Water Storage Variations Research Articles

Mountain Hydrology Based on the Water Balance of the Tropical Basin of the Topo River (Tungurahua–Ecuador)

The Topo River basin, located in the tropical region of Ecuador, is considered a little-known and well-preserved basin, with limited access conditions and scarce data that hinder its hydrological understanding. However, this gap can be addressed through this study, which evaluates morphometric and hydrometeorological factors, relating them to water storage in the Topo River basin and comparing these results with other watersheds. The aim is to identify the morphometric and hydrometeorological factors that control the variability in water storage. Firstly, a morphometric characterization was conducted. Then, a hydrometeorological characterization was carried out based on climatic data from a single station with less than two years of data, along with the calculation of the water balance. Finally, water storage in the Topo basin was compared with the main morphometric and hydrometeorological characteristics of other basins. The results showed that the Topo River basin stores 9.1 mm annually (0.20% of its precipitation), and this storage is the result of its high runoff coefficient. It was concluded that basins with lower precipitation, higher evapotranspiration ranges, larger areas, gentler slopes, smaller altitude ranges, longer rivers, and basins that are narrow and oval-shaped may have higher water storage capacity.

Interannual variations of terrestrial water storage in the East African Rift region

Abstract. The US–German GRACE (Gravity Recovery and Climate Experiment, 2002–2017) and GRACE-FO (GRACE Follow-On, since 2018) satellite missions observe terrestrial water storage (TWS) variations. Over 20 years of data allow for investigating interannual variations beyond linear trends and seasonal signals. However, the origin of observed TWS changes cannot be determined solely with GRACE and GRACE-FO observations. This study focuses on the northern part of the East African Rift around the lakes of Turkana, Victoria, and Tanganyika. It aims to characterise and analyse the interannual TWS variations compared to meteorological and geodetic observations of the water storage compartments (surface water, soil moisture, and groundwater). We apply the STL (Seasonal-Trend decomposition using LOESS) method to decompose the signal into a seasonal signal, an interannual signal, and residuals. By clustering the interannual TWS dynamics for the African continent, we define the exact outline of the study region. We observe a TWS decrease until 2006, followed by a steady rise until 2016, and then the most significant TWS gain in Africa in 2019 and 2020. Besides meteorological variability, surface water storage variations in the lakes explain large parts of the TWS decrease before 2006. The storage dynamics of Lake Victoria alone contribute up to 50 % of these TWS changes. On the other hand, the significant TWS increase around 2020 can be attributed to nearly equal rises in groundwater and surface water storage, which coincide with a substantial precipitation surplus. Soil moisture explains most of the seasonal variability but does not influence the interannual variations. As Lake Victoria dominates the surface water storage variations in the region, we further investigate the lake and the downstream Nile River. The Nalubaale Dam regulates Lake Victoria's outflow. Water level observations from satellite altimetry reveal the impact of dam operations on downstream discharge and on TWS decreases in the drought years before 2006. On the other hand, we do not find evidence for an impact of the Nalubaale Dam regulations on the strong TWS increase after 2019.

Optimizing the estimation of water storage variation in lakes with limited satellite altimetry coverage

Optimizing the estimation of water storage variation in lakes with limited satellite altimetry coverage

Significance testing for cross correlation: A critical examination of correlations between ENSO and GRACE-derived terrestrial water storage variabilities

The cross correlation has a wide range of applications in geophysical fields for measuring linear connections or relationships among physical quantities. Nonetheless, there remains a dearth of comprehensive discourse regarding its statistical significance testing, which is crucial for differentiating meaningful outcomes from those merely stemming from fortuity or pure randomness. Conventional theoretical methods for significance testing, commonly used in statistical analysis tools such as SPSS and MATLAB, are only applicable when dealing with idealized circumstances such as white noise. In discretionary application of these methods to analyze geophysical signals with, say, red noise may result in potentially unjustified conclusions. This study aims to develop a comprehensive approach based on the t-distribution within a rigorous statistical context, aiming to facilitate significance tests of cross correlation for general signals with specified time shifts or ranges. Extensive Monte Carlo experiments substantiate its robustness, thereby paving the way for accurate and expeditious identification of statistically (hence potentially physically) meaningful correlations in general. As an example, we examine critically the previously purported significant correlations between ENSO (El Niño Southern Oscillation) and global terrestrial water storage variations derived from the GRACE (Gravity Recovery and Climate Experiment) satellite mission, demonstrating that they are subject to questioning in the absence of complete significance testing.

