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At least 163 records · Page 9Linked to original sources
USGS2020

The water-year water balance of the Colorado River Basin

Model‐estimated monthly water balance components (i.e., potential evapotranspiration, actual evapotranspiration, and runoff ( R )) for 146 United States (U.S.) Geological Survey 8‐digit hydrologic units located in the Colorado River Basin (CRB) are used to examine the temporal and spatial variability of the CRB water balance for water years 1901 through 2014 (a water year is the period from October 1 of one year through September 30 of the following year). Results indicate that the CRB can be divided into six subregions with similar temporal variability in monthly R . The water balance analyses indicated that approximately 75% of total water‐year R is generated by just one CRB subregion and that most of the R in the basin is derived from surplus ( S ) water generated during the months of October through April. Furthermore, the analyses show that temporal variability in S is largely controlled by the occurrence of negative atmospheric pressure anomalies over the northwestern conterminous U.S. (CONUS) and positive atmospheric pressure anomalies over the southeastern CONUS. This combination of atmospheric pressure anomalies results in an anomalous flow of moist air from the North Pacific Ocean into the CRB, particularly the Upper CRB. Additionally, the occurrence of extreme dry and wet periods in the CRB appears to be related to variability of the Atlantic Multidecadal Oscillation and the Pacific Decadal Oscillation.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2020

Changes in climate and land cover affect seasonal streamflow forecasts in the Rio Grande headwaters

Seasonal streamflow forecast bias, changes in climate, snowpack, and land cover, and the effects of these changes on relations between basin‐wide snowpack, SNOw TELemetry (SNOTEL) station snowpack, and seasonal streamflow were evaluated in the headwaters of the Rio Grande, Colorado. Results indicate that shifts in the seasonality of precipitation and changing climatology are consistent with periods of overprediction and underprediction in streamflow forecasts. Multiple linear regression of SNOTEL data, postcedent precipitation, and land‐cover changes explained 2%–18% more variability in streamflow prediction than using SNOTEL station data alone. Simulated basin‐wide snowpack from a physically based model had significant negative trends in snow water equivalent (−4.33 mm/yr) and snow‐covered area (−0.05%/yr) during the melt period April–June. Simulated streamflow from a precipitation‐runoff model increased an average 5% when the effects of bark beetle‐induced tree mortality were compared to a baseline simulation with static vegetation. The effects of a 2013 wildfire increased simulated seasonal streamflow an average 35% for 1–4 years postfire. The combined effects of climate and land‐cover changes on snowpack‐streamflow relations highlight the difficulty in seasonal streamflow forecasting, which has important implications for water‐resource management.

Colorado↗
USGS2020

The influence of climate variability on the accuracy of NHD perennial and non-perennial stream classifications

National Hydrography Dataset (NHD) stream permanence classifications (SPC; perennial, intermittent, and ephemeral) are widely used for data visualization and applied science, and have implications for resource policy and management. NHD SPC were assigned using a combination of topographic field surveys and interviews with local residents. However, previous studies indicate that non‐NHD, in situ streamflow observations (NNO) frequently disagree with NHD SPC. We hypothesized that differences in annual climate conditions between map creation years and the years NNO were collected contributed to disagreement between NNO and NHD SPC. We compared NHD SPC to 10,055 NNO (classified as “wet” or “dry”) collected in the Pacific Northwest between 1977 and 2015. Annual climate conditions were described with the Palmer Drought Severity Index (PDSI). Stream order was added as a covariate to account for different effects along the stream network. NHD SPC agreed with 80.5% of NNO. “Dry” NNO were five times more likely to disagree with NHD than “wet” NNO ( p < 0.0001). Disagreement was greatest on first‐order streams. When NHD SPC were collected during a wetter period than NNO the probability of disagreement increased by a factor of 1.17 ( p < 0.0001) per unit difference in PDSI. The influence of climate on disagreements between NNO and NHD SPC provides support for the continued development of dynamic models representing SPC as opposed to static NHD classifications.

