The Dotson Ice Shelf has resisted acceleration and ice-front retreat despite high basal-melt rates and rapid disaggregation of the neighboring Crosson Ice Shelf. Because of this lack of acceleration, previous studies have assumed that Dotson is stable. Here we show clear evidence of Dotson's destabilization as it decelerates, contrary to the common assumption that ice-flow deceleration is synonymous with stability. Ungrounding of a series of pinning points initiated acceleration in the Upper Dotson in the early 2000s, which subsequently slowed ice flow in the Lower Dotson. Discharge from the tributary Kohler Glacier into Crosson increased, but non-proportionally. Using ICESat and ICESat-2 altimetry data we show that ungrounding of the remaining pinning points is linked to a tripling in basal melt rates between 2006-2016 and 2016-2020. Basal melt rates on Crosson doubled over the same period. The higher basal melt at Lower Dotson is consistent with the cyclonic ocean circulation in the Dotson cavity, which tends to lift isopycnals and allow warmer deep water to interact with the ice. Given current surface-lowering rates, we estimate that several remaining pinning points in the Upper Dotson will unground within one to three decades. The grounding line of Kohler Glacier will retreat past a bathymetric saddle by the late 2030s and merge into the Smith West Glacier catchment, raising concern that reconfiguration of regional ice-flow dynamics and new pathways for the intrusion of warm modified Circumpolar Deep Water could further accelerate grounding-line retreat in the Dotson-Crosson Ice Shelf System.

We develop a regional hydrological model that applies to arid and semi-arid regions, by explicitly considering the effect of irrigation on the hydrological processes. A new irrigation module is here integrated into the recently introduced Atmospheric and Hydrological Modelling System (AHMS) for the quantitative assessment of basin-scale hydrological response to climate change and the impact of anthropogenic activities on water resources. The land surface, channel routing and groundwater modules of the AHMS are extended here to incorporate the new module. We then apply the model to simulating the hydrological processes in the Yellow River Basin, an arid and semi-arid region where irrigation constitutes the most important source of water use. The model is calibrated and validated using in-situ and remote sensing observations. This study demonstrates the capability of the AHMS for regional hydrological modelling in arid and semi-arid basins where irrigation profoundly influences the water balance.

Holistic approaches are needed to investigate the capacity of current water resource operations and infrastructure to sustain water supply and critical ecosystem health under projected drought conditions. Drought vulnerability is complex, dynamic, and challenging to assess, requiring simultaneous consideration of changing water demand, use and management, hydrologic system response, and water quality. We are bringing together a community of scientists from the U.S. Geological Survey, National Center for Atmospheric Research, Department of Energy, and Cornell University to create an integrated human-hydro-terrestrial modeling framework, linking pre-existing models, that can explore and synthesize system response and vulnerability to drought in the Delaware River Basin (DRB). The DRB provides drinking water to over 15 million people in New York, New Jersey, Pennsylvania, and Delaware. Critical water management decisions within the system are coordinated through the Delaware River Basin Commission and must meet requirements set by prior litigation. New York City has rights to divert water from the upper basin for water supply but must manage reservoir releases to meet downstream flow and temperature targets. The Office of the Delaware River Master administers provisions of the Flexible Flow Management Program designed to manage reservoir releases to meet water supply demands, habitat, and specified downstream minimum flows to repel upstream movement of saltwater in the estuary that threatens Philadelphia public water supply and other infrastructure. The DRB weathered a major drought in the 1960s, but water resource managers do not know if current operations and water demands can be sustained during a future drought of comparable magnitude. The integrated human-hydro-terrestrial modeling framework will be used to identify water supply and ecosystem vulnerabilities to drought and will characterize system function and evolution during and after periods of drought stress. Models will be forced with consistent input data sets representing scenarios of past, present, and future conditions. The approaches used to unify and harmonize diverse data sets and open-source models will provide a roadmap for the broader community to replicate and extend to other water resource issues and regions.

