[1] A long-standing challenge for hydrologists has been a lack of observational data on global-scale basin hydrological behavior. With observations from NASA’s Gravity Recovery and Climate Experiment (GRACE) mission, hydrologists are now able to study terrestrial water storage for large river basins (>200,000 km2), with monthly time resolution. Here we provide results of a time series model of basin-averaged GRACE terrestrial water storage anomaly and Global Precipitation Climatology Project precipitation for the world’s largest basins. We address the short (10 year) length of the GRACE record by adopting a parametric spectral method to calculate frequency-domain transfer functions of storage response to precipitation forcing and then generalize these transfer functions based on large-scale basin characteristics, such as percent forest cover and basin temperature. Among the parameters tested, results show that temperature, soil water-holding capacity, and percent forest cover are important controls on relative storage variability, while basin area and mean terrain slope are less important. The derived empirical relationships were accurate (0.54 ≤ Ef ≤ 0.84) in modeling global-scale water storage anomaly time series for the study basins using only precipitation, average basin temperature, and two land-surface variables, offering the potential for synthesis of basin storage time series beyond the GRACE observational period. Such an approach could be applied toward gap filling between current and future GRACE missions and for predicting basin storage given predictions of future precipitation.

[1] We perform a multi-sensor analysis of water storage and surface height variations of the Caspian Sea, from mid-2002 through 2006. Data from three satellite missions (GRACE, Jason-1, and Aqua) are used to examine the relationship between changes in spatially averaged sea surface height (SSH) and water storage in and around the Caspian Sea. Two composite time series are constructed to represent the mass change signal, the first by removing a model of nearby hydrological signals from the GRACE time series, and the second by subtracting a MODIS SST-based estimate of thermal expansion from the Jason-1 time series. The composite time series agree well (rms difference = 5.2 cm), and a positive trend is seen in both the GRACE (4.5 ± 0.7 cm/yr) and Jason (3.2 ± 0.3 cm/yr) composite time series. This analysis provides an indirect means of validating these data at regional spatial and monthly temporal scales.

[1] The Palmer Drought Severity Index (PDSI) has been widely used to study aridity changes in modern and past climates. Efforts to address its major problems have led to new variants of the PDSI, such as the self-calibrating PDSI (sc_PDSI) and PDSI using improved formulations for potential evapotranspiration (PE), such as the Penman-Monteith equation (PE_pm) instead of the Thornthwaite equation (PE_th). Here I compare and evaluate four forms of the PDSI, namely, the PDSI with PE_th (PDSI_th) and PE_pm (PDSI_pm) and the sc_PDSI with PE_th (sc_PDSI_th) and PE_pm (sc_PDSI_pm) calculated using available climate data from 1850 to 2008. Our results confirm previous findings that the choice of the PE only has small effects on both the PDSI and sc_PDSI for the 20th century climate, and the self-calibration reduces the value range slightly and makes the sc_PDSI more comparable spatially than the original PDSI. However, the histograms of the sc_PDSI are still non-Gaussian at many locations, and all four forms of the PDSI show similar correlations with observed monthly soil moisture (r = 0.4–0.8) in North America and Eurasia, with historical yearly streamflow data (r = 0.4–0.9) over most of the world's largest river basins, and with GRACE (Gravity Recovery and Climate Experiment) satellite-observed water storage changes (r = 0.4–0.8) over most land areas. All the four forms of the PDSI show widespread drying over Africa, East and South Asia, and other areas from 1950 to 2008, and most of this drying is due to recent warming. The global percentage of dry areas has increased by about 1.74% (of global land area) per decade from 1950 to 2008. The use of the Penman-Monteith PE and self-calibrating PDSI only slightly reduces the drying trend seen in the original PDSI. The percentages of dry and wet areas over the global land area and six select regions are anticorrelated (r = −0.5 to −0.7), but their long-term trends during the 20th century do not cancel each other, with the trend for the dry area often predominating over that for the wet area, resulting in upward trends during the 20th century for the areas under extreme (i.e., dry or wet) conditions for the global land as a whole (∼1.27% per decade) and the United States, western Europe, Australia, Sahel, East Asia, and southern Africa. The recent drying trends are qualitatively consistent with other analyses and model predictions, which suggest more severe drying in the coming decades.