Increasing vulnerability of vegetation to Meteorological and Groundwater drought: A Case study in Argentina

Study RegionContinental Argentina, South America. Study FocusThis study integrates multiple data sources to analyze the response of vegetation to meteorological and groundwater drought events in Argentina. It utilizes GRACE satellite data to monitor water storage variations, the GLDAS hydrological model to track soil moisture levels, and NDVI to assess vegetation health, categorized by different vegetation types. Meteorological data facilitated the computation of drought severity using the Standardized Precipitation-Evapotranspiration Index (SPEI). Anomalies in groundwater storage, derived from these data, informed the calculation of the Grace Groundwater Drought Index (GGDI). A comprehensive statistical analysis was conducted to examine the impact of meteorological (SPEI) and groundwater (GGDI) droughts on various vegetation types. New Hydrological Insights for the RegionThe study reveals that from 2002 to 2022, GRACE-TWSA and GLDAS-TWSA displayed consistent trends in Argentina. Meteorological droughts, characterized by higher frequency and intensity, predominantly affect croplands and grasslands. Compared to lagged effects, the cumulative impact of droughts was found to be more significant. Shrublands demonstrated the greatest resistance to drought, whereas vegetation in humid regions showed lower drought tolerance. Notably, the duration associated with the lag effects of meteorological droughts decreased from 2.16 months in 2002–1.52 months in 2020, suggesting an increasing sensitivity of vegetation to these droughts. This underscores the urgency of developing targeted drought resilience and water resource management strategies.

Sharp decline in surface water resources for agriculture and fisheries in the Lower Mekong Basin over 2000-2020

Water resources play a crucial role in the global water cycle and are affected by human activities and climate change. However, the impacts of hydropower infrastructures on the surface water extent and volume cycle are not well known. We used a multi-satellite approach to quantify the surface water storage variations over the 2000–2020 period and relate these variations to climate-induced and anthropogenic factors over the whole basin. Our results highlight that dam operations have strongly modified the water regime of the Mekong River, exhibiting a 55 % decrease in the seasonal cycle amplitude of inundation extent (from 3178 km2 to 1414 km2) and a 70 % decrease in surface water volume (from 1109 km3 to 327 km3) over 2000–2020. In the floodplains of the Lower Mekong Basin, where rice is cultivated, there has been a decline in water residence time by 30 to 50 days. The recent commissioning of big dams (2010 and 2014) has allowed us to choose 2015 as a turning point year. Results show a trend inversion in rice production, from a rise of 40 % between 2000 and 2014 to a decline of 10 % between 2015 and 2020, and a strong reduction in aquaculture growth, from +730 % between 2000 and 2014, to +53 % between 2015 and 2020. All these results show the negative impact of dams on the Mekong basin, causing a 70 % decline in surface water volumes, with major repercussions for agriculture and fisheries over the period 2000–2020. Therefore, new future projects such as the Funan Techo canal in Cambodia, scheduled to start construction at the end of 2024, will particularly affect 1300 km2 of floodplains in the lower Mekong basin, with a reduction in the amount of water received, and other areas will be subjected to flooding. The human, material and economic damage could be catastrophic.

Monthly Monitoring of Inundated Areas and Water Storage Dynamics in China's Large Reservoirs Using Multisource Remote Sensing