Evidence based on sparse tree-ring data suggests a severe sustained drought occurred in the 2nd century CE that could have rivaled medieval period droughts in the Colorado River basin (Gangopadhyay et al. 2022). Most of these tree-ring data have been used in gridded drought reconstructions (Cook et al., 2010) which extend back to 1 CE over an area that includes the intermountain western US. However, the 2nd century drought has not been highlighted in prior studies given the sparseness of the data available for this time period. A new reconstruction of Colorado River flow based on these data documents a notably severe and sustained drought over much of the 2nd century (Gangopadhyay et al. 2022). While this reconstruction suggests that the drought exceeds the severity and duration of any drought in the past 2000 years, a complete assessment of the 2nd century drought is challenging due to the sparseness of data. In this poster presentation, we describe the tree-ring data available, along with other proxy data that provide evidence for the 2nd century drought and support its severity. In our conclusions, we discuss outstanding questions and thoughts for further work.

Geodetic altimeters provide unique observations of the river surface longitudinal profile due to their long repeat periods and densely spaced ground tracks. This information is valuable for calibrating hydraulic model parameters, and thus for producing reliable simulations of water level for flood forecasting and river management, particularly in poorly instrumented catchments. In this study, we present an efficient calibration approach for hydraulic models based on a steady-state hydraulic solver and CryoSat-2 observations. In order to ensure that only coherent forcing/observation pairs are considered in the calibration, we first propose an outlier filtering approach for CryoSat-2 observations in data-scarce regions using simulated runoff produced by a hydrologic model. In the hydraulic calibration, a steady-state solver computes the WSE profile along the river for selected discharges corresponding to the days of CryoSat-2 overpass. In synthetic calibration experiments, the global search algorithm generally recovers the true parameter values in portions of the river where observations are available, illustrating the benefit of dense spatial sampling from geodetic altimetry. The most sensitive parameters are the bed elevations. In calibration experiments with real CryoSat-2 data, validation performance against both Sentinel-3 WSE and in-situ records is similar to previous studies, with RMSD ranging from 0.43 to 1.14 m against Sentinel-3 and 0.60 to 0.73 against in-situ WSE observations. Performance remains similar when transferring parameters to a one-dimensional hydrodynamic model. Because the approach is computationally efficient, model parameters can be inverted at high spatial resolution to fully exploit the information contained in geodetic CryoSat-2 altimetry.

Snowpack accumulation in forested watersheds depends on the amount of snow intercepted in the canopy and its partitioning into sublimation, unloading, and melt. A lack of canopy snow measurements limits our ability to evaluate models that simulate canopy processes and predict snowpack and water supply. Here, we tested whether monitoring changes in wind-induced tree sway can enable snow interception detection and estimation of canopy snow water equivalent (SWE). We monitored hourly tree sway across six years based on 12 Hz accelerometer observations on two subalpine conifer trees in Colorado. We developed an approach to distinguish changes in sway frequency due to thermal effects on tree rigidity versus intercepted snow mass. Over 60% of days with canopy snow had a sway signal in the range of possible thermal effects. However, when tree sway decreased outside the range of thermal effects, canopy snow was present 93-95% of the time, as confirmed with classifications of PhenoCam imagery. Using sway tests, we converted significant changes in sway to canopy SWE, which was correlated with total snowstorm amounts from a nearby SNOTEL site (Spearman r=0.72 to 0.80, p<0.001). Greater canopy SWE was associated with storm temperatures between -7 C and 0 C and wind speeds less than 4 m/s. Lower canopy SWE prevailed in storms with lower temperatures and higher wind speeds. We conclude that monitoring tree sway is a viable approach for quantifying canopy SWE, but challenges remain in converting changes in sway to mass and further distinguishing thermal and mass effects on tree sway.

An analysis of concurrent extreme events of continental precipitation and Integrated Water Vapour Transport (IVT) is crucial to our understanding of the role of the major global mechanisms of atmospheric moisture transport, including that of the landfalling Atmospheric Rivers (ARs) in extratropical regions. For this purpose, gridded data on CPC precipitation and ERA-5 IVT at a spatial resolution of 0.5º were used to analyze these concurrent events, covering the period from Winter 1980/1981 to Autumn 2017. For each season, and for each point with more than 400 non-dry days, several copula models were fitted to model the joint distribution function of the two variables. At each of the analysed points, the best copula model was used to estimate the probability of a concurrent extreme. At the same time, within the sample of observed concurrent extremes, the proportion of days with landfalling ARs was calculated for the whole period and for two 15-year sub-periods, one earlier period and one more recent (warmer) period. Three metrics based on copulas were used to analyse carefully the influence of IVT on extreme precipitation in the main regions of occurrence of AR landfall. The results show that the probability of occurrence of concurrent extremes is strongly conditioned by the dynamic component of the IVT, the wind. The occurrence of landfalling ARs accounts for most of the concurrent extreme days of IVT and continental precipitation, with percentages of concurrent extreme days close to 90% in some seasons in almost all the known regions of maximum occurrence of landfalling ARs, and with percentages greater than 75% downwind of AR landfall regions. This coincidence was lower in tropical regions, and in monsoonal areas in particular, with percentages of less than 50%. With a few exceptions, the role of landfalling ARs as drivers of concurrent extremes of IVT and continental precipitation tends to show a decrease in recent (warmer) periods. For almost all the landfalling AR regions with high or very high probabilities of achieving a concurrent extreme, there is a general trend towards a lower influence of IVT on extreme continental precipitation in recent (warmer) periods.

