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201 results for “Streamflow”
Longitudinal Streamflow in Headwater Streams on Prospect Hill Tract at Harvard Forest 2003
We have initiated long-term monitoring of streamflow in headwater streams on the Prospect Hill Tract at the Harvard Forest. In addition, we have periodically recorded summer flow conditions longitudinally along the length of headwaters within Harvard Forest to obtain information about spatial heterogeneity of flow and of availability of aquatic habitat within these headwaters. In summer of 2003, we recorded streamflow each week at 20-m intervals along the length of two tributaries of Nelson Brook, Tributary A, from Route 32 to its outlet from the Black Gum Swamp, and Tributary B, from its junction with Tributary A to its origin in wetlands north of Prospect Hill Road.
Streamflow data for Albion camp, 1981 - ongoing.
This is a summary of discharges from the Green Lakes Basin (7.1 km2 area) and is based on stage records from the control section in the channel, about 50 m downstream of the culvert under the road at the Albion camp, and consists of daily flow volumes. Initially, instrumentation consisted of a Leupold-Stevens A70 float recorder. The site was initially instrumented with an Omnidata EZ900 data logger system interfaced to a Keller 1 psi pressure transducer on 29 June 1993. In order to establish cross-calibration between the 2 forms of instrumentation, both were planned to be used through 1994. In 2005, a Campbell cr10x data logger was installed; it was replaced by a Campbell cr1000 in 2013.
Streamflow for Martinelli basin, 1982 - ongoing.
This is a summary of discharges from the Martinelli Basin and is based on stage records from the outlet channel 30 m below the road at the foot of the basin.
Streamflow data for Saddle stream, 1999 - ongoing.
This is a summary of discharges from the stream draining Niwot Ridge Saddle to the south and is based on stage records gauged at a timber weir with a 120 degree V-notch plate, located 30 m upstream of Green Lakes road. It consists of daily flow volumes.
Hubbard Brook Experimental Forest: Instantaneous Streamflow by Watershed, 1956 – present
Streamflow at 9 watersheds (12-77 Hectares) within the Hubbard Brook Experimental Forest in New Hampshire, USA has been measured continuously from as early as 1955. Streams are gaged with V-notch weirs, in some cases in combination with rectangular San Dimas flumes, at the outlet of each watershed. Through 2012, stage heights were recorded by means of a mechanical spring-wound clock and pen on a strip-chart recorder. Beginning January 1, 2013, these analog chart recorders were replaced with digital sensors. Overlap with both measurement techniques occurred for several years at all weirs. Streamflow data were gathered by the Hubbard Brook Experimental Forest and contributed to the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Hubbard Brook Experimental Forest: Daily Streamflow by Watershed, 1956 - present
Streamflow at 9 watersheds (12-77 Hectares) within the Hubbard Brook Experimental Forest in New Hampshire, USA has been measured continuously from as early as 1955. Streams are gaged with V-notch weirs, in some cases in combination with rectangular San Dimas flumes, at the outlet of each watershed. Through 2012, stage heights were recorded by means of a mechanical spring-wound clock and pen on a strip-chart recorder. Beginning January 1, 2013, these analog chart recorders were replaced with digital sensors. Overlap with both measurement techniques occurred for several years at all weirs. Streamflow data were gathered by the Hubbard Brook Experimental Forest and contributed to the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Streamflow for Green Lake 4, 1981 - ongoing.
This is a summary of discharges from the upper Green Lakes Basin based on stage records from the outlet of Green Lake 4, and consists of daily flow volumes.
