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At least 55 records · Page 3Linked to original sources
USGS2021

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).

Agricultural and Forest Meteorology↗
USGS2022

From flowering to foliage: Accelerometers track tree sway to provide high-resolution insights into tree phenology

Trees are bioindicators of global climate change and regional urbanization, but available monitoring tools are ineffective for fine-scale observation of many species. Using six accelerometers mounted on two urban ash trees ( Fraxinus americana ), we looked at high-frequency tree vibrations, or change in periodicity of tree sway as a proxy for mass changes, to infer seasonal patterns of flowering and foliage (phenophases). We compared accelerometer-estimated phenophases to those derived from digital repeat photography using Green Chromatic Coordinates (GCC) and visual observation of phenophases defined by the USA National Phenology Network (NPN). We also drew comparisons between two commercial accelerometers and assessed how placement height influenced the ability to extract seasonal transition dates. Most notably, tree sway data showed a greenness signal in an urban environment and produced a clear flowering time-series and peak flowering signal (PF), marking the first observations of a flower phenophase using accelerometer data. Estimated start of spring (SOS) from accelerometers and time-lapse GCC were more similar than start of autumn (SOA); accelerometers lagged behind the time-lapse camera dates by three and four days for SOS and 13 and 14 days for SOA for each tree. Estimates for SOS and SOA from accelerometers and time-lapse cameras aligned closely with different NPN phenophases. The two commercial accelerometers produced similar season onset: a difference of 2.4 to 3.8 days for SOS, 2.1 days for SOA, and 0.5 to 2.0 days for PF. Accelerometers placed at the main crown branch point versus higher in the canopy showed a difference of 0.2 to 4.9 days for SOS and -1.5 to 1.7 days for PF. Our results suggest accelerometers present a novel opportunity to objectively monitor reproductive tree biology and fill gaps in phenology observations. Furthermore, widely available accelerometers show promise for scaling up from individual trees to the landscape level to aid forest management and assessing climate change impacts to tree phenology.

Colorado↗
USGS2022

Prairie wetlands as sources or sinks of nitrous oxide: Effects of land use and hydrology

National and global greenhouse gas (GHG) budgets are continually being refined as data become available. Primary sources of the potent GHG nitrous oxide (N 2 O) include agricultural soil management and burning of fossil fuels, but comprehensive N 2 O budgets also incorporate less prominent factors such as wetlands. Freshwater wetland GHG flux estimates, however, have high uncertainty, and wetlands have been identified as both sources and sinks. Here, we analyzed a regional database of >26,000 N 2 O chamber flux measurements sampled across >150 wetlands from the Prairie Pothole Region (PPR) in the Great Plains of North America. Our goal was to identify important land use and hydrologic drivers of N 2 O flux to help reduce uncertainty in N 2 O models, and to incorporate these drivers into an upscaled estimate of wetland N 2 O emissions from the U.S. portion of the PPR. Within individual wetlands, exposed soils with no standing water, such as along wetland edges, were hotspots that accounted for greater than 90% of wetland N 2 O emissions. In contrast wet (i.e., ponded) areas had minimal or negative N 2 O flux. N 2 O flux from wetlands nested within croplands (16.3–17.3 μg N 2 O m −2 hr −1 ) was, in some instances, nearly double that from wetlands within grasslands (9.2–14.4 μg N 2 O m −2 h −1 ). We estimated that seasonal N 2 O flux from PPR wetlands equated to roughly 0.2% (1.04 Tg CO 2 equivalents) of the U.S. N 2 O budget (c. 2019). Overall, even though PPR wetlands are a small net source of N 2 O to the atmosphere, their emissions are negligible relative to agricultural soil management. Policy and management to restore wetland hydrology and surrounding uplands from cropland to grasslands can reduce landscape N 2 O fluxes. Future activities focused on wetland N 2 O flux would benefit from inclusion of adjacent land use and hydrologic factors, as well as from incorporation of temporally dynamic ponded wetland areas.

