Three-dimensional Budyko framework incorporating terrestrial water storage: Unraveling water-energy dynamics, vegetation, and ocean-atmosphere interactions.

The two-dimensional steady-state Budyko framework, widely used to study water-energy dynamics in landscapes, primarily focused on the partitioning of precipitation into evapotranspiration (ET) and water yield. Though this framework has been extended by incorporating water storage changes into precipitation input for non-steady state conditions, the interactions among water-energy dynamics, vegetation covers, and ocean-atmosphere oscillations within the Budyko framework at finer spatial and temporal scales have been unexplored. This study aims to investigate the interactions of regional hydroclimatic conditions, vegetation, and climate teleconnections over the Indo-China Peninsula (ICP), a region highly vulnerable to climate change. To achieve the objective, we propose a three-dimensional Budyko framework that incorporates the ratio of Gravity Recovery and Climate Experiment (GRACE)-based terrestrial water storage (TWS) or its changes (TWSC) to precipitation (SI/SCI) as the third dimension alongside the traditional two-dimensional Budyko framework. Our findings reveal that TWS has a significant impact on the Budyko framework, particularly during the dry season. The dryness index (DI)/evaporative index (EI) and SI/SCI exhibit positive (strongly negative) linear relationships in the wet (dry) season, respectively. Vegetation covers strongly influence the three-dimensional Budyko framework, with poor performance observed in highly vegetated regions due to high ET demand. Through relative importance analysis, we identify the Silk Road Pattern (SRP) as the most influential climate teleconnection among nine different teleconnections, affecting hydroclimatic conditions over the ICP. Positive (negative) phases of SRP encourage water-limited (energy-limited) ET conditions. This demonstrates that the Budyko parameter is influenced not only by landscapes but also by climate teleconnections, offering potential benefits for Budyko parameter estimation. Furthermore, the linear relationships between DI/EI and SI/SCI in three-dimensional Budyko framework can provide a promising alternative method for evapotranspiration and groundwater estimation.

Gravimetry-based terrigenous freshwater extension in the southwestern South China Sea and its response to monsoon under ENSO.

Terrigenous discharge represents a mass movement from land to oceanic environment. While previous studies characterized terrigenous freshwater via oceanographic (physical and biochemical) data, the persistent fresh water in the far-field ocean via satellite-gravimetric observation has been rarely explored. This paper aims to characterize the spatiotemporal extension of Mekong freshwater and the interchangeable role of runoff and climatic factors in the southwestern South China Sea. Employing wavelet coherence analysis between the in situ runoff and oceanic freshwater variations inferred from satellite gravimetry, the coherence and transport duration were obtained at annual, intra- and inter-annual time scales during 2003-2015. Despite weak relationship at 6-month and 24-month scales in regions away from the estuary, the two time series remained significantly correlated at the 12-month scale with a highly positive coherence over 0.97. Spatial pattern of the annual transport duration further indicated that freshwater firstly flowed alongshore before turning eastward offshore, qualitatively consistent with the northeastward western boundary current and an anticyclonic eddy during the summertime generated from the ocean circulation model. Using partial wavelet coherence, the time-variable relationship at all these three scales was found closely related to the Indian Monsoon and Western North Pacific Monsoon. A series of alternating ENSO events during 2007-2011 were responsible for the inter-annual variations, contributing <5 % to the seasonal freshwater extension. Compared with the averaged transport duration of the isotope method (i.e., 21.5 days) and the geostrophic current computation (i.e., 38.8 days) in the summer of 2007, our method yielded a comparable transport duration of 23.9 days with smaller uncertainties. The wind-driven Ekman transport, however, was primarily responsible for the anticyclonic movement of freshwater transport in the southwestern South China Sea during late summer.

Gravimetry-based water storage shifting over the China-India border area controlled by regional climate variability.

The regional water storage shifting causes nonstationary spatial distribution of droughts and flooding, leading to water management challenges, environmental degradation and economic losses. The regional water storage shifting is becoming evident due to the increasing climate variability. However, the previous studies for climate drivers behind the water storage shifting are not rigorously quantified. In this study, the terrestrial water storage (TWS) spatial shifting pattern during 2002-2017 over the China-India border area (CIBA) is developed using the Gravity Recovery and Climate Experiment (GRACE), suggesting that the Indus-Ganges-Brahmaputra basin (IGBB) was wetting while the central Qinghai-Tibet Plateau (QTP) was drying. Similar drying and wetting patterns were also found in the precipitation, snow depth, Palmer Drought Severity Index (PDSI) and potential evaporation data. Based on our newly proposed Indian monsoon (IM) and western North Pacific monsoon (WNPM) variation indices, the water shifting pattern over the CIBA was found to be affected by the weakening of the variation of IM and WNPM through modulating the regional atmospheric circulation. The weakening of IM and WNPM variations has shown to be attributed to the decreasing temperature gradient between the CIBA and the Indian Ocean, and possibly related to increasing regional temperatures associated with the increasing global temperature. As the global warming intensifies, it is expected that the regional TWS shifting pattern over the CIBA will be further exaggerated, stressing the need of advancing water resources management for local communities in the region.