AbstractHigh‐frequency monitoring of reservoir inundation and water storage changes is crucial for reservoir functionality assessment and hydrological model calibration. Although the integration of optical data with synthetic aperture radar (SAR) backscattering coefficients (backscatters) offers an effective approach, conventional methods struggle to consistently provide accurate retrievals over diverse regions and seasons. In this study, we introduce reservoir‐ and monthly‐specific classification models to enhance the integration of Sentinel‐1 SAR backscatters with optical‐based water dynamics. Our method covers 721 reservoirs with a capacity greater than 0.1 km3 in China during 2017–2021. Furthermore, we leverage multisource satellite altimetry records (e.g., ICESat‐2, CryoSat‐2, and GEDI) and digital elevation models to derive hypsometry relationship (i.e., water level–water area relationship) for reservoirs, enabling the transformation of inundated areas into monthly water storage changes for 662 reservoirs, representing 93% of the total storage capacity of large reservoirs. Validation against in‐situ measurements at 80 reservoirs reveals improved monthly inundated area monitoring compared to existing data sets. Additionally, our reservoir water storage change estimates exhibit an average R2 of 0.79 and a mean relative root mean square error (rRMSE) of 21%. Our findings highlight reservoir water increases from May/June to November and declines in winter–spring in most regions. However, the inter‐annual patterns vary among regions, with increases in Northeast China, the Yellow River basin (YR), and Southwest China, contrasted by declines in Eastern and Northwest China. Inter‐ and intra‐annual variability in reservoir water storage is mainly influenced by natural inflow in Northeast and Northwest China, while anthropogenic factors dominate in the YR, Eastern, and Southwest China.

Effect of Land Use Type on Soil Moisture Dynamics in the Sloping Lands of the Black Soil (Mollisols) Region of Northeast China

This study investigates the spatial and temporal heterogeneity of soil moisture on slopes of China’s northeastern black soil region, focusing on the effects of terrain adjustment and vegetation. Soil moisture dynamics in the 0–60 cm soil layer were measured at 10 cm intervals using the TRIME-PICO64 TDR® device on slopes with similar gradients representing three land use types: transverse ridge tillage (TRT) farmland, terraced fields (TFs) farmland, and pure forest woodland (WL). The results indicate significant variations in soil moisture content and water storage across different land use types in the order of TF > TRT > WL. The study further identified that soil bulk density, porosity, and water-holding indicators were in the order of WL > TF > TRT, inconsistent with the soil moisture results, indicating that soil quality cannot be the sole reason for the differences in moisture. The moisture differences between farmland types (TRT and TF) and WL are substantial, especially during the rainy season. In the rainy season (0–60 cm) and the dry season (30–60 cm), significant differences in moisture content are observed (p < 0.05). Significant differences in moisture content between farmland types are found at 0–40 cm during the rainy season and at 0–10 cm during the dry season. In the rainy season, soil moisture for TRT and TFs first decreases from 26.76% and 30.85% to 22.44% and 25.38%, then slightly increases to 27.01% and 27.07% along the slope. Meanwhile, WL displays the opposite pattern on upper, relatively steep slopes, with soil moisture increasing from 16.66% to 17.81%, and exhibits a pattern of change similar to TRT and TFs on lower, gentler slopes. TFs consistently show higher soil moisture and water storage at all slope positions than TRT and WL. TFs improve soil quality, reduce erosion and sedimentation, and shift the lowest soil moisture content to a lower slope position. During the dry season, soil moisture differences between slope positions for TRT and WL were small. In general, terracing can effectively modulate moisture distribution along slopes, increasing moisture by an average of 0.26~12.43%, while afforestation, despite improving soil quality, leads to an 18.14~31.13% reduction in soil moisture content, with the impact being particularly significant during the rainy season. These findings provide important insights for optimizing land use and ecological construction, including keeping the balance between soil and water conservation, especially for sub-humid slope terrain areas.

Uncertainty analysis on long-term runoff projection from the Budyko framework and a conceptual hydrological model

ABSTRACT Runoff projections are subject to uncertainties related to model structure and parameters. This study aims to analyze uncertainties in long-term runoff estimations from an empirical (Budyko framework) and a conceptual hydrological model (MHD-INPE). Results indicate that both MHD-INPE and Budyko estimations tend to overestimate long-term runoff during years of recurring droughts. Pareto front solutions in MHD-INPE exhibited small uncertainties in long-term runoff estimations regarding parameter calibration (bias between 5 and 7%); differences were observed in low (bellow 5% variation) and high (bellow 10% variation) daily runoff. Related to model structure uncertainties, both models follow similar patterns and performance for a qualitative analysis. Budyko's future projections tend to exceed MHD-INPE's during high precipitation estimates, where at 2000 mm yearly precipitation the estimated runoff from Budyko tends to be 100 mm greater than the hydrological model. Under arid conditions Budyko tends to estimate smaller runoff than MHD-INPE due to variations in soil moisture and water storage not properly represented in Budyko's parameter. Although uncertainties were identified related to model complexity and calibrated parameters, higher uncertainties were identified as related to the climate models. Therefore, the Budyko method is a viable alternative for first-order analysis of long-term impacts.

