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DOE OSTI2022

Hanford Site Rare Plant Monitoring Report for Calendar Year 2022

Rare plants are monitored on the Hanford Site as distribution and abundance data of current and historic rare plant populations are necessary to make well-informed environmental and ecological resource management decisions. The Central Hanford Rare Plant Management Plan (DOE/RL-2021-35) guides rare plant monitoring methodology in the context of resource management at the Hanford Site. In 2022, a rare plant monitoring effort occurred on the portion of the Hanford Site (referred to herein as Central Hanford) managed by the U.S. Department of Energy, Richland Operations Office (DOE-RL; Figure 1). The goal of this effort was to revisit known occurrences of upland rare plant populations on Central Hanford to improve baseline information on locations of rare plant populations on the Hanford Site. Rare upland plants were thoroughly surveyed in 2021 but unusually low precipitation that year limited germination of many upland annual plants. Surveys in 2022 focused on rare upland annual species after the Hanford Site received higher than average spring precipitation that was expected to increase germination. Rainfall from April 2022 to June 2022 was 76% higher than average; however, these months were also colder than average. Winter rainfall from January 2022 to March 2022 was 84% lower than average. The high spring precipitation in 2022 appears to have triggered the germination of some populations of rare upland annuals but the dry winter and cold spring may have inhibited others. Population stability, viability, and threats were evaluated and will be used to inform future management of rare plant species.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

SPRUCE Precipitation Chemistry and Bulk Atmospheric Deposition Beginning in 2013

This data set reports the chemistry of precipitation water that was collected at the SPRUCE site located in the S1 bog and calculated values of bulk atmospheric deposition of solutes in precipitation. Sample collection and analyses started during December of 2013 and will continue for the duration of the experiment. Precipitation samples were collected year round on an event-basis from up to three individual collectors. Samples were either composited or individually analyzed, depending on the total volume of water available relative to the amount needed to complete all laboratory analyses. Funnel/bottle collectors were used to collect rainfall and buckets were used to collect snowfall and mixed precipitation. Samples were analyzed for pH, specific conductivity, nutrient concentrations (ammonium, nitrate, soluble reactive phosphorus, total nitrogen), cation concentrations (calcium, magnesium), anion concentrations (chloride, sulfate), total organic carbon concentrations, and natural-abundance stable isotopes of water (δ18O-H2O and δD-H2O). Bulk deposition was calculated by multiplying rainfall amount by solute concentration for ammonium, nitrate, soluble reactive phosphorus (SRP), total nitrogen, calcium, magnesium, chloride, sulfate, and total organic carbon. All measurements were made at the 8.1-ha S1 bog forest site in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C 4 Grasses in Hawaii

Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non-destructively have not yet been developed for tropical perennial C 4 grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewable energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D) was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, (R 2 = 0.98, 0.96, and 0.97, respectively). The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predicted in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap) models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE)-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations provide a tool for farmers in the tropics to estimate perennial C4 grass biomass and C stock during decision-making for land management and as an environmental sustainability indicator within a renewable energy system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Modeling the Impact of Riparian Hollows on River Corridor Nitrogen Exports

Recent studies in snowmelt-dominated catchments have documented changes in nitrogen (N) retention over time, such as declines in watershed exports of N, though there is a limited understanding of the controlling processes driving these trends. Working in the mountainous headwater East River Colorado watershed, we explored the effects of riparian hollows as N-cycling hotspots and as important small-scale controls on observed watershed trends. Using a modeling-based approach informed by remote sensing and in situ observations, we simulated the N-retention capacity of riparian hollows with seasonal and yearly hydrobiogeochemical perturbations imposed as drivers. We then implemented a scaling approach to quantify the relative contribution of riparian hollows to the total river corridor N budget. We found that riparian hollows primarily serve as N sinks, with N-transformation rates significantly limited by periods of enhanced groundwater upwelling and promoted at the onset of rainfall events. Given these observed hydrologic controls, we expect that the nitrate ( NO 3 - ) sink capacity of riparian hollows will increase in magnitude with future climatic perturbations, specifically the shift to more frequent rainfall events and fewer snowmelt events, as projected for many mountainous headwater catchments. Our current estimates suggest that while riparian hollows provision ~5–20% of NO 3 - to the river network, they functionally act as inhibitors to upland NO 3 - reaching the stream. Our work linking transient hydrological conditions to numerical biogeochemical simulations is an important step in assessing N-retaining features relative to the watershed N budget and better understanding the role of small-scale features within watersheds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Raindrop Size Spectrum in Deep Convective Regions of the Americas