[1] The Murray-Darling Basin in southeast Australia is experiencing one of the most severe droughts observed recently in the world, driven by several years of rainfall deficits and record high temperatures. This paper provides new basin-scale observations of the multiyear drought, integrated to a degree rarely achieved on such a large scale, to assess the response of water resources and the severity of the drought. A combination of Gravity Recovery and Climate Experiment (GRACE) data with in situ and modeled hydrological data shows the propagation of the water deficit through the hydrological cycle and the rise of different types of drought. Our observations show the rapid drying of soil moisture and surface water storages, which reached near-stationary low levels only ∼2 years after the onset of the drought in 2001, with a loss of ∼80 and ∼12 km3 between January 2001 and January 2003, respectively. The multiyear drought has led to the almost complete drying of surface water resources which account for most of the water used for irrigation and domestic purposes. High correlation between observed groundwater variations and GRACE data substantiates the persistent reduction in groundwater storage, with groundwater levels still declining 6 years after the onset of the drought (groundwater loss of ∼104 km3 between 2001 and 2007). The hydrological drought continues even though the region returned to average annual rainfall during 2007.

[1] In this study we estimate a time series of regional groundwater anomalies by combining terrestrial water storage estimates from the Gravity Recovery and Climate Experiment (GRACE) satellite mission with in situ soil moisture observations from the Oklahoma Mesonet. Using supplementary data from the Department of Energy's Atmospheric Radiation Measurement (DOE ARM) network, we develop an empirical scaling factor with which to relate the soil moisture variability in the top 75 cm sampled by the Mesonet sites to the total variability in the upper 4 m of the unsaturated zone. By subtracting this estimate of the full unsaturated zone soil moisture anomalies, we arrive at a time series of groundwater anomalies, spatially averaged over a region approximately 280,000 km2 in area. Results are compared to observed well level data from a larger surrounding region, and show consistent phase and relative inter-annual variability.

[1] Global mean sea level (GMSL) dropped by 5 mm between the beginning of 2010 and mid 2011. This drop occurred despite the background rate of rise, 3 mm per year, which dominates most of the 18-year record observed by satellite altimeters. Using a combination of satellite andin situdata, we show that the decline in ocean mass, which explains the sea level drop, coincides with an equivalent increase in terrestrial water storage, primarily over Australia, northern South America, and Southeast Asia. This temporary shift of water from the ocean to land is closely related to the transition from El Nino conditions in 2009/10 to a strong 2010/11 La Nina, which affected precipitation patterns world-wide.

[1] A reliable snow water equivalent (SWE) product is critical for climate and hydrology studies in Arctic regions. Passive microwave sensors aboard satellites provide a capability of observing global SWE and have produced many SWE datasets. However, these datasets have significant errors in boreal forest regions and where snowpack is deep or wet. The Gravity Recovery and Climate Experiment (GRACE) satellites are measuring changes in terrestrial water storage (TWS), of which snow mass is the primary component in winter Arctic river basins. This paper shows SWE can be derived from GRACE TWS change in regions where the ground is not covered by snow in a summer month if accurate changes in below-ground water storage (including soil water and groundwater) can be provided by a land surface model. Based on gravity change, the GRACE-derived SWE estimates are not affected by the boreal forest canopy and are more accurate in deep snow regions than microwave retrievals. The paper also discusses the uncertainties in the SWE retrievals.

We examine the relative contributions of root zone soil moisture (SM) and groundwater (GW) storage to trends and interannual variability in total water storage (TWS) from essentially the entire Gravity Recovery and Climate Experiment (GRACE) record (2003–2016). Our study region is the Eastern United States where GW generally is shallow, and we use observations and simulations from a suite of land surface models (LSMs) where observations are not available. We first consider Illinois, which has a long‐term network of SM sensors and observation wells. We assessed the uncertainties in GRACE TWS in comparison with the observation‐based TWS using observed SM, well‐derived GW, and model‐reconstructed snow water equivalent. We evaluated LSM SM compared with observations over Illinois; generally good agreement encouraged us to use the LSM‐ensemble average SM, well‐derived GW, and Snow Data Assimilation System snow water equivalent over the entire Eastern United States to examine the relative contribution of storage components to GRACE TWS over this larger domain. Taken together, the three components explained 2%–85% of interannual variability in GRACE TWS across the 2‐digit Hydrologic Unit Code regions. Root zone SM was the dominant contributor to the interannual variability (but not trends) of GRACE TWS over much of the Eastern United States. We also compared three independent approaches to estimating GW: well data, baseflow observations, and GRACE. Despite much smaller magnitudes of variation, baseflow‐derived GW correlated more highly with well‐derived GW over the eastern‐most and Upper Mississippi regions, while GRACE‐derived GW matched better with well‐derived GW over the remaining regions.