High Spatial Resolution in Total Water Storage Variations Inferred From GPS: Case Study in the Great Lakes Watershed, US

AbstractAssessing spatiotemporal water storage variability in the Great Lakes Watershed (GLW) is critical given its transboundary status impacting both Canada and the United States. Here, we apply a novel inversion strategy to global positioning system (GPS) vertical movements to achieve high spatial resolution total water storage (TWS) variations in GLW through improved processing. The steps are composed of removing load changes driven by the lake water fluctuation by forward modeling, isolating the Great Lakes grids to solve the ill‐conditioned problem in inversion, and inverting the GPS residual series to estimate TWS variations on land (TWSGPS). The results show that the regional dense continuous GPS observation network can successfully resolve TWS on land at monthly timescales with 30–45 km spatial resolution. We also could effectively capture fine‐scale TWS features than GRACE/GFO mascon products. GRACE/GFO satellites largely underestimate seasonal and long‐term TWS spatial fluctuations, but their temporal patterns coincide with those from GPS. The average annual amplitude of TWSGPS on land reaches 82.0 mm, greatly exceeding estimates from GRACE/GFO (∼48.0 mm) and composite hydrological model outputs (∼62.0 mm). The seasonal groundwater fluctuations inferred from GPS have peak‐to‐peak amplitudes of ∼40 km3 with the maximum around September. This coincides with that from GRACE/GFO. However, the magnitudes and phases of groundwater storage from GPS vary markedly among the subbasins in GLW, and the different snow and soil moisture amounts measured in each subbasin cause discrepancies among these GPS estimates. This study shows the value of GPS data in spatially downscaling GRACE/GFO data and providing high‐resolution output at spatiotemporal scales with low latency.

Unraveling space and time variability in maximum water storage among sunflower organs: Implications for wetness duration

Vegetation wetness significantly alters the plant microclimate, thereby influencing plant functionality, growth, and yield. Prolonged wetness periods can exacerbate the risk of attack of various plant diseases. Maximum water storage capacity is a crucial parameter for modeling wetness duration, as it sets the upper limit for free water available for evaporation. This study aimed to achieve three main goals: (i) to investigate the maximum water storage capacity of distinct sunflower organs (leaves, stems, and capitula) and their constituent phytoelements, (ii) to establish relationships between maximum water storage and visible morphological characteristics, and (iii) to assess the impact of maximum water storage on phytoelement wetness duration. Morphological and micrometeorological measurements were conducted within a sunflower field plot. Maximum water storage capacity was determined in the laboratory using phytoelements collected from the field. For the capitula and its constituent phytoelements, this capacity was monitored throughout their development. Phytoelement size and orientation were quantified and correlated with their water storage capacity. The influence of phytoelement maximum water storage on wetness duration was investigated through simulation. Notably, we found that the maximum water storage capacity in leaf axils exceeded those in leaf lamina by 43 times. During the flowering and grain-filling stages, capitula exhibited greater water storage, primarily attributed to the contribution from the capitulum front. The area of leaves, stems, and capitula during the flowering stage had a greater impact on their maximum water storage capacity than their orientation. Simulation results revealed that certain phytoelements (e.g., leaf axils and capitulum disk) could remain wet for up to 20 h after most of the canopy, mainly leaves and stems, had dried. This study underscores the importance of examining variability in maximum water storage capacity and its impact on wetness duration within a sunflower canopy at the phytoelement level.

