Pecos Basin Study
Technical Service Center Support
1
Mission Statements
The mission of the Department of the Interior is to protect
and provide access to our Nation’s natural and cultural
heritage and honor our trust responsibilities to Indian Tribes
and our commitments to island communities.
The mission of the Bureau of Reclamation is to manage,
develop, and protect water and related resources in an
environmentally and economically sound manner in the
interest of the American public.
2
Pecos Basin Study
Technical Service Center Support
3
Introduction
This document reports work done by the Technical Service Center (TSC) to support the Pecos Basin
Study (PBS), a component of the WaterSMART program. The objective of the TSC support was to
provide assistance to the Albuquerque Area Office in development of climate and streamflow data used in
the PBS. All data are intended for use in the Pecos Basin RiverWare Model (PBRM), Work on the data
development began in April, 2013 and was completed in August, 2013. Tasks performed by TSC were:
1. Development of climate data for Maurer1 observed (gridded historical climate data developed
from gage record) and 112 Bias Corrected and Spatially Downscaled (BCSD) climate change
projections by PBRM nodes for computation of evapotranspiration, evaporation, and streamflows.
2. Development of VIC routing model for Maurer observed flows for PBRM nodes.
3. Development of VIC routing model for BCSD flows for PBRM nodes.
4. Computation of bias corrected monthly VIC flows for Maurer observed and 112 BCSD climate
change projections for PBRM nodes.
5. Development of HDe climate data for PBRM nodes.
6. Development of HDe daily flows for PBRM nodes.
7. Development of HDe daily depletions for PBRM nodes.
8. Development of HDe daily evaporation for PBRM nodes.
All Hybrid Delta Ensemble (HDe) data development used a spatial average dataset for the basin so that
HDe quadrants by future were common to all HDe datasets.
1
Maurer, E. P., A. W. Wood, J. C. Adam, D. P Lettenmaier and B. Nijssen, 2002, a Long-Term HydrologicallyBased Data Set of Land Surface Fluxes and States for the Conterminous United States, Journal of Climate, 15(22)
3237-3251.
4
Data Types
Three categories of data were developed for the PBS – Meteorological (Met), flow, and irrigation
requirements. Developed data consisted of two types--transient Maurer observed 1950 through 1999 and
112 BCSD traces from 1950 through 2099 and Maurer observed and HDe traces for a simulation period
from 1950 through 1999. The PBRM requires daily flow, evaporation and irrigation requirements. Daily
meteorological data are an output of the HDe meteorological application. Daily flow require a two-step
process whereby monthly HDe flows are developed from monthly bias corrected Maurer Observed and
BCSD flow, then disaggregated to daily. Monthly bias corrected Variable Infiltration Capacity (VIC) flows
were computed as documented elsewhere. Daily flows were computed by disaggregation of monthly bias
corrected flows. Daily irrigation requirements were computed for use with PBRM using an
evapotranspiration model. The same model was used to compute reference evapotranspiration that was
used to compute reservoir evaporation using the historic monthly relation of reservoir evaporation to
reference evapotranspiration.
Monthly precipitation and monthly average precipitation are available for the Maurer observed and BCSD
projections. Daily precipitation, maximum temperature, and minimum temperature are available for the
Maurer observed trace. Maurer observed and BCSD projections data are available from:
http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/dcpInterface.html
HDe is a method to create representative subsets of the full suite of BCSD traces, with the purpose of
reducing the computational intensity of the operational modeling that is based on the projections. HDe
analyses are performed plotting the average difference in temperature and precipitation between the
projected future period and a representative past period. As shown on Figure 1, these results are then
divided into four quadrants and five clusters are created from the four quadrants as well as the “central
tendency”, the area around the center of the plot in which significant changes in either temperature or
precipitation do not exist. The HDe subsets for a quadrant are developed using all data in a given
quadrant.
HDe time series are computed using data of a BCSD cell specific to the target node. HDe quadrants can
be defined using either the target node’s BCSD data or regional BCSD data. For the PBS, the latter
approach was taken using the spatial average option of the BCSD web site as shown on Figure 2. For
this project, the HDe analyses were performed for three thirty-year future periods which are outlined in
Table 1. The projections for each quadrant (an ensemble) are processed by user-specified time periods
by month to develop adjustment factors that are applied to Maurer observed trace to obtain a given HDe
trace. The adjustment factors are applied as:
HDe temperature = Maurer observed temperature + adjustment value
HDe precipitation = Maurer observed precipitation * adjustment factor
The projection subsets used in HDe analysis are listed in Table 2 and include the five categories of
projections used in HEe analyses as well as the Maurer observed dataset. HDe traces are monthly
average temperature and monthly precipitation, consistent with the BCSD traces. The PBRM requires
monthly maximum and minimum temperatures. These data were aggregated from the daily HDe traces.
HDe daily traces are computed by applying the monthly HDe adjustment factors for precipitation and
values for temperatures to the Maurer observed daily trace.
5
Figure 1. Example HDe quadrants.
