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.

Episodes of slow uplift and subsidence of the ground, called bradyseism, characterize the recent dynamics of the Campi Flegrei caldera (Italy). In the last decades two major bradyseismic crises occurred, in 1969/1972 and in 1982/1984, with a ground uplift of 1.70 m and 1.85 m, respectively. Thousands of earthquakes, with a maximum magnitude of 4.2, caused the partial evacuation of the town of Pozzuoli in October 1983. This was followed by about 20 years of overall subsidence, about 1 m in total, until 2005. After 2005 the Campi Flegrei caldera has been rising again, with a slower rate, and a total maximum vertical displacement in the central area of ca. 70 cm. The two signals of ground deformation and background seismicity have been found to share similar accelerating trends. The failure forecast method can provide a first assessment of failure time on present‐day unrest signals at Campi Flegrei caldera based on the monitoring data collected in [2011, 2020] and under the assumption to extrapolate such a trend into the future. In this study, we apply a probabilistic approach that enhances the well‐established method by incorporating stochastic perturbations in the linearized equations. The stochastic formulation enables the processing of decade‐long time windows of data, including the effects of variable dynamics that characterize the unrest. We provide temporal forecasts with uncertainty quantification, potentially indicative of eruption dates. The basis of the failure forecast method is a fundamental law for failing materials: ẇ-α ẅ = A, where ẇ is the rate of the precursor signal, and α, A are model parameters that we fit on the data. The solution when α >1 is a power law of exponent 1/(1 − α) diverging at time Tf , called failure time. In our case study, Tf is the time when the accelerating signals collected at Campi Flegrei would diverge if we extrapolate their trend. The interpretation of Tf as the onset of a volcanic eruption is speculative. It is important to note that future variations of monitoring data could either slow down the increase so far observed, or suddenly further increase it leading to shorter failure times than those here reported. Data from observations at all locations in the region were also aggregated to reinforce the computations of Tf reducing the impact of observation errors.

Shallow glacial aquifers systems are the primary source of drinking water for millions of residents in the upper Midwest and Great Lakes regions of the United States. Studies show that a significant number of municipal and private groundwater wells in these regions are impacted by high nitrate concentrations, which can have negative health impacts for humans. Reducing nitrate contamination through good land management practices will reduce the need for costly nitrate treatment systems and help mitigate other ecological concerns related to nutrient pollution of groundwater. This study presents a Python-based modelling tool that uses a local groundwater flow model and historical land use data (USDA CropScape) to estimate nitrate concentrations at a high-capacity pumping well. Nitrate concentrations predicted by this model are within 5% of median annual values observed at a study site in Waupaca, WI. The model is user-friendly and can easily be adapted to other locations, where it has the potential to help local and state agencies, landowners, and growers make cost-effective decisions about land-use and agricultural practices.

The in-situ magnetospheric exploration of the four large planets of our solar system had started with Pioneer 10’s flyby of Jupiter in Dec. 1973. The second collection of field, particle and radio data of the gas giant was carried out by Pioneer 11 in Dec. 1974, before this spacecraft made its closest approach to Saturn in Sep. 1979. Around the same period, Voyager 1 (2) flew by Jupiter in Mar. (Jul.) 1979 then Saturn in Nov. (Aug.) 1980 (1981). As of today, only Voyager 2 visited the magnetospheres of Uranus (Jan. 1986) and Neptune (Aug. 1989). Galileo had remained the only spacecraft to orbit an outer planet for several years (1995 - 2003) until the arrival of Juno at Jupiter in 2016. Between 2004 and 2017, the Cassini mission had provided a wealth of in-situ data pertinent to the study of magnetospheric particles at Saturn. In this paper, we present our current understanding of the processes that shape the spatial distributions of energetic electrons trapped in the magnetospheres of Jupiter (L < 6), Saturn (L < 15) and Uranus (L < 15) obtained by combining multi-instrument analyses of data from past missions (Pioneer, Voyager, Galileo, Cassini) and computational models of charged particle fluxes. To determine what controls the energy and spatial distributions throughout the different magnetospheres, we compute the time evolution of particle distributions with the help of a diffusion theory particle transport code that solves the governing 3-D Fokker-Planck equation. Particle, field and wave datasets are either used to provide model constraints, assist in modeling physical processes, or validate our simulation results. We first emphasize our latest results regarding the relative (or coupled) role of mechanisms at Saturn, including the radial transport and interactions of electrons with Saturn’s dust/neutral/plasma environments and waves, as well as particle sources from high-latitudes, interchange injections, and outer magnetospheric region. The lessons learned from our modeling of electron distributions at Saturn are used to identify the processes that may be missing in our modeling of Jupiter’s energetic electron environment or those in need to be implemented using new modeling concepts. Our first physics-based modeling of electron populations at Uranus is also assessed with our data-model comparison approach.