Journal of the American Water Resources Associatio↗
USGS2020

elfgen: A new instream flow framework for rapid generation and optimization of flow-ecology relations

Effective water resource management requires practical, data‐driven determination of instream flow needs. Newly developed, high‐resolution flow models and aquatic species databases provide enormous opportunity, but the volume of data can prove challenging to manage without automated tools. The objective of this study was to develop a framework of analytical methods and best practices to reduce costs of entry into flow–ecology analysis by integrating widely available hydrologic and ecological datasets. Ecological limit functions (ELFs) describing the relation between maximum species richness and stream size characteristics (streamflow or drainage area) were developed. Species richness is expected to increase with streamflow through a watershed up to a point where it either plateaus or transitions to a decreasing trend in larger streams. Our results show that identifying the location of this "breakpoint" is critical for producing optimal ELF model fit. We found that richness breakpoints can be estimated using automated low‐supervision methods, with high‐supervision providing negligible improvement in detection accuracy. Model fit (and predictive capability) was found to be superior in smaller hydrologic units. The ELF model ("elfgen" R package available on GitHub: https://github.com/HARPgroup/elfgen ) can be used to generate ELFs using built‐in datasets for the conterminous United States, or applied anywhere else streamflow and biodiversity data inputs are available.

Virginia↗
USGS2020

Application of a new species-richness based flow ecology framework for assessing flow reduction effects on aquatic communities

Water‐resources managers are challenged with maintaining a balance among beneficial uses throughout river networks and need robust means of assessing potential risks to aquatic life resulting from flow alterations. This study generated ecological limit functions from species‐streamflow relations to quantify potential fish richness response to flow alteration and compared results to currently accepted streamflow management guidelines. Modeled responses of absolute richness change were watershed specific and varied among sample sets derived from hydrologic unit classifications of different sizes (large HUC 6 basins to regional scale HUC 8). With a 20% flow reduction, 10% of HUC 8 predicted a richness decrease in one or more taxa. While absolute richness change was consistent across streams within a HUC, percent richness change was stream size dependent. Comparisons with Instream Flow Incremental Methodology habitat models predicted habitat loss greater than percent richness change; however, predictions for habitat and richness decreased similarly as stream size decreased. Watershed‐specific responses from flow reductions could allow water‐resources management decisions to be made locally based on the predicted richness change for certain sized streams. Quantitative results highlight the utility of a richness‐based framework for generating watershed‐specific risk assessments that validate and inform currently employed water‐resources management practices.

Virginia↗
USGS2020

Spatial and temporal patterns of low streamflow and precipitation changes in the Chesapeake Bay Watershed

Spatial and temporal patterns in low streamflows were investigated for 183 streamgages located in the Chesapeake Bay Watershed for the period 1939–2013. Metrics that represent different aspects of the frequency and magnitude of low streamflows were examined for trends: (1) the annual time series of seven‐day average minimum streamflow, (2) the scaled average deficit at or below the 2% mean daily streamflow value relative to a base period between 1939 and 1970, and (3) the annual number of days below the 2% threshold. Trends in these statistics showed spatial cohesion, with increasing low streamflow volume at streamgages located in the northern uplands of the Chesapeake Bay Watershed and decreasing low streamflow volume at streamgages in the southern part of the watershed. For a small subset of streamgages (12%), conflicting trend patterns were observed between the seven‐day average minimum streamflow and the below‐threshold time series and these appear to be related to upstream diversions or the influence of reservoir‐influenced streamflows in their contributing watersheds. Using multivariate classification techniques, mean annual precipitation and fraction of precipitation falling as snow appear to be broad controls of increasing and decreasing low‐flow trends. Further investigation of seasonal precipitation patterns shows summer rainfall patterns, driven by the Atlantic Multidecadal Oscillation, as the main driver of low streamflows in the Chesapeake Bay Watershed.

Delaware, Maryland, New York, Pennsylvania, Virgin↗
USGS2021

Nitrogen and phosphorus sources and delivery from the Mississippi/Atchafalaya River Basin: An update using 2012 SPARROW models

Nitrogen (N) and phosphorus (P) inputs throughout the Mississippi/Atchafalaya River Basin (MARB) have been linked to the Gulf of Mexico hypoxia and water‐quality problems throughout the MARB. To describe N and P loading throughout the MARB, SPAtially Referenced Regression On Watershed attributes (SPARROW) models were previously developed based on nutrient inputs and management similar to 1992 and 2002. In this study, refined SPARROW models were developed with higher resolution basin delineation, updated (2012) source inputs, improved calibration (load) targets, and additional statistical techniques than used in the previous SPARROW models. Based on the refined models, consistent with past models, N and P loads/yields were the highest from the central part of the MARB (Corn Belt) and along the Mississippi River. Agricultural activities remained the most important N and P source, but more so for N because its input, which could now be distinguished from atmospheric deposition, could be estimated. Natural loss of P from geologic material throughout the MARB was an important source, contributing about 23% of the total P from the MARB, and resulted in specific areas, such as Kentucky and Tennessee, being larger sources of P than previously estimated. This information can help managers decide where efforts will have the largest effects (highest ranked areas) on reducing nutrient loading to the Gulf hypoxia and what are the most important sources of N and P in these areas.

