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At least 217 records · Page 12Linked to original sources
USGS2020

Temporal evolution of measured and simulated infiltration following wildfire in the Colorado Front Range, USA: Shifting thresholds of runoff generation and hydrologic hazards

Destructive flash floods and debris flows are a common menace following wildfire. The restoration of protection provided by forests from post-fire floods and debris flows depends on the recovery of infiltration and attendant reduction of infiltration-excess surface runoff generation. This work examines seven years of post-fire infiltration measurements and temporal relations fit to soil-hydraulic properties from the Colorado Front Range, USA to assess infiltration recovery with increasing time since fire. Point-scale Green-Ampt simulations of infiltration across a full spectrum of rainfall events are used to evaluate infiltration changes and shifts in surface runoff generation thresholds with post-fire temporal recovery. Measured and simulated infiltration generally recovered monotonically with increasing time since fire. This indicates a reduced vulnerability to infiltration-excess runoff generation as time elapses, with the greatest risk in the first two years after the fire. The threshold for infiltration-excess runoff advances with increasing time to rainfall events with higher intensity and greater return intervals; by the third year after wildfire only extreme events (30-100 year recurrence) generate surface runoff and by the fifth and seventh year even extreme rainfall events typically fail to generate surface runoff. Remotely-sensed vegetation indices suggest linked, or at least contemporaneous, recovery of understory vegetation and field-saturated hydraulic conductivity at this field site, suggesting coincident recovery of multiple hillslope properties impacting surface runoff generation. This work indicates that the closing of the window of disturbance after wildfire, relative to infiltration-excess runoff generation and corresponding flash flood and debris flow hazards, relies on coupled assessments of hillslope property recovery and stochasticity of high-intensity rainfall. Post-fire hazard assessments using static hillslope properties could fail to predict flash floods and debris flows associated with infrequent extreme rainfall events that strike during the post-fire recovery period when hillslope properties are partially recovered.

Colorado↗
USGS2002

Linking the pacific decadal oscillation to seasonal stream discharge patterns in Southeast Alaska

This study identified and examined differences in Southeast Alaskan streamflow patterns between the two most recent modes of the Pacific decadal oscillation (PDO). Identifying relationships between the PDO and specific regional phenomena is important for understanding climate variability, interpreting historical hydrological variability, and improving water-resources forecasting. Stream discharge data from six watersheds in Southeast Alaska were divided into cold-PDO (1947-1976) and warm-PDO (1977-1998) subsets. For all watersheds, the average annual streamflows during cold-PDO years were not significantly different from warm-PDO years. Monthly and seasonal discharges, however, did differ significantly between the two subsets, with the warm-PDO winter flows being typically higher than the cold-PDO winter flows and the warm-PDO summer flows being typically lower than the cold-PDO flows. These results were consistent with and driven by observed temperature and snowfall patterns for the region. During warm-PDO winters, precipitation fell as rain and ran-off immediately, causing higher than normal winter streamflow. During cold-PDO winters, precipitation was stored as snow and ran off during the summer snowmelt, creating greater summer streamflows. The Mendenhall River was unique in that it experienced higher flows for all seasons during the warm-PDO relative to the cold-PDO. The large amount of Mendenhall River discharge caused by glacial melt during warm-PDO summers offset any flow reduction caused by lack of snow accumulation during warm-PDO winters. The effect of the PDO on Southeast Alaskan watersheds differs from other regions of the Pacific Coast of North America in that monthly/seasonal discharge patterns changed dramatically with the switch in PDO modes but annual discharge did not. ?? 2002 Elsevier Science B.V. All rights reserved.