HDe quadrant determination can use either the site’s precipitation and average temperature or an
alternative precipitation and average temperature that is intended to be a spatial average of the basin.
This is the approach used by the PBS. The spatially averaged Met data set was downloaded from the
BCSD web site.
A simplified method was used to develop bias-corrected HDe flow projections for operations modeling
in URGSOM and PBRM. Rather than develop HDe climate data as input to the VIC models, which would
have required considerable computer as well as human resources, HDe monthly flow traces were
computed as:
HDe flow = Bias corrected Maurer observed flows * adjustment factor
where the adjustment factors were computed from the bias corrected flows using the meteorological
quadrants.
6
Figure 2, PBS Spatial Average Specifications.
7
Table 1. HDe Setup Specifications.
Time Frame Specifications
Observed Historic Time Frame
Output Simulation Period
Start
1950
1950
End
1999
1999
Years
50
50
1950
2099
150
BCSD Period
Historic Base Time Frame
Future 1 Base Time Frame
1950
2010
1999
2039
50
30
Future Range
Name
2020
Future 2 Base Time Frame
2040
2069
30
2050
FALSE
Future 3 Base Time Frame
2070
2099
30
2080
TRUE
Used
FALSE
Table 2 HDe Climate Change Scenarios.
ID
S1
S2
S3
S4
Scenario
Observed Data
Lower Temperature Lower Precipitation
Lower Temperature Higher Precipitation
Higher Temperature Lower Precipitation
Higher Temperature Higher Precipitation
S5
Central
S0
VIC Routing Models
Unrouted VIC flows exist for the Maurer observed trace and all 112 BCSD traces. PBRM and PBRM
require flows to be routed to the headwater inflows points for these operational models. Two routing
models and dataset were created for this purpose:
1. PBRM Maurer observed
2. PBRM BCSD
PBRM flows nodes are listed in Tables 3.
8
Table 3. VIC Model Nodes.
VIC Node
PNSRL
ECASR
ECTSR
PNPDL
PNACM
RHNR
PNLA
CCNLA
PNART
RPDAY
PNLKD
FMLKD
NSLKD
SSLKD
RACAR
PDCAR
DCCAR
BAMAL
PAPCC
PARED
Description
PECOS RIVER ABOVE SANTA ROSA LAKE
LOS ESTEROS CREEK ABOVE SANTA ROSA LAKE
LOS ESTEROS CR TRIB ABOVE SANTA ROSA LAKE
PECOS RIVER NEAR PUERTO DE LUNA
PECOS RIVER NEAR ACME
RIO HONDO NEAR ROSWELL
PECOS RIVER NEAR LAKE ARTHUR
COTTONWOOD CREEK NEAR LAKE ARTHUR
PECOS RIVER NEAR ARTESIA
RIO PENASCO AT DAYTON
PECOS RIVER (KAISER CHANNEL) NEAR LAKEWOOD
FOURMILE DRAW NR LAKEWOOD
NORTH SEVEN RIVERS NR LAKEWOOD
SOUTH SEVEN RIVERS NR LAKEWOOD
ROCKY ARROYO AT HWY BRD NR CARLSBAD
PECOS R AT DAMSITE 3 NR CARLSBAD
DARK CANYON AT CARLSBAD
BLACK RIVER AT MALAGA
PECOS RIVER AT PIERCE CANYON CROSSING
PECOS RIVER AT RED BLUFF
Bias Corrections Methods and Analysis
Simulated flows from the VIC routing models are not usable directly in decision models because the flows
need to be scaled to historic flows. Simulated flows for the Upper Pecos basin were adjusted using a
quantile-mapping bias correction methodology for the 20 PBRM VIC nodes shown in Table 3 using
historic flows from the PBRM model.
For this analysis, biases are characterized using a quantile map. The quantile map features two empirical
cumulative distribution functions (CDFs)-one of simulated flows during the representative historic period,
referred to as the “bias identification period” (1950-1999) and another of the reference observed flows
during this period. The CDFs are constructed at a given runoff location, first on a month-specific basis to
characterize bias in monthly mean flows, then on an annual basis to characterize bias in annual mean
flows and to preserve mass balance. All CDFs are smoothed non-parametrically using a sliding kernel
approach. Figure 3 is a plot of an example CDF. After defining these maps, simulated runoff bias
correction ensues. The quantile maps are interpreted to reveal VIC runoff simulation bias for a given
simulated runoff magnitude. Refer to the “West-Wide Climate Risk Assessment” report for more details
on the methodology.
9
CDF of Simulated Data
Lobatos, Run 6 May
20,000
18,000
1950-1999
16,000
2000-2099
Flow (cfs)
14,000
12,000
10,000
8,000
6,000
4,000
2,000
0
0
0.2
0.4
0.6
0.8
1
Cumulative Probability
Figure 3. Example Cumulative Density Function.
