Christine A. Rumsey
2019
Baseflow estimation and hydroclimatic data input details for the Upper Rio Grande, 1980 to 2015
tables
Denver, Colorado
U.S. Geological Survey
data release
https://doi.org/10.5066/P976XFE8
Rumsey, Christine A.
Miller, Matthew P.
Sexstone, Graham A.
2019
Relating hydroclimatic change to streamflow, baseflow, and hydrologic partitioning in the Upper Rio Grande Basin, 1980 to 2015
tables and figures
https://doi.org/XXXX
Understanding how changing climatic conditions affect streamflow volume and timing is critical for effective water management. In the Rio Grande Basin of the southwest U.S., decreasing snowpack, increasing minimum temperatures, and decreasing streamflow have been observed in recent decades, but the effects of hydroclimatic changes on baseflow, or groundwater discharge to streams, have not been investigated. The dataset created in this data release was used to help support a study to determine how trends in precipitation, snowpack accumulation, and snowmelt rate relate to streamflow, baseflow, and the hydrologic partitioning of baseflow and runoff at 12 sites in the Upper Rio Grande Basin (URGB) during 1980 to 2015. Streamflow was partitioned into baseflow and runoff components at a daily time step using conductivity mass balance hydrograph separation. Trends in annual streamflow, baseflow, runoff, baseflow index, precipitation, snowmelt rate, and peak snow water equivalent (SWE) were evaluated from 1980 to 2015 using the non-parametric Mann-Kendall trend test.
This data release contains details of input data and model output diagnostics to reproduce the results found in the journal article titled "Relating hydroclimatic change to streamflow, baseflow, and hydrologic partitioning in the Upper Rio Grande Basin, 1980 to 2015".
In 2014, the Upper Rio Grande Basin (URGB) of Colorado, New Mexico, Texas, and northern Mexico was chosen as a focus area study (FAS) for the U.S. Geological Survey (USGS) National Water Census. The three main objectives of the USGS National Water Census are to (1) provide a nationally consistent set of indicators that reflect each status and trend relating to the availability of water resources in the United States, (2) provide information and tools that allow users to better understand the flow requirements for ecological purposes, and (3) report on areas of significant competition over water resources and the factors that have led to the competition. The URGB FAS will help meet these objectives through an integrated, comprehensive approach using existing data and studies, established and new technologies, and user-friendly data management and visualization tools. The study will assess water availability in the URGB from the headwaters in southern Colorado to Fort Quitman, Texas. Water availability will be evaluated by assessing surface water and groundwater, and estimating evapotranspiration and water use. Assessment of water-budget components and their interaction will include evaluation of historical and current hydrologic data.
1980
2015
ground condition
None planned
-108.0
-105.0
39.0
35.0
USGS Thesaurus
hydrology
statistical analysis
regressional analysis
time series analysis
hydrographic datasets
time series datasets
precipitation
hydrologic processes
streamflow
water cycle
groundwater and surface-water interaction
water resources
groundwater
surface water
water properties
water supply and demand
water budget
runoff
snow and ice cover
USGS Metadata Identifier
USGS:5cd498ffe4b062989a9e95b6
U.S. Board on Geographic Names
Rio Grande
Rio Chama
Abiquiu Reservoir
Heron Reservoir
Cochiti Lake
Rio Puerco
Monte Vista
Alamosa
Del Norte
Chama
Red River
Taos
Espanola
Santa Fe
Albuquerque
Archuleta County
Conejos County
Costilla County
Alamosa County
Rio Grande County
Mineral County
Hinsdale County
San Juan County
Saguache County
Bernalillo County
Santa Fe County
Sandoval County
McKinley County
Los Alamos County
Taos County
Rio Arriba County
Mora County
Colorado
New Mexico
United States of America
None
none
Christine A. Rumsey
U.S. Geological Survey
Hydrologist
mailing and physical
2329 2329 West Orton Circle
West Valley City
UT
84119
United States
801-908-5022
crumsey@usgs.gov
These data were produced for a study that was part of the U.S. Geological Survey (USGS) National Water Census.