Mississippi/Atchafalaya River Basin↗
USGS2022

Mechanisms controlling climate warming impact on the occurrence of hypoxia in Chesapeake Bay

A Climate change represents an increasing stressor on estuarine and coastal ecosystems. A series of simulations were run using the Integrated Compartment Water Quality Model to determine the magnitude of various mechanisms controlling the effect of climate warming on dissolved oxygen (DO) in the Chesapeake Bay. The results suggested that the average hypoxic volume in the summer would increase by 9% (410 Mm 3 ) from 1995 to 2025 as air temperature increases by 1.06°C and water temperature by 0.9°C. The change in DO solubility contributes 55% of the total climate warming effect, biological rates 33%, and stratification 11%. The Rappahannock Shoal, a hydraulic control point, plays a major role in determining the effect of climate warming on DO in the Bay. Due to the abrupt change in bathymetry, the convergence between seaward-moving freshwater and landward-moving saltwater causes downwelling and enhanced vertical mixing which introduces surface water of higher temperature to the deep channel and accelerates organic matter remineralization and oxygen consumption in deep waters. Surface water DO concentrations will decrease under climate warming conditions due to lower DO solubility, reducing DO flux to the deep channel and contributing to hypoxia development. These findings provide critical information for future management decision making regarding the effects of climate warming on DO in Chesapeake Bay and other estuaries.

Maryland, Virginia↗
USGS2021

OpenET: Filling a critical data gap in water management for the western United States

The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.

western United States↗
USGS2021

A basin-scale approach to estimating recharge in the desert: Anza-Cahuilla groundwater basin, CA

The Anza-Cahuilla groundwater basin located mainly in the semi-arid headwaters of the Santa Margarita River watershed in southern California is the principle source of groundwater for a rural disadvantaged community and two Native American Tribes, the Ramona Band of Cahuilla and the Cahuilla. Groundwater in the study area is derived entirely from precipitation and managing groundwater sustainably requires an accurate assessment of the water balance components, yet long-term estimates do not exist. Demand for groundwater in the region has increased and groundwater quality has decreased due to population growth and increased irrigated cropland. To characterize monthly long-term natural recharge and runoff estimates, a physically-based water balance model (Basin Characterization Model) was locally calibrated and validated using nearby streamgages and published estimates of climatic and hydrologic variables. The average modeled annual recharge and runoff from 1981 to 2010 was 5.4 × 10 6 and 1.2 × 10 7 m 3 , respectively, for the study area. Recharge and runoff do not reliably occur in large amounts every year and recharge rarely occurs in the groundwater basin footprint. These long-term estimates can be used by water managers, stakeholders, and Native American Tribes to develop plans for sustainable management of future water resources, and as inputs to a three-dimensional groundwater model.

California↗
USGS2021

Impacts of climate change on groundwater availability and spring flows: Observations from the highly productive Medicine Lake Highlands/Fall River Springs Aquifer System

Medicine Lake Highlands/Fall River Springs Aquifer System, located in northeastern California, is home to some of the largest first-order springs in the United States. This work assesses the likely effects of projected climate change on spring flow. Four anticipated climate futures (GFDL A2, GFDL B1, CCSM4 rcp 8.5, CNRM rcp 8.5) for California, which predict a range of conditions (generally warming and transitioning from snow to rain with variable amounts of total precipitation), are postulated to affect groundwater recharge primarily by changing evapotranspiration. The linkages between climate variables and spring flow are evaluated using a water balance model that represents the physics of evapotranspiration and recharge, the Basin Characterization Model. Three of the four climate scenarios (GFDL A2, GFDL B1, CCSM4 rcp 8.5) project that by the year 2100, groundwater recharge (and consequently decreased spring flow) will decrease by 27%, 21%, and 9%, respectively. The fourth scenario (CNRM rcp 8.5) showed an increase in recharge of 32% due to a significant increase in precipitation (27%). Evapotranspiration increases due to a shift in the type of precipitation and a longer growing season. While the likelihood of each scenario is outside the scope of this work, unless total precipitation increases dramatically in the future, increased temperatures and decreasing precipitation will likely result in reduced spring flows, along with warmer water temperatures in downstream habitats.