We combine soil moisture (SM) data from AMSR-E and AMSR-2, and changes in terrestrial water storage (TWS) from time-variable gravity data from GRACE to delineate and characterize the evolution of drought and its impact on vegetation growth. GRACE-derived TWS provides spatially continuous observations of changes in overall water supply and regional drought extent, persistence and severity, while satellite-derived SM provides enhanced delineation of shallowdepth soil water supply. Together these data provide complementary metrics quantifying available plant water supply. We use these data to investigate the supply changes from water components at different depths in relation to satellite-based enhanced vegetation index (EVI) and gross primary productivity (GPP) from MODIS and solar-induced fluorescence (SIF) from GOME-2, during and following major drought events observed in the state of Texas, USA and its surrounding semiarid area for the past decade. We find that in normal years the spatial pattern of the vegetation–moisture relationship follows the gradient in mean annual precipitation. However since the 2011 hydrological drought, vegetation growth shows enhanced sensitivity to surface SM variations in the grassland area located in central Texas, implying that the grassland, although susceptible to drought, has the capacity for a speedy recovery. Vegetation dependency on TWS weakens in the shrub-dominated west and strengthens in the grassland and forest area spanning from central to eastern Texas, consistent with changes in water supply pattern. We find that in normal years GRACE TWS shows strong coupling and similar characteristic time scale to surface SM, while in drier years GRACE TWS manifests stronger persistence, implying longer recovery time and prolonged water supply constraint on vegetation growth. The synergistic combination of GRACE TWS and surface SM, along with remote-sensing vegetation observations provides new insights into drought impact on vegetation–moisture relationship, and unique information regarding vegetation resilience and the recovery of hydrological drought.

We analyse data from seven superconducting gravimeter (SG) stations in Europe from 2002 to 2007 from the Global Geodynamics Project (GGP) and compare seasonal variations with data from GRACE and several global hydrological models—GLDAS, WGHM and ERA-Interim. Our technique is empirical orthogonal function (EOF) decomposition of the fields that allows for the inherent incompatibility of length scales between ground and satellite observations. GGP stations below the ground surface pose a problem because part of the attraction from soil moisture comes from above the gravimeter, and this gives rise to a complex (mixed) gravity response. The first principle component (PC) of the EOF decomposition is the main indicator for comparing the fields, although for some of the series it accounts for only about 50per cent of the variance reduction. PCs for GRACE solutions RL04 from CSR and GFZ are filtered with a cosine taper (degrees 20–40) and a Gaussian window (350km). Significant differences are evident between GRACE solutions from different groups and filters, though they all agree reasonably well with the global hydrological models for the predominantly seasonal signal. We estimate the first PC at 10-d sampling to be accurate to 1 μGal for GGP data, 1.5 μGal for GRACE data and 1 μGal between the three global hydrological models. Within these limits the CNES/GRGS solution and ground GGP data agree at the 79per cent level, and better when the GGP solution is restricted to the three above-ground stations. The major limitation on the GGP side comes from the water mass distribution surrounding the underground instruments that leads to a complex gravity effect. To solve this we propose a method for correcting the SG residual gravity series for the effects of soil moisture above the station.

