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.
Current approaches to estimate NOx emissions fail to account for new and small sources, biomass burning, and sources which change rapidly in time, generally don’t account for measurement error, and are either based on models, or do not consider wind, chemistry, and dynamical effects. This work introduces a new, model-free analytical environment that assimilates daily TROPOMI NO2 measurements in a mass-conserving manner, to invert daily NOx emissions. This is applied over a rapidly developing and energy-consuming region of Northwest China, specifically chosen due to substantial economic and population changes, new environmental policies, large use of coal, and access to independent emissions measurements for validation, making this region representative of many rapidly developing regions found across the Global South. This technique computes a net NOx emissions gain of 70% distributed in a seesaw manner: a more than doubling of emissions in cleaner regions, chemical plants, and regions thought to be emissions-free, combined with a more than halving of emissions in city centers and at well-regulated steel and powerplants. The results allow attribution of sources, with major contributing factors computed to be increased combustion temperature, atmospheric transport, and in-situ chemical processing. It is hoped that these findings will drive a new look at emissions estimation and how it is related to remotely sensed measurements and associated uncertainties, especially applied to rapidly developing regions. This is especially important for understanding the loadings and impacts of short-lived climate forcers, and provides a bridge between remotely sensed data, measurement error, and models, while allowing for further improvement of identification of new, small, and rapidly changing sources.
Sediment trapping behind dams is currently a major source of bias in large-scale hydro-geomorphic models, hindering robust analyses of anthropogenic influences on sediment fluxes in freshwater and coastal systems. This study focuses on developing a new reservoir trapping efficiency (Te) parameter to account for the impacts of dams in hydrological models. This goal was achieved by harnessing a novel remote sensing data product which offers high-resolution and spatially continuous maps of suspended sediment concentration across the Contiguous United States (CONUS). Validation of remote sensing-derived surface sediment fluxes against USGS depth-averaged sediment fluxes showed that this remote sensing dataset can be used to calculate Te with high accuracy (R2 = 0.98). Te calculated for 116 dams across the CONUS, using upstream and downstream sediment fluxes from their reservoirs, range from 0.3% to 98% with a mean of 43%. Contrary to the previous understanding that large reservoirs have larger Te and vice versa, these data reveal that large reservoirs can have a wide range of Te values. A suite of 21 explanatory variables were used to develop an empirical Te model using multiple regression. The strongest model predicts Te using five variables: dam height, incoming sediment flux, outgoing water discharge, reservoir length, and Aridity Index. A global model was also developed using explanatory variables obtained from a global dam database to conduct a global-scale analysis of Te. These CONUS- and global-scale Te models can be integrated into hydro-geomorphic models to more accurately predict river sediment transport by representing sediment trapping in reservoirs.
This paper presents a new coupled urban change and hazard consequence model that considers population growth, a changing built environment, natural hazard mitigation planning, and future acute hazards. Urban change is simulated as an agent-based land market with six agent types and six land use types. Agents compete for parcels with successful bids leading to changes in both urban land use – affecting where agents are located – and structural properties of buildings – affecting the building’s ability to resist damage to natural hazards. IN-CORE, an open-source community resilience model, is used to compute damages to the built environment. The coupled model operates under constraints imposed by planning policies defined at the start of a simulation. The model is applied to Seaside, Oregon, a coastal community in the North American Pacific Northwest subject to seismic-tsunami hazards emanating from the Cascadia Subduction Zone. Ten planning scenarios are considered including caps on the number of vacation homes, relocating community assets, limiting new development, and mandatory seismic retrofits. By applying this coupled model to the testbed community, we show: (1) placing a cap on the number of vacation homes results in more visitors in damaged buildings, (2) that mandatory seismic retrofits do not reduce the number of people in damaged buildings when considering population growth, (3) polices diverge beyond year 10 in the model, indicating that many policies take time to realize their implications, and (4) the most effective policies were those that incorporated elements of both urban planning and enforced building codes.
