In this work we employ a reduced-order basis of conservative chemical components to model reactive transport using a Lagrangian (particle tracking) method. While this practice is well-understood in the Eulerian (grid-based) context, its adaptation to a Lagrangian context requires a novel reformulation of particle transport properties. Because the number of conservative-species particles need not change during simulation, spatial resolution stays constant in time, and there is no increase in computational expense due to increasing numbers of product particles. Additionally, this treatment simplifies the interaction between equilibrium and kinetic reactions and allows the use of species-dependent transport operators at the same time. We apply this method to model a suite of simple test problems that include equilibrium and kinetic reactions, and results exhibit excellent match with base-case Eulerian results. Finally, we apply the new method to model a 2D problem concerning the mobilisation of cadmium by a CO$_2$ leak, showing the potential applicability of the proposed methodology.

SKB and several other waste management organizations have established the international SKB Task Force on Modeling of Groundwater Flow and Transport of Solutes (TF GWFTS) to support and interpret field experiments. Objectives of the task force are to develop, test and improve tools for conceptual understanding and simulating groundwater flow and transport of solutes in fractured rocks. Work is organized in collaborative modeling tasks. Task 9 focuses on realistic modeling of coupled matrix diffusion and sorption in heterogeneous crystalline rock matrix at depth, e.g. by inverse and predictive modeling of in-situ transport experiments. Posiva’s REPRO (rock matrix REtention PROperties) experimental campaign has been performed at the ONKALO rock characterization facility in Finland. The two REPRO experiments considered were the Water Phase Diffusion Experiment (WPDE), addressing matrix diffusion in gneiss around a single borehole interval (modeled in Task 9A), and the Through Diffusion Experiment, which is performed between sections of three boreholes and addressed by modeling in Task 9C. The Long-Term Diffusion and Sorption Experiment (LTDE-SD) was an in-situ radionuclide tracer test performed at the Swedish Äspö Hard Rock Laboratory at a depth of about 410 m below sea level. The experimental results indicated a possible deeper penetration of sorbing tracers into the rock matrix than expected. The shape of these tracer penetration profiles was difficult to reproduce. This experiment was modeled and interpreted in Task 9B. Task 9D is addressing the possible benefits of detailed models of the in-situ experiments in safety assessment calculations. The task is performed by upscaling of the WPDE models to conditions applicable for nuclear waste repositories. As Task 9 is now in a finalization process, a number of lessons learned from the 4 sub-tasks have been identified. These include: • field tracer experiments can provide surprises even when well designed and executed, • interaction between the experimentalists and modelers is important and mutually beneficial when investigating anomalous results, • differences in conceptual models have the greatest impact on model outcomes, • it is not trivial to go from modeling of field experiments to safety assessment modeling without making substantial simplifications.

This study was conducted to assess effect of tillage and mulch on soil erosion control in typical agroecological conditions of Benin. In addition, it involved also the assessment of soil moisture and runoff. The experiment was conducted on two sites in Central Benin during the short rain season of 2018. The effect of three tillage practices (contour ridging: CR; slope ridging: SR and no-tillage: NT) and three mulch doses (0 t.ha-1; 3 t.ha-1; and 7 t.ha-1) on soil erosion under maize was investigated at small experimental plots (21 m2). The 7Be method was used to assess the erosion rates, runoff was measured by total collection and soil moisture content was determined by thermo-gravimetric method. The results showed a significant decrease in runoff coefficient and soil loss while increase soil moisture under no-tillage and contour ridges compared to slope ridges. This effect was pronounced with greatest. 3 and 7 tha-1. Highest runoff coefficient and soil loss and the lowest soil moisture were observed under slope ridging without mulch (i.e. SR0M). The 7Be measurement showed high soil losses under SR0M (-10.19 t ha-1) at Dan and under NT0M (-7.36 t ha-1) at Za-zounmè. The treatments NT7M (0.80 t ha-1); SR7M (0.69 t ha-1); IR3M (2.07 t ha-1) and CR7M (4.05 t ha-1) showed deposition at Dan while SR7M (0.23 t ha-1) and CR7M (3.93 t ha-1) showed deposition at Za-zounmè. This study revealed useful information to be taken into consideration when developing soil and water conservation management strategies in Benin.

