Precision monitoring of the subsurface carbon-dioxide plume ensures long-term, sustainable geological carbon storage. Carrigan et al. (2013) and Yang et al. (2014) showed that electrical resistivity tomography (ERT) can accurately map the evolution of the CO2 saturation during geological carbon storage. To better monitor the CO2 plume migration in a storage reservoir, we develop an unsupervised spatiotemporal clustering to process the CO2 saturation maps derived from the ERT measurements acquired over 80 days by Carrigan et al. (2013). Using dynamic time wrapping (DTW) K-means clustering, four distinct clusters were identified in the CO2-storage reservoir. The four clusters exhibit a Davies-Bouldin (DB) index of 0.71, a Calinski-Harabasz (CH) index of 262791, and a DTW-silhouette score of 0.58. Unlike traditional clustering methods, the DTW K-means incorporates a temporal distance metric. Traditional clustering methods, such as Euclidean K-means, agglomerative and meanshift clustering, exhibit a lower performance with DB index of 0.83, 0.95, and 1.01, respectively, and CH index of 157866, 131593, and 69438, respectively. Subsequent statistical analysis indicates that contrast stretching and fast-Fourier transform are strong geophysical signatures of the spatiotemporal evolution of CO2 plume. We also identified a strong correlation between injection flow rate and the spatial evolution of regions with high CO2 content. Finally, the previously computed spatiotemporal clusters were further clustered to discover distinct temporal sequences emerging with respect to the overall CO2 plume distribution in the subsurface. Six distinct temporal clusters of CO2 plume evolution were detected over a period of 2 months. A tensor-based feature extraction was critical for processing the ERT data acquired over 80 days to capture both the temporal and spatial components relevant to the evolution of CO2 plume in the storage reservoir.

Subglacial models represent moulins as cylinders or cones, but field observations suggest the upper part of moulins in the Greenland Ice Sheet have more complex shapes. These more complex shapes should cause englacial water storage within moulins to vary as a function of depth, a relationship not currently accounted for in models. Here, we use a coupled englacial--subglacial conduit model to explore how moulin shape affects depth-dependent moulin water storage and water pressure dynamics within a subglacial channel. We simulate seven different moulin shapes across a range of moulin sizes. We find that the englacial storage capacity at the water level is the main control over the daily water level oscillation range and that depth-varying changes in englacial water storage control the temporal shape of this oscillation. Further, the cross-sectional area of the moulin within the daily oscillation range, but not above or below this range, controls pressures within the connected subglacial channel. Specifically, large cross-sectional areas can dampen daily to weekly oscillations that occur in the surface meltwater supply. Our findings suggest that further knowledge of the shape of moulins around the equilibrium water level would improve englacial storage parameterization in subglacial hydrological models and aid predictions of hydro-dynamic coupling.

Tropical Instability Vortices (TIVs) have a major influence on the physics and biogeochemistry of the equatorial Pacific. Using an eddy-resolving configuration of the Community Earth System Model (CESM-HR) and Lagrangian particle tracking, we examine TIV impacts on the three-dimensional structure and variability of dissolved oxygen (O2) in the upper equatorial Pacific water column. In CESM-HR, the simulated generation and westward propagation of TIVs from boreal summer through winter lead to the seasonal oxygenation of the upper northern equatorial Pacific, exhibited as a deepening of hypoxic depth west of 120ºW. TIV effects on the equatorial Pacific oxygen balance are dominated by eddy-advection and mixing, while indirect TIV effects on O2 consumption play minor roles. These advective effects reflect the transient displacements of isopycnals by eddy pumping as well as vortex transport of oxygen by eddy trapping, stirring, and subduction. TIVs influence on the upper equatorial Pacific O2 distribution and variability has important implications for understanding and modeling marine ecosystem dynamics and habitats, and should be taken into consideration in designing observation networks in this region.