This study compared drop size distribution (DSD) measurements on the surfaces, the corresponding properties, and the precipitation modes among three deep convective regions within the Americas. The measurement compilation corresponded to two sites in the midlatitudes: the U.S. Southern Great Plains and Córdoba Province in subtropical South America, as well as to one site in the tropics: Manacapuru in central Amazonia; these are all areas where intense rain-producing systems contribute to the majority of rainfall in the Americas’ largest river basins. This compilation included two types of disdrometers (Parsivel and 2D-Video Disdrometer) that were used at the midlatitude sites and one type of disdrometer (Parsivel) that was deployed at the tropical site. The distributions of physical parameters (such as rain rate R, mass-weighted mean diameter D m , and normalized droplet concentration N w ) for the raindrop spectra without rainfall mode classification seemed similar, except for the much broader N w distributions in Córdoba. The raindrop spectra were then classified into a light precipitation mode and a precipitation mode by using a cutoff at 0.5 mm h -1 based on previous studies that characterized the full drop size spectra. These segregated rain modes are potentially unique relative to previously studied terrain-influenced sites. In the light precipitation and precipitation modes, the dominant higher frequency observed in a broad distribution of N w in both types of disdrometers and the identification of shallow light precipitation in vertically pointing cloud radar data represent unique characteristics of the Córdoba site relative to the others. As a result, the co-variability between the physical parameters of the DSD indicates that the precipitation observed in Córdoba may confound existing methods of determining the rain type by using the drop size distribution.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Precipitation Characteristics of Warm Season Weather Types in the Southeastern United States of America

Daily weather types (WTs) over the Southeast United States have been analyzed using 850 hPa winds from reanalysis data from March to October of 1979–2019. Six WTs were obtained. WTs 1–3 represent mid-latitude synoptic systems propagating eastward. WT4 is a summer-type pattern predominantly occurring in June–August, with the center of the North Atlantic Subtropical High (NASH) along the Gulf coast in the southern United States. WT5 is most frequent from August to middle October, with the NASH pushed further north and southerly winds over the northern Great Plains. An anticyclone centered at the Carolina coast characterizes WT6, which occurs in all months but is slightly more frequent in the spring and fall, especially in October, corresponding to fair weather in the region. WTs 1, 2 and 3 can persist for only a few days. WTs 4, 5 and 6 can have long spells of persistence. Besides self-persistence, the most observed progression loop is WT1 to WT2, to WT3, and then back to WT1, corresponding to eastward-propagating waves. WTs 4 and 5 are likely to show persistence, with long periods of consecutive days. WT6 usually persists but can also transfer to WT3, i.e., a change from fair weather in the Southeast U.S. to rainy weather in the Mississippi River Valley. A diurnal cycle of precipitation is apparent for each WT, especially over coastal plains. The nocturnal precipitation in central U.S. is associated with WT3. WTs 1–3 are more frequent in El Niño years, corresponding to stronger westerly wave activities and above normal rainfall in the Southeast U.S. in the spring. The positive rainfall anomaly in the Mississippi and Ohio River valley in El Niño years is also associated with more frequent WT3.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Overhead Protection Increases Fuel Quality and Natural Drying of Leaf-On Woody Biomass Storage Piles

Short-rotation woody crops (SRWC) have the potential to make substantial contributions to the supply of biomass feedstock for the production of biofuels and bioproducts. This study evaluated changes in the fuel quality (moisture, ash, and heating value) of stored spring harvested shrub willow (Salix spp.) and hybrid poplar (Populus spp.) chips with respect to pile protection treatments, location within the storage piles, and length of storage. Leaf-on willow and poplar were harvested in the spring, and wood chips and foliage with moisture content in the range of 42.1% to 49.9% (w.b.) were stored in piles for five months, from May to October 2016. Three protection treatments were randomly assigned to the piles. The control treatment had no cover (NC), so piles were exposed to direct solar radiation and rainfall. The second treatment had a canopy (C) installed above the piles to limit direct rainfall. The final treatment had a canopy plus a dome aeration system (CD) installed over the piles. Covering piles reduced and maintained the low moisture content in wood chip piles. Within 30 days of establishment, the moisture content in the core of the C pile decreased to less than 30%, and was maintained between 24%–26% until the end of the storage period. Conversely, the moisture content in the NC piles decreased in the first two months, but then increased to the original moisture content in the core (>45 cm deep) and up to 70% of the original moisture content in the shell (<45 cm deep). For all the treatments in the tested conditions, the core material dried faster than the shell material. The higher heating value (HHV) across all the treatments increased slightly from 18.31 ± 0.06 MJ/kg at harvest to 18.76 ± 0.21 MJ/kg at the end of the storage period. The lower heating value (LHV) increased by about 50% in the C and CD piles by the end of the storage period. However, in the NC piles, the LHV decreased by 3% in the core and 52% in the shell. Leaf-on SRWC biomass stored in piles created in late spring under climatic conditions in central and northern New York showed differing moisture contents when stored for over 60–90 days. Overhead protection could be used to preserve or improve the fuel quality in terms of the moisture content and heating value if more than two months of storage are required. However, the implementation of such management practice will depend on whether the end users are willing to pay a higher price for dryer biomass and biomass with a higher LHV.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Recovery of Forest Structure Following Large-Scale Windthrows in the Northwestern Amazon