Journal of Hydrology↗
USGS2009

Defining restoration targets for water depth and salinity in wind-dominated Spartina patens (Ait.) Muhl. coastal marshes

Coastal wetlands provide valued ecosystem functions but the sustainability of those functions often is threatened by artificial hydrologic conditions. It is widely recognized that increased flooding and salinity can stress emergent plants, but there are few measurements to guide restoration, management, and mitigation. Marsh flooding can be estimated over large areas with few data where winds have little effect on water levels, but quantifying flooding requires hourly measurements over long time periods where tides are wind-dominated such as the northern Gulf of Mexico. Estimating salinity of flood water requires direct daily measurements because coastal marshes are characterized by dynamic salinity gradients. We analyzed 399,772 hourly observations of water depth and 521,561 hourly observations of water salinity from 14 sites in Louisiana coastal marshes dominated by Spartina patens (Ait.) Muhl. Unlike predicted water levels, observed water levels varied monthly and annually. We attributed those observed variations to variations in river runoff and winds. In stable marshes with slow wetland loss rates, we found that marsh elevation averaged 1 cm above mean high water, 15 cm above mean water, and 32 cm above mean low water levels. Water salinity averaged 3.7 ppt during April, May, and June, and 5.4 ppt during July, August, and September. The daily, seasonal, and annual variation in water levels and salinity that were evident would support the contention that such variation be retained when designing and operating coastal wetland management and restoration projects. Our findings might be of interest to scientists, engineers, and managers involved in restoration, management, and restoration in other regions where S. patens or similar species are common but local data are unavailable.

Journal of Hydrology↗
USGS2022

Assessing spatial transferability of a random forest metamodel for predicting drainage fraction

Fully distributed hydrological models are widely used in groundwater management, but model speed and data requirements impede their use for decision support purposes. Metamodels provide a simpler and faster model which emulates the underlying complex model using machine learning techniques. However, metamodel predictions beyond the ranges, in space and/or time, of training data are highly uncertain, and thus it is important to assess the predictive model performance to ranges outside the training data, i.e., model transferability . We present a novel methodology for evaluating model transferability to areas not contained in the training data set, based on various metrics that quantify the differences in covariate distributions between training and testing data. The transferability method can be employed as a screening tool to assess the suitability of a metamodel for spatial prediction beyond its training domain. We evaluated this transferability approach on a Random Forest metamodel of a 1000 km 2 fully distributed coupled groundwater model for predicting drainage fraction, the partitioning of infiltrating water between drains and groundwater. We conducted spatial cross-validation on 9 holdout sub-basins to assess metamodel transferability beyond sampling locations and compared this estimate with a random split-sample validation test. Using mappable covariates only, the metamodel showed high performance (R 2 = 0.79) tested on a 20% randomly sampled holdout. Conversely, metamodel performance significantly decreased for the 9 spatial holdouts (R 2 ranging from 0.13 to 0.61). We document that the proposed transferability metric correlates with metamodel predictive performance, and demonstrate its use to assess model transferability to datasets outside the training data spatial domain.

Journal of Hydrology↗
USGS2024

Remote sensing evapotranspiration in ensemble-based framework to enhance cascade routing and re-infiltration concept in integrated hydrological model applied to support decision making

Integrated hydrological models (IHMs) help characterize the complexity of surface–groundwater interactions. The cascade routing and re-infiltration (CRR) concept, recently applied to a MODFLOW 6 IHM, improved conceptualization and simulation of overland flow processes. The CRR controls the transfer of rejected infiltration and groundwater exfiltration from upslope areas to adjacent downslope areas where that water can be evaporated, re-infiltrated back to subsurface, or discharged to streams as direct runoff. The partitioning between these three components is controlled by uncertain parameters that must be estimated. Thus, by quantifying and reducing those uncertainties, next to uncertainties of the other model parameters (e.g. hydraulic and storage parameters), the reliability of the CRR is improved and the IHM is better suited for decision support modelling, the two key objectives of this work. To this end, the remotely sensed MODIS-ET product was incorporated into the calibration process for complementing traditional hydraulic head and streamflow observations. A total of approximately 150,000 observations guided the calibration of a 13-year MODFLOW 6 IHM simulation of the Sardon catchment (Spain) with daily stress periods. The model input uncertainty was represented by grid-cell-scale parameterization, yielding approximately 500,000 unknown input parameters to be conditioned. The calibration was carried out through an iterative ensemble smoother. Incorporating the MODIS-ET data improved the CRR implementation, and reduced uncertainties associated with other model parameters. Additionally, it significantly reduced the uncertainty associated with net recharge, a critical flux for water management that cannot be directly measured and rather is commonly estimated by IHM simulations.