Water storage depletion is a worsening hydrological problem that limits agricultural production in especially arid/semi-arid regions across the globe. Quantifying water storage dynamics is critical for developing water resources management strategies that are sustainable and protective of the environment. This study uses GRACE (Gravity Recovery and Climate Experiment), GLDAS (Global Land Data Assimilation System) and measured groundwater data products to quantify water storage in Western Jilin (a proxy for semi-arid wetland ecosystems) for the period from January 2002 to December 2009. Uncertainty/bias analysis shows that the data products have an average error <10% (p < 0.05). Comparisons of the storage variables show favorable agreements at various temporal cycles, with R(2) = 0.92 and RMSE = 7.43 mm at the average seasonal cycle. There is a narrowing soil moisture storage change, a widening groundwater storage loss, and an overall storage depletion of 0.85 mm/month in the region. There is possible soil-pore collapse, and land subsidence due to storage depletion in the study area. Invariably, storage depletion in this semi-arid region could have negative implications for agriculture, valuable/fragile wetland ecosystems and people's livelihoods. For sustainable restoration and preservation of wetland ecosystems in the region, it is critical to develop water resources management strategies that limit groundwater extraction rate to that of recharge rate.

Water storage change has implications not only for the hydrological cycle, but also for sustainable water resource management in especially semi-arid river basins. Satellite/remote sensing techniques have gained increasing application in monitoring basin and regional hydrological processes in recent decades. In this study, the latest version of GRACE (Gravity Recovery and Climate Experiment) is used to estimate total water storage change in the Hai River basin (HRB) of Northern China for the period January 2003 to December 2006. Time-series comparisons show a good agreement between the estimated storage change from the GRACE satellite data and in situ hydrological measurement data at especially the seasonal cycle with R = 0.82 and RMSE = 17.25 mm. The good agreement suggests that GRACE detects storage change in the 318 866 km2 HRB study area. It also implies that the in situ hydrological measurements of soil moisture and groundwater sufficiently characterise storage change in the semi-arid river basin. Change in soil moisture storage is less than that in saturated storage, suggesting that storage depletion in the basin is mainly in the saturated zone. Both the GRACE and hydrological measurement data indicate storage loss in the range of 12.72 to 23.76 mm/yr – a phenomenon that has been detected in previous studies in the basin. GRACE hydrology data could therefore be handy in monitoring storage dynamics and water availability in the study area. As GRACE data are available for virtually every region of the world, their application in conjunction with hydrological models could improve hydrological studies. This may lead not only to water balance closures, but also to sustainable water resource management at basin to regional scale.

Water resources play a vital role in ecosystem stability, human survival, and social development in drylands. Human activities, such as afforestation and irrigation, have had a large impact on the water cycle and vegetation in drylands over recent years. The Badain Jaran Desert (BJD) is one of the driest regions in China with increasing human activities, yet the connection between human management and the ecohydrology of this area remains largely unclear. In this study, we firstly investigated the ecohydrological dynamics and their relationship across different spatial scales over the BJD, using multi-source observational data from 2001 to 2014, including: total water storage anomaly (TWSA) from Gravity Recovery and Climate Experiment (GRACE), normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS), lake extent from Landsat, and precipitation from in situ meteorological stations. We further studied the response of the local hydrological conditions to large scale vegetation and climatic dynamics, also conducting a change analysis of water levels over four selected lakes within the BJD region from 2011. To normalize the effect of inter-annual variations of precipitation on vegetation, we also employed a relationship between annual average NDVI and annual precipitation, or modified rain-use efficiency, termed the RUEmo. A focus of this study is to understand the impact of the increasing planted vegetation on local ecohydrological systems over the BJD region. Results showed that vegetation increases were largely found to be confined to the areas intensely influenced by human activities, such as croplands and urban areas. With precipitation patterns remaining stable during the study period, there was a significant increasing trend in vegetation greenness per unit of rainfall, or RUEmo over the BJD, while at the same time, total water storage as measured by satellites has been continually decreasing since 2003. This suggested that the increased trend in vegetation and apparent increase in RUEmo can be attributed to the extraction of ground water for human-planted irrigated vegetation. In the hinterland of the BJD, we identified human-planted vegetation around the lakes using MODIS observations and field investigations. Four lake basins were chosen to validate the relationship between lake levels and planted vegetation. Our results indicated that increasing human-planted vegetation significantly increased the water loss over the BJD region. This study highlights the value of combining observational data from space-borne sensors and ground instruments to monitor the ecohydrological dynamics and the impact of human activities on water resources and ecosystems over the drylands.