Policies to regulate severe surface ozone pollution in cities in India are challenging to develop, due to the complex dependence on precursor emissions of volatile organic compounds (VOCs) and nitrogen oxides (NOx), non-linear chemistry leading to ozone formation, and very limited spatial and temporal surface air quality monitoring. Ratios of space-based observations of formaldehyde (HCHO), an intermediate oxidation product of VOCs, and nitrogen dioxide (NO2) have been used to characterize the sensitivity of surface ozone production to precursor emissions of VOCs and NOx, but interpretation of these depends on the local oxidation regime. Here we develop an improved approach in which we discretize the data into background HCHO due to methane and other long-lived VOCs (regression intercept) and the local relationship (regression slope) between HCHO associated with reactive VOCs and NO2. We apply this to TROPOMI HCHO and NO2 tropospheric columns oversampled to higher spatial resolution than the native pixel resolution of the instrument over the ten most populous cities in India. We use GEOS-Chem to characterize the ozone production regimes and then apply this updated interpretation of the relationship between HCHO and NO2 to the oversampled TROPOMI columns to identify the most effective strategies for regulating ozone and whether these should vary seasonally and spatially.

The CF (Climate and Forecast) Conventions are a community-developed metadata standard for storing and describing Earth system science data in the netCDF binary data format. Numerous existing FOSS (Free and Open Source Software) and commercial software tools can explore, analyze, and visualize data that is encoded using the CF Conventions. The CF community holds annual workshops to develop, refine, and review enhancements to the CF Conventions and to manage the CF governance and processes. The EarthCube netCDF-CF project worked with the CF community on the development of extensions to netCDF-CF. Several of these have been accepted into the CF Conventions. Work on these extensions involved broad participation by members of the existing netCDF-CF community as well as members of science domains not traditionally represented in the netCDF-CF community. This presentation will provide an update of recent work and an overview of CF plans and future activities.

Oceanographic research cruises produce abundant data, using a wide range of methods and equipment; very often through large collaborative efforts. These research endeavors span a broad array of disciplines and are critical to investigating the interplay between biological, geological, and chemical processes in the ocean systems over space and time. The advent of genomic sequencing technologies allows for the analysis of gene expression in a variety of environmental settings, to measure the distribution and significance of metabolites and lipids in organisms and the environment. Despite scientists’ best efforts to carefully curate and share their data with collaborators to advance individual studies and publications, no systematic, unifying framework currently exists to integrate ‘omics data with physical, geochemical, and biological datasets commonly used by the broader geoscience community. As a result, the moment each sample leaves the ship is often the last time each data component appears together in a unified collection. Typically, ‘omics datasets are submitted to nucleotide sequence repositories, whereas contextual environmental data are submitted and stored in specialized data-repositories, or only made available within published papers. This makes it difficult to fully reconnect in-situ data, therefore limiting their reuse in other studies. The development of resources to facilitate the aggregation, publication and reuse of biological datasets along with their physicochemical information is critical for studying marine microbes and the biogeochemical processes in the ocean that they drive. We present Planet Microbe, a cyberinfrastructure resource enabling data discovery and open data sharing for historical and on-going oceanographic sequencing efforts. Several historical oceanographic ‘omics datasets (Hawaii Ocean Time-series (HOT), Bermuda Atlantic Time-series (BATS), Global Ocean Sampling Expedition (GOS)) have been integrated into Planet Microbe along with new oceanic large-scale datasets as the Tara Expeditions and Ocean Sampling Day (OSD). In Planet Microbe, these ’omics data have been reintegrated with their in-situ environmental contextual data, including biological and physicochemical measurements, and information about sampling events, and sampling stations. Finally, cruise tracks, protocols and instrumentation are also linked to these datasets to provide the user with a comprehensive view of the metadata. Additionally, Planet Microbe integrates computational tools using National Science Foundation (NSF) funded Cyberinfrastructure (CyVerse) and provides users with free access to large-scale computing power to analyze and explore these datasets.