Sardon catchment↗
USGS1991

Detectability of the effects of a hypothetical temperature increase on the Thornthwaite moisture index

Climatic changes that result from increasing concentrations of atmospheric carbon dioxide may affect the availability of water for vegetation, groundwater recharge, runoff, and human consumption. Most studies of the effects of climatic change on water resources focus on changes in mean characteristics of hydrologic variables and do not consider the effects of these changes amid natural climatic variability. In this study, the Thornthwaite moisture index, an index of the supply of water in an area (precipitation) relative to the climatic demand for water (potential evapotranspiration), was used to examine the effects of a hypothetical increase in air temperature on moisture conditions in the United States. The effects of a gradual increase in air temperature at the rate of 4°C per 100 years, with no accompanying change in precipitation, was used to induce a change in Thornthwaite moisture index values for the United States in order to: (i) determine the relation between natural variability in climate and the time needed for significant trends in the moisture index to occur in response to hypothetical warming; (ii) identify the characteristics of areas (e.g. wet/cool, hot/dry etc.) that are most likely to be the first to experience significant changes in the moisture index given the hypothetical temperature increase. The increased temperature resulted in increased potential evapotranspiration and a decrease in the moisture index across the United States. Decreases in the moisture index were greatest in cool/wet regions and least in hot/dry regions. The time required to detect significant trends in the moisture index was a function of both the magnitude of change in the moisture index and the natural year-to-year variability of the moisture index. In general, when the ratio of the magnitude of change in the moisture index to the magnitude of variability was large, the time required to detect significant trends was short. This ratio was largest in cool/wet regions resulting in the shortest detection times.

Journal of Hydrology↗
USGS1995

Use of isotopic data to estimate water residence times of the Finger Lakes, New York

Water retention times in the Finger Lakes, a group of 11 lakes in central New York with similar hydrologic and climatic characteristics, were estimated by use of a tritium-balance model. During July 1991, samples were collected from the 11 lakes and selected tributary streams and were analyzed for tritium, deuterium, and oxygen-18. Additional samples from some of the sites were collected in 1990, 1992 and 1993. Tritium concentration in lake water ranged from 24.6 Tritium Units (TU) (Otisco Lake) to 43.2 TU (Seneca Lake).The parameters in the model used to obtain water retention time (WRT) included relative humidity, evaporation rate, tritium concentrations of inflowing water and lake water, and WRT of the lake. A historical record of tritium concentrations in precipitation and runoff was obtained from rainfall data at Ottawa, Canada, analyses of local wines produced during 1977–1991, and streamflow samples collected in 1990–1991. The model was simulated in yearly steps for 1953–1991, and the WRT was varied to reproduce tritium concentrations measured in each lake in 1991. Water retention times obtained from model simulations ranged from 1 year for Otisco Lake to 12 years for Seneca Lake, and with the exception of Seneca Lake and Skaneateles Lake, were in agreement with earlier estimates obtained from runoff estimates and chloride balances. The sensitivity of the model to parameter changes was tested to determine possible reasons for the differences calculated for WRT's for Seneca Lake and Skaneateles Lake. The shorter WRT obtained from tritium data for Lake Seneca (12 years as compared to 18 years) can be explained by a yearly addition of less than 3% by lake volume of ground water to the lake, the exact percentage depending on tritium concentration in the ground water.