Data entries and values in the tables were spot-checked and/or range values were checked for accuracy.
No formal logical accuracy tests were conducted.
Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details.
No formal positional accuracy tests were conducted
U.S. Geological Survey
2019
National Water Information System
csv
Reston, Viriginia
U.S. Geological Survey
https://doi.org/10.5066/F7P55KJN
daily streamflow and discrete specific conductance data
19791001
20150930
ground condition
NWIS
site information
Matthew P. Miller
David D. Susong
Christopher L. Shope
Victor M. Heilweil
Bernard J. Stolp
2014
Continuous estimation of baseflow in snowmelt-dominated streams and rivers in the Upper Colorado River Basin: A Chemical hydrograph separation approach
journal article
Water Resources Research Volume 8
50
Pages 6986-6999
https://doi.org/10.1002/2013WR014939
online
2014
publication date
Miller and others, 2014
hydrograph separation approach
Christine A. Rumsey
Matthew P. Miller
Gregory E. Schwarz
Robert M. Hirsch
David D. Susong
2017
The role of baseflow in dissolved solids delivery to streams in the Upper Colorado River Basin
journal article
Hydrological Process Volume 31
26
Pages 4705-4718
https://onlinelibrary.wiley.com/doi/full/10.1002/hyp.11390
online
2017
publication date
Rumsey and others, 2017
baseflow
Gregory E. Schwarz
Anne B. Hoos
R.B. Alexander
R.A. Smith
2006
The SPARROW Surface Water-Quality Model--Theory, application and user documentation
document
Teachniques and Methods
6-B3
Reston, Virginia
U.S. Geological Survey
https://pubs.er.usgs.gov/publication/tm6B3
online
2006
publication date
Schwarz and others, 2016
Fluxmaster
Natural Resources Conservation Service
2019
Snow Telemetry data
database
Portland, OR
Natural Resources Conservation Service
https://www.wcc.nrcs.usda.gov/snow/
online
19791001
20150930
ground condition
SNOTEL
snow water equivalent and precipitation data
A conductivity-mass-balance (CMB) hydrograph separation approach was used to estimate daily and long-term mean annual baseflow discharge following the methodology outlined in the accompanying report (Rumsey et al., in review). This approach requires daily streamflow and daily specific conductance as inputs. Measured daily streamflow (Q) and discrete specific conductance (SC) data were obtained from 17 U.S. Geological Survey (USGS) stream gages from the National Water Information System (NWIS) database (https://waterdata.usgs.gov/nwis). Data spanned water years (WY) 1980 to 2015, with periods of record varying from 5 to 36 years (median length of record was 21 years). Due to data limitations, data span different time periods at different gages. Sites chosen had to meet criteria required for CMB hydrograph separation as discussed in Miller and others (2014) and Rumsey and others (2015), and all sites were located in watersheds with snowmelt-dominated hydrology.
To estimate daily and long-term mean annual baseflow discharge using CMB, daily estimates of SC were required at each stream gage site. Using discrete SC and daily streamflow data (from NWIS), Fluxmaster (Schwarz and others, 2006) was used to estimate daily SC with four regression equations (see below), which calculated SC loads as a function of mean daily streamflow, time, and season. For the calculation of long-term mean annual baseflow, SC loads were detrended to a base year of 2000 for all sites and equations to allow for comparison of loads among sites with differing periods of record, sample sizes, and temporal variability in discharge. Estimated daily SC loads were subsequently converted to daily SC values (µS/cm) for use in calculating baseflow discharge. A second set of three Fluxmaster regression equations (see below) were used to estimate non-detrended daily SC to estimate daily baseflow discharge for use in subsequent Mann Kendall trend analyses of baseflow. Regression equations were eliminated if estimated and observed loads differed by more than 15 percent. The best-fit regression equation was selected as the equation that produced the lowest Akaike information criteria (AICc) value (Fluxmaster fit statistics provided in data table).
