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At least 343 records · Page 19

Assessment of Methods to Control Invasive Reed Canarygrass (Phalaris arundinacea) in Tidal Freshwater Wetlands

Controlling non-native invasive species is a significant challenge facing natural area managers in North America and around the world. Reed canarygrass (Phalaris arundinacea), is invasive in temperate freshwater wetlands throughout the United States and Canada. While methods for the prevention or elimination of reed canarygrass are generally well established, methods suitable for the unique conditions in tidal wetlands remain poorly understood. Namely, prolonged inundation of tidal wetlands for control purposes may only be accomplished with a concomitant loss of habitat connectivity and other functions. Restoration practitioners aiming to design self-sustaining wetlands in the lower Columbia River and estuary, on the northwestern Pacific Coast, have found that reed canarygrass is widespread and quick to establish throughout the 176-river-kilometer tidal freshwater floodplain. Here we report the results of a comprehensive effort to develop the knowledge base for control in tidal wetlands, through systematic review of the scientific literature, interviews with experienced practitioners, and field observations at nine Pacific Northwest sites. The review framework incorporated practical considerations and key environmental conditions: elevation related to hydrologic regime, salinity, shade, and nutrient availability. The results support implementation of multiple methods for a minimum of five years, on the largest possible area, ideally the watershed scale. Applicable methods include control in advance of restoration, topographic modification such as scrape-downs and mounds; establishing strong native competitors; and periodic, targeted control. Formal field experiments are needed to evaluate factors that influence control. Developing science-based, effective, practicable approaches to control reed canarygrass should improve restoration outcomes in natural areas.

intertidal, invasive, Phalaris arundinacea, reed c↗

Greater vulnerability of snowmelt-fed river thermal regimes to a warming climate

While the advective flux from cool melt runoff can be a significant source of thermal energy to mountainous rivers, it has been a much less addressed process in river temperature modeling and thus our understanding is limited with respect to the spatiotemporal effect of melt on river temperatures at the watershed scale. In particular, the extent and magnitude of the melt cooling effect in the context of a warming climate are not yet well understood. To address this knowledge gap, we improved a coupled hydrology and stream temperature modeling system, Distributed Hydrology Soil Vegetation Model and River Basin Model (DHSVM-RBM), to account for the thermal effect of cool snowmelt runoff on river temperatures. The model was applied to a snow-fed river basin in the Pacific Northwest to evaluate the responses of snow, hydrology, stream temperatures, and potential fish growth to future climates. Historical simulations suggest that snowmelt can notably reduce the basin-wide peak summer temperatures particularly at high-elevation tributaries, while the thermal impacts of melt water can persist through the summer along the mainstem. Ensemble climate projections suggested that a warming climate will decrease basin mean peak snow and summer streamflow by 92% and 60% by the end of the century. Due to the compounded influences of warmer temperatures, lower flows and diminished cooling from melt, rivers reaches in high elevation snow-dominated areas were projected to be most vulnerable to future climate change, showing the largest increases in summer peak temperatures. As a result, thermal habitat used by anadromous Pacific salmon was projected to exhibit substantially lower growth potential during summer in future. These results have demonstrated the necessity of accounting for snowmelt influence on stream temperature modeling in mountainous watersheds.

54 ENVIRONMENTAL SCIENCES↗

Model scripts associated with “Revisiting controls on hyporheic respiration with knowledge-guided machine learning at continental scale”

NOTE: The manuscript associated with this data package is currently in review. The data/scripts may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final scripts and additional metadata. This data package is associated with the publication “Revisiting controls on hyporheic respiration with knowledge-guided machine learning at continental scale” submitted to Environmental Science & Technology (Zheng et al. 2026). The project combines mechanistic process modeling with knowledge-guided machine learning (KGML) to evaluate how organic matter chemistry, microbial biomass, and physical substrate accessibility regulate realized respiration rates across river corridors. All data used in this paper have been previously published and can be accessed at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719 (Goldman et al., 2020). This data package contains 3 R-markdown (Rmd) preprocessing scripts for the previously published data and subsequent modelling workflows. The full workflow with input and output data can be found in the associated GitHub repository at https://github.com/jianqiuz/KGML-WHONDRS.