New York↗
USGS2017

Remote measurement of river discharge using thermal particle image velocimetry (PIV) and various sources of bathymetric information

Although river discharge is a fundamental hydrologic quantity, conventional methods of streamgaging are impractical, expensive, and potentially dangerous in remote locations. This study evaluated the potential for measuring discharge via various forms of remote sensing, primarily thermal imaging of flow velocities but also spectrally-based depth retrieval from passive optical image data. We acquired thermal image time series from bridges spanning five streams in Alaska and observed strong agreement between velocities measured in situ and those inferred by Particle Image Velocimetry (PIV), which quantified advection of thermal features by the flow. The resulting surface velocities were converted to depth-averaged velocities by applying site-specific, calibrated velocity indices. Field spectra from three clear-flowing streams provided strong relationships between depth and reflectance, suggesting that, under favorable conditions, spectrally-based bathymetric mapping could complement thermal PIV in a hybrid approach to remote sensing of river discharge; this strategy would not be applicable to larger, more turbid rivers, however. A more flexible and efficient alternative might involve inferring depth from thermal data based on relationships between depth and integral length scales of turbulent fluctuations in temperature, captured as variations in image brightness. We observed moderately strong correlations for a site-aggregated data set that reduced station-to-station variability but encompassed a broad range of depths. Discharges calculated using thermal PIV-derived velocities were within 15% of in situ measurements when combined with depths measured directly in the field or estimated from field spectra and within 40% when the depth information also was derived from thermal images. The results of this initial, proof-of-concept investigation suggest that remote sensing techniques could facilitate measurement of river discharge.

Journal of Hydrology↗
USGS1999

Riparian zone flowpath dynamics during snowmelt in a small headwater catchment

The hydrology of the near-stream riparian zone in upland humid catchments is poorly understood. We examined the spatial and temporal aspects of riparian flowpaths during snowmelt in a headwater catchment within the Sleepers River catchment in northern Vermont. A transect of 15 piezometers was sampled for Ca, Si, DOC, other major cations, and ??18O. Daily piezometric head values reflected variations in the stream hydrograph induced by melt and rainfall. The riparian zone exhibited strong upward discharge gradients. An impeding layer was identified between the till and surficial organic soil. Water solute concentrations increased toward the stream throughout the melt. Ca concentrations increased with depth and DOC concentrations decreased with depth. The concentrations of Ca in all piezometers were lower during active snowmelt than during post-melt low flow. Ca data suggest snowmelt infiltration to depth; however, only upslope piezometers exhibited snowmelt infiltration and consequent low ??18O values, while ??18O values varied less than 0.5% in the deep riparian piezometers throughout the study period. Ca and ??18O values in upslope piezometers during low streamflow were comparable to Ca and ??18O in riparian piezometers during high streamflow. The upland water Ca and ??18O may explain the deep riparian Ca dilution and consistent ??18O composition. The temporal pattern in Ca and ??18O indicate that upland water moves to the stream via a lateral displacement mechanism that is enhanced by the presence of distinct soil/textural layers. Snowmelt thus initiates the flux of pre-melt, low Ca upland water to depth in the riparian zone, but itself does not appear at depth in the riparian zone during spring melt. This is despite the coincident response of upland groundwater and stream discharge.The hydrology of the near-stream riparian zone in upland humid catchments is poorly understood. We examined the spatial and temporal aspects of riparian flowpaths during snowmelt in a headwater catchment within the Sleepers River catchment in northern Vermont. A transect of 15 piezometers was sampled for Ca, Si, DOC, other major cations, and ??18O. Daily piezometric head values reflected variations in the stream hydrograph induced by melt and rainfall. The riparian zone exhibited strong upward discharge gradients. An impeding layer was identified between the till and surficial organic soil. Water solute concentrations increased toward the stream throughout the melt. Ca concentrations increased with depth and DOC concentrations decreased with depth. The concentrations of Ca in all piezometers were lower during active snowmelt than during post-melt low flow. Ca data suggest snowmelt infiltration to depth; however, only upslope piezometers exhibited snowmelt infiltration and consequent low ??18O values, while ??18O values varied less than 0.5 per mil in the deep riparian piezometers throughout the study period. Ca and ??18O values in upslope piezometers during low streamflow were comparable to Ca and ??18O in riparian piezometers during high streamflow. The upland water Ca and ??18O may explain the deep riparian Ca dilution and consistent ??18O composition. The temporal pattern in Ca and ??18O indicate that upland water moves to the stream via a lateral displacement mechanism that is enhanced by the presence of distinct soil/textural layers. Snowmelt thus initiates the flux of pre-melt, low Ca upland water to depth in the riparian zone, but itself does not appear at depth in the riparian zone during spring melt. This is despite the coincident response of upland groundwater and stream discharge.