Improved Remotely Sensed Total Basin Discharge and Its Seasonal Error Characterization in the Yangtze River Basin.

Total basin discharge is a critical component for the understanding of surface water exchange at the land-ocean interface. A continuous decline in the number of global hydrological stations over the past fifteen years has promoted the estimation of total basin discharge using remote sensing. Previous remotely sensed total basin discharge of the Yangtze River basin, expressed in terms of runoff, was estimated via the water balance equation, using a combination of remote sensing and modeled data products of various qualities. Nevertheless, the modeled data products are presented with large uncertainties and the seasonal error characteristics of the remotely sensed total basin discharge have rarely been investigated. In this study, we conducted total basin discharge estimation of the Yangtze River Basin, based purely on remotely sensed data. This estimation considered the period between January 2003 and December 2012 at a monthly temporal scale and was based on precipitation data collected from the Tropical Rainfall Measuring Mission (TRMM) satellite, evapotranspiration data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite, and terrestrial water storage data collected from the Gravity Recovery and Climate Experiment (GRACE) satellite. A seasonal accuracy assessment was performed to detect poor performances and highlight any deficiencies in the modeled data products derived from the discharge estimation. Comparison of our estimated runoff results based purely on remotely sensed data, and the most accurate results of a previous study against the observed runoff revealed a Pearson correlation coefficient (PCC) of 0.89 and 0.74, and a root-mean-square error (RMSE) of 11.69 mm/month and 14.30 mm/month, respectively. We identified some deficiencies in capturing the maximum and the minimum of runoff rates during both summer and winter, due to an underestimation and overestimation of evapotranspiration, respectively.

Akaike's Bayesian Information Criterion for the Joint Inversion of Terrestrial Water Storage Using GPS Vertical Displacements, GRACE and GLDAS in Southwest China.

Global navigation satellite systems (GNSS) techniques, such as GPS, can be used to accurately record vertical crustal movements induced by seasonal terrestrial water storage (TWS) variations. Conversely, the TWS data could be inverted from GPS-observed vertical displacement based on the well-known elastic loading theory through the Tikhonov regularization (TR) or the Helmert variance component estimation (HVCE). To complement a potential non-uniform spatial distribution of GPS sites and to improve the quality of inversion procedure, herein we proposed in this study a novel approach for the TWS inversion by jointly supplementing GPS vertical crustal displacements with minimum usage of external TWS-derived displacements serving as pseudo GPS sites, such as from satellite gravimetry (e.g., Gravity Recovery and Climate Experiment, GRACE) or from hydrological models (e.g., Global Land Data Assimilation System, GLDAS), to constrain the inversion. In addition, Akaike's Bayesian Information Criterion (ABIC) was employed during the inversion, while comparing with TR and HVCE to demonstrate the feasibility of our approach. Despite the deterioration of the model fitness, our results revealed that the introduction of GRACE or GLDAS data as constraints during the joint inversion effectively reduced the uncertainty and bias by 42% and 41% on average, respectively, with significant improvements in the spatial boundary of our study area. In general, the ABIC with GRACE or GLDAS data constraints displayed an optimal performance in terms of model fitness and inversion performance, compared to those of other GPS-inferred TWS methodologies reported in published studies.

Water Level Reconstruction and Prediction Based on Space-Borne Sensors: A Case Study in the Mekong and Yangtze River Basins.