Biogeochemistry↗

Elevation distributed micro-climatology data in a coastal glaciated watershed

Air temperature, ground temperature and relative humidity data were collected in a longitudinal transect of the Nooksack watershed at varying elevations from 500 to 1800 m above sea level. Data were collected by anchoring sensors from trees above winter snow levels and shaded from direct solar radiation. Paired sensors were also buried 3 cm under ground near each air temperature sensor to determine snow absence or presence. Select sites included relative humidity sensors to indicate whether precipitation was occurring. Data were collected every 3-4 h from December 2015 to Sept 2018 (with ongoing collection). Code for analysis of daily mean, minimum, maximum, and temperature change with elevation (lapse rates) are available on Github (https://doi.org/10.5281/zenodo.3239539). The sensor download and intermediate data products are available on HydroShare at (http://www.hydroshare.org/resource/222e832d3df24dea9bae9bbeb6f4219d) with publicly accessible visualization available from the Nooksack Observatory at data.cuahsi.org. Hydrologic models are generally structured with a single annual average lapse rate parameter which assumes a linear temperature gradient with elevation. The daily data (2016-2018) is used as part of ongoing studies on the non-linear dynamics and temporal variability of temperature with elevation to improve assessments of watershed function and salmon habitat.

54 ENVIRONMENTAL SCIENCES↗

High-Performance Simulation of Dynamic Hydrologic Exchange and Implications for Surrogate Flow and Reactive Transport Modeling in a Large River Corridor

Hydrologic exchange flows (HEFs) have environmental significance in riverine ecosystems. Key river channel factors that influence the spatial and temporal variations of HEFs include river stage, riverbed morphology, and riverbed hydraulic conductivity. However, their impacts on HEFs were often evaluated independently or on small scales. In this study, we numerically evaluated the combined interactions of these factors on HEFs using a high-performance simulator, PFLOTRAN, for subsurface flow and transport. The model covers 51 square kilometers of a selected river corridor with large sinuosity along the Hanford Reach of the Columbia River in Washington, US. Three years of spatially distributed hourly river stages were applied to the riverbed. Compared to the simulation when riverbed heterogeneity is not ignored, the simulation using homogeneous riverbed conductivity underestimated HEFs, especially upwelling from lateral features, and overestimated the mean residence times derived from particle tracking. To derive a surrogate model for the river corridor, we amended the widely used transient storage model (TSM) for riverine solute study at reach scale with reactions. By treating the whole river corridor as a batch reactor, the temporal changes in the exchange rate coefficient for the TSM were derived from the dynamic residence time estimated from the hourly PFLOTRAN results. The TSM results were evaluated against the effective concentrations in the hyporheic zone calculated from the PFLOTRAN simulations. Our results show that there is potential to parameterize surrogate models such as TSM amended with biogeochemical reactions while incorporating small-scale process understandings and the signature of time-varying streamflow to advance the mechanistic understanding of river corridor processes at reach to watershed scales. However, the assumption of a well-mixed storage zone for TSM should be revisited when redox-sensitive reactions in the storage zones play important roles in river corridor functioning.

Fang, Yilin↗

Evaluation of distributed process-based hydrologic model performance using only a priori information to define model inputs