We conduct the first 4D-Var inversion of NH3 accounting for NH3 bidirectional flux, using CrIS satellite NH3 observations over Europe in 2016. We find posterior NH3 emissions peak more in springtime than prior emissions at continental to national scales, and annually they are generally smaller than the prior emissions over central Europe, but larger over most of the rest of Europe. Annual posterior anthropogenic NH3 emissions for 25 European Union members (EU25) are 25% higher than the prior emissions and very close(<2% difference) to other inventories. Our posterior annual anthropogenic emissions for EU25, the UK, the Netherlands, and Switzerland are generally 10-20% smaller than when treating NH3 fluxes as uni-directional emissions, while the monthly regional difference can be up to 34% (Switzerland in July). Compared to monthly mean in-situ observations, our posterior NH3 emissions from both schemes generally improve the magnitude and seasonality of simulated surface NH3 and bulk NHx wet deposition throughout most of Europe, whereas evaluation against hourly measurements at a background site shows the bi-directional scheme better captures observed diurnal variability of surface NH3. This contrast highlights the need for accurately simulating diurnal variability of NH3 in assimilation of sun-synchronous observations and also the potential value of future geostationary satellite observations. Overall, our top-down ammonia emissions can help to examine the effectiveness of air pollution control policies to facilitate future air pollution management, as well as helping us understand the uncertainty in top-downNH3emission estimates associated with treatment of NH3surface exchange.

Land surface/Earth System models depend upon accurate simulation of evapotranspiration (ET) to avoid excessive biases in simulated energy, water, and carbon cycles. The Canadian Land Surface Scheme including biogeochemical Cycles (CLASSIC), the land surface scheme of the Canadian Earth System Model (CanESM) shows reasonable ET fluxes globally, but CLASSIC’s partitioning into evaporation (E) and transpiration (T) can be improved. Specifically, CLASSIC exhibited a high soil evaporation (Es) bias in sparsely vegetated areas during wet periods, which can deplete soil water and decrease photosynthesis and T later in the year. A dry surface layer (DSL) parameterization was implemented to address biases in Es through an increased surface resistance to water vapour and heat fluxes. In arid/semi-arid regions, the DSL decreased Es, leading to improved seasonality of ET and increased gross primary productivity (GPP) due to an increase in soil moisture. The DSL simulations significantly (t-test, p<0.01) increased T/ET from 0.25 in baseline CLASSIC to 0.30 in the DSL simulations. T/ET was further increased to 0.41 (p<0.01), comparable to the CMIP5 model mean, by allowing T to occur from the dry canopy fraction while water evaporates from the wet fraction. This mainly affected densely vegetated areas, where T and ET increased significantly (p<0.01) and canopy E was reduced (p<0.01). In seasonally dry tropical forests, higher T and ET reduced GPP. Despite increases in arid/semi-arid regions, the reduced GPP in tropical forests resulted in ∼1.6% lower global GPP (p=0.018) than baseline CLASSIC. Including these modifications in CanESM might reduce biases in climate.

Due to spatial scaling effects, there is a discrepancy in mineral dissolution rates in porous media measured at different spatial scales. Many reasons for this spatial scaling effect can be given. We investigate one such reason, i.e. how pore-scale spatial heterogeneity in porous media affects overall mineral dissolution rates. Using the bundle-of-tubes model as an analogy for porous media, we show that the Darcy-scale reaction order increases as the statistical similarity between the pore sizes and the effective-surface-area ratio of the porous sample decreases. The analytical results quantify mineral spatial heterogeneity using the Darcy-scale reaction order and give a mechanistic explanation to the usage of reaction order in Darcy-scale modeling. The relation is used as a constitutive relation of reactive transport at the Darcy scale. We test the constitutive relation by simulating flow-through experiments. The proposed constitutive relation is able to model the solute breakthrough curve of the simulations. In addition, our results imply that we can infer mineral spatial heterogeneity of a porous medium using measured solute concentration over time in a flow-through dissolution experiment.