Geological Carbon Sequestration mitigates climate change by capturing and storing carbon emissions in deep geologic formations. Dissolution trapping is one mechanism by which CO2 can be trapped in a deep formation. However, heterogeneity can significantly influenced dissolution efficiency. This work addresses the injection of CO2 in perfectly stratified saline formations under uncertainty. Monte Carlo two-phase flow compositional simulations involving the dissolution of CO2 into brine and evaporation of water into the CO2-rich phase are presented. We systematically analyzed the interplay between heterogeneity and buoyant forces, which is shown to control the migration of the CO2 plume as well as the temporal evolution of dissolution efficiency. Results show that when buoyant forces are important, vertical segregation controls the overall behavior of CO2, diminishing the influence of small-scale heterogeneity on dissolution. However, when buoyant forces are relatively small compared to the degree of heterogeneity, CO2 migrates preferentially through high permeability layers and dissolution efficiency increases with heterogeneity due to the stretching of the CO2 plume that enhances mixing. As a result, in this situation, the upscaling of permeability leads to an underestimation of the dissolution efficiency. A review of field sites shows that dissolution is heterogeneity-controlled in most real systems. Knowing that most numerical models cannot afford to represent heterogeneity at an adequate scale, results indicate that dissolution efficiency can be typically underestimated by a factor close to 1.5.

Mathematical models for stream depletion typically use the constant-head Dirichlet boundary condition or the general Robin boundary condition at the stream. Both approaches fix stream stage as constant during pumping. Fixed the stream stage implies the stream acts as an infinite water source with depletion affecting stream discharge but having no impact on stream stage. We refer to this depletion without drawdown as the “depletion paradox.” It is a glaring model limitation, ignoring the most observable adverse effect of long-term groundwater abstraction near a stream – dry streambeds. Our field data demonstrate that stream stage responds to pumping near the stream. This motivates the development of a model considering transient stream drawdown using the concepts of finite stream storage and mass continuity at the stream-aquifer interface. The models include the cases for fully- and non-penetrating the stream. First-order mass transfer is also assumed across the streambed. The proposed model reduces to the fixed-stage model as stream storage becomes infinitely large and the confined flow case with a no-flow boundary at the streambed when stream storage vanishes. Sensitivity analysis for hydraulic properties of the stream-aquifer system is also included. Our results suggest that fixed-stage models (a) underestimate late-time aquifer drawdown to pumping adjacent to a stream and (b) overestimate the available groundwater supply from streams to pumping wells because of the infinite stream storage assumption. This can have significant implications for the sustainable management of water resources in interacting stream-aquifer systems with heavy groundwater abstraction.

Subsurface tile drainage (TD) is a dominant agriculture water management practice in the United States (US) to enhance crop production in poorly-drained soils. Assessments of field- or watershed-level (<50 km2) hydrologic impacts of tile drainage are becoming common; however, a major gap exists in our understanding of regional (>105 km2) impacts of tile drainage on hydrology. The National Water Model (NWM) is a distributed 1-km resolution hydrological model designed to provide accurate streamflow forecasts at 2.7 million reaches across the US. The current NWM lacks tile drainage representation which adds considerable uncertainty to streamflow forecasts in tile-drained areas. In this study, we quantify the performance of the NWM with a newly incorporated tile drainage scheme over the heavily tile-drained Midwestern US. Implementing a tile drainage scheme enhanced the uncalibrated model performance by about 20% to 50% of the calibrated NWM (Calib). The calibrated NWM with tile drainage (CalibTD) showed enhanced accuracy with higher event hit rates and lower false alarm rates than Calib. CalibTD showed better performance in high-flow estimations as tile drainage increased streamflow peaks (14%), volume (2.3%), and baseflow (11%). Regional water balance analysis indicated that tile drainage significantly reduced surface runoff (-7% to -29%), groundwater recharge (-43% to -50%), evapotranspiration (-7% to -13%), and soil moisture content (-2% to -3%). However, infiltration and soil water storage potential significantly increased with tile drainage. Overall, our findings highlight the importance of incorporating the tile drainage process into the operational configuration of the NWM.