Traditional numerical models usually use extensive observed hydraulic-head data as calibration targets. However, this calibration process is not applicable in remote areas with limited or no monitoring data. This study presents an approach to calibrate a large-scale groundwater flow model using the monthly Gravity Recovery and Climate Experiment (GRACE) satellite data, which have been available globally on a spatial grid of 1° in the geographic coordinate system since 2002. A groundwater storage anomaly isolated from the terrestrial water storage (TWS) anomaly is converted into hydraulic head at the center of the grid, which is then used as observed data to calibrate a numerical model to estimate aquifer hydraulic conductivity. The aquifer system in the remote and hyperarid Qaidam Basin, China, is used as a case study to demonstrate the applicability of this approach. A groundwater model using FEFLOW is constructed for the Qaidam Basin and the GRACE-derived groundwater storage anomaly over the period 2003–2012 is included to calibrate the model, which is done using an automatic estimation method (PEST). The calibrated model is then run to output hydraulic heads at three sites where long-term hydraulic head data are available. The reasonably good fit between the calculated and observed hydraulic heads, together with the very similar groundwater storage anomalies from the numerical model and GRACE data, demonstrate that this approach is generally applicable in regions of groundwater data scarcity.Résumé Les modèles numériques traditionnels utilisent de nombreuses données piézométriques observées pour leur calage. Toutefois, cette procédure de calage n’est pas applicable pour les régions éloignées où les mesures sont rares ou inexistantes. Cette étude présente une approche pour caler un modèle d’écoulement souterrain à grande échelle en utilisant les données mensuelles du satellite d’enregistrement gravimétrique et d’étude de climat (GRACE), disponibles sur une grille spatiale de 1° dans le système de coordonnées géographiques depuis 2002. Une anomalie de stockage d’eau souterraine isolée de l’anomalie terrestre de stockage d’eau (TWS) est convertie en cote piézométrique au centre de la maille de la grille, et est utilisée comme donnée d’observation pour caler un modèle numérique afin d’estimer la conductivité hydraulique de l’aquifère. Le système aquifère du bassin éloigné et hyperaride de Qaidam, Chine, est utilisé comme cas d’étude pour démontrer la faisabilité de cette approche. FEFLOW est utilisé pour modéliser les écoulements souterrains du bassin de Qaidam. L’anomalie de stockage d’eau souterraine déduite des données de GRACE sur la période 2003–2012 est utilisée pour caler le modèle, à partir d’une méthode d’estimation automatique des paramètres (PEST). Le modèle calé simule ensuite les niveaux piézométriques de trois sites pour lesquels de longues séries chronologiques piézométriques observées sont disponibles. La relativement bonne correspondance entre les niveaux piézométriques calculés et observés, ainsi que la similitude entre les anomalies de stockage d’eau souterraine du modèle numérique et de celles de GRACE, démontrent que cette approche est généralement applicable pour les régions pauvres en données sur les eaux souterraines.ResumenLos modelos numéricos tradicionales habitualmente utilizan una gran cantidad de datos observados de la carga hidráulica como patrones de calibración. Sin embargo, este proceso de calibración no es aplicable en áreas remotas con datos de monitoreo limitados o no existentes. Este estudio presenta un enfoque para