Water level (WL) measurements denote surface conditions that are useful for monitoring hydrological extremes, such as droughts and floods, which both affect agricultural productivity and regional development. Due to spatially sparse in situ hydrological stations, remote sensing measurements that capture localized instantaneous responses have recently been demonstrated to be a viable alternative to WL monitoring. Despite a relatively good correlation with WL, a traditional passive remote sensing derived WL is reconstructed from nearby remotely sensed surface conditions that do not consider the remotely sensed hydrological variables of a whole river basin. This method's accuracy is also limited. Therefore, a method based on basin-averaged, remotely sensed precipitation from the Tropical Rainfall Measuring Mission (TRMM) and gravimetrically derived terrestrial water storage (TWS) from the Gravity Recovery and Climate Experiment (GRACE) is proposed for WL reconstruction in the Yangtze and Mekong River basins in this study. This study examines the WL reconstruction performance from these two remotely sensed hydrological variables and their corresponding drought indices (i.e., TRMM Standardized Precipitation Index (TRMM-SPI) and GRACE Drought Severity Index (GRACE-DSI)) on a monthly temporal scale. A weighting procedure is also developed to explore a further potential improvement in the WL reconstruction. We found that the reconstructed WL derived from the hydrological variables compares well to the observed WL. The derived drought indices perform even better than those of their corresponding hydrological variables. The indices' performance rate is owed to their ability to bypass the influence of El Niño Southern Oscillation (ENSO) events in a standardized form and their basin-wide integrated information. In general, all performance indicators (i.e., the Pearson Correlation Coefficient (PCC), Root-mean-squares error (RMSE), and Nash⁻Sutcliffe model efficiency coefficient (NSE)) reveal that the remotely sensed hydrological variables (and their corresponding drought indices) are better alternatives compared with traditional remote sensing indices (e.g., Normalized Difference Vegetation Index (NDVI)), despite different geographical regions. In addition, almost all results are substantially improved by the weighted averaging procedure. The most accurate WL reconstruction is derived from a weighted TRMM-SPI for the Mekong (and Yangtze River basins) and displays a PCC of 0.98 (and 0.95), a RMSE of 0.19 m (and 0.85 m), and a NSE of 0.95 (and 0.89); by comparison, the remote sensing variables showed less accurate results (PCC of 0.88 (and 0.82), RMSE of 0.41 m (and 1.48 m), and NSE of 0.78 (and 0.67)) for its inferred WL. Additionally, regardless of weighting, GRACE-DSI displays a comparable performance. An external assessment also shows similar results. This finding indicates that the combined usage of remotely sensed hydrological variables in a standardized form and the weighted averaging procedure could lead to an improvement in WL reconstructions for river basins affected by ENSO events and hydrological extremes.

Potential Seasonal Terrestrial Water Storage Monitoring from GPS Vertical Displacements: A Case Study in the Lower Three-Rivers Headwater Region, China.

This study uses the observed vertical displacements of Global Positioning System (GPS) time series obtained from the Crustal Movement Observation Network of China (CMONOC) with careful pre- and post-processing to estimate the seasonal crustal deformation in response to the hydrological loading in lower three-rivers headwater region of southwest China, followed by inferring the annual EWH changes through geodetic inversion methods. The Helmert Variance Component Estimation (HVCE) and the Minimum Mean Square Error (MMSE) criterion were successfully employed. The GPS inferred EWH changes agree well qualitatively with the Gravity Recovery and Climate Experiment (GRACE)-inferred and the Global Land Data Assimilation System (GLDAS)-inferred EWH changes, with a discrepancy of 3.2-3.9 cm and 4.8-5.2 cm, respectively. In the research areas, the EWH changes in the Lancang basin is larger than in the other regions, with a maximum of 21.8-24.7 cm and a minimum of 3.1-6.9 cm.

A New Perspective on Fault Geometry and Slip Distribution of the 2009 Dachaidan Mw 6.3 Earthquake from InSAR Observations.

On 28 August 2009, the northern margin of the Qaidam basin in the Tibet Plateau was ruptured by an Mw 6.3 earthquake. This study utilizes the Envisat ASAR images from descending Track 319 and ascending Track 455 for capturing the coseismic deformation resulting from this event, indicating that the earthquake fault rupture does not reach to the earth's surface. We then propose a four-segmented fault model to investigate the coseismic deformation by determining the fault parameters, followed by inverting slip distribution. The preferred fault model shows that the rupture depths for all four fault planes mainly range from 2.0 km to 7.5 km, comparatively shallower than previous results up to ~13 km, and that the slip distribution on the fault plane is complex, exhibiting three slip peaks with a maximum of 2.44 m at a depth between 4.1 km and 4.9 km. The inverted geodetic moment is 3.85 × 10(18) Nm (Mw 6.36). The 2009 event may rupture from the northwest to the southeast unilaterally, reaching the maximum at the central segment.

Earth surface deformation in the North China Plain detected by joint analysis of GRACE and GPS data.

Mass redistribution of the Earth causes variable loading that deforms the solid Earth. While most recent studies using geodetic techniques focus on regions (such as the Amazon basin and the Nepal Himalayas) with large seasonal deformation amplitudes on the order of 1-4 cm due to hydrologic loading, few such studies have been conducted on the regions where the seasonal deformation amplitude is half as large. Here, we use joint GPS and GRACE data to investigate the vertical deformation due to hydrologic loading in the North China Plain, where significant groundwater depletion has been reported. We found that the GPS- and GRACE-derived secular trends and seasonal signals are in good agreement, with an uplift magnitude of 1-2 mm/year and a correlation of 85.0%-98.5%, respectively. This uplift rate is consistent with groundwater depletion rate estimated from GRACE data and in-situ groundwater measurements from earlier report studies; whereas the seasonal hydrologic variation reflects human behavior of groundwater pumping for agriculture irrigation in spring, leading to less water storage in summer than that in the winter season. However, less than 20% of weighted root-mean-squared (WRMS) reductions were detected for all the selected GPS stations when GRACE-derived seasonal deformations were removed from detrended GPS height time series. This discrepancy is probably because the GRACE-derived seasonal signals are large-scale, while the GPS-derived signals are local point measurements.