Aquifer remediation with in situ soil washing techniques and enhanced oil removal typically involve the injection of liquid solutions into the geological formation to displace and mobilize non-aqueous phase liquids (NAPLs). The efficiency of these systems is oftentimes low because the displacing fluid bypasses large quantities of NAPL due to the inherent complexity of a heterogeneous natural system. Here, chaotic advection generated by a rotating periodic injection pulse is proposed as a method to enhance NAPL removal and mixing. To evaluate the method, we perform two-phase flow simulations in multiple realizations of random permeability fields with different correlation structures and connectivity between injection and extraction wells embedded in a five-spot pattern. Results show that chaotic advection can significantly improve removal efficiency and mixing depending on several controlling factors. Chaotic advection effects are more significant under unfavorable conditions, i.e., when injection and extraction wells are well-connected through preferential channels, permeabilities are highly heterogeneous, and/or the mobility ratio between the wetting and the non-wetting fluid is larger than one. Removal efficiency reaches its maximum value when the Kubo number is close to one, i.e., when the saturation front travels one range of the permeability field in an injection pulse. These effects can develop in just a few cycles. However, removal efficiency should undergo first an early stage with detrimental effects in order to maximize removal in the long term. Chaotic advection not only enhances NAPL removal and mixing, but also reduces the uncertainty, making the system more reliable and less dependent on heterogeneity.

Enhanced water management systems depend on accurate estimation of hydraulic properties of subsurface formations. This is while hydraulic conductivity of geologic formations could vary significantly. Therefore, using information only from widely spaced boreholes will be insufficient in characterizing subsurface aquifer properties. Hence, there is a need for other sources of information to complement our hydro-geophysics understanding of a region of interest. This study presents a numerical framework where information from different measurement sources is combined to characterize the 3-dimensional random field representing the hydraulic conductivity of a watershed in a Multi-Fidelity estimation model. Coupled with this model, a Bayesian experimental design will also be presented that is used to select the best future sampling locations. This work draws upon unique capabilities of electrical resistivity tests as well as statistical inversion. It presents a Multi-Fidelity Gaussian Processes (Kriging) model to estimate the geological properties in Upper Sangamon Watershed in east central Illinois, using multi-source observation data, obtained from electrical resistivity and pumping tests. We demonstrate the accuracy of Co-Kriging that is dependent on the locations and the distribution of both the high- and low-fidelity data, and also discuss its comparison with Single-High-Fidelity Kriging results. The uncertainties and confidence in the measurements and parameter estimates are then quantified and are in turn used to design future cycles of data collection to further improve the confidence intervals.

The U.S. Geological Survey and Sonoma County Water Agency (SCWA) are engaged in a cooperative project to characterize the hydrogeology of southern Sonoma Valley, a groundwater basin in the northern California Coast Ranges where groundwater represents about 60% of the valley’s water supply. The basin lies near the Sonoma volcanic field and major transverse faults of the San Francisco Bay region, resulting in a complex aquifer system comprising volcanic and sedimentary rocks and unconsolidated sediments that are cut by faults and overlain to the south by recent Bay Muds of San Francisco Bay. Geologic sections were constructed using geologic maps and lithologic data from over 1,500 water wells compiled by SCWA to describe the subsurface geologic configuration relative to groundwater pumping wells. This work suggests an aquifer system extending to about 900 feet below land surface (ft bls), consisting of upper and lower aquifer units separated by an intermediate unit with lower hydraulic conductivity, overlying and partly interfingering with a complex suite of volcanic rocks. SCWA constructed a four-layer hydrostratigraphic model of the basin using spatial trends in the lithologic data. The hydrostratigraphic layers defined by SCWA include multiple mapped geologic formations because of heterogeneity and complex interfingering between stratigraphic units. Water from selected wells was analyzed for specific conductance, major and minor ions, nutrients, stable isotopes, carbon isotopes, and tritium. Well data were categorized by completed perforation interval into shallow wells (< 200 ft bls), mid-depth wells (200–500 ft bls), and deep wells (> 500 ft bls). Shallow wells typically have water types related to recent mountain-front recharge, and, near the tidal marshlands north of San Pablo Bay, have high chloride and total dissolved solid concentrations associated with modern saline-water intrusion. Mid-depth and deep wells have water with poor water-quality, likely influenced by connate water from consolidated marine sediments, or a mixture of water from consolidated sediments and thermal water. This cooperative basin characterization of subsurface geology, hydrostratigraphy, and water chemistry will enable SCWA to make strategic water management decisions in Sonoma Valley.