Fully distributed, integrated surface–subsurface hydrological models (ISSHMs) have seen renewed interest due to availability of better software, high performance computing facilities, and high-resolution, spatially extensive data products. ISSHMs are valuable as tools for advancing system understanding as they can resolve multiple processes defined on the plot scale including three-dimensional interaction of surface water and groundwater. Here, we evaluated the performance of an ISSHM, the Advanced Terrestrial Simulator (ATS), on seven diverse catchments across the continental US using widely available data products to define model inputs without calibration. We compare the ATS-simulated streamflow and evapotranspiration with gauge observations and MODIS-derived evapotranspiration, respectively. Using the Kling-Gupta Efficiency (KGE) as metric, ATS with default data products performed reasonably well at 6 of 7 catchments for streamflow. However, in one of those 6 catchments ATS had poor performance on baseflow and ATS’s overall performance was thus judged to be inadequate despite the acceptable KGE. ATS performance for evapotranspiration was good in all 7 catchments using default data products. In the two catchments where ATS streamflow performance using default data products was not acceptable, the performance was significantly improved by using local information on subsurface properties below the soil. We also compare the model-simulated streamflow and evapotranspiration with the Sacramento soil moisture accounting (SAC-SMA) model, a semi-distributed model that was calibrated on a catchment-by-catchment basis. Uncalibrated ATS performance is comparable to the calibrated SAC-SMA model in terms of streamflow while ATS performance is similar to or better (much better in certain catchments) in reproducing MODIS-derived evapotranspiration. Reasonably good performance of ATS without catchment-specific calibration provides new confidence in the ISSHM class of models and community data products as tools for advancing understanding of watershed function in a changing environment.

54 ENVIRONMENTAL SCIENCES↗

How does Mercury Methylation Respond to Intensive Forest Management and the Creation of Anoxia in Floodplain Soils

This research endeavor, entitled “How does Mercury Methylation Respond to Intensive Forest Management and the Creation of Anoxia in Floodplain Soils?” represents a collaborative effort undertaken by the University of North Carolina at Greensboro, led by Principal Investigator Dr. James S. Coleman, the United States Forest Service Santee Experimental Forest (SEF) Station Director Dr. Carl C. Trettin as Co-Principal Investigator, and The Chinese University of Hong Kong Dr. Martin Tsz-Ki Tsui and Dr. Alex T. Chow serving as Co-Principal Investigators. The overarching objective of this proposed project was to capture and elucidate the immediate and short-term effects of forest disturbances, namely clear-cutting and thinning, on the biogeochemical cycling of mercury (Hg) within the SEF in Huger, South Carolina. To accomplish this objective, a two-year exploratory study was proposed to conduct soil sampling and measurements of Hg and toxic methylmercury (MeHg), and soil physiochemical data within the experimental watershed (WS77) at SEF, following the clear-cutting process initiated for the preparation of the native longleaf pine restoration project by the USFS. Based on our mercury and hydrological data assessment, we concluded that the implementation of forest management practices, particularly mechanical thinning and clear-cutting, appears to enhance the potential for Hg methylation. Furthermore, these forest management practices may disrupt and alter the storage, mobility, and transformations of atmospherically deposited Hg in these lowland forests. We advocate for further research to comprehensively evaluate the impact of forest management on Hg cycling within forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗

The weathered bedrock vadose zone: A hidden control on water availability in the western United States (Final Technical Report)

This report summarizes the research completed during the project entitled "The weathered bedrock vadose zone: A hidden control on water availability in the western United States" (Award: DE-SC0018039). The report covers work completed between 9/15/17 and 9/14/20. The objective of the exploratory project work was to evaluate the overarching hypothesis that the subsurface underlying actively eroding landscapes is systematically structured as a result of a balance between weathering and erosion and that this structure leads to dynamic moisture storage within weathered rock. To accomplish project objectives, we characterized hillslope weathering profile structure and conducted subsurface moisture monitoring across four study sites with comparable bedrock types but differing erosion rate and hydroclimate: The Angelo Coast Range Reserve (ACRR), Sagehorn-Russell Ranch (SRR), Antelope Valley Ranch (AVR), and the LBNL Watershed Function Scientific Focus Area (SFA). New characterization and monitoring infrastructure at the AVR and SFA sites was established through this project and enables long-term monitoring of hydrologic and carbon fluxes at the sites for comparison with long-term monitoring in other sites. Deep drilling, downhole logging, and characterization of chemistry and porosity of rock recovered from drilling reveals two weathering fronts across the sites. A shallower front is marked by the extent of pervasive fracturing and oxidation of pyrite and organic carbon. A deeper weathering front is marked by the appearance of open fractures and discoloration. At the AVR site, multiple ridge tops of different hillslope length were investigated to establish the relationship between the weathering front and topography. Drilling reveals that the fraction of the hillslope relief that is weathered scales with hillslope length, consistent with the theoretical framework that guided the project relating groundwater drainage with landscape evolution. With the establishment of new boreholes, we have documented significant water storage in weathered bedrock using low-field borehole nuclear magnetic resonance (NMR) across all four sites. In the upper 4 m of bedrock, the average water contents at ACRR, AVR, SRR, and SFA are approximately 25%, 16%, 25%, 23% respectively. At the ACRR site, where long-term monitoring via neutron probe surveys and time-domain transmission sensors are available, we have demonstrated that NMR reliably records moisture content and importantly, moisture content dynamics in weathered bedrock. Across all sites, our NMR monitoring has also revealed that a considerable fraction of the water storage occurs in fractures or pores that are significantly larger than the fine-grained bedrock matrix of the parent rock. To identify the proportion of water storage occurring in fractures and large pores, we analyzed the NMR signal by evaluating both the sum of echoes and an inversion of the NMR signal for a distribution of T2 relaxation times. Both methods reveal that at least 20% of the water storage occurs in fractures and larger pores across all sites. To constrain the interpretation of the in-situ field-scale NMR measurements, we compare the NMR response in the field to independent pore-structure information obtained via helium pycnometry. Results support the inference that dynamic seasonal water storage is dominantly restricted to the fracture network, which can reach 7% of the total volume. This dynamic range in water content is comparable to that of some soils, underscoring the need to understand how this region of the Earth System is structured, and functions as a hydrologic reservoir.