Searching for life on other planets and planetary bodies poses a number of challenges, especially given that there is currently no clear evidence that lifeforms can only conform to characteristics observed on Earth. While current astrobiology missions operate under the assumption that any astrobiological entities of interest will have similar properties to organisms on Earth (‘canonical’ lifeforms), the current convention of searching for direct evidence of such lifeforms (e.g. organic compounds, genetic material, etc.) is largely exclusionary to any biologically valid lifeforms which are not currently a part of the canonical model of life that is used to drive exploratory efforts. It is proposed that the definition of life be broadened to include any entities capable of maintaining homeostasis relative to an entropic environment. Thus, instead of the traditional strategy of searching for direct evidence of life conforming to Earth-based standards, i.e., looking for specific organic compounds, a new strategy could be used to indirectly identify lifeforms through their utilization of environmental resources (e.g. as energy sources).

The Beijing-Tianjin-Hebei Metropolitan Region is the biggest urbanized megalopolis in North China. The region has one the lowest water resources availability per capita in China and around the world. Rapid economic development in the past 40 years has resulted in substantially increased water consumption in the region which led to various water security problems including huge burden on water supply, groundwater overdraft, serious damage of river and lake ecosystems etc. Water scarcity has now become one of the largest limiting factors that hinders the further development of the region. The objective of water resources management in this region is thus to ensure healthy balances between the natural and the societal water circulation. This means we need to protect the natural hydrological flow to maintain water's service functions, and in the meantime fulfill the increasing water demand for economic growth. In the present study, we inspected past evolution and future trend of the region's water budget, and subsequently proposed methods for restricting water use and promoting multi-source water supply optimization. This research also reviewed some new concepts and technologies which can potentially help us overcome the water security challenges in the Beijing-Tianjin-Hebei region.

How do formal and informal land use changes have the potential to create unique, and potentially synergistic, risks to communities? Traditionally environmental geochemists privilege certain analytical approaches to evaluate the risk in a system, but when using a participatory approach, the emphasis is instead placed on using the “just right” tools co-discovered with members of the community. In this study we partnered with the LEAD Agency, an environmental advocacy group with a long history of co-designing research agendas to address community concerns to study trace legacy metals in floodplain soils at the Tar Creek Superfund Site in Ottawa County, Oklahoma. At Tar Creek, large mine waste (chat) piles and acid mine seepage have contaminated surrounding communities with zinc, lead, and cadmium. Heavy metal contamination of floodplains at mining sites like Tar Creek involve a complex set of biogeochemical interactions that are controlled by land use patterns (e.g. reworking chat piles and downstream dams), transport pathways, and changing climate making it difficult to prioritize interventions aimed at reducing exposure. Using a participatory research approach, this study integrates (1) community initiated geochemical investigation of wind transportable Pb, (2) monitoring of nutrient loading to assess potential for eutrophication, which would increase metal transport and mobility in Tar Creek, and (3) examines the connections between social and political issues at Tar Creek and how these affect both scientific research and what remediation strategies are tenable. Our action based research aims to support our community partners in their goals:(1) to establish the Rights of Tar Creek through LEAD’s Clean Water Protection Ordinance, which would establish the right to clean water and legally recognize the rights of Tar Creek to exist, regenerate, and flourish, and (2) to expand the EPA’s definition of OU5, which would increase funding for remediation in Ottawa County.