Knowledge of soil properties is essential for risk assessment of vapor intrusion (VI). Data assimilation (DA) provides a valuable means to characterize contaminated sites by fusing the information contained in the measurement data (such as concentrations of volatile organic chemicals). Nevertheless, the application of DA in risk assessment of VI is quite limited. Moreover, soil heterogeneity is often overlooked in VI-related research. To fill these knowledge gaps, we apply a state-of-the-art DA method based on deep learning (DL), that is, ES(DL), to better characterize the contaminated sites in VI risk assessment. The effectiveness of ES(DL) is well demonstrated by three representative scenarios with increasing soil heterogeneity. The results clearly show that ignoring soil heterogeneity will significantly undermine one’s ability to make reasonable decisions in VI risk assessment. As a preliminary attempt of applying an advanced DA method in VI research, this work provides implications for the potential of using DL and DA in complex problems that couple hydrological and environmental processes.

Global change is a change in the planetary energy balance. It is usually expressed as a change in near-surface (2 m) air temperature (Ta), but changes to Ta represent only part of the atmospheric energy balance, which includes specific humidity (q) and more. We analyzed MERRA-2 reanalysis data and 15 Atmospheric Model Intercomparison Project (AMIP) models over the 1980-2014 period. Some 41%, 37%, and 49% of the near-surface atmosphere showed significant increases in ET, ESH, and E, respectively. The average increase in ET (ESH) was 10.6 J kg−1 year−1 (11.5 J kg−1 year−1) but AMIP models estimated that ET (14.5 J kg−1 year−1) exceeded ESH (13.7 J kg−1 year−1). Global near-surface Ta would have increased at more than twice the observed rate if energy was not partitioned into latent heat. Results demonstrate the critical role that q plays in recent changes to near-surface atmospheric energy.

Nutrient pollution is considered one of America’s most widespread, costly, and challenging environmental problems. Artificial Floating Islands (AFIs), a phytoremediation technology, has been proven as an efficient, environmental-friendly, and cost-effective strategy to address this issue. However, most previous studies of AFIs were done in controlled conditions at mesocosm experiments. In addition, limited information exists on the use of AFIs as a nutrient remediation/prevention strategy in Ohio. This study aims to fill these gaps. We are currently undertaking a combination of mesocosm and natural experiment to assess the nutrient-removal efficiency of AFI systems in the Milliron Research Wetlands (at the Ohio State University Mansfield campus), and establish a performance baseline for two native aquatic plant species, Carex comosa and Eleocharis palustris. In this study, 18 AFIs, 6 planted with Carex comosa, 6 with Eleocharis palustris, and 6 have no plants, were deployed in a section of the Milliron Research Wetlands. Physical and chemical parameters are being monitored bi-weekly. The AFI systems are constructed using PVC pipes to provide buoyance, EVA foam mats as platforms, and nylon nets to cover the system. Each AFI unit has nine luffa sponges, inserted in the foam mat, to hold aquatic plant seedlings, keep the moisture of roots, and enlarge the surface area for bacterial biofilm development. Since nutrient removal from the wetland is affected by numerous natural processes, a mesocosm experiment was set up to assist the quantification of nutrient removal due specifically to the presence of AFIs. The mesocosm experiment mimics the natural experiment at the wetland and contain 12 equal-size tanks containing water pumped directly from the wetland, 3 of which have AFIs with Carex comosa, 3 have Eleocharis palustris, 3 have no plants, and 3 contain just water from the wetland. Physical and chemical measurements (as well as sample collections) are performed weekly in the tanks. Water in the tanks are exchanged bi-weekly. Preliminary results show that the AFI systems quickly developed large root systems and extensive bacterial biofilms. The effects of the associations between plant biomass, biofilm development, and changing chemical and physical conditions will be investigated as the experiment progresses.