Trends in several precipitation variables were analyzed using the non-parametric Regional Mann Kendall test for trend to understand streamflow and baseflow trends in the context of climate variability. Daily measurements of precipitation and snow water equivalent (SWE) were obtained from Natural Resources Conservation Service (NRCS) snowpack telemetry (SNOTEL) stations in the URGB (https://www.wcc.nrcs.usda.gov/snow/). To pair streamflow trends with precipitation trends, SNOTEL stations were assigned to streamgages if they were located within the delineated watershed of each streamgage. The period of record at each SNOTEL station was trimmed to match the period of available baseflow discharge data available at each streamgage, resulting in 14 SNOTEL stations with periods of record that overlapped baseflow discharge data.
The processes used to develop the dataset used in the baseflow estimation and trend analysis are fully described in the accompanying journal article by Rumsey and others (in review).
Detrended (to 2000) Fluxmaster regression equations :
model 1) log(DS) = intercept + b_1log(flow) + b_2log(flow)2 + b_3sin(2πT) + b_4cos(2πT) + b_5sin(2πT)2 + b_6cos(2πT)2 + b_7T + b_8T2
model 2) log(DS) = intercept + b_1log(flow) + b_2log(flow)2 + b_3sin(2πT) + b_4cos(2πT) + b_5sin(2πT)2 + b_6cos(2πT)2 + b_7T
model 3) log(DS) = intercept + b_1log(flow) + b_2sin(2πT) + b_3cos(2πT) + b_4sin(2πT)2 + b_5cos(2πT)2 + b_6T
model 6) log(DS) = intercept + b_1log(flow) + b_2T
Non-detrended Fluxmaster regression equations:
model 1b) log(DS) = intercept + b_1log(flow) + b_2log(flow)2 + b_3sin(2πT) + b_4cos(2πT) + b_5sin(2πT)2 + b_6cos(2πT)2
model 4) log(DS) = intercept + b_1log(flow) + b_2sin(2πT) + b_3cos(2πT) + b_4sin(2πT)2 + b_5cos(2πT)2
model 7) log(DS) = intercept + b1log(flow)
,where DS = dissolved solids; flow = mean daily streamflow (cfs); T is decimal time; b_n = regression coefficients determined by Fluxmaster
streamflow Fluxmaster regression equation:
log(flow) = intercept + b_1sin(2πT) + b_2cos(2πT) + b_3sin(2πT)^2 + b_4cos(2πT)^2 + AR3; where flow = mean daily streamflow (cfs); T is decimal time; b_n = regression coefficients determined by Fluxmaster; and AR3 is a 3-day autoregression trem in the residuals to account for serial correlation in the daily streamflow values
NWIS
Miller and others, 2014
Rumsey and others, 2017
Schwarz and others, 2006
2018
Baseflow_and_SNOTEL_metadata
NWIS and SNOTEL site information, Fluxmaster model diagnostics, and select results
Producer generated
USGS_station_ID
USGS streamgage station number
Producer defined
USGS station ID
station_name
USGS streamgage station name
Producer defined
USGS station name
dec_lat_va
Latitude in decimal degrees
Producer defined
35.08917
37.76695
decimal degrees
dec_long_va
Longitude in decimal degrees
Producer defined
-106.83
-105.50
decimal degrees
coord_datum_cd
Latitude and longitude (horizontal) coordinate datum
Producer defined
NAD83
North American Datum of 1983
Producer-defined.