Journal of Hydrology↗
USGS2008

Inverse modeling of surface-water discharge to achieve restoration salinity performance measures in Florida Bay, Florida

The use of numerical modeling to evaluate regional water-management practices involves the simulation of various alternative water-delivery scenarios, which typically are designed intuitively rather than analytically. These scenario simulations are used to analyze how specific water-management practices affect factors such as water levels, flows, and salinities. In lieu of testing a variety of scenario simulations in a trial-and-error manner, an optimization technique may be used to more precisely and directly define good water-management alternatives. A numerical model application in the coastal regions of Florida Bay and Everglades National Park (ENP), representing the surface- and ground-water hydrology for the region, is a good example of a tool used to evaluate restoration scenarios. The Southern Inland and Coastal System (SICS) model simulates this area with a two-dimensional hydrodynamic surface-water model and a three-dimensional ground-water model, linked to represent the interaction of the two systems with salinity transport. This coastal wetland environment is of great interest in restoration efforts, and the SICS model is used to analyze the effects of alternative water-management scenarios. The SICS model is run within an inverse modeling program called UCODE. In this application, UCODE adjusts the regulated inflows to ENP while SICS is run iteratively. UCODE creates parameters that define inflow within an allowable range for the SICS model based on SICS model output statistics, with the objective of matching user-defined target salinities that meet ecosystem restoration criteria. Preliminary results obtained using two different parameterization methods illustrate the ability of the model to achieve the goals of adjusting the range and reducing the variance of salinity values in the target area. The salinity variance in the primary zone of interest was reduced from an original value of 0.509 psu2 to values 0.418 psu2 and 0.342 psu2 using different methods. Simulations with one, two, and three target areas indicate that optimization is limited near model boundaries and the target location nearest the tidal boundary may not be improved. These experiments indicate that this method can be useful for designing water-delivery schemes to achieve certain water-quality objectives. Additionally, this approach avoids much of the intuitive type of experimentation with different flow schemes that has often been used to develop restoration scenarios. ?? 2007 Elsevier B.V. All rights reserved.

Journal of Hydrology↗
USGS2014

Developing and testing temperature models for regulated systems: a case study on the Upper Delaware River

Water temperature is an important driver of many processes in riverine ecosystems. If reservoirs are present, their releases can greatly influence downstream water temperatures. Models are important tools in understanding the influence these releases may have on the thermal regimes of downstream rivers. In this study, we developed and tested a suite of models to predict river temperature at a location downstream of two reservoirs in the Upper Delaware River (USA), a section of river that is managed to support a world-class coldwater fishery. Three empirical models were tested, including a Generalized Least Squares Model with a cosine trend (GLScos), AutoRegressive Integrated Moving Average (ARIMA), and Artificial Neural Network (ANN). We also tested one mechanistic Heat Flux Model (HFM) that was based on energy gain and loss. Predictor variables used in model development included climate data (e.g., solar radiation, wind speed, etc.) collected from a nearby weather station and temperature and hydrologic data from upstream U.S. Geological Survey gages. Models were developed with a training dataset that consisted of data from 2008 to 2011; they were then independently validated with a test dataset from 2012. Model accuracy was evaluated using root mean square error (RMSE), Nash Sutcliffe efficiency (NSE), percent bias (PBIAS), and index of agreement (d) statistics. Model forecast success was evaluated using baseline-modified prime index of agreement (md) at the one, three, and five day predictions. All five models accurately predicted daily mean river temperature across the entire training dataset (RMSE = 0.58–1.311, NSE = 0.99–0.97, d = 0.98–0.99); ARIMA was most accurate (RMSE = 0.57, NSE = 0.99), but each model, other than ARIMA, showed short periods of under- or over-predicting observed warmer temperatures. For the training dataset, all models besides ARIMA had overestimation bias (PBIAS = −0.10 to −1.30). Validation analyses showed all models performed well; the HFM model was the most accurate compared other models (RMSE = 0.92, both NSE = 0.98, d = 0.99) and the ARIMA model was least accurate (RMSE = 2.06, NSE = 0.92, d = 0.98); however, all models had an overestimation bias (PBIAS = −4.1 to −10.20). Aside from the one day forecast ARIMA model (md = 0.53), all models forecasted fairly well at the one, three, and five day forecasts (md = 0.77–0.96). Overall, we were successful in developing models predicting daily mean temperature across a broad range of temperatures. These models, specifically the GLScos, ANN, and HFM, may serve as important tools for predicting conditions and managing thermal releases in regulated river systems such as the Delaware River. Further model development may be important in customizing predictions for particular biological or ecological needs, or for particular temporal or spatial scales.