Monthly time series of rainfall, potential evapotranspiration and streamflow for 201 catchments in South-East Australia
<p>The data set contains data for 201 catchments located in South-Eastern Australia. The data was extracted from the datasets collated by Lerat, Thyer et al. (2020) including rainfall and potential-evapotranspiration data obtained from the Bureau of Meteorology Australian Water Outlook website (Frost, Ramchurn et al. 2016) and streamflow data obtained from the Bureau of Meteorology Water Data Online website (Bureau of Meteorology 2019). The data was collected over the period from 1980 to 2018, split into the two sub-periods 1980-1999 (Period 1) and 1999-2018 (Period 2).</p><p> </p><p>Bureau of Meteorology. (2019). "Water Data Online." from <a href="http://www.bom.gov.au/waterdata">http://www.bom.gov.au/waterdata</a>.</p><p>Frost, A. J., A. Ramchurn and A. Smith (2016). "The bureau's operational AWRA landscape (AWRA-L) Model." Bureau of Meteorology Technical Report.</p><p>Lerat, J., M. Thyer, D. McInerney, D. Kavetski, F. Woldemeskel, C. Pickett-Heaps, D. Shin and P. Feikema (2020). "A robust approach for calibrating a daily rainfall-runoff model to monthly streamflow data." Journal of Hydrology<strong>591</strong>: 125129.</p>
Recent Upper Colorado River Streamflow Declines Driven by Loss of Spring Precipitation
<div> <div> <p>The dataset accompanying the manuscript titled "Recent Upper Colorado River Streamflow Declines Driven by Loss of Spring Precipitation" provides comprehensive information on streamflow patterns in the Colorado River since 2000. The dataset is needed to run the analysis available on GitHub available <a href="https://github.com/dlhogan97/Spring-Precipitation-Effect-CO-River.git">here</a>. This is version 2, please use this version for the most up-to-date results.</p> <p><strong>Please read the accompanying README (available in the README.md file) for individual file descriptions and file nesting strategy that should be employed to easily reproduce this analysis.</strong></p> <p>The dataset covers a range of variables related to streamflow and precipitation, including but not limited to discharge measurements, seasonal variations, and relevant meteorological data. The primary focus of the dataset is to elucidate the observed streamflow deficits in the Colorado River, attributing these changes to decreased spring precipitation.</p> <p>Key features of the dataset include:</p> <ul> <li> <p>Time Coverage: The dataset spans a specified time range that aligns with the investigation into recent streamflow deficits in the Colorado River between 1964 and 2022.</p> </li> <li> <p>Spatial Scope: It includes data from relevant monitoring stations along within the Upper Colorado River, but focusing in the hydrologically vital headwater regions, providing a spatially distributed perspective.</p> </li> <li> <p>Variables: The dataset encompasses a variety of variables essential for understanding streamflow dynamics, with a particular emphasis on the impact of reduced spring precipitation.</p> </li> </ul> <p>Researchers and stakeholders interested in hydrological patterns, climate-driven changes, and water resource management in the Colorado River Basin will find this dataset valuable. It serves as a foundational resource for reproducibility, further analysis, and collaboration within the scientific community. The dataset is deposited on Zenodo to facilitate open access, sharing, and citation for broader research endeavors.</p> </div> </div>
Seasonal streamflow hindcast data for the Upper Segura and Upper Tagus river basins
<p>The datasets provided here have been produced as part of the IMPREX project for work package 11, task 2. The aim was to evaluate the performance of climate model-based seasonal hydrological forecasting system that is used to predict drought indices of the Segura River Basin and the Tajo-Segura Water transfer System. These indices rely on forecasted discharge values and describe the expected status of the water availability in both systems. Also, for the Tagus basin, the forecasts can be used to determine the amount of water transferred to the Segura river basin. The key involved stakeholder is the River Basin Authority of the Segura Basin that uses these drought indices for drought mitigation actions. This task developed and evaluated a forecasting system for these drought indices.</p> <p>The dataset - <strong>Pseudo_Obs_SPHY_Spain02_Output.csv</strong> include streamflow simulations for the Entrepenas and Buendia discharge stations located in the Upper Tagus basin, Spain in addition to the Fuensanta and Cenajo discharge stations located in the Segura river basin, Spain. Hydrological outputs are produced using The Spatial Processes in Hydrology (SPHY) model (Terink et al., 2015) forced by the Spain02 V4 meteorological dataset (Herrera et al., 2016) for the period 1979-2010. Please note however that there are known issues with the Spain02 dataset for the years 2007-2010 that affect this dataset.</p> <p>The dataset <strong>- SPHY_ECMWF_S5_Output.csv </strong>includes streamflow simulations for the same locations using the SPHY model albeit forced with the ECMWF SEAS5 hindcast data for the period 1981-2010. The column “LD” represents lead month where the first month of hindcasts is signaled as 1, second as 2 and third as 3. The “Ens” column refers to the individual ensemble members as 25 in total are used for this setup.</p>
Daily streamflow (Bisley area, 5 stations: Q1, Q2, Q3, Sabana, Puente Roto)
The daily data are summarized to monthly as follows: Daily average CFS are summed for each month and multiplied by 86400 (seconds per day) to yield cubic feet per month. This value is divided by the particular watershed area and multiplied by another conversion factor to yield cm water equivalent depth discharged by each watershed per month. This allows direct hydrologic comparison of watersheds of different sizes. Time series plots illustrate the biennial periodicity of high and low discharges, and particular floods and droughts. October 1970 was the historic flood for PR, recently exceeded during the passage of Hurricane Hortense in September 1996. The historic drought occurred during 1993-1994 and is clearly visible in these records. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
USGS Long-term daily streamflow data at several LEF locations
Vist the USGS water data center (https://waterdata.usgs.gov) for more information on these discharge and other data collected in Northeastern Puerto Rico. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Saddle catchment Distributed Hydrology Soil Vegetation Model Simulation (DHSVM) surface variable outputs (SWE, snowmelt, streamflow, soil moisture), 2 meter, 2000-2019.