The dynamics of forest recovery after windthrows (i.e., broken or uprooted trees by wind) are poorly understood in tropical forests. The Northwestern Amazon (NWA) is characterized by a higher occurrence of windthrows, greater rainfall, and higher annual tree mortality rates (~2%) than the Central Amazon (CA). We combined forest inventory data from three sites in the Iquitos region of Peru, with recovery periods spanning 2, 12, and 22 years following windthrow events. Study sites and sampling areas were selected by assessing the windthrow severity using remote sensing. At each site, we recorded all trees with a diameter at breast height (DBH) ≥ 10 cm along transects, capturing the range of windthrow severity from old-growth to highly disturbed (mortality > 60%) forest. Across all damage classes, tree density and basal area recovered to >90% of the old-growth values after 20 years. Aboveground biomass (AGB) in old-growth forest was 380 (±156) Mg ha -1 . In extremely disturbed areas, AGB was still reduced to 163 (±68) Mg ha -1 after 2 years and 323 (± 139) Mg ha -1 after 12 years. This recovery rate is ~50% faster than that reported for Central Amazon forests. The faster recovery of forest structure in our study region may be a function of its higher productivity and adaptability to more frequent and severe windthrows. These varying rates of recovery highlight the importance of extreme wind and rainfall on shaping gradients of forest structure in the Amazon, and the different vulnerabilities of these forests to natural disturbances whose severity and frequency are being altered by climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Farmers’ Perception of Climate Change and Its Impacts on Agriculture

Climate change and climate variability drive rapid glacier melt and snowpack loss, extreme precipitation and temperature events, and alteration of water availability in the Himalayas. There is increasing observational evidence of climate change impacts on water resource availability and agricultural productivity in the central Himalayan region. Here, we assess the farmers’ perception of climate change and its impacts on agriculture in western Nepal. We interviewed 554 households and conducted eight focus group discussions to collect farmers’ perceptions of temperature and rainfall characteristics, water availability, onset and duration of different seasons, and the impacts of such changes on their lives and livelihoods. Our results indicate that the farmers’ perceptions of rising annual and summer temperatures are consistent with observations. Perception, however, contradicts observed trends in winter temperature, as well as annual, monsoon, and winter precipitation. In addition, farmers are increasingly facing incidences of extreme events, including rainfall, floods, landslides, and droughts. These hazards often impact agricultural production, reducing household income and exacerbating the economic impacts on subsistence farmers. Integrated assessment of farmers’ perceptions and hydrometeorological observations is crucial to improving climate change impact assessment and informing the design of mitigation and adaptation strategies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Urbanization-induced urban heat island and aerosol effects on climate extremes in the Yangtze River Delta region of China