Over the last century, runoff from farms and cities, along with land cover and land use changes, have drastically altered the mass balance of nutrients in aquatic systems, affecting both their ecological functioning and the living communities they support. Here we present the results of a multi-year, long-term study designed to assess the control of land-use and hydrology on nutrient fate and transport within a mixed land-use watershed in north-central Ohio. A total of 64 streams (with a mix of urban, cropland, pasture, and forest catchments) have been sampled periodically since the summer of 2008. Hydrological conditions during the study period exhibited marked seasonality, with usually dry winter seasons (average ppt: 23.5±7.4 cm) and wet spring seasons (average ppt: 34.5±8.1 cm). Runoff generation in response to precipitation events is faster in streams draining developed catchments and slowest in forested streams, where runoff is generated only by events > 10 mm/day. Hydrologic connectivity in the watershed appear to be limited, since only about 25% of precipitation inputs were translated into quick flow. There is a significant, positive correlation between runoff and nutrient concentrations (R2 values are: 0.40 for streams draining urban landscapes, 0.34 for forested streams, 0.30 for cropland, and 0.28 for pastureland). We also observed significant inter-annual and seasonal variations on both DIN (p = 0.02) and PO4 concentrations (p < 0.01). Compared to dry years, nutrient fluxes during wetter years are, on average, 16% higher in urban catchments and 47% higher in forested catchments, but 32% lower in pasture-dominated catchments. Baseflow is responsible for only between 20-30% of the annual nutrient export from the watershed.

Inland waters are recognized as a significant source of CO2 to the atmosphere; however, the global magnitude of this flux remains uncertain. In particular, CO2 concentrations and fluxes in stream systems are extremely variable at scales of 10’s to 100’s of meters, complicating monitoring and prediction efforts. Thus, models of pCO2 that capture these scales of spatial variability are necessary for the accurate prediction and monitoring of stream CO2 fluxes. Despite a strong conceptual framework for the hydrologic processes that control stream CO2, predictive models to date have been empirical, based on Strahler stream order and regressions between observed pCO2 and landscape variables. We hypothesize that models incorporating well-described hydrologic processes may lead to new insights into the magnitude of various CO2 sources and improve predictions. Here, we develop and apply a process-based stream network model of CO2 based on NHDplus flowlines and driven by groundwater inputs, hyporheic exchange, water-column metabolism, advective transport, and atmospheric exchange. Model output is compared with 151 measurements of pCO2 (424 - 9718 ppm) collected in August, 2019 across the upper East River watershed in Gothic, CO, a mountainous, high-elevation headwaters system within the Colorado River basin. We find that modeled pCO2 captures observed spatial patterns and predicts measured values with a RMSE of ~250 ppm and R2 of 0.47 (p<10-15). Additionally, our process-based model performs significantly better than a multiple linear regression model between observations and a geomorphic variables (r2=0.35, p<10-7). Estimates from an optimized stream network model give additional insight into CO2 sources, suggesting that groundwater accounts for 70-80% of evasion fluxes, hyporheic processes for 20-30%, and water-column metabolism for ~1% across the East River watershed. The ability of our model to predict pCO2 at the spatial scales of variability may provide an important next step in estimating global CO2 fluxes, and future research will test the predictive power of process-based models at regional and global scales.