58 GEOSCIENCES↗

An Integrated Hydrological and Water Management Study of the Entire Nile River System - Lake Victoria to Nile Delta

The Nile basin River system spans 3 million km(exp 2) distributed over ten nations. The eight upstream riparian nations, Ethiopia, Eretria, Uganda, Rwanda, Burundi, Congo, Tanzania and Kenya are the source of approximately 86% of the water inputs to the Nile, while the two downstream riparian countries Sudan and Egypt, presently rely on the river's flow for most of the their needs. Both climate and agriculture contribute to the complicated nature of Nile River management: precipitation in the headwaters regions of Ethiopia and Lake Victoria is variable on a seasonal and inter-annual basis, while demand for irrigation water in the arid downstream region is consistently high. The Nile is, perhaps, one of the most difficult trans-boundary water issue in the world, and this study would be the first initiative to combine NASA satellite observations with the hydrologic models study the overall water balance in a to comprehensive manner. The cornerstone application of NASA's Earth Science Research Results under this project are the NASA Land Data Assimilation System (LDAS) and the USDA Atmosphere-land Exchange Inverse (ALEXI) model. These two complementary research results are methodologically independent methods for using NASA observations to support water resource analysis in data poor regions. Where an LDAS uses multiple sources of satellite data to inform prognostic simulations of hydrological process, ALEXI diagnoses evapotranspiration and water stress on the basis of thermal infrared satellite imagery. Specifically, this work integrates NASA Land Data Assimilation systems into the water management decision support systems that member countries of the Nile Basin Initiative (NBI) and Regional Center for Mapping of Resources for Development (RCMRD, located in Nairobi, Kenya) use in water resource analysis, agricultural planning, and acute drought response to support sustainable development of Nile Basin water resources. The project is motivated by the recognition that accurate, frequent, and spatially distributed estimates of the water balance are necessary for effective water management. This creates a challenge for watersheds that are large, include data poor regions, and/or span multiple nations. All of these descriptors apply to the Nile River basin, yet successful management of the Nile is critical for development and political stability in the region. For this reason, improved hydrological data to support cooperative water management in the Nile basin is a priority for USAID, the US State Department, the World Bank and other international organizations. In this project, the U.S. based research team is working with partners at RCMRD, Nile Basin Initiative (NBI), and their member national-level agencies to develop satellite-based land cover maps, satellite-derived evapotranspiration estimates (using the ALEXI algorithm), and NASA's Land Data Assimilation System (LDAS) customized to match identified information needs. The cornerstone applied sciences product of the project is the development of a customized "Nile LDAS" that will produce optimal estimates of hydrological states and fluxes, as vetted against the in situ observations of NBI and RCMRD member organizations and independent satellite-derived hydrological estimates. Nile LDAS will be applied to improve the reliability of emerging Decision Support Systems in applications that include drought monitoring, reservoir management, and irrigation planning. The end-users such as RCMRD, NBI, Ethiopian and Kenya Meteorological and Famine Early Warning System Network (FEWSNet) will be the eventual benefactors of this work. There will be a capacity building process involving the above end-user organizations and transfer the models and the results for these organizations to execute for future use. The team has already initiated this study and the early results of first years' work are shown. The plan is to complete this work by late 2013.