Iowa, Minnesota, Montana, North Dakota, South Dako↗
USGS2022

Causality guided machine learning model on wetland CH4 emissions across global wetlands

Wetland CH 4 emissions are among the most uncertain components of the global CH 4 budget. The complex nature of wetland CH 4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH 4 emissions. In this study, we used the flux measurements of CH 4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH 4 emissions at sub-seasonal scale. We found that soil temperature is the dominant factor for CH 4 emissions in all studied wetland types. Ecosystem respiration (CO 2 ) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH 4 emissions differed by up to a factor of 4 under a +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH 4 emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH 4 emissions within earth system land models.

Agricultural and Forest Meteorology↗
USGS2023

Operationalizing crop model data assimilation for improved on-farm situational awareness

The ability of ‘digital agriculture’ to support on-farm decision making is predicated on the real-time combination of observations and prior knowledge into an integrated digital environment. The mathematical discipline that seeks to provide this integration is known as model data assimilation (DA), with demonstrated benefits including improved predictive reliability, and the capacity to identify unexpected changes in field conditions and potential measurement errors. Despite routine adoption in other fields, the delayed adoption of DA in agriculture is due to the need to express end-of-season outcomes such as yield, update forecasts of these outcomes throughout the growing season as data become available, and enhance forecast reliability. To overcome these challenges, three guiding principles are introduced, providing a means to operationalize crop model DA for robust on-farm decision support. We apply the guiding principles using a South Australian viticulture case study. Our case study involves application of an iterative form of a widely used DA algorithm (ensemble Kalman filter) to dynamically update both static parameters and states associated with a grapevine simulation model. Daily weather data as well as fortnightly ground-based leaf area index (LAI) data are used for assimilation. It is shown how crop model DA can lead to not only significant improvements in forecasts of LAI but also to forecasts of end-of-season yield. The guiding principles also enable observations of greatest value to be identified throughout the season. This study highlights the role that formal crop model DA can play in agricultural decision support through enhancing situational awareness in real time.

Agricultural and Forest Meteorology↗
USGS2024

A comparative analysis of OpenET for evaluating evapotranspiration in California almond orchards

The almond industry in California faces water management challenges that are being exacerbated by droughts, climate change, and groundwater sustainability legislation. The Tree-crop Remote sensing of Evapotranspiration eXperiment (T-REX) aims to explore opportunities to improve precision irrigation management for woody perennial cropping systems. Almond orchards in the California Central Valley were equipped with eddy covariance flux measurements to evaluate satellite remote sensing-based evapotranspiration (RSET) models. OpenET provides high-resolution (30-m spatial and daily temporal) RSET data, synthesizing decades of research for practical water management. This study provides an evaluation of OpenET performance at six almond sites covering a large range in soils, age, and variety. It also compares OpenET ensemble evapotranspiration (ET) data with applied irrigation and precipitation records over an additional 148 almond orchards located in the Central Valley of California. Results show OpenET models, including the ensemble ET value, produced reasonable and actionable ET values, with overall coefficient of determination (R 2 ) and mean absolute error values of 0.73- and 0.95-mm d −1 at the daily time step, respectively. However, given the temporal sampling of Landsat (8-day revisit) and the interpolation methods used, the assessed ET models had difficulty in capturing short-term variability in almond ET; for example, the rapid decline in measured ET observed as a response to lack of irrigation preceding and during almond harvest. The study also drew attention to the spatial complexity in scenarios where irrigated orchards are surrounded by hot/dry areas, causing discrepancies between measured and modeled ET values. In comparison with irrigation records, OpenET ensemble ET was capable of quantifying water input (applied irrigation + precipitation) in almond orchards to within 13 % when evaluating monthly data. Initial results presented here reinforce the idea that RSET models, such as in OpenET, are powerful tools, yet their application requires nuanced understanding and careful consideration of local conditions.

California↗
USGS2025

Network of networks: Time series clustering of AmeriFlux sites

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under-sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.