The Saddle Catchment of the Niwot Ridge LTER is a densely observed, high elevation site that is ideal for hydrological model simulation and calibration. The files produced are the result of a calibration of the Distributed Hydrology Soil Vegetation model (DHSVM) using observationally based states and forcings. Input state files of vegetation, soil properties, shading, and elevation were generated using ground and satellite observations, which, in the case of coarse-resolution or point scale observations, were then interpolated to match the high resolution of the model (2-meter grid cells). Temporally continuous meteorological forcings at the hourly time-step were used to force the model to produce an hourly simulation of the surface and subsurface hydrology within the Saddle catchment. DHSVM was calibrated to effectively reproduce the annual cycle (r^2) and total volume (percent bias) of observed runoff using observations of streamflow at the outflow pour point of the Saddle Catchment from 2001-2019. Calibrated parameters include the lateral conductivity of soil types, exponential decrease of soil conductivity, snow roughness, the snow melting temperature threshold, and the vertical conductivity of the soils. The resulting simulation generated spatially distributed time series of the snow water equivalent, snow melt, precipitation, total evapotranspiration, potential evapotranspiration, and a time-series of the total runoff generated at the outflow pour-point of the Saddle catchment. This data package contains the spatially distributed time series of snow water equivalent, snow melt, and runoff, as well as the model configuration file. Outputs of precipitation, total evapotranspiration, actual evapotranspiration, as well as model inputs are archived separately on the Environmental Data Initiative.
Streamflow data for Saddle Stream 16, 2020 - ongoing.
This is a summary of discharges from the stream draining Niwot Ridge Saddle to the south and is based on stage records gauged at a timber weir with a 120-degree V-notch plate installed in the fall of 2019. The weir is located approximately 380 meters SW of the Tundra Lab, and 240 meters upstream of the saddle stream weir, which was installed in 1999. It consists of average daily flow volumes in m^3. LOCATION. 40.051473782595195, -105.59131521489772 The study site is the stream draining Niwot Saddle to the south, 380 meters downstream of the source of the stream on the Niwot Saddle (near the Tundra Lab) and 240 meters upstream of the existing saddle stream weir. It is gauged at a timber weir with a 120-degree V-notch plate. TIMING. Weir was installed in the fall of 2019 by Henry Brandes and Tyler Lampard. Flow measurements began in the summer of 2020, ongoing, daily during the field season (usually from late April to early September).
Data archive for journal paper "Assimilation of Sentinel-1 Backscatter into a Land Surface Model with River Routing and Its Impact on Streamflow Simulations in Two Belgian Catchments"
<p>The datasets archived here include data assimilation results presented in the journal paper, "Assimilation of Sentinel-1 Backscatter into a Land Surface Model with River Routing and Its Impact on Streamflow Simulations in Two Belgian Catchments" (https://doi.org/10.1175/JHM-D-22-0198.1). The output was produced by combining land surface modeling (Noah-MP with HYMAP river routing) and Sentinel-1 backscatter data, applying a 1D Ensemble Kalman Filter using the NASA Land Information System. We provide Netcdf daily output files for 6 different experiments</p><p>- OLfd and OLgw: model-only (open-loop, OL) for two different model settings (fd: free drainage and gw: SIMTOP groundwater option) <br>- DASMfd and DASMgw: data assimilation (DA) with soil moisture (SM) updating for two different model settings (fd: free drainage and gw: SIMTOP groundwater option) <br>- DASMLAIfd and DASMLAIgw: data assimilation (DA) with soil moisture (SM) and leaf area index (LAI) updating for two different model settings (fd: free drainage and gw: SIMTOP groundwater option) </p><p>Each experiment directory contains five subdirectories (DAOBS, EnKF, ROUTING, RTM, SURFACEMODEL) with corresponding outputs as described in https://nasa-lis.github.io/LISF/LIS_users_guide/LIS_users_guide.html</p>