As a high-nutrient and low-chlorophyll region, the modern Gulf of Alaska (GoA) is strongly impacted by the limitation of iron. Paleostudies along the Alaskan slope have mainly focused on reconstructing environmental conditions over the past 18 ka. Based on micropaleontological, biogeochemical and sedimentological parameters, we explore a sediment record covering the past 54 ka at Integrated Ocean Drilling Program Site U1419 to understand the impact of orbital and suborbital-scale climate variability on productivity and sea-surface conditions. Close to the Cordilleran Ice Sheet (CIS), Site U1419 is ideally located to elucidate how the evolution of a large ice mass and glacial processes affected orbital- and suborbital-scale changes in nutrients-(e.g., iron) supply. Meltwater discharge from the northern CIS impacted sea surface dynamics of GoA coastal waters. The corresponding increase in bulk biogenic concentrations during Marine Isotope Stage (MIS) 3 and MIS 2 (54 – 17.3 ka) suggests a direct impact from iron fertilization. Cooling of surface waters played no primary role in the occurrence of primary producers. The inundation of the subaerially exposed continental shelf during the last deglacial (17.3-10 ka) warming could have served as a major micronutrients source. Low productivity after the last deglaciation suggests reduced iron availability. Our multiproxy approach reveals a more complete picture of late Quaternary productivity variations compared to earlier studies along the Alaskan margin. The impact of tidewater glaciers and meltwater discharge on past marine productivity and nutrient budget dynamics of high-latitude coastal regions is discussed.

In the energy transition context, the design of integrated multi-energy systems is key for reaching ambitious sustainability objectives. Due to the intermittent nature of the renewable energy sources, introducing technologies for storing and transforming energy in different carriers (e.g., electricity, gas, heat) is, in fact, a strategic solution for fully exploiting the renewable power generation, increasing the flexibility of the system, and contributing to the decarbonization. Although the need to rely on multi-energy systems is widely shared, identifying their optimal design requires the use of complex modelling tools able to characterize the territory, simulate the system dynamics, and evaluate the solutions with respect to different sustainability objectives. To support the decarbonization decision-making process, in this work we develop a three-step modelling chain for planning optimal multi-energy systems at the local scale. More precisely, we first perform a territory characterization by estimating, through different methodologies, input data of renewable resource availability, territory exploitation potential, and energy demand of electricity and heat. Then, we carry out a multi-energy analysis identifying Pareto optimal system designs with respect to two sustainability objectives, namely the Net Present Cost and the CO2 emissions. Finally, we perform an intersectoral Multi Criteria Analysis-Cost Benefit Analysis (MCA-CBA) for evaluating the solutions obtained in the previous step with respect to a wide range of indicators representing energy, economic, and social acceptance aspects. The CBA approach is adopted for evaluating the financial and economic viability of the investment options, while the assessment of non-monetary impacts is performed through the MCA approach. We apply the modelling chain to the real case study of Sulcis Iglesiente (Sardinia, Italy), a territory characterized by carbon-intensive industries, recently selected for receiving funding from the Just Transition Fund launched by the EU Commission in the context of the Green Deal. Expected results aim to demonstrate the validity of the proposed modelling chain in the identification of the best interventions for supporting the decarbonization and the sustainable development of Sulcis Iglesiente.

Recent shifts in the behaviour of natural watersheds suggest acute challenges for water planning under climate change. Shifts towards less annual streamflow for a given annual precipitation have now been reported on multiple continents, usually in response to a multi-year drought. Future drying under climate change may induce similar unexpected hydrological behaviour, and 15 this commentary discusses the implications for water planning and management. Commonly-used hydrological models poorly represent the shifting behaviour and cannot be relied upon to anticipate future shifts. Thus, their use may result in underestimation of hydroclimatic risk and exposure to “surprise” reductions in water supply, relative to projections. The onus is now on hydrologists to determine the underlying causes of shifting behaviour and incorporate more dynamic realism into 20 operational models. Main points 1. Drought-induced hydrological shifts towards less streamflow for a given precipitation have been reported across multiple continents. 2. Future drying under climate change may induce similar unexpected behaviour. 25 3. Such behaviour creates additional uncertainty in runoff projections, and may lead to ‘surprise’ reductions in future streamflow. Main text In a recent article, Peterson et al. (2021) reported shifts in hydrological behaviour induced by the “Millennium” drought (1997-2010) in Australia and persisting years after the drought ended. 30 Reductions in water resources during and after this drought were far more extreme than expected, even given low rainfall (Saft et al., 2015), because many watersheds shifted into a seemingly different state of streamflow behaviour. Concerningly, some watersheds remain in this state despite a return to near-average climate conditions, so that a year of average rainfall now produces less streamflow than it did before the drought (Peterson et al., 2021). With similar hydrological 35 shifts reported elsewhere in the world, including the USA (Avanzi et al., 2020), China (Tian et al.,