Agricultural and Forest Meteorology↗
USGS2025

Beyond optimality: Dryland ecosystems infrequently use water efficiently for carbon gain

Optimality theory assumes plants maximize carbon gain per unit water lost and is often implemented to scale leaf-level carbon gain and water use to regional and global scales. Optimality theory is often mathematically represented by assuming plant water-use efficiency (WUE) scales with VPD k , where k = ½ represents expected optimal behavior. It is unclear, however, if this relationship holds in arid and semi-arid ecosystems that are strongly impacted by soil and atmospheric moisture status. We used data from seven flux tower sites along an aridity gradient in New Mexico to answer: how does the relationship between WUE and VPD compare to expectations based on optimality theory? To address this question, we integrated the Dynamic Evapotranspiration Partitioning Approach for Rapid Timescales with a stochastic antecedent model to estimate ecosystem-level WUE (GPP/T) and the net sensitivity of WUE to VPD, or k Dynamic , which we compare to the theoretical optimal sensitivity of k = ½. Our results show that optimality theory is not always appropriate, and k Dynamic often deviates from ½, especially at some of the more arid sites or during periods of low soil moisture. At less arid, higher elevation sites, k Dynamic is most consistent with optimality theory at moderate VPD levels, but not at high VPD. In general, the sensitivity of WUE to VPD is highly variable such that k Dynamic exhibits notable daily and seasonal variability, suggesting highly dynamic stomatal behavior. These results emphasize that representing plant water-use strategies as dynamic in time and space is critical to improving large-scale estimates of plant water use.

New Mexico↗
USGS2026

Lowland tropical forests remain a methane sink under warming and long-term hurricane disturbance recovery

Methane (CH 4 ) is a potent greenhouse gas, and tropical forests account for roughly one–third of global atmospheric CH 4 uptake by soils. Projected warming and more frequent hurricanes in these ecosystems may alter soil CH 4 sink strength, as warmer and wetter soils enhance methanogenesis activity. We measured soil CH 4 and CO 2 efflux during the calendar summer months of 2023 and 2024 alongside continuous records of soil moisture, soil and air temperature, and precipitation in an in–situ warming experiment (TRACE) located in a lowland tropical forest in Puerto Rico, six to seven years after Hurricanes Irma and Maria (2017). The realized warming (∼1.95°C) enhanced soil respiration only in summer 2023 ( p < 0.05), but net soil CH 4 uptake was invariant in both campaigns ( p > 0.05). Instead, sampling day and between–plot variability explained soil CH 4 dynamics much more than treatment contrasts. Importantly, CH 4 uptake was consistently coupled to CO 2 efflux, suggesting tight linkages between methanotrophic and heterotrophic activities. Between treatments, CH 4 and CO 2 responses to soil temperature variation were less sensitive in warmed plots, which may suggest weak metabolic upregulation under elevated temperatures. Together, these findings indicate that lowland tropical soils remain CH 4 sink even under warming and years after hurricane disturbance, with CH 4 dynamics driven more by spatial and temporal variability than experimental warming. Long–term, high–resolution monitoring integrating soil biogeochemistry and microbial processes will be critical to determine whether the observed net CH 4 uptake signal represents a sustainable or transient response under continued warming and disturbance.