Global groundwater volumes in the upper 2 km of the Earth’s continental crust – critical for water security – are well estimated. Beyond these depths, a vast body of largely saline and non-potable groundwater exists down to at least 10 km —a volume that has not yet been quantified reliably at the global scale. Here, we estimate the amount of groundwater present in the upper 10 km of the Earth’s continental crust by examining the distribution of sedimentary and cratonic rocks with depth and applying porosity-depth relationships. We demonstrate that groundwater in the 2-10 km zone (what we call ‘deep groundwater’) has a volume comparable to that of groundwater in the upper 2 km of the Earth’s crust. These new estimates make groundwater the largest continental reservoir of water, ahead of ice sheets, provide a basis to quantify geochemical cycles, and constrain the potential for large-scale isolation of waste fluids.

Moisture recycling via evapotranspiration (ET) is often invoked as a mechanism for the high deuterium excess signals observed in continental precipitation (dP). However, a global-scale analysis of precipitation monitoring station isotope data shows that metrics of ET contributions to precipitation (van der Ent et al., 2014) explain little dp variability on seasonal timescales. This occurs despite the fact that ET contributions increase by ~50% in continental locations such as the Eurasian interior from wet to dry seasons. To explain this apparent paradox, we hypothesize that the effects of ET on dP are dampened during dry seasons due to contributions from isotopically-evolved residual water storage that act to lower the d-excess of ET fluxes (dET), in combination with changes in transpiration fraction (T/ET). To test this hypothesis, we develop a parsimonious two-season (wet, dry) model for dET incorporating residual water storage and ET partitioning effects. We find that in environments with limited water storage, such as shallow-rooted grasslands, dry season dET is lower than wet season dET despite lower relative humidity. As global average ratios of annual water storage to precipitation are relatively low (Guntner et al., 2007), these dynamics may be widespread over continents. In environments where water storage is not limiting, such as groundwater-dependent ecosystems, dry season dET is still likely lower; however, this effect arises instead due to higher seasonal T/ET when energy-driven plant water use is enhanced and surface evaporation is relatively limited by water availability. Together, these analyses also indicate multiple mechanisms by which dET may be lower than dp during the same season, challenging the view that moisture recycling feedback increases the dp in continental interiors. This work demonstrates the potential complexity of seasonal dp dynamics and cautions against simple interpretations of dP as a process tracer for moisture recycling. References: Guntner et al., 2007. Water Resour. Res., 43, W05416. van der Ent et al., 2014. Earth Syst. Dynam., 5, 471–489.

We examined the effect of land cover on stream discharge in hilly catchment streams during extreme rain events. Three years of rainfall-runoff observations, between January 2014 and December 2016, were collected in eleven neighbouring catchments. Each catchment was dominated by a different land cover, namely natural shola forests, natural grasslands and wattle (Acacia mearnsii). Rain intensities between percentiles 25-90, 90-95 and over 95 were categorised as light, heavy and extreme and were used to study stream discharge responses. Land cover significantly influenced the hydrologic response to extreme rain events. During light rains (< 38 mm/day), grassland dominated catchments showed higher discharge than shola (0.01 mm/s) and wattle (0.004 mm/s). However, during extreme rain events (> 71 mm/day) discharge was significantly higher in wattle dominated catchments when compared to the natural shola (0.033 mm/s) and grasslands (0.023 mm/s). Antecedent moisture conditions played a major role in determining peak flows along with rainfall, catchment shape and drainage density.