Abstract. The WRF-Chem model coupled with a single-layer urban canopy model (UCM) is integrated for 5 years at convection-permitting scale to investigate the individual and combined impacts of urbanization-induced changes in land cover and pollutant emissions on regional climate in the Yangtze River Delta (YRD) region in eastern China. Simulations with the urbanization effects reasonably reproduced the observed features of temperature and precipitation in the YRD region. Urbanization over the YRD induces an urban heat island (UHI) effect, which increases the surface temperature by 0.53 °C in summer and increases the annual heat wave days at a rate of 3.7 d yr−1 in the major megacities in the YRD, accompanied by intensified heat stress. In winter, the near-surface air temperature increases by approximately 0.7 °C over commercial areas in the cities but decreases in the surrounding areas. Radiative effects of aerosols tend to cool the surface air by reducing net shortwave radiation at the surface. Compared to the more localized UHI effect, aerosol effects on solar radiation and temperature influence a much larger area, especially downwind of the city cluster in the YRD. Results also show that the UHI increases the frequency of extreme summer precipitation by strengthening the convergence and updrafts over urbanized areas in the afternoon, which favor the development of deep convection. In contrast, the radiative forcing of aerosols results in a surface cooling and upper-atmospheric heating, which enhances atmospheric stability and suppresses convection. The combined effects of the UHI and aerosols on precipitation depend on synoptic conditions. Two rainfall events under two typical but different synoptic weather patterns are further analyzed. It is shown that the impact of urban land cover and aerosols on precipitation is not only determined by their influence on local convergence but also modulated by large-scale weather systems. For the case with a strong synoptic forcing associated with stronger winds and larger spatial convergence, the UHI and aerosol effects are relatively weak. When the synoptic forcing is weak, however, the UHI and aerosol effects on local convergence dominate. This suggests that synoptic forcing plays a significant role in modulating the urbanization-induced land-cover and aerosol effects on individual rainfall event. Hence precipitation changes due to urbanization effects may offset each other under different synoptic conditions, resulting in little changes in mean precipitation at longer timescales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Climate seasonality limits leaf carbon assimilation and wood productivity in tropical forests

Here, the seasonal climate drivers of the carbon cycle in tropical forests remain poorly known, although these forests account for more carbon assimilation and storage than any other terrestrial ecosystem. Based on a unique combination of seasonal pan-tropical data sets from 89 experimental sites (68 include aboveground wood productivity measurements and 35 litter productivity measurements), their associated canopy photosynthetic capacity (enhanced vegetation index, EVI) and climate, we ask how carbon assimilation and aboveground allocation are related to climate seasonality in tropical forests and how they interact in the seasonal carbon cycle. We found that canopy photosynthetic capacity seasonality responds positively to precipitation when rainfall is < 2000 mm yr -1 (water-limited forests) and to radiation otherwise (light-limited forests). On the other hand, independent of climate limitations, wood productivity and litterfall are driven by seasonal variation in precipitation and evapotranspiration, respectively. Consequently, light-limited forests present an asynchronism between canopy photosynthetic capacity and wood productivity. First-order control by precipitation likely indicates a decrease in tropical forest productivity in a drier climate in water-limited forest, and in current light-limited forest with future rainfall < 2000 mm yr -1 .

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites

Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. For this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Evaluating uncertainty in aerosol forcing of tropical precipitation shifts

Abstract. An observed southward shift in tropical rainfall over land between 1950 and 1985, followed by a weaker recovery post-1985, has been attributed to anthropogenic aerosol radiative forcing and cooling of the Northern Hemisphere relative to the Southern Hemisphere. We might therefore expect models that have a strong historic hemispheric contrast in aerosol forcing to simulate a further northward tropical rainfall shift in the near-term future when anthropogenic aerosol emission reductions will predominantly warm the Northern Hemisphere. We investigate this paradigm using a perturbed parameter ensemble (PPE) of transient coupled ocean–atmosphere climate simulations that span a range of aerosol radiative forcing comparable to multi-model studies. In the 20th century, in our single-model ensemble, we find no relationship between the magnitude of pre-industrial to 1975 inter-hemispheric anthropogenic aerosol radiative forcing and tropical precipitation shifts. Instead, tropical precipitation shifts are associated with major volcanic eruptions and are strongly affected by internal variability. However, we do find a relationship between the magnitude of pre-industrial to 2005 inter-hemispheric anthropogenic aerosol radiative forcing and future tropical precipitation shifts over 2006 to 2060 under scenario RCP8.5. Our results suggest that projections of tropical precipitation shifts will be improved by reducing aerosol radiative forcing uncertainty, but predictive gains may be offset by temporary shifts in tropical precipitation caused by future major volcanic eruptions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Patterns and rates of soil movement and shallow failures across several small watersheds on the Seward Peninsula, Alaska