Habib, Shahid↗

BioRT‐HBV 1.0: A Biogeochemical Reactive Transport Model at the Watershed Scale

Abstract Reactive Transport Models (RTMs) are essential tools for understanding and predicting intertwined ecohydrological and biogeochemical processes on land and in rivers. While traditional RTMs have focused primarily on subsurface processes, recent watershed‐scale RTMs have integrated ecohydrological and biogeochemical interactions between surface and subsurface. These emergent, watershed‐scale RTMs are often spatially explicit and require extensive data, computational power, and computational expertise. There is however a pressing need to create parsimonious models that require minimal data and are accessible to scientists with limited computational background. To that end, we have developed BioRT‐HBV 1.0, a watershed‐scale, hydro‐biogeochemical RTM that builds upon the widely used, bucket‐type HBV model known for its simplicity and minimal data requirements. BioRT‐HBV uses the conceptual structure and hydrology output of HBV to simulate processes including advective solute transport and biogeochemical reactions that depend on reaction thermodynamics and kinetics. These reactions include, for example, chemical weathering, soil respiration, and nutrient transformation. The model uses time series of weather (air temperature, precipitation, and potential evapotranspiration) and initial biogeochemical conditions of subsurface water, soils, and rocks as input, and output times series of reaction rates and solute concentrations in subsurface waters and rivers. This paper presents the model structure and governing equations and demonstrates its utility with examples simulating carbon and nitrogen processes in a headwater catchment. As shown in the examples, BioRT‐HBV can be used to illuminate the dynamics of biogeochemical reactions in the invisible, arduous‐to‐measure subsurface, and their influence on the observed stream or river chemistry and solute export. With its parsimonious structure and easy‐to‐use graphical user interface, BioRT‐HBV can be a useful research tool for users without in‐depth computational training. It can additionally serve as an educational tool that promotes pollination of ideas across disciplines and foster a diverse, equal, and inclusive user community.

Sadayappan, Kayalvizhi↗

Meteorological, reference evapotranspiration and estimated transpiration data, July 2020-Dec 2021, Slate River Floodplain, Crested Butte, Colorado

This data package includes a time series of meteorological data (air temperature, relative humidity, barometric pressure, precipitation, wind speed, soil heat flux, incoming shortwave radiation, incoming longwave radiation, outgoing shortwave radiation and outgoing longwave radiation) from the Slate River floodplain outside Crested Butte, Colorado, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The package also includes reference evapotranspiration calculated via the Penman-Monteith equation and an estimate of willow (Salix spp.) evapotranspiration using the method of Irmak et al., J. Hydrology, 2013. Due to two malfunctioning sensors (incoming shortwave radiation from Oct 2020-May 2021 and incoming longwave radiation from May 2021-March 2022), observed net radiation and calculated evapotranspiration are only included from July-October 2020. However, users may be able to extend calculated evapotranspiration using estimates of these two parameters from other sources. Both sensors have been replaced and data beyond 2021 be uploaded to this repository when it is available.Within the data package, "FLMD.csv" describes file-level metadata and "dd.csv" defines column headers and universal terms across the dataset. The data package includes 3 "*data.csv" files, two for meteorological data for 2020 and 2021 and one for reference evapotranspiration and transpiration data from 2020 ("SLT_OBJ2_PenmanMonteith_2020_data.csv"). Each "*data.csv" file of meteorological data has a corresponding "*_InstallationMethods.csv" file that describes the location, sensor model, sensor serial number and other metadata corresponding to each measured parameter. We also include a Jupyter notebook ("PenmanMonteithET_Calculations.ipynb") that details the assumptions and equations used to calculate daily and hourly reference evapotranspiration and daily willow transpiration from raw meteorological data.