California↗
USGS2022

DSWEmod - The production of high-frequency surface water map composites from daily MODIS images

Optical satellite imagery is commonly used for monitoring surface water dynamics, but clouds and cloud shadows present challenges in assembling complete water time series. To test whether the daily revisit rate of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery can reduce cloud obstruction and improve high-frequency surface water mapping, we compared map results derived from Landsat (30-m) and MODIS (250-m) data across the state of California for 2003–2019. We adapted the Dynamic Surface Water Extent (DSWE) model in Google Earth Engine to generate surface water map composites from MODIS imagery every 5, 10, 15, and 30 days, and compared products to monthly Landsat-based DSWE maps. Results for DSWEmod (DSWE MODIS) in California suggest that more than 5% data loss (cloud obstruction, etc.) was present in only 2% of the 15-day time series, as compared to 32% of the monthly Landsat DSWE time series. The five-day DSWEmod composites averaged 8.4% obscuration in the winter months. Area estimates derived from cloud-filtered MODIS and Landsat monthly products have the highest linear correlations compared to streamgage discharge records, suggesting that monthly scale analyses best explain the relationship between surface water area and general streamflow dynamics. Shorter-interval DSWEmod products have lower correlations but utility for understanding the timing of surface water peaks and past flood events.

Journal of the American Water Resources Associatio↗
USGS2022

Quantifying streamflow depletion from groundwater pumping: A practical review of past and emerging approaches for water management

Groundwater pumping can cause reductions in streamflow (“streamflow depletion”) that must be quantified for conjunctive management of groundwater and surface water resources. However, streamflow depletion cannot be measured directly and is challenging to estimate because pumping impacts are masked by streamflow variability due to other factors. Here, we conduct a management-focused review of analytical, numerical, and statistical models for estimating streamflow depletion and highlight promising emerging approaches. Analytical models are easy to implement, but include many assumptions about the stream and aquifer. Numerical models are widely used for streamflow depletion assessment and can represent many processes affecting streamflow, but have high data, expertise, and computational needs. Statistical approaches are a historically underutilized tool due to difficulty in attributing causality, but emerging causal inference techniques merit future research and development. We propose that streamflow depletion-related management questions can be divided into three broad categories (attribution, impacts, and mitigation) that influence which methodology is most appropriate. We then develop decision criteria for method selection based on suitability for local conditions and the management goal, actionability with current or obtainable data and resources, transparency with respect to process and uncertainties, and reproducibility.

Journal of the American Water Resources Associatio↗
USGS2022

Water-use data in the United States: Challenges and future directions

In the United States, greater attention has been given to developing water supplies and quantifying available waters than determining who uses water, how much they withdraw and consume, and how and where water use occurs. As water supplies are stressed due to an increasingly variable climate, changing land-use, and growing water needs, greater consideration of the demand side of the water balance equation is essential. Data about the spatial and temporal aspects of water use for different purposes are now critical to long-term water supply planning and resource management. We detail the current state of water-use data, the major stakeholders involved in their collection and applications, and the challenges in obtaining high-quality nationally consistent data applicable to a range of scales and purposes. Opportunities to improve access, use, and sharing of water-use data are outlined. We cast a vision for a world-class national water-use data product that is accessible, timely, and spatially detailed. Our vision will leverage the strengths of existing local, state, and federal agencies to facilitate rapid and informed decision-making, modeling, and science for water resources. To inform future decision-making regarding water supplies and uses, we must coordinate efforts to substantially improve our capacity to collect, model, and disseminate water-use data.

Journal of the American Water Resources Associatio↗
USGS2022

Ephemeral stream network extraction from lidar-derived elevation and topographic attributes in urban and forested landscapes

Under-representations of headwater channels in digital stream networks can result in uncertainty in the magnitude of headwater habitat loss, stream burial, and watershed function. Increased availability of high-resolution (<2 m) elevation data makes the delineation of headwater channels more attainable. In this study, elevation data derived from light detection and ranging was used to predict ephemeral stream networks across a forested and urban watershed in the Maryland Piedmont USA. A method was developed using topographic openness (TO) and wetness index to remotely predict the extent of stream networks. Predicted networks were compared against a comprehensive field survey of the ephemeral network in each watershed to evaluate performance. Comparisons were also made to the U.S. Geological Survey National Hydrography Dataset (NHD) and a flow accumulation approach where a single drainage area threshold defined channel initiation. Although the NHD and flow accumulation methods resulted in low commission errors, omission errors were highest in these networks. The TO-based networks detected a larger number of ephemeral channels, but with higher commission error. Small ephemeral channels with less defined banks or originating at groundwater seeps were difficult to detect in all methods. Comparisons between forested and urban watersheds also highlight the difficulty of identifying headwater channels using topographic attributes in human-modified landscapes.