Abstract. Thawing permafrost can alter topography, ecosystems, and sediment and carbon fluxes, but predicting landscape evolution of permafrost-influenced watersheds in response to warming and/or hydrological changes remains an unsolved challenge. Sediment flux and slope instability in sloping saturated soils have been commonly predicted from topographic metrics (e.g., slope, drainage area). In addition to topographic factors, cohesion imparted by soil and vegetation and melting ground ice may also control spatial trends in slope stability, but the distribution of ground ice is poorly constrained and hard to predict. To address whether slope stability and surface displacements follow topographic-based predictions, we document recent drivers of permafrost sediment flux present on a landscape in western Alaska that include creep, solifluction, gullying, and catastrophic hillslope failures ranging in size from a few meters to tens of meters, and we find evidence of rapid and substantial landscape change on an annual timescale. We quantify the timing and rate of surface movements using a multi-pronged, multi-scalar dataset including aerial surveys, interannual GPS surveys, synthetic aperture radar interferometry (InSAR), and climate data. Despite clear visual evidence of downslope soil transport of solifluction lobes, we find that the interannual downslope surface displacement of these features does not outpace downslope displacement of soil in locations where lobes are absent (downslope movement means: 7 cm yr−1 for lobes over 2 years vs. 10 cm yr−1 in landscape positions without lobes over 1 year). Annual displacements do not appear related to slope, drainage area, or modeled total solar radiation but are likely related to soil thickness, and volumetric sediment fluxes are high compared to temperate landscapes of comparable bedrock lithology. Time series of InSAR displacements show accelerated movement in late summer, associated with intense rainfall and/or deep thaw. While mapped slope failures do cluster at slope–area thresholds, a simple slope stability model driven with hydraulic conductivities representative of throughflow in mineral and organic soil drastically overpredicts the occurrence of slope failures. This mismatch implies permafrost hillslopes have unaccounted-for cohesion and/or throughflow pathways, perhaps modulated by vegetation, which stabilize slopes against high rainfall. Our results highlight the breadth and complexity of soil transport processes in Arctic landscapes and demonstrate the utility of using a range of synergistic data collection methods to observe multiple scales of landscape change, which can aid in predicting periglacial landscape evolution.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Effects of coupling a stochastic convective parameterization with the Zhang–McFarlane scheme on precipitation simulation in the DOE E3SMv1.0 atmosphere model

Abstract. A stochastic deep convection parameterization is implemented into the US Department of Energy (DOE) Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1.0 (EAMv1). This study evaluates its performance in simulating precipitation. Compared to the default model, the probability distribution function (PDF) of rainfall intensity in the new simulation is greatly improved. The well-known problem of “too much light rain and too little heavy rain” is alleviated, especially over the tropics. As a result, the contribution from different rain rates to the total precipitation amount is shifted toward heavier rain. The less frequent occurrence of convection contributes to suppressed light rain, while more intense large-scale and convective precipitation contributes to enhanced heavy total rain. The synoptic and intraseasonal variabilities of precipitation are enhanced as well to be closer to observations. The sensitivity of the rainfall intensity PDF to the model vertical resolution is examined. The relationship between precipitation and dilute convective available potential energy in the stochastic simulation agrees better with that in the Atmospheric Radiation Measurement (ARM) observations compared with the standard model simulation. The annual mean precipitation is largely unchanged with the use of the stochastic scheme except over the tropical western Pacific, where a moderate increase in precipitation represents a slight improvement. The responses of precipitation and its extremes to climate warming are similar with or without the stochastic deep convection scheme.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Upscaling instantaneous to daily evapotranspiration using modelled daily shortwave radiation for remote sensing applications: An artificial neural network approach

Upscaling instantaneous evapotranspiration retrieved at any specific time-of-day (ET i ) to daily evapotranspiration (ET d ) is a key challenge in mapping regional ET using polar orbiting sensors. Various studies have unanimously cited the shortwave incoming radiation ( R S ) to be the most robust reference variable explaining the ratio between ET d and ET i . This study aims to contribute in ET i upscaling for global studies using the ratio between daily and instantaneous incoming shortwave radiation ( R Sd / R Si ) as a factor for converting ET i to ET d . This paper proposes an artificial neural network (ANN) machine-learning algorithm first to predict R Sd from R Si followed by using the R Sd / R Si ratio to convert ET i to ET d across different terrestrial ecosystems. Using R Si and R Sd observations from multiple sub-networks of the FLUXNET database spread across different climates and biomes (to represent inputs that would typically be obtainable from remote sensors during the overpass time) in conjunction with some astronomical variables (e.g. solar zenith angle, day length, exoatmospheric shortwave radiation), we developed the ANN model for reproducing R Sd and further used it to upscale ET i to ET d . The efficiency of the ANN is evaluated for different morning and afternoon times of day, under varying sky conditions, and also at different geographic locations. R S -based upscaled ET d produced a significant linear relation ( R 2 = 0.65 to 0.69), low bias (-0.31 to -0.56 MJ m -2 d -1 ; approx. 4 %), and good agreement (RMSE 1.55 to 1.86 MJ m -2 d -1 ; approx. 10 %) with the observed ET d , although a systematic overestimation of ET d was also noted under persistent cloudy sky conditions. Inclusion of soil moisture and rainfall information in ANN training reduced the systematic overestimation tendency in predominantly overcast days. An intercomparison with existing upscaling method at daily, 8-day, monthly, and yearly temporal resolution revealed a robust performance of the ANN-driven R S -based ET i upscaling method and was found to produce lowest RMSE under cloudy conditions. Sensitivity analysis revealed variable sensitivity of the method to biome selection and high ET d prediction errors in forest ecosystems are primarily associated with greater rainfall and cloudiness. As a result, the overall methodology appears to be promising and has substantial potential for upscaling ET i to ET d for field and regional-scale evapotranspiration mapping studies using polar orbiting satellites.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Numerical modeling and sensitivity analysis of seawater intrusion in a dual-permeability coastal karst aquifer with conduit networks