Delaware, New York, Pennsylvania↗
USGS1983

Relation of concealed faults to water quality and the formation of solution features in the Floridan aquifer, northeastern Florida, U.S.A.

Geological and hydrological information on the Floridan aquifer in northeastern Florida indicates that isolated occurrences of water having relatively high chloride concentration in the upper part of the aquifer may be associated with buried faults. Water having chloride concentrations of more than 700 mg l −1 occurs in the deeper zone of the aquifer at depths below ∼ 600 m below sea level in the coastal and east-central part of the study area. This deep salty water is under higher artesian pressure than water in the shallower, generally freshwater zones, but it is restricted from moving upward by relatively impermeable dolomite beds. Two buried faults with vertical displacements of 30–45 m are in areas where relatively high concentrations of chloride have been detected in water in the upper part of the aquifer. Geochemical, artesian pressure, and water temperature data show that the source of the relatively high concentrations of chloride in water in the upper part of the aquifer is from the deeper zone. This indicates that the faults may have breached the dolomite confining beds and allowed the upward movement of salty water from the deeper zone. The upward movement of mineralized water along the faults may also have formed some of the solution features found in the aquifer near the faults. In this area, freshwater in the upper part of the aquifer is normally saturated with respect to calcite and dolomite. However, water from wells tapping the upper part of the aquifer near the faults is not fully saturated suggesting that the mixing of deep mineralized water with shallower freshwater produces a mixture that is not saturated with respect to these minerals and allows for the dissolution of limestone in the aquifer near the faults. Dissolution of limestone may also be occurring at the freshwater-saltwater interface in the deeper zones of the aquifer.

Florida↗
USGS2014

Placing prairie pothole wetlands along spatial and temporal continua to improve integration of wetland function in ecological investigations

We evaluated the efficacy of using chemical characteristics to rank wetland relation to surface and groundwater along a hydrologic continuum ranging from groundwater recharge to groundwater discharge. We used 27 years (1974–2002) of water chemistry data from 15 prairie pothole wetlands and known hydrologic connections of these wetlands to groundwater to evaluate spatial and temporal patterns in chemical characteristics that correspond to the unique ecosystem functions each wetland performed. Due to the mineral content and the low permeability rate of glacial till and soils, salinity of wetland waters increased along a continuum of wetland relation to groundwater recharge, flow-through or discharge. Mean inter-annual specific conductance (a proxy for salinity) increased along this continuum from wetlands that recharge groundwater being fresh to wetlands that receive groundwater discharge being the most saline, and wetlands that both recharge and discharge to groundwater (i.e., groundwater flow-through wetlands) being of intermediate salinity. The primary axis from a principal component analysis revealed that specific conductance (and major ions affecting conductance) explained 71% of the variation in wetland chemistry over the 27 years of this investigation. We found that long-term averages from this axis were useful to identify a wetland’s long-term relation to surface and groundwater. Yearly or seasonal measurements of specific conductance can be less definitive because of highly dynamic inter- and intra-annual climate cycles that affect water volumes and the interaction of groundwater and geologic materials, and thereby influence the chemical composition of wetland waters. The influence of wetland relation to surface and groundwater on water chemistry has application in many scientific disciplines and is especially needed to improve ecological understanding in wetland investigations. We suggest ways that monitoring in situ wetland conditions could be linked with evolving remote sensing technology to improve our ability to better inform decisions affecting wetland sustainability and provide periodic inventories of wetland ecosystem services to document temporal trends in wetland function and how they respond to contemporary land-use change.