Lake sedimentation rate represents a synthetic metric of ecosystem functioning. Many localized studies have reported a significant association between land use/land cover changes and lake sediment mass accumulation rates, with a few global syntheses echoing these findings at larger scales. In the literature, studies evaluating lead-210 (210Pb) for establishing sediment chronologies will report at least one of three dating models, but the constant rate of supply (C.R.S.) model is the most widely used. However, it is often unclear how or why this model is selected, despite its influence on the interpretation of many subsequent analyses about ecosystem dynamics and functioning. It would thus be advantageous to design an objective and semi-automated way of choosing among dating models. We measured radioisotopic activities in 37 sediment cores across four ecozones of eastern Canada and developed an approach to assess model fit for the three commonly applied dating models. The derived chronologies were then used to evaluate the spatial and temporal variation in sedimentation rates across four ecozones in Canada (covering a surface area of 2.2 x 10^6 km2). We observed a recent increase in lake sedimentation rates across most lakes, as has been observed globally, albeit with significant differences in the magnitude of sedimentation rates across ecozones. Across all lakes, we found that regional human population counts and mean annual air temperatures were significant temporal predictors of variation in mass accumulation rates. Overall, this analytical framework offers an objective approach for assessing fit and selecting among sediment age models, which contributes to a more robust quantification of sedimentation rates. With this first application, we provide a quantitative assessment of how lake sedimentation rates vary across a northern lake-rich region and have responded to environmental change.

We hypothesize that onshore saline groundwater in delta systems may have resulted from rapid shoreline progradation during the Holocene. To explore this hypothesis, we develop a model for the transport of saline groundwater in a shore-normal longitudinal cross-section of an evolving ocean margin. The transport model uses a control volume finite element model (CVFEM), where the mesh of node points evolves with the changing aquifer geometry while enforcing local mass balance around each node. The progradation of the shoreline and evolution of the aquifer geometry is represented by assuming the shoreline advances at a prescribed speed with fixed top and foreset slopes. The combined model of transport and progradation, is used to predict the transient trapping of saline water under an advancing shore-line across a range of realistic settings for shoreline velocity and aquifer hydraulic properties. For homogeneous aquifers, results indicate that the distance behind the shoreline, over which saline water can be detected, is controlled by the ratio of the shoreline prorogation rate to the aquifer velocity and the Peclet number. The presence of confining units probably had the greatest impact in sequestering onshore seawater behind an advancing shoreline. Further support for the validity of the proposed model is provided by fitting model predictions to data from two field sites (Mississippi River and Bengal Deltas); the results illustrate consistent agreement between predicted and observed locations of fossil seawater.

New Caledonia owns about 25% of the world’s nickel resources, and around 9% of the world’s reserves, distributed over 300,000 hectares of concessions allocated to date (18% of the total surface of the main island). Supergene weathering of ultramafic rocks have led to the genesis of lateritic nickel-rich ores of garnierite type (NiO> 1.5%) and / or iron oxi-hydroxide type (NiO <1.5%) under tropical lateritic conditions that have prevailed over 30 millions of years. These conditions have shaped the landscapes while offering Ni-rich regolith easy to exploit by open pit mining. Since 1880, nickel has been so far used as an economic driver and a societal development impetus. Since 1998, three worldwide projects have been developed, using pyrometallurgy (Ni-Si) and more recently hydrometallurgy (Ni-Fe) ore processes. However, natural erosion, anthropogenic disturbances (climate change, fires, urbanization, mining) can add up to disrupt the whole terrestrial and marine ecosystem functioning at the regional scale.This critical mined zone is covered by terrestrial ecosystems of great endemic biodiversity and adjoining a lagoon that has been listed as a UNESCO World Heritage Site in 2008. Such ecosystems are a valuable natural resource for the sustainable future for the next generations. Are mining and preserving ecosystems compatible, and for what economic and societal model? The conference reviews a collective research approach (mining, terrestrial and marine ecosystems impacts, restoration, biorecycling) to address this question. The corpus of acquired knowledge allows to propose an inclusive model of responsible mining activity, based on the “co-valorization” of both non-renewable and renewable primary resources through the development of circular economy and bio-economy principles, and applied all along the “mining ecosystem” project management. Considering i)the present day low GDP input of nickel mining in New Caledonia, the 98% dependency rate from fossil sources of energy, the CO2 emissions and the volatile Ni-market international context, this model, if followed, will reinforce the societal cohesion and develop a sustainable economy diversification, while enhancing energy transition and a better ecological efficiency.