drain_area_va_km2
Drainage area upstream of streamgage, in square kilometers
Producer defined
93
44699
square kilometers
site_elevation_m
Site elevation, in meters
Producer defined
1509
2578
meters
start_dt_flow_FM
start date of flow data (MM/DD/YYYY) - used for Fluxmaster input; applicable for both detrended and non-detrended Fluxmaster models
Producer defined
10/01/1979
09/30/2015
(MM/DD/YYYY)
end_dt_flow
end date of flow data (MM/DD/YYYY) - used for Fluxmaster input; applicable for both detrended and non-detrended Fluxmaster models
Producer defined
09/30/2000
09/30/2015
(MM/DD/YYYY)
flow_pCode
NWIS parameter code of mean daily flow
Producer defined
00060
mean daily discharge, cubic feet per second
USGS NWIS
start_dt_wq_FM
start date of water quality data (MM/DD/YYYY) - used for Fluxmaster input; applicable for both detrended and non-detrended Fluxmaster models
Producer defined
10/3/1979
3/17/1987
(MM/DD/YYYY)
end_dt_wq_FM
end date of water quality data (MM/DD/YYYY) - used for Fluxmaster input; applicable for both detrended and non-detrended Fluxmaster models
Producer defined
10/16/1985
8/31/2016
(MM/DD/YYYY)
wq_pCode
NWIS parameter code of discrete water quality data
Producer defined
00095
Specific conductance, water, unfiltered, microsiemens per centimeter at 25 degrees Celsius
USGS NWIS
num_SC_obs
number of SC observations used to build Fluxmaster regression models
Producer defined
25
291
FM_reg_eq_d
Detrended Fluxmaster regression equation
Producer defined
1
equation 1; sites where detrended Fluxmaster regression equation 1 was selected to model daily SC (see "Process" section for equation definition)
Producer-defined.
2
equation 2; sites where detrended Fluxmaster regression equation 2 was selected to model daily SC (see "Process" section for equation definition)
Producer-defined.
3
equation 3; sites where detrended Fluxmaster regression equation 3 was selected to model daily SC (see "Process" section for equation definition)
Producer-defined.
6
equation 6; sites where detrended Fluxmaster regression equation 6 was selected to model daily SC (see "Process" section for equation definition)
Producer-defined.
r2_d
R-squared fit statistic of selected Fluxmaster model; detrended Fluxmaster model (detrended to year 2000)
Producer defined
0.42
0.90
rmse_d
root mean square error of selected Fluxmaster model; detrended Fluxmaster model (detrended to year 2000)
Producer defined
0.11
0.27
OoverE_d
ratio of average observed to average estimated specific conductance of selected Fluxmaster model; detrended Fluxmaster model (detrended to year 2000)
Producer defined
0.98
1.05
AICc_d
Akaike information criteria (corrected); detrended Fluxmaster model (detrended to year 2000)
Producer defined
-413
56
int_coef_d
coefficient of model intercept; detrended Fluxmaster model (detrended to year 2000)
Producer defined
4.53
8.35
int_p_d
p-value of partial t-test of intercept coefficient; detrended Fluxmaster model (detrended to year 2000)
Producer defined
0
0
loge(flow)_coef_d
coefficient for natural log of flow term; detrended Fluxmaster model (detrended to year 2000)
Producer defined
-0.71
0.19
loge(flow)_p_d
p-value of partial t-test of natural log of flow coefficient; detrended Fluxmaster model (detrended to year 2000)
Producer defined
0
0.96
loge(flow)2_coef_d
coefficient for natural log of flow squared term; detrended Fluxmaster model (detrended to year 2000)
Producer defined
-0.05
0.04
loge(flow)2_p_d
p-value of partial t-test of natural log of flow squared coefficient; detrended Fluxmaster model (detrended to year 2000)
Producer defined
0.01
0.70
sin_coef_d
coefficient for seasonal sine term; detrended Fluxmaster model (detrended to year 2000)
Producer defined
-0.12
0.21
sin_p_d
p-value of partial t-test of seasonal sine coefficient; detrended Fluxmaster model (detrended to year 2000)