Analysis of terrestrial water storage variations in South Korea using GRACE satellite and GLDAS data in Google Earth Engine

ABSTRACT With the requirement of a macroscopic approach to understanding the relationship between water resources and hydrological phenomena, such as severe droughts under climate change, this study investigates South Korea’s long-term terrestrial water storage (TWS) using GRACE satellite data. A detailed analysis of water balance in TWS, based on the GLDAS model outputs in Google Earth Engine, reveals the following results: (1) TWS anomaly shows an average decrease of −33.5 mm year−1 from 2003 to 2016; (2) spatial shifts in TWS anomaly (−1.176 to −0.424 cm) unveil regional water storage dynamics, indicating negative temporal slope changes per grid cell (−0.393 to −0.225); (3) contributions of precipitation to TWS are not always straightforward, due to runoff inefficiencies affecting water storage and groundwater; (4) accessible water, integrating surface water and groundwater linked only to the shallow layer’s soil moisture, constrains deep groundwater accounting, emphasizing the need for local groundwater surveys in further research.

Assessing water storage variations in La Plata basin and sub-basins from GRACE, global models data and connection with ENSO events

ABSTRACT The La Plata basin is one of the largest river basins in the world, draining about a fifth of the South American continent. It is a system of great hydrological significance, sensitive to extreme events, and also has the most economic development in the region. This work analyses the total water storage (TWS) changes over the La Plata basin from the GRACE (Gravity Recovery And Climate Experiment) mission and compares it with TRMM (Tropical Rainfall Measuring Mission) rainfall data. Subsequently, a study was conducted on the main sub-basins for the period 2003 to 2017 to identify regional-scale variations in TWS. Precipitation and GLDAS (Global Land Data Assimilation System) runoff data was evaluated in these areas, along with their connections to ENSO (El Niño Southern Oscillation) episodes. The results suggest that the majority of TWS variations are associated with extreme climatic events, such as the 2009 drought, and are linked to ENSO periods. The statistical analysis indicates a significant correlation between severe Niño/Niña episodes and changes in TWS in the sub-basins.

Revealing the Hidden Consequences of Increased Soil Moisture Storage in Greening Drylands

Vegetation primarily draws water from soil moisture (SM), with restoration in drylands often reducing SM storage (SMS). However, anomalies have been detected in the Beijing–Tianjin Sand Source Region (BTSSR) of China via the Global Land Data Assimilation System (GLDAS) and Gravity Recovery and Climate Experiment (GRACE). This study quantified the sources of increased SMS in drylands to elucidate the effects of vegetation restoration on SMS. The results indicated the following: (1) In vegetated drylands, 46.2% experienced a significant increase in SMS while 53.8% remained stable; both were positively correlated with the normalised difference vegetation index (NDVI). (2) The increase in SMS was accompanied by a decrease in groundwater storage (GWS), as indicated by the significant correlation coefficients of −0.710 and −0.569 for SMS and GWS, respectively. Furthermore, GWS served as the primary source of water for vegetation. (3) The results of the redundancy analysis (RDA) indicated that the initial vegetation, the driver of the observed trend of increased SMS and decreased GWS, accounted for 50.3% of the variability in water storage. Therefore, to sustain dryland ecosystems, we recommend that future vegetation restoration projects give due consideration to the water balance while concurrently strengthening the dynamic monitoring of SMS and GWS.

Temporal and spatial variations of terrestrial water storage in the northeastern Tibetan Plateau retrieved by GNSS observations

The variation of solid Earth's hydrologic loading could cause the elastic vertical deformation of the crust, and the Global Navigation Satellite System (GNSS) could effectively monitor the vertical displacement of surface loads. However, the widely used Green's function method does not work well in areas where GNSS sites are sparse. Here, the vertical displacement time series of GNSS stations and the Slepian basis function method have been applied to convert displacement signals into spatial spectrum signals. The elastic mass load theory is used to study the changes in terrestrial water storage on the Northeastern Tibetan Plateau (NETP). The temporal and spatial characteristics of seasonal water changes are well-represented by the GNSS, the Gravity Recovery and Climate Experiment (GRACE), and the Global Land Data Assimilation System (GLDAS). Several data points suggest that the change in water storage shows a gradual increase from the northeast to the southwest. The greatest annual amplitude of water storage retrieved by GNSS is ∼159 mm, which is greater than the ∼47 mm and ∼44 mm obtained by GRACE and GLDAS. These results demonstrate that GNSS is capable of capturing small-scale hydrological changes in this region, whereas GRACE and GLDAS data tend to underestimate seasonal variations in water storage. We also used GNSS to describe the hydrological drought conditions in NETP, showing that GNSS could be used as an independent method to characterize hydrological drought events. The findings suggest it could observe water storage with high spatial and temporal resolution and aid in comprehending regional hydrological trends with a sparse GNSS station network.