Optical televiewer borehole logging within a crevassed region of fast-moving Store Glacier, Greenland, revealed the presence of 35 high-angle planes that cut across the background primary stratification. These planes were composed of a bubble-free layer of refrozen ice, most of which hosted thin laminae of bubble-rich ‘last frozen’ ice, consistent with the planes being the traces of former open crevasses. Several such last-frozen laminae were observed in four traces, suggesting multiple episodes of crevasse reactivation. The frequency of crevasse traces generally decreased with depth, with the deepest detectable trace being 265 m below the surface. This is consistent with the extent of the warmer-than-modelled englacial ice layer in the area, which extends from the surface to a depth of ~400 m. Crevasse trace orientation was strongly clustered around a dip of 63° and a strike that was offset by 71° from orthogonal to the local direction of principal extending strain. The traces’ antecedent crevasses were therefore interpreted to have originated upglacier, probably ~8 km distant involving mixed-mode (I and III) formation. We conclude that deep crevassing is pervasive across Store Glacier, and therefore also at all dynamically similar outlet glaciers. Once healed, their traces represent planes of weakness subject to reactivation during their subsequent advection through the glacier. Given their depth, it is highly likely that such traces - particularly those formed downglacier - survive surface ablation to reach the glacier terminus, where they may represent foci for fracture and iceberg calving.

Concerns about water security often inform climate risk-related decisions made by environmentally focused investors (Porritt, 2001; Stern, 2006). Yet, potential liabilities for damage caused by extreme flood and drought events linked to global warming present risks that are not always reflected in share prices (Krosinsky et al., 2012). Considering the highly destructive nature of such events, we query whether companies, or specific sectors, could and should be held at least partially liable for their emission-releasing business activities. Recent articles (Rayer & Millar, 2018; Rayer et al., 2020) estimate that under a hypothetical climate liability regime, North Atlantic hurricane seasons might increasingly generate 1-2% losses on market capitalizations (or share prices) for the top seven carbon-emitting, publicly listed companies. In this paper, we extend the concept of the climate liability regime to estimate the impact of global flood- and drought-related damages on the share prices of nine fossil-fuel firms (including the seven mentioned by Rayer et al. (2020)). Following Rayer et al. (2020), we use incremental climate impacts and historical corporate emissions to estimate that climate change-related global flood and drought damages for the period of 2012 to 2016 amount to approximately 2-3% of the top nine carbon-emitting companies’ market capitalizations. We also include a discussion of moral responsibility and the proportion of obligations between producers and users. Quantifying impacts from extreme weather events increases salience and serves as an example of how science can identify and address the important business questions, pertinent to both investors and companies, that arise from a changing climate. References Krosinsky, C., Robins, N., & Viederman, S. (2012). Evolutions in sustainable investing. John Wiley & Sons. Porritt, J. (2001). The world in context. HRH The Prince of Wales’ Business and the Environment Programme, Cambridge. Rayer, Q. G., & Millar, R. J. (2018). Investing in Extreme Weather Conditions. Citywire Wealth Manager®, (429) 36. Rayer, Q., Pfleiderer, P., & Haustein, K. (2020). Global Warming and Extreme Weather Investment Risks. Palgrave Macmillan. https://doi.org/10.1007/978-3-030-38858-4_3 Stern, N. (2006). Stern Review executive summary. London.

In northern Fennoscandia, semi-alluvial boulder-bed channels with coarse glacial legacy sediment are abundant, and due to widespread anthropogenic manipulation during timber-floating, unimpacted reference reaches are rare. The landscape context of these semi-alluvial rapids— with numerous mainstem lakes that buffer high flows and sediment connectivity in addition to a regional low sediment yield— contribute to low amounts of fine sediment and incompetent flows to transport boulders. To determine the morphodynamics of semi-alluvial rapids and potential self-organization of sediment with multiple high flows, a flume experiment was designed and carried out to mimic conditions in semi-alluvial rapids in northern Fennoscandia. Two slope setups (2% and 5%) were used to model a range of flows (Q1 (summer high flow), Q2, Q10 & Q50) in a 8 x 1.1 m flume with a sediment distribution analogous to field conditions; bed topography was measured using structure-from-motion photogrammetry after each flow to obtain DEMs. No classic steep coarse-bed channel bedforms (e.g., step-pools) developed. However, similarly to boulder-bed channels with low relative submergence, at Q10 and Q50 flows, sediment deposited upstream of boulders and scoured downstream. Because the Q50 flow was not able to re-work the channel by disrupting grain-interlocking from preceding lower flows, transporting boulders, or forming channel-spanning boulders, the channel-forming discharge is larger than the Q50. These results have implications for restoration of gravel spawning beds in northern Fennoscandia and highlight the importance of large grains in understanding channel morphodynamics.