Producer defined
0.00
0.85
cos_coef_d
coefficient for seasonal cosine term; detrended Fluxmaster model (detrended to year 2000)
Producer defined
-0.0911
0.0897
cos_p_d
p-value of partial t-test of seasonal cosine coefficient; detrended Fluxmaster model (detrended to year 2000)
Producer defined
0
0.8567
sin2_coef_d
coefficient for squared seasonal sine term; detrended Fluxmaster model (detrended to year 2000)
Producer defined
-0.1202
0.0780
sin2_p_d
p-value of partial t-test of squared seasonal sine coefficient; detrended Fluxmaster model (detrended to year 2000)
Producer defined
0
0.7606
cos2_coef_d
coefficient for squared seasonal cosine term; detrended Fluxmaster model (detrended to year 2000)
Producer defined
-0.1279
0.1212
cos2_p_d
p-value of partial t-test of squared seasonal cosine coefficient; detrended Fluxmaster model (detrended to year 2000)
Producer defined
0.0024
0.9657
time_coef_d
coefficient for time term; detrended Fluxmaster model (detrended to year 2000)
Producer defined
-0.0152
0.0348
time_p_d
p-value of partial t-test of time coefficient; detrended Fluxmaster model (detrended to year 2000)
Producer defined
0
0.7155
time2_coef_d
coefficient for squared time term; detrended Fluxmaster model (detrended to year 2000)
Producer defined
-0.0022
0.0022
time2_p_d
p-value of partial t-test of squared time coefficient; detrended Fluxmaster model (detrended to year 2000)
Producer defined
0
0.0688
FM_reg_eq_nd
Non-detrended Fluxmaster regression equation; selected non-detrended regression equation/model for each streamgage; selected based on good-fit metrics
Producer defined
1b
equation 1b; sites where non-detrended Fluxmaster regression equation 1b was selected to model daily SC (see "Process" section for equation definition)
Producer-defined.
4
equation 4; sites where non-detrended Fluxmaster regression equation 4 was selected to model daily SC (see "Process" section for equation definition)
Producer-defined.
7
equation 7; sites where non-detrended Fluxmaster regression equation 7 was selected to model daily SC (see "Process" section for equation definition)
Producer-defined.
r2_nd
R-squared fit statistic of selected Fluxmaster model; non-detrended Fluxmaster model
Producer defined.
0.39
0.90
rmse_nd
root mean square error of selected Fluxmaster model; non-detrended Fluxmaster model
Producer defined
0.13
0.34
OoverE_nd
ratio of average observed to average estimated specific conductance of selected Fluxmaster model; non-detrended Fluxmaster model
Producer defined
0.97
0.09
AICc_nd
Akaike information criteria (corrected); non-detrended Fluxmaster model
Producer defined
-355
133
int_coef_nd
coefficient of model intercept; non-detrended Fluxmaster model
Producer defined
4.4442
8.3534
int_p_nd
p-value of partial t-test of intercept coefficient; non-detrended Fluxmaster model
Producer defined
0
0
loge(flow)_coef_nd
coefficient for natural log of flow term; non-detrended Fluxmaster model
Producer defined
-0.7102
0.2204
loge(flow)_p_nd
p-value of partial t-test of natural log of flow coefficient; non-detrended Fluxmaster model
Producer defined
0
0.9579
loge(flow)2_coef_nd
coefficient for natural log of flow squared term; non-detrended Fluxmaster model
Producer defined
-0.0353
0.0435
loge(flow)2_p_nd
p-value of partial t-test of natural log of flow squared coefficient; non-detrended Fluxmaster model
Producer defined
0.0103
0.0632
sin_coef_nd
coefficient for seasonal sine term; non-detrended Fluxmaster model
Producer defined
-0.0789
0.2119
sin_p_nd
p-value of partial t-test of seasonal sine coefficient; non-detrended Fluxmaster model
Producer defined
0
0.4423
cos_coef_nd
coefficient for seasonal cosine term; non-detrended Fluxmaster model
Producer defined
-0.0911
0.0958
cos_p_nd