Puerto Rico, Sabana Field Research Station↗
USGS2002

Energy budget above a high-elevation subalpine forest in complex topography

Components of the energy budget were measured above a subalpine coniferous forest over two complete annual cycles. Sensible and latent heat fluxes were measured by eddy covariance. Bowen ratios ranged from 0.7 to 2.5 in the summer (June–September) depending upon the availability of soil water, but were considerably higher (∼3–6) during winter (December–March). Energy budget closure averaged better than 84% on a half-hourly basis in both seasons with slightly greater closure during the winter months. The energy budget showed a dependence on friction velocity ( u ∗ ), approaching complete closure at u ∗ values greater than 1 m s −1 . The dependence of budget closure on u ∗ explained why energy balance was slightly better in the winter as opposed to summer, since numerous periods of high turbulence occur in winter. It also explained the lower degree of energy closure (∼10% less) during easterly upslope flow since these periods were characterized by low wind speeds ( U <4 m s −1 ) and friction velocities ( u &#x2217; &lt;0.5 "> u∗<0.5 m s −1 ). Co-spectral analysis suggests a shift of flux density towards higher frequencies under conditions where closure was obtained. It is suggested that low frequency contributions to the flux and advection were responsible for the lack of day-time energy budget closure. These effects were reduced at high friction velocities observed at our site. Our ability to close the energy budget at night was also highly dependent on friction velocity, approaching near closure (∼90%) at u ∗ values between 0.7 and 1.1 m s −1 . Below this range, the airflow within the canopy becomes decoupled with the flow above. Above this range, insufficient temperature resolution of the sonic anemometer obscured the small temperature fluctuations, rendering measurements intractable.

Agricultural and Forest Meteorology↗
USGS2003

Partitioning of water flux in a Sierra Nevada ponderosa pine plantation

The weather patterns of the west side of the Sierra Nevada Mountains (cold, wet winters and hot, dry summers) strongly influence how water is partitioned between transpiration and evaporation and result in a specific strategy of water use by ponderosa pine trees (Pinus ponderosa) in this region. To investigate how year-round water fluxes were partitioned in a young ponderosa pine ecosystem in the Sierra Nevada Mountains, water fluxes were continually measured from June 2000 to May 2001 using a combination of sap flow and eddy covariance techniques (above- and below-canopy). Water fluxes were modeled at our study site using a biophysical model, FORFLUX. During summer and fall water fluxes were equally partitioned between transpiration and soil evaporation while transpiration dominated the water fluxes in winter and spring. The trees had high rates of canopy conductance and transpiration in the early morning and mid-late afternoon and a mid-day depression during the dry season. We used a diurnal centroid analysis to show that the timing of high canopy conductance and transpiration relative to high vapor pressure deficit (D) shifted with soil moisture: during periods of low soil moisture canopy conductance and transpiration peaked early in the day when D was low. Conversely, during periods of high soil moisture canopy conductance and transpiration peaked at the same time or later in the day than D. Our observations suggest a general strategy by the pine trees in which they maximize stomatal conductance, and therefore carbon fixation, throughout the day on warm sunny days with high soil moisture (i.e. warm periods in winter and late spring) and maximize stomatal conductance and carbon fixation in the morning through the dry periods. FORFLUX model estimates of evaporation and transpiration were close to measured/calculated values during the dry period, including the drought, but underestimated transpiration and overestimated evaporation during the wet period. ?? 2003 Elsevier Science B.V. All rights reserved.

Agricultural and Forest Meteorology↗
USGS2003

Climate warming could reduce runoff significantly in New England, USA

The relation between mean annual temperature (MAT), mean annual precipitation (MAP) and evapotranspiration (ET) for 38 forested watersheds was determined to evaluate the potential increase in ET and resulting decrease in stream runoff that could occur following climate change and lengthening of the growing season. The watersheds were all predominantly forested and were located in eastern North America, along a gradient in MAT from 3.5??C in New Brunswick, CA, to 19.8??C in northern Florida. Regression analysis for MAT versus ET indicated that along this gradient ET increased at a rate of 2.85 cm??C-1 increase in MAT (??0.96 cm??C-1, 95% confidence limits). General circulation models (GCM) using current mid-range emission scenarios project global MAT to increase by about 3??C during the 21st century. The inferred, potential, reduction in annual runoff associated with a 3??C increase in MAT for a representative small coastal basin and an inland mountainous basin in New England would be 11-13%. Percentage reductions in average daily runoff could be substantially larger during the months of lowest flows (July-September). The largest absolute reductions in runoff are likely to be during April and May with smaller reduction in the fall. This seasonal pattern of reduction in runoff is consistent with lengthening of the growing season and an increase in the ratio of rain to snow. Future increases in water use efficiency (WUE), precipitation, and cloudiness could mitigate part or all of this reduction in runoff but the full effects of changing climate on WUE remain quite uncertain as do future trends in precipitation and cloudiness.