calibrar un modelo de flujo de agua subterránea a gran escala usando los datos satelitales mensuales de Gravity Recovery and Climate Experiment (GRACE), que han estado disponibles globalmente a nivel mundial con una malla espacial de 1° en el sistema de coordenadas geográficas desde 2002. Una anomalía aislado del almacenamiento de agua subterránea a partir de la anomalía del almacenamiento de agua terrestre (TWS) fue convertida en una carga hidráulica en el centro de la malla, la cual es luego usada como un dato observado para calibrar un modelo numérico para estimar la conductividad hidráulica del acuífero. Se usó un sistema acuífero en la remota e hiperárida cuenca de Qaidam, China, como un caso de estudio para demostrar la aplicabilidad de este enfoque. Se construyó un modelo de agua subterránea usando FEFLOW para la cuenca de Qaidam y la anomalía del almacenamiento de agua subterránea proveniente del GRACE durante el período 2003–2012 se incluyó para calibrar el modelo, el cual es usado como un método de estimación automático (PEST). El modelo calibrado es luego corrido para obtener las cargas hidráulicas de salida en tres sitios donde los datos a largo plazo de las cargas hidráulicas están disponibles. El razonable buen ajuste entre las cargas hidráulicas calculadas y observadas, conjuntamente con anomalías muy similares del almacenamiento del agua subterránea a partir del modelo numérico y de los datos GRACE, demostraron que esta aproximación es generalmente aplicable en regiones que presentan escasez de datos de agua subterránea.摘要传统的地下水数值模型采用大量的地下水监测数据作为拟合目标。然而,这种方法在有很少甚至没有地下水观测数据的偏远地区难以应用。本研究提出了一种利用重力恢复和气候实验卫星数据 (GRACE)校准大尺度地下水流数值模型的方法。该数据是自2002年以来发布,其时间尺度为1个月,空间尺度为1度,可免费下载的。提出的方法中,先将陆地水储量(TWS) 推算的地下水储量变异数据转化为相应网格中心位置的水头值,然后将这些值作为数值模型参数率定时的拟合目标。本研究以偏远的极端干旱的中国柴达木盆地为例来展示该方法的可行性。本研究利用FEFLOW软件在柴达木盆地建立了地下水流数值模型,并用2003–2012年反演的地下水储量变异数据用于模型校准,其中采用了自动参数估计方法 (PEST)。经过校准的模型模拟的与GRACE反演的地下水储量变异数据具有较好的相似性,而且在三个具有长期地下水位观测位置的模拟和监测值具有吻合较好。这些结果展示了本研究提出的方法可以用于地下水数据缺乏地区的地下水模型校准。ResumoOs modelos numéricos tradicionais normalmente usam longas séries de dados de carga hidráulica como alvos de calibração. No entanto, esse processo de calibração não é aplicável em áreas remotas com dados de monitoramento limitados ou ausentes. Este trabalho apresenta uma abordagem para calibrar um modelo de fluxo subterrâneo de larga escala usando os dados do satélite GRACE, os quais são disponibilizados globalmente numa grade espacial de 1° no sistema de coordenadas geográficas desde 2002. Uma anomalia no armazenamento de água subterrânea isolada da anomalia de armazenamento terrestre (AAT, Armazenamento de Água Terrestre) é convertida em carga hidráulica no centro da grade, que é então usada como dado observado para calibrar um modelo numérico para estimar a condutividade hidráulica do aquífero. O sistema aquífero na remota e hiperárida bacia do Qaidam, China, é usado como estudo de caso para demonstrar a aplicabilidade dessa abordagem. O FEFLOW foi usado para construir um modelo de água subterrânea para a bacia do Qaidam e a anomalia de armazenamento subterrâneo derivada do GRACE referente ao período 2003–2012 é incluída para calibrar o modelo por meio de um método automático de estimativa (PEST). O modelo calibrado é então executado para fornecer cargas hidráulicas em três áreas onde dados de carga hidráulica de longo prazo estão disponíveis. Um ajuste razoavelmente bom entre as cargas observadas e calculadas, juntamente com as anomalias do modelo numérico e dos dados do GRACE bastante similares, demonstram que essa abordagem é, em geral, aplicável em regiões com escassez de dados.