54 ENVIRONMENTAL SCIENCES↗

NASA-Modified Precipitation Products to Improve EPA Nonpoint Source Water Quality Modeling for the Chesapeake Bay

The Environmental Protection Agency (EPA) has estimated that over 20,000 water bodies within the United States do not meet water quality standards. Ninety percent of the impairments are typically caused by nonpoint sources. One of the regulations in the Clean Water Act of 1972 requires States to monitor the Total Maximum Daily Load (TMDL), or the amount of pollution that can be carried by a water body before it is determined to be "polluted", for any watershed in the U.S.. In response to this mandate, the EPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a Decision Support Tool (DST) for assessing pollution and to guide the decision making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program -- Fortran (HSPF), computes daily stream flow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA modified/NOAA precipitation data. Using these data within HSPF, stream flow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better stream flow statistics and, ultimately, in improved water quality assessment.

Nigro, Joseph↗

Hydropower Infrastructure - LAkes, Reservoirs, and RIvers (HILARRI), v4

HILARRI is a database of links between major datasets of operational hydropower dams and powerplants, and inland water bodies. These connections are critical for conducting large-scale analysis of hydropower infrastructure and their associated natural and engineered water systems. Features include: – Dams from the National Inventory of Dams (2025) and the Global Reservoir and Dam Database (GRanD v1.3) – Hydropower plants from the Existing Hydropower Assets dataset (EHA 2025) – Power plants that are listed in the 2025 U.S. Hydropower Development Pipeline Data or were listed in previous versions of the dataset These hydropower infrastructure features are linked to several major datasets that provide hydrologic and hydraulic information relevant for analysis of hydropower systems that includes the integral water resources. That information comes from: – Products from the National Hydrography Dataset (NHD) – NHDPlusV2 Medium Resolution river network flowlines, – NHD waterbodies (limited to lakes and reservoirs), – NHD Watershed Boundary Dataset (HUC12-level for the Conterminous United States (CONUS)) – NHD High Resolution waterbodies – HydroLAKES water bodies (lakes and reservoirs) – LAGOS-US lakes and reservoirs – EPA National Lakes Assessment (2007, 2012, 2017, and 2022) – The Reservoir Sedimentation Database (RESSED) – EPA SuRGE sampling locations Unique identifiers are used to facilitate joining to the original full datasets. For example, characteristics of NHD flowlines such as estimated average flow rate can be joined from the NHDPlusV2 dataset to a dam or power plant listed in HILARRI based on the ID field, “COMID”, that is common to both datasets. HILARRI only includes basic information about identifiers, location, and data quality or usage notes. It does not contain the attributes or time series data associated with these sites. The HILARRI dataset incorporates information from several datasets to facilitate more effective and accurate analysis of hydropower infrastructure and their associated waterbodies. For example, dams were checked against the most recent American Rivers Dam Removal Database to identify and flag facilities that may no longer exist. Additionally, dams that are listed multiple times in the NID are identified and flagged to avoid double-counting when analyzing and summarizing information. Other quality flags include certainty of operational hydropower (i.e., if one or more datasets indicates hydropower at a particular location), whether an associated water body is accurate or composed of multiple polygons, or whether there is a known issue with reported characteristics in one of the underlying datasets. These additional data flags are designed to increase confidence in data usage for individual to large-scale analyses.

Hansen, Carly [ORNL] (ORCID:0000000193280838)↗

Remote sensing-aided systems for snow qualification, evapotranspiration estimation, and their application in hydrologic models

The design of general remote sensing-aided methodologies was studied to provide the estimates of several important inputs to water yield forecast models. These input parameters are snow area extent, snow water content, and evapotranspiration. The study area is Feather River Watershed (780,000 hectares), Northern California. The general approach involved a stepwise sequence of identification of the required information, sample design, measurement/estimation, and evaluation of results. All the relevent and available information types needed in the estimation process are being defined. These include Landsat, meteorological satellite, and aircraft imagery, topographic and geologic data, ground truth data, and climatic data from ground stations. A cost-effective multistage sampling approach was employed in quantification of all the required parameters. The physical and statistical models for both snow quantification and evapotranspiration estimation was developed. These models use the information obtained by aerial and ground data through appropriate statistical sampling design.