A heat danger day is defined as an extreme when the heat stress index (a combined temperature and humidity measure) exceeding 41 ℃, warranting public heat alerts. This study assesses future heat risk (i.e., heat danger days times the population at risk) based on the latest Coupled Model Intercomparison Project phase 6 (CMIP6) projections. In recent decades (1995-2014) China’s urban agglomerations (Beijing-Tianjin-Hebei, Yangtze River Delta, Middle Yangtze River, Chongqing-Chengdu, and Pearl River Delta) experienced no more than 3 heat danger days per year, but this number is projected to increase to 3-13 days during the population explosion period (2041-2060) under the high-emission pathways (SSP3-7.0 and SSP5-8.5). This increase will result in approximately 260 million people in these agglomerations facing more than 3 heat danger days annually, accounting for 19% of the total population of China, and will double the current level of overall heat risk. During the period 2081-2100, there will be 8-67 heat danger days per year, 60-90% of the urban agglomerations will exceed the current baseline number, and nearly 310 million people (39% of the total China population) will be exposed to the danger, with the overall heat risk exceeding 18 times the present level. The greatest risk is projected in the Pearl River Delta region with 67 heat danger days to occur annually under SSP5-8.5. With 65 million people (68% of the total population) experiencing increased heat danger days, the overall heat risk in the region will swell by a factor of 50. Conversely, under the low-emission pathways (SSP1-2.6 and SSP2-4.5), the annual heat danger days will remain similar to the present level or increase slightly. The result indicates the need to develop strategic plans to avoid the increased heat risk of urban agglomerations under high emission-population pathways.

Droughts are particularly disastrous in South Africa and other arid regions, that are water-scarce by nature due to low rainfall and water sources. According to some studies, droughts are not uncommon in Africa’s drylands and have been rising in dry African terrain. South Africa’s provinces were severely affected recently by drought events. This study aimed at evaluating drought disaster and climate trends in the Free State Province of South Africa and to identify drought drivers using regression-based algorithms. The study used high-resolution downscaled climate change projections under three Representative Concentration Pathways (RCP). Three future periods comprising the short (the 2030s), medium (2040s) and long term (2050s) compared to the current period are analysed to understand the potential magnitude of projected climate change-related drought. The study revealed that the year 2001 and 2016 witnessed extreme drought conditions where drought index is between 0 and 20% across the entire province during summer, while the year 2003, 2004, 2007 and 2015 observed severe drought conditions across the region with variation from one part to the other. The result shows that from -24.5 to -25.5 latitude, the area witnessed a decrease in precipitation (80 to 120mm) across the time slice and an increase in the latitude -26° to -28° S for summer seasons, which is more prominent in the year 2041 to 2050. More so, findings from this study showed that agricultural lands, cultivated grasslands, and barren surfaces were influenced or impacted by drought disaster, especially in 2015, one of the drought years in Free State Province. From the feature selection results, the influence of climate proxies and anthropogenic factors on EVI shows the ecological situation within the study area.