Rain belts in East Asia frequently pose threats to human societies and natural systems. Advances in a skillful forecast on heavy precipitation require a deeper understanding of the preconditioned environments and the hydrologic cycle. Here, we disentangle 15 dominant moisture channels along four corridors reaching the Somali Jet, South Asia, Bay of Bengal and Pacific basin for the warm-season rain belts. Among them, the Somali and South Asian channels were underappreciated in the literature. The results also highlight the importance of terrestrial moisture sources and the close relationship between the moisture pathways and rain belts' characteristics. Back-tracing the weather within a 2-week lead time reveals the pre-existing weather systems and circumglobal wave trains that govern the moisture channels. Findings from this work develop a better understanding of East Asian rain belts' water cycle and may offer insights into model evaluation and heavy rainfall prediction at a longer lead time.

Storage and subsequent release of water is a key function of catchments that moderates the impact of meteorological and climate extremes. Despite the fact that many key hydrological processes depend upon storage, there are relatively few studies that focus on storage itself. Storage is difficult to quantify due to catchment heterogeneity and the paucity of data on key catchment characteristics that largely determine storage, such as soil, hydrogeology, and topography. We adopt a multi-method approach to estimate the dynamic and extended dynamic storages using hydrometric data in 69 catchments in the Murray-Darling Basin in south-eastern Australia. We test relationships between the derived catchment storages and hydrological and physical characteristics that potentially control storage. The study catchments tended to have small dynamic storages relative to the extended dynamic storage; proportionally the dynamic storages were all less than 10\% of the extended dynamic storage. While storage estimates produced by the different methods and study catchments varied, the order in which they ranked was consistent. Correlations between catchment characteristics and estimates of storage were inconsistent; however, the results indicated that greater storage is strongly associated with steeper catchments and smoother hydrographs. This study highlights limitations in the current methodology to derive storage and the quality of widely applied hydrometric data. We reinforce the need to collect data that can validate storage estimates and call for new approaches that can broadly estimate storage at the catchment scale.

Construction with freeboard – vertical height of a structure above the minimum required – is commonly accepted as a sound investment for flood hazard mitigation. However, determining the optimal height of freeboard poses a major decision problem. This research introduces a life-cycle benefit-cost analysis (LCBCA) approach for optimizing freeboard height for a new, single-family residence, while incorporating uncertainty, and, in the case of insured homes, considering the costs from losses, insurance, and freeboard (if any) to the homeowner and National Flood Insurance Program (NFIP) separately. Using a hypothetical, case study home in Metairie, Louisiana, results show that adding 2 ft. of freeboard at the time of construction might be considered the optimal option given that it yields the highest net benefit, but the highest net benefit-cost ratio occurs for the 1 ft. freeboard. Even if flood loss reduction is not considered when adding freeboard, the savings in annual insurance premiums alone are sufficient to recover the construction costs paid by the homeowner if at least one foot of freeboard is included at construction. Collectively, these results based on conservative assumptions suggest that at the time of construction, even a small amount of freeboard provides a huge savings for the homeowner and (especially) for the financially-strapped NFIP. For community planners, the results suggest that wise planning with reasonable expectations on the front end makes for a more sustainable community.