Global Sensitivity Analysis (GSA) has long been recognized as an indispensable tool for model analysis. GSA has been extensively used for model simplification, identifiability analysis, and diagnostic tests, among others. Nevertheless, computationally efficient methodologies are sorely needed for GSA, not only to reduce the computational overhead, but also to improve the quality and robustness of the results. This is especially the case for process-based hydrologic models, as their simulation time is often too high and is typically beyond the availability for a comprehensive GSA. We overcome this computational barrier by developing an efficient variance-based sensitivity analysis using copulas. Our data-driven method, called VISCOUS, approximates the joint probability density function of the given set of input-output pairs using Gaussian mixture copula to provide a given-data estimation of the sensitivity indices. This enables our method to identify dominant hydrologic factors by recycling pre-computed set of model evaluations or existing input-output data, and thus avoids augmenting the computational cost. We used two hydrologic models of increasing complexity (HBV and VIC) to assess the performance of the proposed method. Our results confirm that VISCOUS and the original variance-based method can detect similar important and unimportant factors. However, while being robust, our method can substantially reduce the computational cost. The results here are particularly significant for, though not limited to, process-based models with many uncertain parameters, large domain size, and high spatial and temporal resolution.
In support of the American College & University Presidents’ Climate Leadership Commitments, the University of Maryland College Park (UMD) has established a goal to become climate neutral by 2050. While much progress has been made to lower the University’s carbon footprint across multiple emissions sectors, tree conservation or restoration has traditionally been excluded due to concerns about the reliability and consistency of the science. For the past several years, faculty and students in UMD’s Department of Geographical Sciences have been working with state governments across the region to inform climate action planning with advanced forest carbon science. However, with student support and leadership, we identified an opportunity to retool this same science to help UMD “walk the walk” and advance our own forest climate goals in parallel with Maryland and other U.S. Climate Alliance states. By partnering with the Office of Sustainability and other land management entities, we have been able to directly inform the campus climate action plan with robust forest carbon estimates as well as influence and support the carbon budgeting process of all universities that have pledged support for the “Carbon Commitment.” Unlike state governments, the university’s approach to sustainability broadly follows that of a corporation, requiring enhanced collaboration to ensure the science is provided in user-relevant formats while remaining consistent with science approaches utilized by state partners. Our experience during the first year of this project underscores the value of building out scientific approaches that meet specific stakeholder needs while remaining poised to adapt these tools in support of new partnerships and collaborations.
International frameworks for climate mitigation that build from national actions have been developed under the United National Framework Convention on Climate Change and advanced most recently through the Paris Climate Agreement. In parallel, sub-national actors have set greenhouse gas (GHG) reduction goals and developed corresponding climate mitigation plans. Within the U.S., multi-state coalitions have formed to facilitate coordination of related science and policy. Here, utilizing the forum of the NASA Carbon Monitoring System’s Multi-State Working Group (MSWG), we collected and reviewed climate mitigation plans for 11 states in the Regional Greenhouse Gas Initiative (RGGI) region of the Eastern U.S. For each state we reviewed the 1) policy framework for climate mitigation, 2) GHG reduction goals, 3) inclusion of forest carbon in the state’s climate action plan, 4) existing science used to estimate forest carbon, and 5) stated needs for carbon monitoring science. Across the region, we found important differences across all categories. While all states have GHG reduction goals and framework documents, nearly three-quarters of all states do not account for forest carbon when planning GHG reductions; those that do account for forest carbon use a variety of scientific methods with various levels of planning detail and guidance. We suggest that a common, efficient, standardized forest carbon monitoring system would provide important benefits to states and the geographic region as a whole. In addition, such a system would allow for more effective transparency and progress tracking to support state, national, and international efforts to increase ambition and implementation of climate goals.
In continuous permafrost regions, pathways for transport of sub-permafrost groundwater to the surface sometimes perforate the frozen ground and result in the formation of a pingo. Explanations offered for the locations of such pathways have so far included hydraulically conductive geological units and faults. On Svalbard, several pingos locate at valley flanks where these controls are apparently lacking. Intrigued by this observation, we elucidated the geological setting around such a pingo with electrical resistivity tomography. The inverted resistivity models showed a considerable contrast between the uphill and valley-sides of the pingo. We conclude that this contrast reflects a geological boundary between low-permeable marine sediments and consolidated strata. Groundwater presumably flows towards the pingo spring through glacially induced fractures in the strata immediately below the marine sediments. Our finding suggests that flanks of uplifted Arctic valleys deserve attention as possible discharge locations for deep groundwater and greenhouse gasses to the surface.