Korram, S.↗

The contribution of space observations to water resources management; Proceedings of the Symposium, Bangalore, India, May 29-June 9, 1979

The symposium focused on hydrology, soil moisture estimation and ground water exploration, wetlands monitoring and water quality estimation, hydrometeorology, snow and ice monitoring, and evapotranspiration estimation. Other problems discussed include surface water and flood mapping, watershed runoff estimation and prediction, and new space systems contributing to water resources management.

Salomonson, V. V.↗

Potomac River Basin Water Resources: Assessing Water Quality and Quantity in the National Capital Region Using NASA Earth Observations

The Potomac River Basin (PRB) is responsible for providing drinking water to over 5 million residents and plays a significant role in the health of the Chesapeake Bay. Therefore, it is important to understand the relationship between water quality, landcover, and the hydrological cycle within the PRB. The National Park Service (NPS) has monitored 37 streams within the National Park Units in Maryland, Virginia, West Virginia and Washington, D.C. This project aimed to help the NPS better understand trends in water quality to supplement their ability to monitor changes in the National Capital Region Network (NCRN). Google Earth Engine, ArcGIS Pro, R, and Python were used for data retrieval, visualization, and analysis. Earth observations included Landsat 5 TM and Landsat 8 OLI/TIRS imagery. Ancillary data included the USDA Cropland Data Layer, Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS), and soil moisture data from the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS). We compared Land use/land cover (LULC), Normalized Difference Vegetation Index (NDVI), precipitation and soil moisture data to water quality data provided by the NPS at a watershed level. LULC change maps were also generated for the PRB between 2008 and 2022. We found significant correlations between precipitation, soil moisture, NDVI, and water quality. Correlations were found between certain land use types and water quality metrics, but findings varied greatly between watersheds. These insights emphasize the imperative of strategic watershed management in preserving the integrity of key aquatic systems.

Landsat↗

How extreme rainfall and failing dams unleashed the Derna flood disaster

On September 11, 2023, Storm Daniel unleashed unprecedented rainfall over the Wadi Derna watershed, triggering one of the most devastating floods in modern history, striking Derna, a coastal city in Libya. This study reconstructs the disaster using an integrated modeling approach that combines satellite imagery, hydrologic, hydraulic, and geotechnical simulations, machine learning, eyewitness accounts, and digital elevation data to assess the impact of cascading dam failures. Our findings reveal that the region’s dams, even if structurally sound, would have provided minimal protection against the extreme runoff. However, their failure unleashed a destructive surge wave, amplifying the disaster’s magnitude and devastation. Here, we show that the collapse of aging flood control infrastructures, compounded by inadequate risk assessment and emergency preparedness, dramatically escalated the disaster’s impact. Our findings underscore the urgent need for systematic dam safety evaluations, enhanced flood forecasting, and adaptive risk management strategies that address climate extremes and infrastructure vulnerabilities.

Hydrology↗

WHONDRS River Corridor Surface Water Metabolites and Geochemistry from Global Sites

This dataset supports a broader study examining the character of organic matter that may be delivered to subsurface sediments via hydrologic exchange. To implement the global survey, free stream sampling kits were provided to interested volunteers throughout the world. Samples were collected with minimal constraints in terms of location, but following strict protocols, and shipped for metabolomic analysis via Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). In addition, basic geochemistry analyses (e.g., dissolved organic matter concentration) were conducted, standardized photos of each field system were taken, and extensive metadata were captured. Sampling began in 2018 and is ongoing as of 2025. This dataset is comprised of one folders of field photos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data, and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocol; and (7) a subfolder with sample data. The sample data subfolder contains (1) surface water dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) methods codes; (3) surface water FTICR methods; and (4) a subfolder of 12 Tesla (12T) FTICR-MS data. This folder contains three subfolders, one containing the.xml files, one containing the CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, or .png. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.

Biogeochemistry↗