Intercropping impacts growth in the forage cactus, but complementarity affords greater productivity, competitive ability, biological efficiency and economic return

CONTEXTSoil and climatic conditions limit forage production in semi-arid environments. Planting crops adapted to these elements, combined with management practices such as intercropping and irrigation, can ensure the sustainability of animal feed. OBJECTIVEThe aim of this study was to evaluate growth, forage productivity, soil water balance, water indices and the indices of biological efficiency, competitive ability, and economic return in a dense crop of forage cactus, grasses, and legumes under single and intercropping systems in a semi-arid environment. METHODSThe study was carried out from 2020 to 2022 in Serra Talhada, Pernambuco, Brazil. The plants used were the ‘Orelha de Elefante Mexicana’ (OEM) clone of the forage cactus, pigeon pea (‘crioula’), millet (‘Bulk-01’) and sorghum (‘SF15’). A randomised block design was adopted, with three repetitions, including single crops of the forage cactus, sorghum, millet and pigeon pea, as well as the cactus intercropped with pigeon pea, millet and sorghum. Biometrics and biomass were checked to determine morpho-physiological indices, phenology, cutting time, biological efficiency and competitive ability. The soil moisture was also monitored, and the soil water balance quantified. The water indices and economic return were then calculated. RESULTS AND CONCLUSIONSGrowth rates and phenology were not affected by intercropping, only by the cutting time. During the first season, the single sorghum and cactus-pigeon pea system showed a variation in soil water storage of 26 mm, while during the second season, the single cactus stored 66.74 mm. The actual evapotranspiration ranged from 1109 in the cactus-millet system to 1152 mm in the single cactus and millet (1st season), and from 1510 in the single cactus to 1570 mm in the sorghum (2nd season). The cactus-sorghum system was the most productive, with 460.53 Mg FM ha−1 and 43.55 Mg DM ha−1 in season one, while in season two, the single cactus obtained 237.64 Mg FM ha−1 and 26.71 Mg DM ha−1. Intercropping promotes more productive stability and feed diversity, as well as greater biological efficiency, competitive ability and economic return. SIGNIFICANCEUnderstanding the changes that exist in a intercropping system is important, especially in semi-arid regions, since these have distinct characteristics that impact the development of crops. Thus, this work contributes comprehensively to resilient practices for the semi-arid, seeking to ensure the sustainability of the intercropping systems and understand the interrelationship between species from the management adopted.

Study on the vertical deformations induced by terrestrial water storage changes in Huang-Huai-Hai river basin

Terrestrial water storage (TWS) variations are associated with water mass movements, which may cause the deformation displacements of the Global Navigation Satellite System (GNSS) stations. This study investigates the spatio-temporal TWS variations and addresses the relationship between deformation variations observed in the Huang-Huai-Hai River Basin (HHHRB) and local hydrological features. Results indicate that the vertical velocities at the GNSS stations induced by TWS changes are relatively small, and the impacts of the terrestrial water storage changes are mainly reflected in the changes of seasonal characteristics. Although there is a downward TWS trend from 2011 to 2022 in most HHHRB areas, velocities from the vertical displacements of both Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GFO) and the GNSS reflect that the HHHRB is undergoing an uplift process, while the magnitude of the GRACE/GFO derived velocities is much smaller than that of the GNSS solutions. Common hydrological deformations estimated from GRACE/GFO and GNSS measurements reveal that the TWS-derived displacements can explain 54.5% of the GNSS seasonal variations, with the phases of terrestrial water storage advancing by about one month relative to GNSS common signal phases. Moreover, the decrease of the groundwater storage in the HHHRB has been accelerating since 2008. After reaching its lowest level around mid-2020, it began to rise rapidly, which might be closely related to the implementation of the South-North Water Transfer Central Project.