This study presents the first comparison of seasonal groundwater storage (GWS) variations derived from GRACE satellite data with groundwater‐level measurements in the High Plains Aquifer, USA (450,000 km2). Correlation between seasonal GRACE terrestrial water storage (TWS) and the sum of GWS estimated from field measurements (2,700 wells) and soil moisture (SM) simulated by a land surface model is high (R = 0.82). Correlation between GRACE‐derived and measured GWS is also significant (R = 0.58). Seasonal GRACE‐derived TWS and GWS changes were detectable (≥ uncertainty) in 7 and 5 out of 9 monitored periods respectively whereas maximum changes (between winter/spring and summer/fall) in TWS and GWS were detectable in all 5 monitored periods. These results show the potential for GRACE to monitor GWS changes in semiarid regions where irrigation pumpage causes large seasonal GWS variations.

This discussion paper has been under review for the journal Hydrology and Earth System Sciences (HESS). Please refer to the corresponding final paper in HESS. The published article is copyrighted by the author(s) and published by Copernicus Publications on behalf of the European Geosciences Union. The published article can be found at: http://hdl.handle.net/1957/57160

This Report was prepared for and submitted to the Graduate School of the Ohio State University as a dissertation in partial fulfillment of the requirements for the PhD degree.

The purpose of this study is to evaluate the components of the land surface water budget in the four land surface models (Noah, SAC-Sacramento Soil Moisture Accounting Model, (VIC) Variable Infiltration Capacity Model, and Mosaic) applied in the newly implemented National Centers for Environmental Prediction (NCEP) operational and research versions of the North American Land Data Assimilation System version 2 (NLDAS-2). This work focuses on monthly and annual components of the water budget over 12 National Weather Service (NWS) River Forecast Centers (RFCs). Monthly gridded FLUX Network (FLUXNET) evapotranspiration (ET) from the Max-Planck Institute (MPI) of Germany, U.S. Geological Survey (USGS) total runoff (Q), changes in total water storage (dS/dt, derived as a residual by utilizing MPI ET and USGS Q in the water balance equation), and Gravity Recovery and Climate Experiment (GRACE) observed total water storage anomaly (TWSA) and change (TWSC) are used as reference data sets. Compared to these ET and Q benchmarks, Mosaic and SAC (Noah and VIC) in the operational NLDAS-2 overestimate (underestimate) mean annual reference ET and underestimate (overestimate) mean annual reference Q. The multimodel ensemble mean (MME) is closer to the mean annual reference ET and Q. An anomaly correlation (AC) analysis shows good AC values for simulated monthly mean Q and dS/dt but significantly smaller AC values for simulated ET. Upgraded versions of the models utilized in the research side of NLDAS-2 yield largely improved performance in the simulation of these mean annual and monthly water component diagnostics. These results demonstrate that the three intertwined efforts of improving (1) the scientific understanding of parameterization of land surface processes, (2) the spatial and temporal extent of systematic validation of land surface processes, and (3) the engineering-oriented aspects such as parameter calibration and optimization are key to substantially improving product quality in various land data assimilation systems.

The mass balance of water storage on the Tibetan Plateau (TP) is a complex dynamic system that has responded to recent global warming due to the special regional characteristics and geographical environment on the TP. In this study, we present global positioning system (GPS), gravity recovery and climate experiment (GRACE) and follow-on (FO) observations obtained during the 2002–2020 period to identify hydrological changes on the TP. The spatial long-term trends in the GRACE/GRACE-FO data show continuous glacier mass losses around the Himalayas and accumulated mass on the inner TP due to the increased water mass in lakes. The singular spectrum analysis (SSA) was applied for interpolation of the data gap with GRACE/GRACE-FO. We evaluated the correlation between the vertical displacements obtained from 214 continuous GPS stations and GRACE/GRACE-FO-modeled water mass loads and found a high correlation, with spatial variabilities associated with the seasonal terrestrial water storage (TWS) pattern. The common-mode component obtained from continuous GPS coordinates was decomposed using principal component analysis (PCA) and presented different periodic signals related to interannual fluctuations in hydrology and the dynamics of the inner Earth. Moreover, the various characteristics of precipitation and temperature revealed similar interannual fluctuations to those of the El Niño/Southern Oscillation. We conclude that the GPS-inferred interannual fluctuations and the corresponding GRACE/GRACE-FO-modeled hydrological loads reflect climate responses. These findings shed light on the complex role of the spatiotemporal climate and water mass balance on the TP since the beginning of the 21st century.

The hydrological budget of a region is determined based on the horizontal and vertical water fluxes acting in both inward and outward directions. These integrated water fluxes vary, altering the total water storage and consequently the gravitational force of the region. The time-dependent gravitational field can be observed through the Gravity Recovery and Climate Experiment (GRACE) gravimetric satellite mission, provided that the mass variation is above the sensitivity of GRACE. This study evaluates mass changes in prominent reservoir regions through three independent approaches viz. fluxes, storages, and gravity, by combining remote sensing products, in-situ data and hydrological model outputs using WaterGAP Global Hydrological Model (WGHM) and Global Land Data Assimilation System (GLDAS). The results show that the dynamics revealed by the GRACE signal can be better explored by a hybrid method, which combines remote sensing-based reservoir volume estimates with hydrological model outputs, than by exclusive model-based storage estimates. For the given arid/semi-arid regions, GLDAS based storage estimations perform better than WGHM.