The entire western US is in the midst of a megadrought. Combined with high temperatures, increasingly severe droughts are causing widespread forest mortality. In the Sierra Nevada, CA in particular, the Mediterranean climate exposes montane forests to water stress due to the summer drought. Normally, the slow melting of the winter snowpack helps to alleviate summer water stress, especially in riparian ecosystems that benefit from subsurface lateral inputs along a hillslope. However, the loss of the snowpack due to snow drought could potentially eliminate these buffering effects. This research aims to address the role of subsurface lateral redistribution in mediating vegetation responses to drought along a hillslope. We apply a spatially-distributed ecohydrologic model (RHESSys) to an experimental hillslope in a snow-dominated watershed in the Sierra Nevada, CA. We incorporate observed sap flow data from the experimental hillslope to estimate the relative differences in onset of water stress for upslope and riparian sites, which is used to constrain RHESSys drainage parameter uncertainty. Then, we run hypothetical multi-year drought experiments to investigate how climate variability translates to water stress on a hillslope. Our results challenge the common assumption that riparian forests are buffered against drought stress by subsurface lateral inputs. For all drought types, both upslope and riparian sites experience severe losses of net primary productivity (NPP), and on average upslope sites are more adversely affected (upslope loss of NPP = 50% vs. riparian = 35%). But even in a wet year, as temperatures rise and the snowpack disappears (i.e., warm snow drought), vegetation approaches a threshold response that destabilizes the riparian buffering effect. Our results show that for 12% of all scenarios, riparian NPP decreases more than upslope NPP, as a consequence of earlier snowmelt. Interactions between climate variability and ecophysiological uncertainty produce scenarios that exhibit the riparian threshold response. By recognizing the conditions that determine riparian sensitivity to drought, management actions can be proactive in preserving this important hydrological refugia.

Virtual reality (VR) is an important tool for several applications in science, industry, and education. Previous studies have already shown how the use of VR at full scale is an effective tool for outcrops characterization even at centimetre scale [1]. We aim to extend the use of this approach in various fields of planetary exploration, from outcrop to regional scale. This regional approach may provide an effective support for the planning and management of future missions, but also for geological and geomorphological studies and mapping. Among the most obvious advantages of the use of virtual reality are the lack of optical deformations and approximate dimensions of the two-dimensional display (such as display, projections and printed cartography) and the opportunity to layer various levels of information through a new concept of superposition. The VR environment is derived from several multi-scale elements: medium to high-resolution elevation data, photogrammetric 3D models, orthophotos, multispectral data, thematic maps and vector data transformed into three-dimensional digital representations placed in the study context. The first tests are based on stereogrammetry (using USGS ISIS [2] and NASA ASP [3]) of the lunar LRO (LROC-NAC) [4] and Martian MRO (CTX and HiRISE) [5] and MEX (HRSC) [6] missions and on data and cartography realized through external open-source GIS tools (GDAL libraries, QGIS, GRASS) and virtual tools developed to be used within the VR environment. In our tests, for example, the Rock Abundance analysis results have been shown not only as thematic maps but also as digital representations of floating boulders on the surface. This has been achieved by placing major rock elements (>1m) in the position detected from satellite imagery and smaller elements, estimated from size-frequency distributions studies, with a preliminary semi-random distribution. References [1] Mouélic S. L. et al. (2019), Geophys. Res. Abstr, Vol. 21. [2] Becker K. J. et al. (2013), LPSC, Vol. 44. [3] Moratto Z. M. et al. (2010), LPSC, No. 1533, p. 2364. [4] Robinson M. S. et al. (2010), Space Sci. Rev., 150: 81-124. [5] McEwen A. S. et al. (2007), J. Geophys. Res. Planets, 112.E5 [6] Neukum G. & Jaumann R. (2004). Mars Express: The Scientific Payload, Vol. 1240, pp. 17-35.