Permafrost degradation poses an increasingly serious threat of glacial lake outburst floodings (GLOFs) in the Tibetan Plateau. It is therefore of great practical significance to analyze the freeze-thaw state in moraine dams and associated impacts on dam stability. We simulated the soil temperature of the Longbasaba moraine dam based on the heat transfer module of COMSOL Multiphysics. The results show that the soil temperature of the moraine dam can be adequately simulated using the COMSOL Multiphysics heat transfer module and the simulated temperature values are generally consistent with the observed trends, yielding root mean square errors (RMSEs) less than 1.58 ℃ and Nash-Sutcliffe efficiency coefficients (NSEs) between 0.66 and 0.93. The average annual increase of the active layer depth was 0.026 m/a from 1959 to 2020. The buried ice inside the moraine dam was evidently melting and the maximum buried ice thawing depth under scenarios SSP1-2.6, SSP2-4.5, and SSP5-8.5 in CMIP6 (Coupled Model Intercomparison Project Phase 6) is expected to be 11.3 m, 18.4 m, and 23.5 m, respectively, by the end of the century, which indicates a continuous deterioration of the moraine dam stability.
Tidal currents are known to influence basal melting of Antarctic ice shelves through two types of mechanisms: local processes taking place within the boundary current adjacent to the ice shelf-ocean interface and far-field processes influencing the properties of water masses entering the cavity. The separate effects of these processes are poorly understood, limiting our ability to parameterize tide-driven ice shelf-ocean interactions. Here we focus on the small-scale processes within the boundary current and we apply a one-dimensional plume model to a range of ice base geometries characteristic of Antarctic ice shelves to study the sensitivity of basal melt rates to different representations of tide-driven turbulent mixing. Our simulations demonstrate that the direction of the relative change in melt rate due to tides depends on the approach chosen to parameterize entrainment of ambient water into the plume, a process not yet well constrained by observations. A theoretical assessment based on an analogy with tidal bottom boundary layers suggests that tide-driven shear at the ice shelf-ocean interface enhances mixing through the pycnocline. Under this assumption our simulations predict an increase in melt and freeze rates along the base of the ice shelf when adding tides into the model. An approximation is provided to account for this response in basal melt rate parameterizations that neglect the effect of tide-induced turbulent mixing
Abstract It has been debated globally that the COVID-19 lockdown had significantly diminished the emission levels of anthropogenic greenhouse gases (GHGs). However, different countries possess different footprints of GHGs emission. In regions with inconsistent air quality observation, spaceborne sensors can provide synoptic assessment of air quality with time-based environmental decision making. In this study, we utilised satellite data to quantify the temporal dynamics of carbon monoxide (CO) and nitrogen dioxide (NO2) between the pre-lockdown (January–March 2020), lockdown (April–July 2020) and post-lockdown (August–September 2020) periods in Nigeria. Periodic TROPOspheric Monitoring Instrument (TROPOMI) datasets were acquired from the Google Earth Engine Sentinel-5 Explorer and the Copernicus Open Access Hub. The Population-Weighted Mean Concentration (PWEC) of CO and NO2 was computed using raster-based population data and place-based air quality estimates. The associated economic correlates were computed using data mined from TROPOMI and available health records of Nigeria. Satellite data analysis showed that aggregate CO reduced by 35.1% (25.32⋅105 tons) and 9.06% (6.54⋅105 tons) and NO2 plummeted by 32.81% (22,500 tons) and 11.63% (5,360 tons) during the lockdown and post-lockdown periods across the 36 States of the country. While mobility rate dwindled substantially, mortality rate savings from the exposure to damaging effects of the GHGs were roughly $ 14 million (CO) and $10 million (NO2). The fluxes in CO and NO2 suggest that anthropogenic interference in air quality accounting can aid the understanding of the convoluted human–nature relationships for sustainable environmental management.
The insular Caribbean is a region influenced by Atlantic Ocean climate variability. Effects of low-frequency atmospheric circulation patterns on the precipitation of the Caribbean have been well documented. However, individual modes of variability are usually only considered in isolation. Here we analyse the combined and individual effects of the North Atlantic Oscillation (NAO) and the Atlantic Meridional Mode (AMM) on insular Caribbean precipitation. This work focuses on the Early Rainfall Season (ERS, April-July), which explains much of the interannual variability in precipitation for this region, from 1960-2016. Correlation analysis compare monthly NAO and AMM indices from the National Oceanic and Atmospheric Administration (NOAA) against monthly Caribbean precipitation from the Climate Research Unit (CRU) year-by-year climate variables by country. Sea surface temperature (SST) and sea level pressure (SLP) composites using NOAA data were also created to analyse regional patterns. Analysis of the results show that the NAO and AMM presented a correlation of opposite signs and affected the Eastern Caribbean (from Dominican Republic to Grenada) during ERS, resulting in precipitation anomalies above/below ± 10%. The combined and individual effects of NAO and AMM indicate that Feb-Mar NAO and AMM are significant correlated to May-Jun Eastern Caribbean precipitation anomalies. More frequent and consistent regional effects on precipitation anomalies, and more regionally spread and persistent SLP and SST were registered when both NAO and AMM occurred together in the previous winter. These results could be helpful in seasonal forecasting, by indicating whether a wetter or drier ERS would be expected based on the previous season NAO and AMM activity.