Maryland↗
USGS2022

Predicting near-term effects of climate change on nitrogen transport to Chesapeake Bay

Understanding effects of climate change on nitrogen fate and transport in the environment is critical to nutrient management. We used climate projections within a previously calibrated spatially referenced regression (SPARROW) model to predict effects of expected climate change over 1995 through 2025 on total nitrogen fluxes to Chesapeake Bay and in watershed streams. Assuming nitrogen inputs and other watershed conditions remain at 2012 levels, effects of increasing temperature, runoff, streamflow, and stream velocity expected between 1995 and 2025 will include an estimated net 6.5% decline in annual nitrogen delivery to the bay from its watershed. This predicted decline is attributable to declines in the delivery of nitrogen from upland nonpoint sources to streams due to predicted warmer temperatures. Such temperature-driven declines in the delivery of nitrogen to streams more than offset predicted increased delivery to and within streams due to increased runoff and streamflow and may be attributable to increasing rates of denitrification or ammonia volatilization or to changes in plant phenology. Predicted climate-driven declines in nitrogen flux are generally similar across the watershed but vary slightly among major nonpoint source sectors and tributary watersheds. Nitrogen contributions to the bay from point sources are not affected by temperature-driven changes in delivery from uplands and are therefore predicted to increase slightly between 1995 and 2025.

Chesapeake Bay watershed↗
USGS2022

Effect of restoration on plant greenness and water use in relation to drought in the riparian corridor of the Colorado River delta

Revitalization of the Colorado River delta riparian corridor and increasing riparian plant greenness and water use may be accomplished by added water and restoration efforts to offset declines measured since 2000 by Landsat. We use the two-band Enhanced Vegetation Index (EVI2; a proxy for greenness) and evapotranspiration (ET, mm/day) using EVI2 and potential ET(ETo) from Yuma Valley. We assess if restoration with only 7.5% landcover had an impact on the unrestored reach-level landcover by measuring these two metrics, EVI2 and ET(EVI2) by comparing restored and unrestored areas. A key finding is that over 21-years EVI2 in the unrestored corridor decreased by 23.6% and ET(EVI2) decreased by 32% (0.87 mm/day). Since 2011, the unrestored reaches lost EVI2 (11%) and −0.73 mm/day ET(EVI2) (28%), but restored sites increased in EVI2 (36%) and 0.58 mm/day ET(EVI2) (20%). Water delivered to restored sites increased EVI2 by 33.6% and 1.29 mm/day ET(EVI2) (58%). EVI2 and ET(EVI2) as a function of the Standardized Precipitation Evapotranspiration Index for drought periods highlight that restored and unrestored sites respond differently. Unrestored reaches are in decline; restored sites show increases in EVI2 and ET(EVI2). Restored sites do not have a significant impact on unrestored adjacent area, but smaller surface flows, a greater reliance on directed agricultural return flows, and deliveries of water to active restoration sites have revitalized habitat and increased ecosystem services in the delta.

Colorado River delta↗
USGS2022

Spatial and temporal variations in phosphorus loads in the Illinois River Basin, Illinois USA

Total phosphorus (TP) loads in many rivers in the north-central United States have increased, including the Illinois River at Valley City, Illinois, USA, which increased 39% from the periods 1989–1996 to 2015–2019 despite efforts to reduce loads from point and nonpoint sources. Here, we quantify long-term variations in phosphorus (P) loads in the Illinois River and its tributaries and identify factors that may be causing the variations. We calculated river loads of dissolved (DP) and particulate P (PP), total and volatile suspended solids (TSS and VSS), and other potentially related constituents at 41 locations. DP loads generally increased and PP and TSS loads generally decreased from 1989–1996 to 2015–2019. During 1989–1996, P accumulated in the lower basin between Marseilles and Valley City (excluding monitored tributaries). This portion of the basin is very flat and accumulates sediment. During 2015–2019, this section shifted from being a net sink to being a net source of P, accounting for 78% of the increased TP load at Valley City. We present evidence supporting several mechanisms that could have caused this shift: increased DP and chloride loads, reduced sulfate and nitrate concentrations influencing ionic strength and redox potential in the sediments, and increased VSS loads at Valley City possibly indicating greater algal production and contributing to hypoxia in lower river sediments. Additional research is needed to quantify the relative importance of these mechanisms.

Illinois, Indiana, Wisconsin↗