Extreme rainfall can be calamitous to the ecosystem, life, society, and economy through rapidly developing (flash) floods and is likely to intensify in a warmer future climate. Such intensification is however less well understood for the rainfall in short durations (e.g., hourly; 1h) due to the coarse time-scale of climate models. This study proposes an artificial neural network (ANN) model for disaggregating coarser time-scale (i.e., 3h) rainfall datasets to finer time-scale (i.e., 1h) extreme rainfall (i.e., annual maximum series (AMS)), targeting a data-scarce county like Cambodia by using the 1h rainfall dataset and multiple meteorological covariates datasets (e.g., temperature, wind velocity, and surface latent & sensible heat flux (SLHF&SSLF)) provided by ERA5 reanalysis products. The ANN model was trained by using the information of extreme rainfall events extracted from this 1h rainfall dataset and of the associated simultaneous weather conditions signified by specific combinations of these meteorological covariates. The rationale is that future extreme rainfall patterns will resemble the historical extreme rainfall patterns if similar weather conditions exist during the extreme rainfall events. Covariate importance analysis shows that the most important covariates for the disaggregation are SLHF&SSLF and wind velocity. The proposed ANN model reproduced the observed 1h AMS satisfactorily, with R2 of 0.93 and mean absolute percentage error (MAPE) of 6.1%, averaged for the study area. This ANN model is flexible enough to be extended to other time scales (e.g., daily to sub-hourly) and can be used for similar studies globally. Future work will consider more meteorological covariates, which can be both provided by the ERA5 reanalysis products and climate models, as the predictors.

Natural and human-made extreme events can alter residential electricity demand in urban areas and stress the electricity grid. Different types of residential electricity consumers, which in some cases account for more than 30% of customers, can present different consumption patterns. Residential electricity demands have been widely analyzed considering single-family consumers; however, multi-family consumers remain comparatively understudied. The deployment of smart electricity meters enables the identification of single- and multi-family residential electricity consumption patterns at high temporal resolution. Using smart electricity meter data for the greater Chicago area, we compare electricity demand profiles reported by smart meters from single- and multi-family consumers in a large and diverse urban environment. The study provides a comprehensive analysis of daily electricity demand profiles of these two types of residential consumers to identify peak electricity consumption times and magnitudes. The analysis also presents correlations of the electricity demand with socioeconomic data at the zip code level. Preliminary results show that median building age, percent of occupancy, and mean commute time are statistically significant predictors of multi-family electricity consumption. Results suggest that single-family consumers have comparable correlation when using the same socioeconomic data with respect to the multi-family users. Uncovering differences between single- and multi-family electricity demands can assist city planners and utility managers to develop tailored demand management strategies.

To precisely describe the dynamics of vegetation cover in high-density urban areas, this study evaluates the spatial and temporal consistency of the Normalized Difference Vegetation Index (NDVI) from multiple satellite data sources. The study areas of Downtown Beijing target at two scales: the district scale, and the neighborhood scale. Results show that Planet, Sentinel-2, Landsat-8, and MODIS share a similar spatial pattern; Sentinel-2, Landsat-8, and MODIS correlate in the temporal change of NDVI at both spatial scales in 2019, but AVHRR does not present useful information of spatial patterns of urban green space or urban vegetation dynamics at these two scales. Seasonal contrast derived from Sentinel-2 and Landsat-8 can be visualized through seasonal variation ratio to assist urban green space planning. This study highlights the usefulness of existing satellite observations in monitoring a variety of urban greening typologies at the neighborhood scale for improving urban environmental planning.

Remediation of contaminated soil sites is important to our environment and the growing population that interacts with these resources. Contamination of soil due to leaks, spills and seepage is a worldwide problem usually diagnosed by costly and time-consuming methods primarily using wet chemistry. Problems in remediation efforts involve finding technologies that are less time-consuming and more cost effective over time. Field portable spectrometers that cover key spectral ranges in the ultraviolet, visible and near infrared regions provide a solution for fast and easy identification of contaminants in soil. Using a field portable spectrometer to measure Petroleum Hydrocarbons (TPH) in soil is a fast and nondestructive method of analysis. Applying UV-VIS-NIR technology to these samples hydrocarbon spectra can potentially be characterized by four main absorption features at 1180nm, 1380, 1730nm, and 2310nm. This presentation aims to highlight the utility of field portable NIR technology for researchers in addressing potentially contaminated environments.