Crystalline basement aquifers are characterized by complex flow pathways controlled by varying overburden stratigraphy and thickness as well as fracture network and connectivity within the crystalline rocks. Understanding the hydraulic connection within the fracture network and the overburden regolith is critical to predicting recharge/discharge and contaminant transport pathways. In this study, we combined geophysical imaging with multiple hydraulic testing to quantify hydraulic connectivity within the crystalline basement aquifers at the Ibadan Hydrogeophysical Research Site (IHRS) in Ibadan, Nigeria. The 50 m × 50 m field experimental site is first of its kind established in 2019 to investigate hydrological dynamics within these complex crystalline basement aquifers in sub–Saharan Africa. We acquired multiple parallel 2D electrical resistivity profiles which were also jointly inverted to obtain multiple 2D and 3D electrical resistivity tomograms of the subsurface. The resistivity tomograms were later constrained with lithological profiles from 4 test wells installed down to depths of 30 m at the site to create a conceptual model elucidating potential flow pathways. We also performed a series of 12 hours pumping tests and a NaCl tracer test to estimate flow and transport parameters including hydraulic conductivity, aquifer storage, yield, and groundwater travel time and to assess connection between the four test wells. The resistivity tomograms show 3 major resistivity zones interpreted as a clay-rich topsoil, a saturated weathered overburden, and a fractured basement rock. The delineated fractured bedrock shows an undulating topography with several primary fracture successions at 9, 14, 16 and 22 m. Hydraulic conductivities from pumping tests range from 2.6 x 10-7 to 1.2 x 10-5 m/s for the fractures and 1.7 x 10-10 to 6.4 x 10-6 m/s for the matrix while specific storage range from 3.5 x 10-8 to 1.8 x 10-3. Preferential flow is also observed with stronger connection between wells A and C. Results of this study provide a basis for detailed numerical study which will be focused on predicting recharge and solute transport under different flow and climate regime. This work will provide a scalable framework for a sustainable management of groundwater resources within the crystalline basements of Nigeria.

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.

Volcanic flood basalt eruptions have covered 1000s of km2 with basalt deposits up to kilometers thick. The massive size and extended duration result in enormous releases of climactically-relevant gases such as SO2 and CO2. However, it is still unknown precisely how flood basalt eruptions influence climate via eruption rates and cadence, height of the volcanic plumes, and relative degassing abundance of species like SO2. Once eruptions occur, the complex interplay of photochemistry, greenhouse gas warming, changes to the atmospheric circulation, and aerosol-cloud interactions can only be properly simulated with a comprehensive global climate model (GCM). We created an eruption scenario for the Goddard Chemistry Climate Model (GEOSCCM) that emits SO2 in the near-surface atmosphere constantly and four times per year an explosive eruption that emits much more SO2 in the upper troposphere/lower stratosphere. The eruption lasts for 4 years and emits 30 Gt of SO2 total. This corresponds to ~1/10th of what may have been emitted during the Wapshilla Ridge eruption phase of the Columbia River flood basalt eruption 15-17 Ma. We use a pre-industrial atmosphere and otherwise modern initial and boundary conditions. The massive flux of SO2 into the atmosphere is quickly converted to H2SO4 aerosols. Global area-weighted mean visible band sulfate aerosol optical depth reaches 220 near the end of the eruption, comparable to cumulonimbus clouds. This reduces the surface shortwave radiative flux by 85% and top-of-atmosphere outgoing longwave flux by 70%. Contrary to our expectations, we find that the climate warms during and immediately following the eruption after a very brief initial cooling. Global mean surface temperature peaks 3-4 years after the eruption ends with a +6 K anomaly relative to a baseline simulation without the eruption. Post-eruption regional temperatures, particularly near-equatorial continental areas, see drastic rises of summertime temperatures with monthly mean temperatures equaling or exceeding 40°C. These temperature responses are radiative- and circulation-driven. The eruption warms and raises the tropical tropopause, allowing a massive flux of water vapor into the stratosphere. Stratospheric water vapor, usually ~3 parts per million reaches 1-2 parts per thousand.