For science to reliably support new discoveries, its results must be reproducible. This has proven to be a challenge in many fields including fields that rely on computational methods as a means for supporting new discoveries. Reproducibility in these studies is particularly difficult because they require open, documented sharing of data and models and careful control of underlying hardware and software dependencies so that computational procedures executed by the original researcher are portable and can be run on different hardware or software and produce consistent results. Despite recent advances in making scientific work more findable, accessible, interoperable and reusable (FAIR), fundamental questions in the conduct of reproducible computational studies remain: Can published results be repeated in different computing environments? If yes, how similar are they to previous results? Can we further verify and build on the results by using additional data or changing computational methods? Can these changes be automatically and systematically tracked? This presentation will describe our EarthCube project to advance computational reproducibility and make it easier and more efficient for geoscientists to preserve, share, repeat and replicate scientific computations. Our approach is based on Sciunit software developed by prior EarthCube projects which encapsulates application dependencies composed of system binaries, code, data, environment and application provenance so that the resulting computational research object can be shared and re-executed on different platforms. We have deployed Sciunit within the HydroShare JupyterHub platform operated by the Consortium of Universities for the Advancement of Hydrologic Science Inc. (CUAHSI) for the hydrology research community and will present use cases that demonstrate how to preserve, share, repeat and replicate scientific results from the field of hydrologic modeling. While illustrated in the context of hydrology, the methods and tools developed as part of this project have the potential to be extended to other geoscience domains. They also have the potential to inform the reproducibility evaluation process as currently undertaken by journals and publishers.

We investigate the flow-wise variation of the hydraulic conductivity inside a non-uniformly shaped fracture with permeable walls. Using lubrication theory for viscous flows, in conjunction with the Beavers–Joseph–Saffman boundary condition at the permeable walls, we obtain an analytical expression for the velocity profile, conductivity, and wall permeation velocity. These predictions highlight the effects of geometric variation (through the local slope of the aperture’s flow-wise variation), the permeability of the walls (through a dimensionless slip coefficient), and the effect of flow inertia (through a Reynolds number). The theory is validated against an OpenFOAM(R) solver for the Navier–Stokes equations subject to a tensorial slip boundary condition, showing good agreement. The mathematical results have implications on system-level (multiscale) modeling of hydraulically fractured reservoirs, in which the Darcy conductivity of each non-uniform passage must be accurately accounted for, throughout the fractured porous rock.

A simple yet flexible and robust algorithm is described for fully partitioning an arbitrary dataset into compact, non-overlapping groups or classes, sorted by size, based entirely on a pairwise similarity matrix and a user-specified similarity threshold. Unlike many clustering algorithms, there is no assumption that natural clusters exist in the dataset, though clusters, when present, may be preferentially assigned to one or more classes. The method also does not require data objects to be compared within any coordinate system but rather permits the user to define pairwise similarity using almost any conceivable criterion. The method therefore lends itself to certain geoscientific applications for which conventional clustering methods are unsuited, including two non-trivial and distinctly different datasets presented as examples. In addition to identifying large classes containing numerous similar dataset members, it is also well-suited for isolating rare or anomalous members of a dataset. The method is inductive, in that prototypes identified in representative subset of a larger dataset can be used to classify the remainder.

Water volume estimates of shallow desert lakes are the basis for water balance calculations, important both for water resource management and paleohydrology/climatology. Water volumes are typically inferred from bathymetry mapping; however, being shallow, ephemeral and remote, bathymetric surveys are scarce in such lakes. We propose a new, remote-sensing based, method to derive the bathymetry of such lakes using the relation between water occurrence, during >30-yr of optical satellite data, and accurate elevation measurements from the new Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2). We demonstrate our method at three locations where we map bathymetries with ~0.3 m error. This method complements other remotely sensed, bathymetry-mapping methods as it can be applied to: (a) complex lake systems with sub-basins, (b) remote lakes with no in-situ records, and (c) flooded lakes. The proposed method can be easily implemented in other shallow lakes as it builds on publically accessible global data sets.

Climate models generally project an increase in the winter North Atlantic Oscillation (NAO) index under a future high-emissions scenario, alongside an increase in winter precipitation in northern Europe and a decrease in southern Europe. The extent to which future forced NAO trends are important for European winter precipitation trends and their uncertainty remains unclear. We show using the Multimodel Large Ensemble Archive that the NAO plays a small role in northern European mean winter precipitation projections for 2080-2099. Conversely, half of the model uncertainty in southern European mean winter precipitation projections is potentially reducible through improved understanding of the NAO projections. Extreme positive NAO winters increase in frequency in most models as a consequence of mean NAO changes. These extremes also have more severe future precipitation impacts, largely because of mean precipitation changes. This has implications for future resilience to extreme positive NAO winters, which frequently have severe societal impacts.