Heavy metals are often prevalent in urban settings due to many possible legacy and modern pollution sources, and are essential to quantify because of the potential adverse health effects associated with them. Of particular importance is lead (Pb), because there is no safe level of exposure, and it especially harms children. Through our partnership with community scientists in the Marion County (Indiana, United States) area, we measured Pb and other heavy metal concentrations in various household media. Community scientists completed screening kits that were then analyzed in the laboratory via X-Ray fluorescence (XRF) to quantify heavy metal concentrations in dust, soil, and paint to determine potential hazards in individual homes. Early results point to renters being significantly more likely to contain higher concentrations of Pb, zinc (Zn), and copper (Cu) in their soil versus homeowners, irrespective of soil sampling location at the home, and home age was significantly negatively correlated with Pb and Zn in soil and Pb in dust across all homes. Analysis of paired soil, dust, and paint samples revealed several important relationships such as significant positive correlations between indoor vacuum dust Pb, dust wipe Pb, and outdoor soil Pb. Our collective results point to rental status being an important determinant of possible legacy metal pollution exposure in Indianapolis, and housing age being reflective of both past and possibly current Zn and Pb pollution at the household scale in dust and soil. Thus, future environmental pollution work examining rental status versus home ownership, as well as other household data such as home condition and resident race/ethnicity, is imperative for better understanding environmental justice issues surrounding not just Pb, but other heavy metals in environmental media as well.

Filter-feeding gelatinous macrozooplankton (FFGM), namely salps, pyrosomes and doliolids, are increasingly recognized as an essential component of the marine ecosystem. Unlike crustacean zooplankton (e.g., copepods) that feed on preys that are an order of magnitude smaller, filter-feeding allows FFGM to have access to a wider range of organisms, with predator over prey ratios as high as 10$^5$:1. In addition, most FFGM produce carcasses and/or fecal pellets that sink 10 times faster than those of copepods. This implies a rapid and efficient export of organic matter to depth. Even if these organisms represent $<$5\% of the overall planktonic biomass, the induced organic matter flux could be substantial. Here we present a first estimate of the influence of FFGM organisms on the export of particulate organic matter to the deep ocean based on the marine biogeochemical model NEMO-PISCES. In this new version of PISCES, two processes characterize FFGM: the preference for small organisms due to filter feeding, and the rapid sinking of carcasses and fecal pellets. To evaluate our modeled FFGM distribution, we compiled FFGM abundance observations into a monthly biomass climatology using a taxon-specific conversion. A model-observation comparison supports the model ability to quantify the global and large-scale patterns of FFGM biomass distribution, but reveals an urgent need to better understand the factors triggering the boom-and-bust FFGM dynamics before we can reproduce the observed spatio-temporal variability of FFGM. FFGM contribute strongly to carbon export at depth (0.4 Pg C yr$^{-1}$ at 1000 m), particularly in low-productivity region (up to 40\% of organic carbon export at 1000 m) where they dominate macrozooplankton by a factor of 2. The FFGM-induced export increases in importance with depth, with a simulated transfer efficiency close to one.

Carbon dioxide (CO2) levels have been shown to be rising dramatically as a result of increased anthropogenic activity. One way of countering excessive CO2 emissions is by restoring natural ecosystems that have historically been found to be efficient carbon sinks. In order to be economically viable, these efforts must consider biomes with long-term sustained carbon sequestration capacities. Low interannual variation in this sink capacity minimizes risk of sequestration reversal. The goal of this study was to compare the interannual variability of carbon at four proximate Ameriflux eddy covariance sites across northern Wisconsin and Michigan’s upper peninsula with up to two decades of observations per site. Two wetlands (Allequash Creek (US-ALQ) and Lost Creek (US-Los)) and an unmanaged and managed forest (Sylvania Wilderness Area (US-Syv) and Willow Creek (US-WCr), respectively) were considered. To consider the fuller carbon budget for wetlands, we also incorporated stream discharge data from the United States Geological Survey. In most of the measured years, on average, NEE in both types of ecosystems was negative (carbon uptake by the ecosystem). US-ALQ and US-Los had a yearly averaged standard deviation of ~4.3 µmol CO2 m-2 s-1, while for US-Syv and US-WCr it was ~5.5 and ~6.3 respectively, implying greater variability for the forests than wetlands. Interannual water availability (precipitation and discharge) was the main driver for wetland carbon variation while radiation was the best predictor of carbon dynamics in the forests. Our results demonstrate that for this region, wetlands are a more reliable biome for carbon storage on a decadal scale than forests. In addition, this capacity may be enhanced through restoration efforts focusing more on water availability rather than afforestation/reforestation.