p-value of partial t-test of seasonal cosine coefficient; non-detrended Fluxmaster model
Producer defined
0
0.9213
sin2_coef_nd
coefficient for squared seasonal sine term; non-detrended Fluxmaster model
Producer defined
-0.1202
0.1245
sin2_p_nd
p-value of partial t-test of squared seasonal sine coefficient; non-detrended Fluxmaster model
Producer defined
0.0054
0.6668
cos2_coef_nd
coefficient for squared seasonal cosine term; non-detrended Fluxmaster model
Producer defined
-0.1279
0.1212
cos2_p_nd
p-value of partial t-test of squared seasonal cosine coefficient; non-detrended Fluxmaster model
Producer defined
0.0024
0.6247
bfSC_d
mean baseflow specific conductance, detrended model, calculated as the mean of annual 95th percentile values of SC, in µS/cm
Producer defined
123
796
µS/cm
bfSC_nd
mean baseflow specific conductance, non-detrended model, calculated as the mean of annual 95th percentile values of SC, in µS/cm
Producer defined
132
889
µS/cm
start_dt_bf
start date of annual baseflow estimation (MM/DD/YYYY); also represents starting dates of SNOTEL data
Producer defined
10/01/1979
10/01/1987
(MM/DD/YYYY)
end_dt_bf
end date of annual baseflow estimation (MM/DD/YYYY); also represents ending dates of SNOTEL data
Producer defined
09/30/1985
09/30/2015
(MM/DD/YYYY)
annual_baseflow_volume_d
annual baseflow volume - detrended model, in m3/yr
Producer defined
12933438
933117487
cubic meters per year
annual_baseflow_yield_d
annual baseflow yield - detrended model, in mm/yr
Producer defined
8
154
mm per year
annual_streamflow_volume
annual streamflow volume, in m3/yr
Producer defined
23382952
1352205739
cubic meters per year
BFI
baseflow index (baseflow volume/streamflow volume)
Producer defined
0.29
0.69
COV_annual_baseflow
coefficient of variation of mean annual baseflow
Producer defined
0.10
0.39
95%_CI_baseflow
95th percent confidence interval of baseflow estimates; ± value to get upper and lower limits, in m3/yr
Producer defined
6847258
220456419
cubic meters per year
COV_BFI
coefficient of variation of baseflow index
Producer defined
0
0.003
95%_CI_BFI
95th percent confidence interval of baseflow index; ± value to get upper and lower limits
Producer defined
0
0.003
SNOTEL_station_IDs
List of SNOTEL stations located upstream of each streamgage and with adequate record to match baseflow period of record; each number is a SNOTEL ID
Producer defined
316
Bateman
NRCS SNOTEL Data
394
Chamita
NRCS SNOTEL Data
430
Culebra #2
NRCS SNOTEL Data
431
Cumbres Trestle
NRCS SNOTEL Data
491
Gallegos Peak
NRCS SNOTEL Data
532
Hopewell
NRCS SNOTEL Data
580
Lily Pond
NRCS SNOTEL Data
624
Middle Creek
NRCS SNOTEL Data
665
North Costilla
NRCS SNOTEL Data
708
Quemazon
NRCS SNOTEL Data
715
Red River Pass #2
NRCS SNOTEL Data
744
Senorita Divide #2
NRCS SNOTEL Data
840
Upper San Juan
NRCS SNOTEL Data
857
Whiskey Ck
NRCS SNOTEL Data
FM_reg_eq_Q
Fluxmaster daily streamflow regression equation
Producer defined
1c
streamflow regression model used in Fluxmaster models
Producer defined
U.S. Geological Survey - Science Base
U.S. Geological Survey
mailing and physical
Denver Federal Center
Denver
CO
80225
1-888-275-8747
sciencebase@usgs.gov
Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty.
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Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.
Although these data have been processed successfully on a computer system at the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. The USGS or the U.S. Government shall not be held liable for improper or incorrect use of the data described and/or contained herein.
20200827
Christine A Rumsey
U.S. Geological Survey
Hydrologist
mailing and physical
2329 2329 West Orton Circle
West Valley City
UT
84119
United States
801-908-5022
crumsey@usgs.gov
Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998