrations increased 1.2–2.6-fold above background levels, resulting from increases in bicarbonate alkalinity (from injectate solution) and Ca concentrations (from cation exchange). In general, more U(VI) was mobilized in shallower zones of the aquifer, where finer-grained sediments and higher solid phase U content were found compared to deeper zones. An equilibrium-based reactive transport model incorporating a laboratory-based surface complexation model derived from the same location predicted the general trends in dissolved U(VI) during the tracer test but greatly overpredicted the concentrations of U(VI), indicating that the system was not at equilibrium. Inclusion of a multirate mass transfer model successfully simulated the nonequilibrium desorption behavior of U(VI). Local sediment properties such as sediment texture (weight percent

Description: The surface energy balance algorithm for land (SEBAL) has been designed and widely used (and misused) worldwide to estimate evapotranspiration across varying spatial and temporal scales using satellite remote sensing over the past 15 yr. It is, however, beset by visual identification of a hot and cold pixel to determine the temperature difference (dT) between the surface and the lower atmosphere, which is assumed to be linearly correlated with surface radiative temperature (Trad) throughout a scene. To reduce ambiguity in flux estimation by SEBAL due to the subjectivity in extreme pixel selection, this study first demonstrates that SEBAL is of a rectangular framework of the contextual relationship between vegetation fraction (fc) and Trad, which can distort the spatial distribution of heat flux retrievals to varying degrees. End members of SEBAL were replaced by a trapezoidal framework of the fc-Trad space in the modified surface energy balance algorithm for land (M-SEBAL). The warm edge of the trapezoidal framework is determined by analytically deriving temperatures of the bare surface with the largest water stress and the fully vegetated surface with the largest water stress implicit in both energy balance and radiation budget equations. Areally averaged air temperature (Ta) across a study site is taken to be the cold edge of the trapezoidal framework. Coefficients of the linear relationship between dT and Trad can vary with fc but are assumed essentially invariant for the same fc or within the same fc class in M-SEBAL. SEBAL and M-SEBAL are applied to the soil moisture-atmosphere coupling experiment (SMACEX) site in central Iowa, U.S. Results show that M-SEBAL is capable of reproducing latent heat flux in terms of an overall root-mean-square difference of 41.1 W m−2 and mean absolute percentage difference of 8.9% with reference to eddy covariance tower-based measurements for three landsat thematic mapper/enhanced thematic mapper plus imagery acquisition dates in 2002. The retrieval accuracy of SEBAL is generally lower than M-SEBAL, depending largely on the selected extremes. Spatial distributions of heat flux retrievals from SEBAL are distorted to a certain degree due to its intrinsic rectangular framework.

Description: A key challenge in managing semiarid basins, such as in the Murray-Darling in Australia, is to balance the trade-offs between the net benefits of allocating water for irrigated agriculture, and other uses, versus the costs of reduced surface flows for the environment. Typically, water planners do not have the tools to optimally and dynamically allocate water among competing uses. We address this problem by developing a general stochastic, dynamic programming model with four state variables (the drought status, the current weather, weather correlation, and current storage) and two controls (environmental release and irrigation allocation) to optimally allocate water between extractions and in situ uses. The model is calibrated to Australia's Murray River that generates: (1) a robust qualitative result that “pulse” or artificial flood events are an optimal way to deliver environmental flows over and above conveyance of base flows; (2) from 2001 to 2009 a water reallocation that would have given less to irrigated agriculture and more to environmental flows would have generated between half a billion and over 3 billion U.S. dollars in overall economic benefits; and (3) water markets increase optimal environmental releases by reducing the losses associated with reduced water diversions.

Description: Proliferation of evapotranspiration (ET) products warrants comparison of these products. The study objective was to assess uncertainty in ET output from four land surface models (LSMs), Noah, Mosaic, VIC, and SAC in NLDAS-2, two remote sensing-based products, MODIS and AVHRR, and GRACE-inferred ET from a water budget with precipitation from PRISM, monitored runoff, and total water storage change (TWSC) from GRACE satellites. The three cornered hat method, which does not require a priori knowledge of the true ET value, was used to estimate ET uncertainties. In addition, TWSC or total water storage anomaly (TWSA) from GRACE was compared with water budget estimates of TWSC from a flux-based approach or TWSA from a storage-based approach. The analyses were conducted using data from three regions (humid – arid) in the South Central US as case studies. Uncertainties in ET are lowest in LSM ET (~5 mm/month), moderate in MODIS- or AVHRR-based ET (10 – 15 mm/month), and highest in GRACE-inferred ET (20 – 30 mm/month). There is a tradeoff between spatial resolution and uncertainty, with lower uncertainty in the coarser-resolution LSM ET (~14 km) relative to higher uncertainty in the finer-resolution (~ 1 ‒ 8 km) RS ET. Root-mean-square (RMS) of uncertainties in water budget estimates of TWSC is about half of RMS of uncertainties in GRACE-derived TWSC for each of the regions. Future ET estimation should consider a hybrid approach that integrates strengths of LSMs and satellite-based products to constrain uncertainties.

Description: Abstract The precipitation partitioning between evapotranspiration (ET) and runoff (R) at the land surface is controlled by atmospheric boundary layer and terrestrial hydrological processes. These processes in land surface models are manifested primarily as stomatal conductance, soil moisture limitation factor to transpiration (β‐factor), turbulence, and runoff generation. What are the sensitivities of precipitation partitioning to the parameterizations of these processes? To address this overarching question, the annual and seasonal means of ET and R over the conterminous United States were simulated using 48 configurations of the Noah land surface model with multiparameterization options (Noah‐MP). The Sobol' total sensitive index was used to quantify the sensitivity of ET and R to the parameterizations of the four processes mentioned above. Results show that the sensitivities of the annual means depend on climatic conditions and the interplay between ET and R plays an important role. In humid regions, precipitation is mostly partitioned into R, whereas the simulations can be more sensitive to ET's parameterizations. In arid regions, ET accounts for the major partition, whereas the simulations can be more sensitive to the runoff parameterization. Seasonal means exhibit different sensitivities from the annual means. The seasonal mean ET is more sensitive to ET's parameterizations, and R is more sensitive to the runoff parameterization. The β‐factor, which is neglectable for the annual means, is important for summer‐time ET. Mediated by the terrestrial water storage memories, ET interplays R across seasons. The winter‐time R is still sensitive to the stomatal conductance that only modulates growing‐season ET.