Anthropogenic subsurface urban heat islands (SUHIs) in groundwater under cities are known worldwide. SUHIs are potentially threats to springs because much spring fauna, like trout, amphipods, and rare plants, is cold stenothermal. The city of Minneapolis, Minnesota, USA, has a SUHI documented by the temperature of an underground spring, dubbed “Little Minnehaha Falls,” inside Schieks Cave, which is located 23 m below the central core of the city. In 2000 the temperature of that spring was elevated 11°C above regional background groundwater temperatures (8°C) at this latitude (45°N). A thermometric survey of the cave and nearby tunnel seepages in 2007 found that an abandoned drill-hole through the bedrock ceiling of the cave was discharging groundwater with a temperature of 17.9°C. By comparison, groundwater in the deep water-table below the cave was closer to natural background temperatures for the region. The unusually warm groundwater was thereby localized to the strata above the cave. This is the strongest signal of anthropogenic groundwater warming in the state of Minnesota and is attributed to vertical heat conduction from basements and pavements. Minneapolis is unique among SUHIs in that a cave forms a natural collection gallery deep below the city surface, whereas the literature is almost exclusively based on data from observation wells.

Traditional urban drainage degrades receiving waters. Alternative approaches have potential to protect downstream waters, but widespread adoption requires robust demonstration of their feasibility and effectiveness. We conducted a catchment-scale experiment over 19 years to assess the effect of dispersed stormwater control measures (SCMs), measured as a reduction in effective imperviousness (EI) on stream water quality in 6 sites on 2 streams. We compared changes in those sites over 7 years as EI decreased, to changes in the 12 preceding years, and in 3 reference and 2 control streams. SCMs reduced phosphorus concentrations and summer temperature to reference levels in dry weather where EI was sufficiently reduced, but effects were smaller with increased antecedent rain. SCMs also reduced nitrogen concentrations which were influenced by septic tank seepage in all sites. SCMs had no effect on suspended solids concentrations, which were lower in urban than in reference streams. SCMs increased electrical conductivity: along with reduced temperature this is evidence of increased contribution of groundwater to baseflows. This experiment strengthens inference that urban stormwater drainage increases contaminant concentrations in streams, and demonstrates that such impacts are reversible and likely preventable. Variation in degree of water quality improvement among experimental sites suggests that achieving reference water quality would require SCMs with large retention capacity intercepting runoff from nearly all impervious surfaces, thus requiring more downslope space and water demand. EI is a useful metric for predicting stream water quality responses to SCMs, allowing better catchment prioritization and SCM design standards for stream protection.

A portion of pore water is typically in a state of unfrozen condition in frozen soils due to the complex soil-water interactions. The variation of the amount of unfrozen water and ice has a significant influence on the physical and mechanical behaviors of the frozen soils. Several empirical, semi-empirical, physical and theoretical models are available in the literature to estimate the unfrozen water content (UWC) in frozen soils. However, these models have limitations due to the complex interactions of various influencing factors that are not well understood or fully established. For this reason, in the present study, an artificial neural network (ANN) modeling framework is proposed and the PyTorch package is used for predicting the UWC in soils. For achieving this objective, extensive UWC data of various types of soils tested under various conditions were collected through an extensive search of the literature. The developed ANN model showed good performance for the test dataset. In addition, the model performance was compared with two traditional statistical models for UWC prediction on four additional types of soils and found to outperform these traditional models. Detailed discussions on the developed ANN model, and its strengths and limitations in comparison to different other models are provided. The study demonstrates that the proposed ANN model is simple yet reliable for estimating the UWC of various soils. In addition, the summarized UWC data and the proposed machine learning modeling framework are valuable for future studies related to frozen soils.