Agricultural and Forest Meteorology↗
USGS2003

Airflows and turbulent flux measurements in mountainous terrain: Part 1. Canopy and local effects

We have studied the effects of local topography and canopy structure on turbulent flux measurements at a site located in mountainous terrain within a subalpine, coniferous forest. Our primary aim was to determine whether the complex terrain of the site affects the accuracy of eddy flux measurements from a practical perspective. We observed displacement heights, roughness lengths, spectral peaks, turbulent length scales, and profiles of turbulent intensities that were comparable in magnitude and pattern to those reported for forest canopies in simpler terrain. We conclude that in many of these statistical measures, the local canopy exerts considerably more influence than does topographical complexity. Lack of vertical flux divergence and modeling suggests that the flux footprints for the site are within the standards acceptable for the application of flux statistics. We investigated three different methods of coordinate rotation: double rotation (DR), triple rotation (TR), and planar-fit rotation (PF). Significant variability in rotation angles at low wind speeds was encountered with the commonly used DR and TR methods, as opposed to the PF method, causing some overestimation of the fluxes. However, these differences in fluxes were small when applied to large datasets involving sensible heat and CO 2 fluxes. We observed evidence of frequent drainage flows near the ground during stable, stratified conditions at night. Concurrent with the appearance of these flows, we observed a positive bias in the mean vertical wind speed, presumably due to subtle topographic variations inducing a flow convergence below the measurement sensors. In the presence of such drainage flows, advection of scalars and non-zero bias in the mean vertical wind speed can complicate closure of the mass conservation budget at the site.

Agricultural and Forest Meteorology↗
USGS1997

Estimating millet production for famine early warning: An application of crop simulation modelling using satellite and ground-based data in Burkina Faso

Early warning of impending poor crop harvests in highly variable environments can allow policy makers the time they need to take appropriate action to ameliorate the effects of regional food shortages on vulnerable rural and urban populations. Crop production estimates for the current season can be obtained using crop simulation models and remotely sensed estimates of rainfall in real time, embedded in a geographic information system that allows simple analysis of simulation results. A prototype yield estimation system was developed for the thirty provinces of Burkina Faso. It is based on CERES-Millet, a crop simulation model of the growth and development of millet ( Pennisetum spp.). The prototype was used to estimate millet production in contrasting seasons and to derive production anomaly estimates for the 1986 season. Provincial yields simulated halfway through the growing season were generally within 15% of their final (end-of-season) values. Although more work is required to produce an operational early warning system of reasonable credibility, the methodology has considerable potential for providing timely estimates of regional production of the major food crops in countries of sub-Saharan Africa.

Agricultural and Forest Meteorology↗
USGS2016

Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought

This study examines the evolution of several model-based and satellite-derived drought metrics sensitive to soil moisture and vegetation conditions during the extreme flash drought event that impacted major agricultural areas across the central U.S. during 2012. Standardized anomalies from the remote sensing based Evaporative Stress Index (ESI) and Vegetation Drought Response Index (VegDRI) and soil moisture anomalies from the North American Land Data Assimilation System (NLDAS) are compared to the United States Drought Monitor (USDM), surface meteorological conditions, and crop and soil moisture data compiled by the National Agricultural Statistics Service (NASS). Overall, the results show that rapid decreases in the ESI and NLDAS anomalies often preceded drought intensification in the USDM by up to 6 wk depending on the region. Decreases in the ESI tended to occur up to several weeks before deteriorations were observed in the crop condition datasets. The NLDAS soil moisture anomalies were similar to those depicted in the NASS soil moisture datasets; however, some differences were noted in how each model responded to the changing drought conditions. The VegDRI anomalies tracked the evolution of the USDM drought depiction in regions with slow drought development, but lagged the USDM and other drought indicators when conditions were changing rapidly. Comparison to the crop condition datasets revealed that soybean conditions were most similar to ESI anomalies computed over short time periods (2–4 wk), whereas corn conditions were more closely related to longer-range (8–12 wk) ESI anomalies. Crop yield departures were consistent with the drought severity depicted by the ESI and to a lesser extent by the NLDAS and VegDRI datasets.