Long-distance seawater intrusion has been widely observed through the subsurface conduit system in coastal karst aquifers as a source of groundwater contaminant. In this study, seawater intrusion in a dual-permeability karst aquifer with conduit networks is studied by the two-dimensional density-dependent flow and transport SEAWAT model. Local and global sensitivity analyses are used to evaluate the impacts of boundary conditions and hydrological characteristics on modeling seawater intrusion in a karst aquifer, including hydraulic conductivity, effective porosity, specific storage, and dispersivity of the conduit network and of the porous medium. The local sensitivity analysis evaluates the parameters' sensitivities for modeling seawater intrusion, specifically in the Woodville Karst Plain (WKP). A more comprehensive interpretation of parameter sensitivities, including the nonlinear relationship between simulations and parameters, and/or parameter interactions, is addressed in the global sensitivity analysis. The conduit parameters and boundary conditions are important to the simulations in the porous medium because of the dynamical exchanges between the two systems. The sensitivity study indicates that salinity and head simulations in the karst features, such as the conduit system and submarine springs, are critical for understanding seawater intrusion in a coastal karst aquifer. The evaluation of hydraulic conductivity sensitivity in the continuum SEAWAT model may be biased since the conduit flow velocity is not accurately calculated by Darcy's equation as a function of head difference and hydraulic conductivity. In addition, dispersivity is no longer an important parameter in an advection-dominated karst aquifer with a conduit system, compared to the sensitivity results in a porous medium aquifer. In the end, the extents of seawater intrusion are quantitatively evaluated and measured under different scenarios with the variabilities of important parameters identified from sensitivity results, including salinity at the submarine spring with rainfall recharge, sea level rise, and a longer simulation time under an extended low rainfall period.

58 GEOSCIENCES↗

DOE OSTI2025

Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability

A declining spring snowpack is expected to have widespread effects on montane and subalpine forests in western North America and across the globe. The way that tree water demands respond to this change will have important impacts on forest health and downstream water subsidies. Here, we present data from a network of sap velocity sensors and xylem water isotope measurements from three common tree species (Picea engelmannii, Abies lasiocarpa and Populus tremuloides) across a hillslope transect in a subalpine watershed in the Upper Colorado River basin. We use these data to compare tree- and stand-level responses to the historically high spring snowpack but low summer rainfall of 2019 against the low spring snowpack but high summer rainfall amounts of 2021 and 2022. From the sap velocity data, we found that only 40 % of the trees showed an increase in cumulative transpiration in response to the large snowpack year (2019), illustrating the absence of a common response to interannual spring snowpack variability. The trees that increased water use during the year with the large spring snowpack were all found in dense canopy stands – irrespective of species – while trees in open-canopy stands were more reliant on summer rains and, thus, more active during the years with modest snow and higher summer rain amounts. Using the sap velocity data along with supporting measurements of soil moisture and snow depth, we propose three mechanisms that lead to stand density modulating the tree-level response to changing seasonality of precipitation: Topographically mediated convergence zones have consistent access to recharge from snowmelt which supports denser stands with high water demands that are more reliant and sensitive to changing snow. Interception of summer rain in dense stands reduces the throughfall of summer rain to surface soils, limiting the sensitivity of the dense stands to changes in summer rain. Shading in dense stands allows the snowpack to persist deeper into the growing season, providing high local reliance on snow during the fore-summer (early-summer) drought period. Combining data generated from natural gradients in stand density, like this experiment, with results from controlled forest-thinning experiments can be used to develop a better understanding of the responses of forested ecosystems to futures with reduced spring snowpack.

54 ENVIRONMENTAL SCIENCES↗