North Dakota↗
USGS2024

Unravelling spatial heterogeneity of inundation pattern domains for 2D analysis of fluvial landscapes and drainage networks

Fluvial landscape analysis is an essential part of geomorphology, hydrology, ecology, and cartography. It is traditionally focused on the transition between hillslopes and channel domain, in which the network drainage is represented by static flow lines. However, the natural fluctuations of the processes occurring in the watershed induce lateral and longitudinal expansions and contractions in the drainage patterns and variations of stream surface area. These dynamics can be better understood by introducing a two-dimensional (2D) view of catchment hydrography, in which river width and floodplain are included in the analysis. The novelty introduced in this work is the development of a hydrodynamic hierarchical framework (HHF) to analyse the transitions among geomorphic and hydrographic features of the fluvial landscape, distinguishing hillslope, unchanneled valleys, floodplains, and single/multithreads channels. HHF is based on the estimation of nested inundation pattern domains (IPDs) from digital elevation models and 2D hydrodynamic modeling. IPDs are defined by scaling laws that characterize log–log relations between watershed drainage density and unit discharge thresholds extracted from a 2D direct rainfall method (DRM) under steady state solutions. The physical significance of the IPDs is analysed within the context of both the physiographic features of the fluvial landscape and the rainfall rates employed as input for the modeling approach. Initially, the spatial heterogeneity of the IPDs is used to derive stream width metrics as a function of the rainfall rate. Then, a spatial index, representative of the IPDs' heterogeneity, is introduced as a measure of the susceptibility of the drainage network surface area to expansion and contraction. Finally, the consistency of the results is assessed in comparison to another hydrodynamic-based method for fluvial landscape analysis recently proposed in the literature. The proposed approach is analysed using challenging mountain and low-relief environments, characterized by multithread channels, meander cut-offs, oxbow lakes, and extreme landscapes that feature glacial outwash, permafrost, and peatlands.

Alaska↗
USGS2016

Simulating future water temperatures in the North Santiam River, Oregon

A previously calibrated two-dimensional hydrodynamic and water-quality model (CE-QUAL-W2) of Detroit Lake in western Oregon was used in conjunction with inflows derived from Precipitation-Runoff Modeling System (PRMS) hydrologic models to examine in-lake and downstream water temperature effects under future climate conditions. Current and hypothetical operations and structures at Detroit Dam were imposed on boundary conditions derived from downscaled General Circulation Models in base (1990–1999) and future (2059–2068) periods. Compared with the base period, future air temperatures were about 2 °C warmer year-round. Higher air temperature and lower precipitation under the future period resulted in a 23% reduction in mean annual PRMS-simulated discharge and a 1 °C increase in mean annual estimated stream temperatures flowing into the lake compared to the base period. Simulations incorporating current operational rules and minimum release rates at Detroit Dam to support downstream habitat, irrigation, and water supply during key times of year resulted in lower future lake levels. That scenario results in a lake level that is above the dam’s spillway crest only about half as many days in the future compared to historical frequencies. Managing temperature downstream of Detroit Dam depends on the ability to blend warmer water from the lake’s surface with cooler water from deep in the lake, and the spillway is an important release point near the lake’s surface. Annual average in-lake and release temperatures from Detroit Lake warmed 1.1 °C and 1.5 °C from base to future periods under present-day dam operational rules and fill schedules. Simulated dam operations such as beginning refill of the lake 30 days earlier or reducing minimum release rates (to keep more water in the lake to retain the use of the spillway) mitigated future warming to 0.4 and 0.9 °C below existing operational scenarios during the critical autumn spawning period for endangered salmonids. A hypothetical floating surface withdrawal at Detroit Dam improved temperature control in summer and autumn (0.6 °C warmer in summer, 0.6 °C cooler in autumn compared to existing structures) without altering release rates or lake level management rules.