Due to its substantial role on the Earth’s biogeochemical cycles and human health, nitrogen is recognized as one of the major water quality indicators of Sustainable Development Goal 6.3.2. Quantifying these potential impacts in large spatial scales still appears to be a grand challenge because of the high computational demand required by the distributed physically based global models and their intensive data requirements for calibration and validation. The former prevents a comprehensive analysis of the full spectrum of the model behavior under different conditions, and the latter impinges on the reliability of model-based inference. To tackle this problem, we developed a data-driven model using a spatio-temporal Random Forest algorithm to predict levels of nitrogen at 0.5-degree spatial resolution from 1992 to 2010 across the world. Several variables representing livestock, climate, hydrology, topography, etc. have been selected as predictors. The response variable of interest was nitrate–nitrite, which is responsible for the high risk of infant methemoglobinemia. Our results indicate that changes in the nitrogen concentration is mainly driven by cattle and sheep population, fertilizer application, precipitation, and temperature variability, implying livestock population, climate change, and anthropogenic forces can be important risk factors for global water quality deterioration. Furthermore, using the predicted levels of nitrogen, we characterized large-scale water quality patterns, and thus identified a few major ‘hot spots’ of water quality. The proposed model can also help assess potential impacts of future scenarios (e.g., livestock production or land use change) on global water quality conditions for better development of effective policy strategies.

It is reported that metallic iron may exist under shallow lower mantle conditions (Frost et al., 2004). If metallic iron exists, it has an important chemical and physical impact on lower mantle materials. In our previous High-pressure High-temperature experiments, metallic iron was successfully formed in (Mg,Fe)O. However, when we used different metal-oxygen fugacity buffers, it was found that the generated metallic iron existed in the form of alloy. Iron-rich alloys with different compositions even have different physical forms, such as granular and dendritic shapes. In the actual lower mantle, metallic iron produced from (Mg,Fe)O may also form alloys when encountering ferrous metals, and the physical and chemical properties of metallic iron are very different from those of alloys. Therefore the formation of iron-rich alloys is worth our attention. In this study, different metal-oxygen fugacity buffers (Cr, Ti, TIC) were used to study the formation of iron-rich alloy in (Mg, Fe) O under high temperature (1573k, 1773K) and high pressure (3GPa, 15GPa). When the oxygen fugacity is lower than a certain level, metallic iron is formed, and due to the existence of metal-oxygen fugacity buffers, the formed metallic iron will be alloyed with the around metal-oxygen fugacity buffers. At the same time, a reaction zone appears between the sample zone and oxygen fugacity buffers. Martirosyan et al. (2016) also found similar experimental results. We measured the alloy composition and content, the left composition of ((Mg, Fe) O) and oxygen fugacity buffers around the sample area to understand the formation process of iron-rich alloys in our experiments. Preliminary results will be displayed and their implications discussed.

The COVID-19 pandemic has increased the risk of global public health and has the potential to cause severe food and water insecurity due to economic recession during lockdown for people living in low-middle income countries like Bangladesh where capital resources are scarce. There is growing evidence that household food and water insecurity has been associated with poor psychological outcomes. The objective of this study was to determine the association between household food and water insecurity with mental health and whether these differed among urban-rural households. A cross-sectional online survey was conducted with 545 participants immediately after the COVID-19 lockdown period in Bangladesh (August 1-September 30, 2020). Household food and water security were determined using a 9-item Household Food Insecurity Access Scale (HFIAS) (score range 0-27) and a 12-item Household Water Insecurity Experiences (HWISE) scale (score range 0-36), respectively. The Perceived Stress Scale (PSS) was used to evaluate mental health. Multivariable logistic regression examined the association between household food and water insecurity with perceived stress, adjusting socioeconomic characteristics. An urban-rural stratified analysis was also performed. About 72.84% (397) respondents reported high stress and more than 70% of households suffered from food and water insecurity during the lockdown period. After adjusting covariates, logistic regression model results show that food insecurity was associated with a 1.07-point increase in high perceived stress (OR=1.07, 95% CI=1.01-1.11, p<0.01) while water insecurity was associated with 1.03 times greater odds of high perceived stress (OR=1.03, 95% CI=0.93-1.23, p<0.05). In stratified analysis, only food insecurity was associated with high perceived stress in the urban household (OR=1.08, 95% CI=1.00-1.11, p<0.05). However, none of the household insecurity was associated with perceived stress in rural households. Interventions that promote equal access to resources for low-income individuals will likely to be more effective to alleviate economic burden of pandemic.