In dry regions, millions of people depend on freshwater provided by the mountain cryosphere. Its likely depletion would make productive land-use management and access to water supply an even more urgent priority. Therefore water-security-oriented policies increasingly rely on solid information feedbacks for projections provided by Earth Sciences. Nevertheless, this type of research still has a lot to understand regarding headwater catchment hydrology, the top global “water towers.” For example, there are many theoretical and logistical uncertainties: “data deserts” in isolated areas, outdated legislation, or scarce research funding. Yet, one more important issue to highlight is the evolving nature of hydric resources, particularly where baselines have a large uncertainty and supply to many as in dry regions in the Andes or the Himalayas. The main concern here is the legislative inadequacy for evolving hydric resources as their baselines change. For example, groundwater within transboundary or paleowater aquifers could have unaccounted climate-sensitive recharge sources (e.g., permafrost thaw). Hence, the specific way of legislating mountain groundwater could turn ambiguous and useless. By reviewing particular legislation and landing the discussion on study cases in mountainous areas, we commit to showing the inadequacy of current legislation on hydric-potential evolution. Overall, water-security-oriented legislation will not assess and protect headwater catchments within the spectrum of different recharge processes throughout different hydroclimatic zones. First, the “evolving value” of specific catchments changes the nominal priority and purpose for protection. Secondly, a consistent failure to assess incommensurable (latent), climate-sensitive fractions of water supply structure is also found. Therefore, the policy recommendation is to use a hydric scale absorbing all nested processes necessary for hydric supply to persist, requiring defining a lifespan for legislation.

Global change has led to the increased duration and frequency of droughts and may affect the microbial-mediated biochemical processes of intermittent rivers and ephemeral streams (IRES). Effects of flow desiccation on the physical structure and community structure of benthic biofilms of IRES have been addressed, however the dynamic responses of biofilm functions related to ecosystem processes during the dry-wet transition remain poorly understood. Herein, dynamic changes in biofilm metabolic activities were investigated during short-term (25-day) and long-term (90-day) desiccation, both followed by a 20-day rewetting period. Distinct response patterns of biofilm metabolism were observed based on flow conditions. Specifically, biofilms were completely desiccated after 10 days of drying. Biofilm ecosystem metabolism, represented by the ratio of gross primary production (GPP) and community respiration (CR), was significantly inhibited during desiccation and gradually recovered back to autotrophic after rewetting due to the high resilience of GPP. Also, the potential metabolic activities of biofilms were maintained during desiccation and showed a tendency to recover after rewetting. While long-term desiccation caused irreparable damage to the total carbon metabolism of biofilms that could not be recovered to the control level even after 20 days of rewetting. Moreover, the metabolic activities of amine and amino acids showed an inconsistent pattern of recovery with total carbon metabolism, indicating the development of selective carbon metabolism. This research provides direct evidence that the increased non-flow periods affects biofilm-mediated carbon biogeochemical processes, which should be taken into consideration for the decision-making of the ecological and environmental flow of IRES.

Terrestrial Gamma-ray Flashes exhibit slopes of ionizing radiation associated with bremsstrahlung. Bremsstrahlung has a continuous spectrum of radiation from radio waves to ionizing radiation. The Poynting vector of the emitted radiation, i.e., the radiation pattern around a single particle under the external lightning electric field during interaction with other particles or atoms, is not quite well known. The overall radiation pattern arises from the combination of radiation of parallel and perpendicular motions of a particle caused by the acceleration from the lightning electric field and the bremsstrahlung. The calculations and displays of radiation patterns are generally limited to a low-frequency approximation for radio waves and separate parallel and perpendicular motions. Here we report the radiation patterns of combined parallel and perpendicular motions from accelerated relativistic particles at low and high frequencies of the bremsstrahlung process with an external lightning electric field. The primary outcome is that radiation patterns have four relative maxima with two forward peaking and two backward peaking lobes. The asymmetry of the radiation pattern, i.e., the different intensities of forward and backward peaking lobes, are caused by the Doppler effect. A novel outcome is that bremsstrahlung has an asymmetry of the four maxima around the velocity vector caused by the curvature of the particle's trajectory as it emits radiation. This mathematical modeling helps to better understand the physical processes of a single particle's radiation pattern, which might assist the interpretation of observations with networks of radio receivers and arrays of gamma-ray detectors.