We use numerical solutions of the Richard’s Equations for 3D porous media to investigate the influence of agricultural subsurface drainage as a hydrologic process and its effect on the hydrologic regime of a watershed. Specifically, we determine the relation between subsurface seepage and subsurface storage in hillslopes with (drained) and without (undrained) subsurface drainage. Simulations are performed in Hydrus3D and the output is analyzed with MATLAB’s curve fitting tools, to create simple ordinary differential equations that represent the relationship between subsurface flow and subsurface storage for hillslopes of varying topographical gradients and shapes. We have determined an ‘activation point’ below which the seepage/storage relationship is roughly linear, and above which the drained and undrained simulations behave according to different nonlinear functional forms. Although the seepage/storage relationship of flat hillslopes have parametric consistencies independent of the hillslope gradient, the addition of curvature increases the complexity. In this work, we describe approximations to account for curved hillslopes. From our formulation, subsurface flow for varying hillslopes can be approximated using only the water storage and the topography of the hillslope. Reducing the system from partial differential equations (Hydrus) to ordinary differential equations improves scalability of the model. Simplified equations are used to study the consequences of large-scale changes in agricultural landscapes due to subsurface drainage.

In the last decades, the urbanization process and population growth resulted in a substantial increase of water consumption for agricultural, industrial, and residential purposes. The characterization of the interplay between environmental variables and water resources plays a critical role for establishing effective water management policies. In this paper, we apply the Canonical Correlation Analysis (CCA) in a set of climate and hydrological indicators to investigate the behavior of these environmental variables over time in different geographical regions of California, as well as the relationship among these regions. CCA served as base to establish a temporal graph that models the relation between the stations over time, and advanced graph visualization techniques are used to produce patterns that aids in the comprehension of the underlying phenomena. Our results identified important temporal patterns, such as heterogeneous behavior in the dry season and lower correlation between the stations in La Niña years. We show that the combination of CCA and visual analytics can assist water experts in the identification of important climate and hydrological events in different scenarios.

Future projections of sea-level rise used to assess coastal flooding hazards and exposure throughout the 21st century and devise risk mitigation efforts often lack an accurate estimate of coastal Vertical Land Motion (VLM) rate, driven by anthropogenic and non-climate factors in addition to climatic factors. The Chesapeake Bay (CB) region of the United States is experiencing one of the fastest rates of relative sea-level rise on the Atlantic coast of the United States. This study uses a combination of space-borne Interferometric SAR (InSAR), Global Navigation Satellite System (GNSS), Light Detecting and Ranging (LIDAR) datasets, available National Oceanic and Atmospheric Administration (NOAA) long term tide gauge data, and sea-level rise projections from the Intergovernmental Panel on Climate Change (IPCC), AR6 WG1 to quantify the regional rate of RSLR and future flooding hazards for the years 2030, 2050, and 2100. By the year 2100, the total inundated areas from SLR and subsidence are projected to be 454-600 for Shared Socioeconomic Pathways (SSPs) 1-1.9 to 5-8.5 respectively, and 343-627 only from SLR. The effect of storm surges based on Hurricane Isabel can increase the inundated area to 849-1117 km2 under different VLM and SLR scenarios. We present that accurate estimates of the VLM rate, such as those obtained here, are essential to revise IPCC projections and obtain accurate maps of coastal flooding and inundation hazards. The results provided here inform policymakers when assessing hazards associated with global climate changes and local factors in CB, required for developing risk management and disaster resilience plans.

We revisited the June, 2010 - October, 2011 Guy-Greenbrier earthquake sequence in central Arkansas using PhaseNet, a deep neural network trained to pick P and S arrival times. We applied PhaseNet to continuous waveform data and used phase association and hypocenter relocation to locate nearly 90,000 events. Our catalog suggests that the sequence consists of two adjacent earthquake sequences on the same fault and that the second sequence may be associated with the wastewater disposal well to the west of the Guy-Greenbrier Fault, rather than the wells to the north and the east that were previously implicated. We find that each sequence is comprised of many small clusters that exhibit diffusion along the fault at shorter time scales. Our study demonstrates that machine learning based earthquake catalog development is now feasible and will yield new insights into earthquake behavior.