Critical freshwater resources lying within mid-latitude mountain glaciers are vulnerable to a rapidly changing climate. The Lehman Rock Glacier is the only extant glacier mapped within the Great Basin National Park in Nevada. As part of an effort to understand this specialized alpine environment, we have been studying this area and conducting observations with annual student research visitations since 2005. Deploying mixed methods including an embedded sensor network, paleoclimate reconstructions, hydrological observations, and unmanned aerial system (UAS) operations, our team has documented diverse evidence of climate change over interannual to millennial scales. Starting in 2015, we conducted annual surveys of the rock glacier to measure topographic changes. Initially, we used balloon-borne photogrammetry, capturing 600+ images over about 0.1 km2 at an altitude of 500m above ground level (AGL). Despite impartial terrain coverage (50-80%) caused by limited control of the balloon rig in the air, digital elevation modeling (DEM) differencing resolved a net volume loss of 5,300m3 between 2015 and 2016. Submission of a Certification Of Approval (COA) granted our team permission to fly a UAV for the first time within the National Park in 2018 and 2019 to map the rock glacier. UAS surveying over successive days in August with > 80% horizontal and vertical overlap helped achieved 100% coverage with 900+ photos. Using previous year’s DEMs, we have optimized autonomous flight planning at 80m AGL and 168m AGL at 8.5mh and 20kmh, respectively. We will present our most recent computations of the glacier changes from years 2018 and 2019 and discuss how UAS instrumentation techniques are helping us observe changing glacier conditions at centimeter-scale resolution, better understand ecosystem relationships, and improve capabilities to model future landscapes all while mitigating mountain safety issues.
Fire, as a strong disturbance type, can exert significant impacts on biosphere, hydrosphere, geosphere, cryosphere, atmosphere and human society. It can inherently trigger both critical transitions in ecosystems and dramatic changes in landscapes, which can be detected as alternations in land cover types. However, the general changing patterns and possible influential factors of post-fire landscape change remain largely unclear on a global scale. Obtaining such knowledge is of great value in advancing the understanding of fire ecology and promoting sustainable fire management. Here, we combined the satellite observations of long-term land cover and burned areas to assess the global post-fire landscape change patterns from 2005 to 2015. The results showed that the identified areas with post-fire landscape change accounted for approximately 0.36–0.74% of the annual global burned areas during the study period and were most common in countries such as Brazil, Argentina, and the D.R. Congo. The most common landscape change types were “forest-to-agriculture” (31.93%), “forest-to-shrubland” (26.23%) and “agriculture-to-forest” (18.74%) in 2005, 2010 and 2015, respectively. In addition, the conversion between agriculture and forest as well as the shrubland and forest after fire were found to be bidirectional. After assessing 14 fire-related climatic, topographic, ecological and socioeconomic factors that could potentially influence the post-fire landscape change occurrence probability, burned area size and vegetation cover diversity were identified as the two strongest predictors, followed by aspect, fire intensity and slope. Our results provide a global overview of post-fire landscape change patterns and offer guidance for making sustainable fire management policies.
A catchment in southern England, UK, included a substantial area of bare ground within the surrounding heathland and woodland. Runoff from this area has, in the past, contributed large volumes of sediment to a large lake; although this input is now significantly reduced as a result of previous and on-going management works that are reported on in this paper. Historic realignment and re-sectioning of the main watercourse, has also resulted in the overdeepening, vertical and lateral erosion of the stream channel resulting in downstream transport of sediment to the lake. In addition to sediment erosion, the associated limited connectivity with the floodplain and focus of sediment transport in the fluvial channel has been a key factor in the shallowing and deterioration in the condition of the lake. Over the last 15 years a wide range of investigative, monitoring and management work has been undertaken within the catchment by a partnership between UK Government organisations, a local authority and a charity, with continuous involment by the author throughout this period. This work has evaluated the causes and effects associated with this erosion and transportation, tested and defined viable practical solutions (the delivery of natural sediment and flood management solutions and habitat restoration) and delivered a series of sustainable management interventions to reduce erosion, promote sediment deposition and to reconnect the stage zero and larger fluvial pathways to the floodplain – supporting the restoration of the lake. These works have resulted in the reduction in erosion at source and increased deposition through the catchment system, ultimately contributing to the improvement in condition of the lake and associated wetland habitats. Works in the headwaters of the catchment focused on defining the existing distribution, status and significance of areas of sediment generation, transport and deposition to the stream and lake, facilitating sustainable sediment management within this area. Works in the lower reaches focused on slowing flow velocities and diverting higher velocity sediment rich flows into new channels to reconnect with the floodplain and promote deposition. Management measures included the use of small diversion channels through woodland with the creation of glades to increase understory recovery and sediment deposition; use of geotextile cells filled with sand, gravel or stone to increase the flow path, reduce velocity and promote out of channel flooding and deposition of sediment; use of scrub and woody material to form leaky dams and increase channel roughness promoting out of bank flooding and deposition; use of online ponds, backwaters and embayments; blanking off channels to promote overland flow through woodland to reduce flow depth and velocity and promote deposition; use of leaky dams to promote higher flows transporting sediment into new sinuous channels and allowing out of bank flooding to promote sediment deposition.