As a result of uneven density of data collection, level-2 satellite gravimetry data suffer from global north-south striping. By applying various filtering methods, several studies have addressed the mitigation of the data. However, the studies mainly addressed the issue on a global scale, and the local effects were not considered. On the other hand, water research, especially inland hydrology, usually deals with small-scale fitures such as lakes and watersheds. Therefore, the local data de-striping methods need special attention. This research presents a new analytical method to de-stripe gravimetry data based on the spatial contrast of signals. The approach strikes a balance between de-striping and signal preservation. Using a-priori information obtained from the gravimetry data, the de-striping method first estimates the spatial gradient of the signal and optimizes a Poisson filter based on this information to de-stripe the data. Unlike the other approaches, the optimized filter is dynamic and accounts for temporal variations in the signal contrast, such as seasonality. The proposed approach is applied to ten globally distributed study areas to derive a general scheme. Detailed processes and evaluations are applied to two study areas: the Caspian Sea and the Congo River Basin. Results are visually assessed for spatial fit and for temporal consistency by comparison with results from other filters. The use of a dynamic filter set specified for each region and time point allows us to preserve local hydrologic signals that are susceptible to globally optimized filters. It also allows filter-related errors to be effectively constrained.

Thawing of ice-rich permafrost and subsequent ground subsidence can form characteristic landforms, and the resulting topography they create are collectively called “thermokarst”. The impact of wildfire on thermokarst development remains uncertain. Here we report on the post-wildfire ground deformation associated with the 2014 wildfire near Batagay, Eastern Siberia. We used Interferometric Synthetic Aperture Radar (InSAR) to generate both long-term (1-4 years) and short-term (sub-seasonal to seasonal) deformation maps. Based on two independent satellite-based microwave sensors, we could validate the dominance of vertical displacements and their heterogeneous distributions without relying on in-situ data. The inferred time-series based on L-band ALOS2 InSAR data indicated that the cumulative subsidence at the area of greatest magnitude was greater than 30 cm from October 2015 to June 2019, and that the rate of subsidence slowed in 2018. The burn severity was rather homogeneous, but the cumulative subsidence magnitude was larger on the east-facing slopes where the gullies were also predominantly developed. The correlation suggests that the active layer on the east-facing slopes might have been thinner before the fire. Meanwhile, C-band Sentinel-1 InSAR data with higher temporal resolution showed that the temporal evolution included episodic changes in terms of deformation rate. Moreover, we could unambiguously detect frost heave signals that were enhanced within the burned area during the early freezing season but were absent in the mid-winter. We could reasonably interpret the frost heave signals within a framework of premelting theory instead of assuming a simple freezing and subsequent volume expansion of pre-existing pore water.

In Mongolia, overuse and degradation of groundwater is a serious issue, mainly in the urban and economic hub, Ulaanbaatar, and the Southern Gobi mining hub. In order to explicitly quantify spatio-temporal variations in water availability, a process-based eco-hydrology model, NICE (National Integrated Catchment-based Eco-hydrology) (Nakayama and Watanabe, 2004), was applied to two contrasting river basins including these hubs. The authors built a high-resolution grid data representing water use for livestock, urban populations, and mining by combining a global dataset, statistical data, GIS data, observation data, and field surveys. The model simulated the effects of climatic change and human-induced disturbances on water resources during 1980-2018 (Nakayama et al., 2021). Although drinking by herders’ livestock had some impact on the hydrologic change, the groundwater level in the Tuul River was shown to have been extremely degraded by water use in Ulaanbaatar over the last few decades whereas that in the Galba River has declined markedly as a result of Oyu Tolgoi mining since 2010. Analysis of the relative contribution of environmental factors also helped us to separate the effects of climatic change and human activities on spatio-temporal change in the groundwater level. Further, they extended NICE to couple with inverse method for sensitivity analysis and parameter estimation of anthropogenic water uses (NICE-INVERSE). This new model quantified the spatio-temporal variations of livestock water use in these river basins (Nakayama, et al., in press). The livestock water use was generally small for each soum (district), and could also be heavily returned back to the ecosystems. The result also showed a temporal decreasing trend of unit water use in some typical livestock (cattle, sheep, and goats), suggesting a substantial increase in water stress due to local-regional eco-hydrological degradation by urbanization and mining. Sensitivity analysis and inverse estimation of model parameters helped to improve the accuracy of hydrologic budgets in basins. This methodology is powerful for evaluating spatio-temporal variations of water availability and supporting water management in regions with fewer inventory data.