Agricultural and Forest Meteorology↗
USGS2014

Report of Committee on Glaciers, 1942–43

The personnel of the Committee at present is as follows: Harry Fielding Reid, Professor Emeritus of Geology, Johns Hopkins University, 608 Cathedral Street, Baltimore, Maryland William H. Hobbs, Professor Emeritus of Geology, University of Michigan, Ann Arbor, Michigan Colonel Lawrence Martin, Chief, Division of Maps, Library of Congress, Washington, D.C. James E. Church, Professor of Meteorology and President, International Commission of Snow and Glaciers, Agricultural Experiment Station, University of Nevada, Reno, Nevada First Lieutenant William Osgood Field, Jr., home address, 18 West Twelfth Street, New York City Oliver Kehrlein, Chairman, Committee on Glacier Studies, Sierra Club, 1050 Mills Tower, San Francisco, California Kenneth N. Phillips, Associate Hydraulic Engineer, Water Resources Branch, Geological Survey, Chairman, Research Committee of the Masamas, 606 Post‐Office Building, Portland, Oregon William S. Cooper, Professor of Botany, University of Minnesota, Minneapolis, Minnesota Lieutenant Colonel Gerald FitzGerald, Army Air Corps, Washington, D.C. Laurence M. Gould, Professor of Geology, Carleton College, Northfield, Minnesota Arthur Johnson, Hydraulic Engineer, Conservation Branch, Geological Survey, 1105 Washington Building, Tacoma, Washington François E. Matthes (Chairman), Senior Geologist, Section of Glacial Geology, Geological Survey, Washington, D.C. The Committee is fortunate in having its membership reinforced by the addition of ARTHUR JOHNSON, who for several years has had charge of the repetitive plane‐table surveys of the lower Nisqually Glacier, on Mount Rainier—a project which the Geological Survey is carrying on in cooperation with the city of Tacoma, Washington. To him the Committee is indebted for data concerning the losses in volume of ice which the Nisqually Glacier is sustaining from year to year.

Eos, Transactions, American Geophysical Union↗
USGS1987

Effects of surface coal mining and reclamation on the geohydrology of six small watersheds in west-central Indiana

The watersheds studied include mined and reclaimed; mined and unreclaimed; and unmined, agricultural land uses, and are each < 3 sq mi in area. Surface water, groundwater, and meteorologic data for the 1981 and 1982 water years were used to describe and compare hydrologic systems of the six watersheds and to identify hydrologic effects of mining and reclamation. Peak discharges were greater at the agricultural watersheds than at the unreclaimed watersheds, primarily because of large final-cut lakes in the unreclaimed watersheds. Annual runoff was greatest at the unreclaimed watersheds, intermediate at the agricultural watersheds, and least at the reclaimed watersheds. Hydrologic effects of mining were identified by comparing the hydrologic systems at mined and unreclaimed watersheds with those at unmined, agricultural watersheds. Comparisons of the hydrologic systems of these watersheds indicate that surface coal mining without reclamation has the potential to increase annual runoff, base flow, and groundwater recharge to the bedrock; reduce peak flow rates and variation in flow; lower the water table in upland areas; change the relation between surface water and groundwater divides; and create numerous, local flow systems in the shallow groundwater. Hydrologic effects of reclamation were identified by comparing the hydrologic systems at mined and reclaimed watersheds with those at mined and unreclaimed watersheds. Reclamation has the potential to decrease annual runoff, base flow, and recharge to the bedrock; increase peak flow rates, variation in flow, and response to thunderstorms; reestablish the premining relation between surface and groundwater divides; and create fewer local flow systems in the shallow groundwater.

Indiana↗