Limited research has evaluated the mental health effects of compounding disasters (e.g., hurricanes followed by a heat wave), and few studies have relied on crisis lines for post-disaster mental health surveillance. This study examined changes in crisis help-seeking for individuals in Louisiana, USA, before and after Hurricane Ida (2021), a storm that co-occurred during the COVID-19 pandemic, subsequent hurricane, and corresponding heatwave. An interrupted time series analysis for a single and multiple group comparisons were used to examine pre-and post- changes in crisis text volume (any crisis text, substance use, thoughts of suicide, stress/anxiety and bereavement) among help-seeking individuals in communities that received individual and public assistance disaster declarations. Results showed a significant increase in crisis texts for any reason, thoughts of suicide, stress/anxiety, and bereavement in the short-term impact period. In the continued impact period, there was an increase in crisis texts for any crisis event, substance use, thoughts of suicide, stress/anxiety, and bereavement. Findings highlight the need for more mental health support for residents directly impacted by concurrent disasters.
Urbanization tends to increase runoff volumes, which might cause flooding and reduce groundwater recharge. Since the design of impermeable urban elements is based on the water flow volume before their construction, once they are erected the induced change to the local drainage pattern might generate flooding of the newly developed and previously developed areas. As such, precise modeling is essential to allow municipal watershed-sensitive hydrological design, which may prevent impervious urban surface expansion negative impacts. The digital elevation model that represents the watershed relief at any given location is the hydrological modeling base layer, which is necessary for describing urban landscapes and watersheds. The common notion is that the finer the elevation model resolution is, the more precise the hydrological model will be. Nevertheless, it is suggested that over-accuracy might be redundant. In the same manner, the land use classification resolution should be aligned with the modeling requirements. Such careful evaluation of the modeling resolution will reduce the computing resources needed for the modeling procedure and may be utilized as a sensitivity filter for insignificant tributaries of the hydrological network. This paper demonstrates a nominal procedure for urban watershed sub-basin analysis, which is the initial stage for detailed urban runoff modeling. It was found that the scale-optimized model performed very well and was found suitable for the prediction of runoff volume and discharge from a mainly urban, mountainous karstic watershed.
Does river topography have stage thresholds for maintaining fluvial landforms, and if so how can they be quantified? Geomorphic covariance structure analysis offers a novel, systematic framework for evaluating nested topographic patterns in river corridors. In this study, a threshold in mountain river stage was hypothesized to exist; above this stage landform structure is organized to be freely self-maintaining via flow convergence routing morphodynamics. A 13.2 km segment of the canyon-confined Yuba River, California, was studied using 2944 cross-sections. Geomorphic covariance structure analysis was carried out on a meter-resolution topographic model to test the hypothesis. A critical stage threshold governing flow convergence routing morphodynamics was evident in several metrics. Below this threshold, narrow/high “nozzle” and wide/low “oversized” landforms that are out-of-phase with flow convergence routing morphodynamics dominated (excluding “normal channel”), while above it wide/high “wide bar” and narrow/low “constricted pool” landforms consistent with the flow convergence mechanism were dominant. Three-level nesting of co-located base-bankfull-flood stage landforms was dictated by canyon confinement, with nozzle-nozzle-nozzle nesting as the top permutation, excluding normal channel. In conclusion, this study demonstrates a significantly different and highly effective approach to finding process-based fluvial thresholds that can complement pre-existing methods, such as estimating incipient sediment motion, to get at more powerful dynamics controlling fluvial landforms structure.