Streamflow, precipitation, soil moisture, and ephemeral stream nitrogen data for St. Croix, USVI
<p>These datasets were collected from two ephemeral stream sites within the Salt River watershed on St. Croix, USVI using high frequency (15-minute) sensors. The stream nitrogen data were collected via grab samples and were analyzed with a benchtop spectrophotometer. The data were collected to better understand the influence of precipitation and soil moisture conditions on stream nitrogen concentrations. </p>
Reference Mean and Low Streamflow for all Brazilian Catchments Generated Using Machine Learning Models
<p>This dataset provides comprehensive hydrological information for river networks in Brazil, focusing on reference streamflows, specifically long-term mean flows (qm) and low flows exceeded 95% of the time (q95). Covering over 400,000 ungauged river points, the dataset was developed using advanced machine learning models trained on environmental descriptors and validated against data from 1,069 gauging stations spread across the country. The machine learning pipeline evaluated six regression models to achieve high predictive accuracy (R² > 0.8 for qm and > 0.7 for q95). The 62 environmental descriptors - encompassing climate, topography, land cover, lithology, and water storage characteristics - that were used as features for the models are also included.</p> <p>Key features:</p> <ul> <li><strong>Spatial Coverage:</strong> Brazilian territory and the Amazon River basin, based on the <a href="https://metadados.snirh.gov.br/geonetwork/srv/api/records/f7b1fc91-f5bc-4d0d-9f4f-f4e5061e5d8f" target="_blank" rel="noopener">BHO 5k</a> dataset of officially adopted river networks.</li> <li><strong>Outputs:</strong> Predicted qm and q95 values for each river stretch, with 90% and 75% confidence intervals to account for prediction uncertainty.</li> <li><strong>Environmental Descriptors:</strong> Aggregated from upstream catchment area.</li> </ul> <p> </p>
Wflow SBM streamflow estimates for CAMELS data set
<p>The dataset contains 3 simulated timeseries at the basin outlet for the CAMELS dataset created with the wflow_sbm model at various spatial resolutions (3km, 1km, 200m). The data set includes the calculated objective functions NSE, KGE 2009, KGE 2012, and KGE NP.</p>
Streamflow drought hazard indicators for monitoring drought risk for human water supply and river ecosystems at the global scale
<p><strong>1) Indicators of streamflow drought hazard (SDHI) as computed by WaterGAP 2.2d (climate data WFDEI-GPCC) for the whole globe except Antarctica, spatial resolution: 0.5°, monthly data for the reference period 1986-2015:</strong></p> <p><strong>Indicators of drought magnitude: </strong>SPI12, SPEI12, SSI1, SSI12, EP1, RDQI1</p> <p><strong>Indicators of drought severity: </strong>CDQI1-Q50, CDQI1-Q80, CDQI1-Q80-HS, CDQI1-WUs, CDQI1-WUs-EFR, CDQI1-Q50_f, CDQI1-Q80_f, CDQI1-WUs_f, CDQI1-WUs-EFR_f, CEP1(20%)_f, CRDQI1(-50%)_f</p> <p><strong>2) WaterGAP grid cell IDs ("arcid") with longitude and latitude </strong>(WaterGAP_ArcID_lon_lat.txt)</p> <p><strong>3) Streamflow observations and SDHI (based on observations) for two GRDC gauging stations: </strong>Input_Figure_2_Little_Colorado_River.txt (station near Cameron) and Input_Figure_2_Danube_River.txt (station at Hofkirchen)</p> <p><strong>4) WaterGAP output: Mean monthly surface water abstractions in km3 per month: </strong>Mean_monthly_WUs_km3_per_month_WFDEI_GPCC_ant_22d_1986_2015.txt</p> <p><strong>5) Input data for computing Pearson correlation between SSI1 based on observations and each of the five indicators SSI1 (simulated), SPI3, SPI6, SPI9, and SPI12.</strong> Indicators computed for 218 out of 220 GRDC gauging stations with continuous streamflow observations between 1986 and 2015. The folder also contains a list of the 220 GRDC station numbers and the related WaterGAP grid cell ID ("arcid").</p> <p> </p>
Data for figures in the global streamflow change paper
<p>This is the dataset used for generating figures 1-4 in the manuscript of "<strong>Future global streamflow declines likely more severe than previously estimated</strong>"</p>
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