Oregon↗
USGS2025

Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA

Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.

Florida↗
USGS1983

The saltwater-freshwater interface in the Tertiary limestone aquifer, southeast Atlantic outer-continental shelf of the U.S.A.

Hydrologic testing in an offshore oil well abandoned by Tenneco, Inc., determined the position of the saltwater-freshwater interface in Tertiary limestones underlying the Florida-Georgia continental shelf of the U.S.A. Previous drilling (JOIDES and U.S.G.S. AMCOR projects) established the existence of freshwater far offshore in this area. At the Tenneco well 55 mi. (∼88 km) east of Fernandina Beach, Florida, drill-stem tests made in the interval 1050–1070 ft. (320–326 m) below sea level in the Ocala Limestone recovered a sample with a chloride concentration of 7000 mg l −1 . Formation water probably is slightly fresher. Pressure-head measurements indicated equivalent freshwater heads of 24–29 ft. (7.3–8.8 m) above sea level. At the coast (Fernandina Beach), a relatively thin transition zone separating freshwater and saltwater occurs at a depth of 2100 ft. (640 m) below sea level. Fifty-five miles (∼88 km) offshore, at the Tenneco well, the base of freshwater is ∼1100 ft. (∼335 m) below sea level. The difference in approximate depth to the freshwater-saltwater transition at these two locations suggests an interface with a very slight landward slope. Assuming the Hubbert interface equation applies here (because the interface and therefore freshwater flow lines are nearly horizontal) the equilibrium depth to the interface should be 40 times the freshwater head above sea level. Using present-day freshwater heads along the coast in the Hubbert equation results in depths to the interface of less than the observed 2100 ft. (640 m). Substituting predevelopment heads in the equation yields depths greater than 2100 ft. (640 m). Thus the interface appears to be in a transient position between the position that would be compatible with present-day heads and the position that would be compatible with predevelopment heads. This implies that some movement of the interface from the predevelopment position has occurred during the past hundred years. The implied movement is incompatible with the hypothesis that the freshwater occurring far offshore in this area is trapped water remaining since the Pleistocene Epoch.

Florida, Georgia↗
USGS2007

Recent climate trends and implications for water resources in the Catskill Mountain region, New York, USA

Climate scientists have concluded that the earth’s surface air temperature warmed by 0.6 °C during the 20th century, and that warming induced by increasing concentrations of greenhouse gases is likely to continue in the 21st century, accompanied by changes in the hydrologic cycle. Climate change has important implications in the Catskill region of southeastern New York State, because the region is a source of water supply for New York City. We used the non-parametric Mann–Kendall test to evaluate annual, monthly, and multi-month trends in air temperature, precipitation amount, stream runoff, and potential evapotranspiration (PET) in the region during 1952–2005 based on data from 9 temperature sites, 12 precipitation sites, and 8 stream gages. A general pattern of warming temperatures and increased precipitation, runoff, and PET is evident in the region. Regional annual mean air temperature increased significantly by 0.6 °C per 50 years during the period; the greatest increases and largest number of significant upward trends were in daily minimum air temperature. Daily maximum air temperature showed the greatest increase during February through April, whereas minimum air temperature showed the greatest increase during May through September. Regional mean precipitation increased significantly by 136 mm per 50 years, nearly double that of the regional mean increase in runoff, which was not significant. Regional mean PET increased significantly by 19 mm per 50 years, about one-seventh that of the increase in precipitation amount, and broadly consistent with increased runoff during 1952–2005, despite the lack of significance in the mean regional runoff trend. Peak snowmelt as approximated by the winter–spring center of volume of stream runoff generally shifted from early April at the beginning of the record to late March at the end of the record, consistent with a decreasing trend in April runoff and an increasing trend in maximum March air temperature. This change indicates an increased supply of water to reservoirs earlier in the year. Additionally, the supply of water to reservoirs at the beginning of winter is greater as indicated by the timing of the greatest increases in precipitation and runoff—both occurred during summer and fall. The future balance between changes in air temperature and changes in the timing and amount of precipitation in the region will have important implications for the available water supply in the region.

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