A Regionally Refined and Mass‐Consistent Atmospheric and Hydrological De‐Aliasing Product for GRACE, GRACE‐FO and Future Gravity Missions

AbstractDe‐aliasing products are used in the estimation process of satellite‐based gravity field computation to reduce errors from high‐frequency mass variations that alias into monthly gravity fields. The latest official product is AOD1B RL07 and describes non‐tidal atmosphere and oceanic mass variations at 3‐hourly resolution. However, the model‐based de‐aliasing products are inevitably incomplete and prone to temporally and spatially correlated errors that substantially contribute to errors in the estimated gravity fields. Here, we investigate possible enhancement of current de‐aliasing products by nesting a regional high‐resolution atmospheric reanalysis over Europe into a global reanalysis. As further novelty we include almost mass consistent terrestrial water storage variability from a regional hydrological model nested into a global model as additional component of the de‐aliasing product. While we find in agreement with earlier studies only minor contributions from increasing the temporal resolution beyond 3‐hourly data, our investigations suggest that contributions from continental hydrology and from regional non‐hydrostatic atmospheric modeling to sub‐monthly mass variations could be relevant already for gravity fields estimated from current gravity missions. Moreover, in the context of extreme events, we find regionally contributions from additional moisture fields, such as cloud liquid water, in the order of a few mm over Europe. We suggest this needs to be taken into account when preparing data analysis schemes for future space gravimetric missions.

Water availability identification from GRACE dataset and GLDAS hydrological model over data-scarce river basins of Ethiopia

ABSTRACT The nature of the heterogeneity of terrestrial water storage in the main river basins of Ethiopia is poorly understood. In river basins, measurements of terrestrial water storage changes are exceedingly rare in all temporal dimensions. This study investigates the spatiotemporal variation of water storage in the main river basins of Ethiopia using the Gravity Recovery and Climate Experiment (GRACE) with Global Land Data Assimilation System (GLDAS). The results revealed significant variation in liquid water equivalents from GRACE and terrestrial water storage from GLDAS for each river basin, following a seasonal pattern. I found that GRACE and GLDAS datasets can be combined effectively to evaluate the long-term water storage in large-scale basins with limited hydrological data, and the obtained result provides a reliable outcome that will be essential for the establishment of climate change adaptation pathways in the future for essential water resource management and optimization.

Integrated study of water levels and water storage variations using GNSS-MR and remote Sensing: A case study of Sarez Lake, the world's Highest-Altitude dammed lake

Sarez Lake, recognized as the world's highest-altitude dammed lake, necessitates meticulous monitoring of dam deformation, lake water levels, and water storage fluctuations to ensure its safety. In pursuit of this critical objective, a Global Navigation Satellite System (GNSS) monitoring network has been established around the lake to compute real-time station coordinates for deformation monitoring. GNSS Multipath Reflectometry (GNSS-MR) technology has been introduced as an innovative approach, enabling water level retrieval through conventional GNSS geodetic receivers. However, the complex and rugged terrain surrounding Sarez Lake poses challenges to the application of GNSS-MR in this region. This research is dedicated to addressing the challenges posed by the limited available elevation range selection and the retrieval of inter-site water level combinations in such demanding terrain. It proposes a novel method for effectively discerning valid Signal-to-Noise Ratio (SNR) arcs and an inter-site inter-signal water level combination retrieval approach, resulting in a continuous sequence of water level retrievals for this region. The incorporation of remote sensing techniques further facilitates the estimation of water storage fluctuations in the area. The outcomes of this study demonstrate the efficacy of GNSS-MR in capturing the lake's seasonal water-level variations, with retrieval uncertainties ranging from centimeters to low decimeters. The fusion of GNSS-MR with remote sensing data offers a comprehensive approach for monitoring the water levels and water storage fluctuations of Sarez Lake within its challenging environmental conditions. This research provides a valuable methodology applicable to the study and monitoring of other dammed lakes.