Water scarcity, population growth and climate change dilemmas imperatively require adaption strategies for a more efficient and sustainable use of water resources. Agricultural systems are part of a wider network, where all social, economic and, ecologic parameters must be taken into consideration to assess the performance and resilience of said network. The importance of accounting the complexity of human decisions and their impact on the water cycle has been increasingly studied, nevertheless the integration and analysis of different decision making theories into hydrological models still remains a major challenge and uncertainty source. Therefore, the ongoing project is aimed to improve the understanding of social dynamics in agrohydrological networks by assessing different irrigation practices including rainfed agriculture and deficit irrigation within a hydro-economic network. We developed an agent-based model (ABM) of farmer decision making on crop water productivity and groundwater levels using two existing optimization models: (i) the Assessment, Prognosis, Planning and Management Tool (APPM) (Schmitz, et al. 2010) that integrates the complex interactions of the strongly nonlinear meteorological, hydrological and agricultural phenomena, considering the socio-economic aspects and (ii) the Deficit Irrigation Toolbox (DIT) (Schütze and Mialyk 2019) to maximize crop-water productivity by analyzing the crop yield response to climate change, soil variability, water management practices. The developed ABM was assessed with the different theories on human decision-making based on the Modelling Human Behavior (MoHuB) framework (Schlüter, et al. 2017). As a result of this study, a sensitivity analysis of how different behavioral theories affect the dynamics of social-ecological systems which enables the evaluation of the robustness of policy implementation to different assumptions of human behavior where cooperation is a mechanism to improve resilience. This research was funded by the Technische Universität Dresden, by means of the Excellence Initiative by the German Federal and State Governments.

Students K-16 in the United States and Canada joined their GLOBE Program peers from across the world in collecting water quality measurements during a week-long data-collection period in September, led by the GLOBE Africa Regional Coordination Office. The project was built off of other GLOBE collaborations around spring phenology measurements (Europe) and expeditions to Mt. Kilimanjaro and Lake Victoria (Africa). The efforts and resulting analysis of Collaboration: Water were supported by an international team of scientists, faculty and education professionals. The GLOBE Program Country Coordinators from the U.S. and Canada share the project goals, discuss the results of the September data challenge and how these lead into the community-based collaboration projects being developed between schools. Some of the projects will be presented during the International Virtual Science Symposium and Student Research Symposia in spring 2020. This project works on several levels. It creates resiliency locally through community-based inquiry, supports the development of 21st Century critical thinking, collaboration and communication skills and places the community investigations into the global context of the United Nations Sustainable Development Goal 6 (Clean Water and Sanitation). Along with tools, templates and the benefits of participation, the presenters will share how other communities can be involved in the March data collection event.

It is now widely understood that seasonal snow cover in the Western United States is melting earlier than in past decades. This could have significant consequences for human populations and ecosystems dependent on regularity in timing and magnitude of downstream flows that originate as snow. However, while earlier melt is well established, less is known about intra-annual changes in the spatial and temporal distribution of accumulation and ablation (melt) cycles in the core winter months and spring months, i.e. the ‘persistence’ of seasonal snow cover. This is significant because changes to the persistence of seasonal snow in the winter and spring could have important implications for other snow cover characteristics such as albedo, as well as ancillary hydrologic factors such as soil moisture and runoff. To understand these changes in persistence, this project focuses on study basins in different climatic zones of the Columbia river basin, capturing the shift from maritime snowpack in the west to alpine snowpack in the east. The research relies on a combination of time series analysis of NRCS SNOTEL stations and snow courses and use of an optical remote sensing product which is based on the MODIS MOD10A1 dataset. To compensate for significant winter and spring cloud cover, particularly in the Pacific Northwest, a temporal and spatial gap filling approach utilizing higher spatial resolution products (e.g. Landsat and Sentinel 2) is implemented primarily in Google Earth Engine. The seasonal snow persistence from the MODIS-based product is evaluated using additional Landsat, Sentinel 2 and Planet Labs data, as well as data from the in situ monitoring stations. Finally, changes in intra-annual seasonal snow cover persistence are characterized for core winter, spring and early summer months along an elevational gradient and across study sub-basins.