Figures 4 through 7 show example bias correction outputs for two example basins with low and high
biases. Low bias stations have simulation outputs that match both the annual volume and seasonal
timing well. High bias stations fail to capture either the seasonal flow patterns or the annual runoff
volume. Figures 4 and 6 show monthly observed (black line), simulated (red line), and
bias-corrected simulated (cyan line) flow volumes for water years 1950–1999 for the Rio Blanco below
Blanco site.
Figure 5 shows monthly mean volume (left panel) and annual mean volumes (right panel) including biascorrected simulated flow (BCF) calculated from water years 1950–1999 for the Rio Blanco below Blanco
site. Figure 7 shows monthly mean volume (left panel) and annual mean volumes (right panel) including
bias-corrected simulated flow (BCF) calculated from water years 1950–1999 for the Galisteo Creek
below Galisteo Dam site.
In the Rio Grande basin, increased variability of bias corrected flows after year 2000 spurred a review of
bias corrected flows and procedures. The review confirmed that the bias corrected flows were computed
correctly. In the future period (2000-2099) however, simulated values can exist that are larger (smaller)
than the maximum (minimum) historical simulated values. This point is illustrated on Figure 3 which plots
CDF’s of flow for the historic and future simulated time periods,
From the two CDFs we can see that, in the future simulation, about a 20% chance of having a flow that
exceeds the maximum historical simulated flow (~10,000 cfs) exists. In these instances, the simulated
flow cannot be directly mapped to a historical observed flow because it is outside the upper end of the
historical simulated CDF. Therefore, the simulated flow is scaled by the ratio of the maximum observed
flow to the maximum historical simulated flow over the same (19501-99) period.
10
20 40
0
TAF
Monthly Volumes, WY 1950-1999 (n=43)
1950
1952
1954
1956
1958
1960
20 40
0
TAF
Water Year
1962
1964
1966
1968
1970
20 40
0
TAF
Water Year
1972
1974
1976
1978
1980
1982
20 40
0
TAF
Water Year
1982
1984
1986
1988
OBS
Water Year
SIM
1990
1992
BCF
Figure 4. Historical Simulated Runoff, Small-Bias Example: Monthly Time Series Before and
After Bias Correction.
11
Annual Mean Volumes
Water Years 1950-1999
80
OBS
SIM
BCF
60
20
40
TAF
10
0
5
TAF
15
20
Mean Monthly Volumes
Water Years 1950-1999
Figure 5. Historical Simulated Runoff, Small-Bias Example: Monthly and Annual Means Before
and After Bias Correction.
12
8 12
0
4
TAF
Monthly Volumes, WY 1950-1999 (n=43)
1952
1954
1956
1958
1960
8 12
Water Year
0
4
TAF
1950
1964
1966
1968
1970
8 12
Water Year
0 4
TAF
1962
1974
1976
1978
1980
1982
8 12
Water Year
0
4
TAF
1972
1982
1984
1986
1988
OBS
Water Year
SIM
1990
1992
BCF
Figure 6. Historical Simulated Runoff, Large-Bias Example: Monthly Time Series Before and
After Bias Correction.
13
Annual Mean Volumes
Water Years 1950-1999
4
Mean Monthly Volumes
Water Years 1950-1999
0
0
10
20
TAF
2
1
TAF
3
30
OBS
SIM
BCF
Figure 7. Historical Simulated Runoff, Large-Bias Example: Monthly and Annual Means Before
and After Bias Correction.
14
Figure 8 shows the simulated and bias corrected flow for the May data for the sixth run at the Lobatos
station. From the simulated data we find 21 instances (out of 100 May flow values) where there post 2000
simulated flow data exceeds the historical maximum simulated flow (~10,000 cfs). In the bias corrected
data these are the only instances where the bias corrected flow exceeds the historical simulated
maximum.
Figure 8. Comparison of Various Projections.
(1950-1999) all runs for all stations will result in flows that are at or below historic levels. However, post2000 (2000-2099) simulated flows that are greater than the historical simulated flows can result in flows
that are greater than the historical observed maximum (or less than the historical observed minimum).
This is expected and is done in an effort to maintain the increased variance and extreme values that are
simulated with the climate projections.
Extrapolating this discussion to the entire dataset, we find e that in the time period before 2000
15
PBRM Data
HDe daily Met data traces were developed to support computation of evapotranspiration using the
Penman-Monteith method for use in the PBRM model. The process was similar to PBRM climate data
development except that daily maximum temperature, minimum temperature, and precipitation are
generated from the HDe data manager. HDe Irrigation requirements were computed using the ET model.
HDe evaporation was computed as a function of reference ET using an application developed for the
PBS.
HDe flow traces for PBRM were generated using methods previously noted. Two additional
circumstances were addressed in the development of PBRM HDe daily flows. First, PBRM performs its
operational calculations based on a mix of upstream total flows and downstream local inflows (aka gains
or accretions). Bias corrections are performed on total flows. Therefore, total flows were computed from
the upstream total flows and downstream local flows. Conversely, the computations were reversed to
spatially disaggregate HDe flows before they were temporally disaggregated for use in PBRM.
To support the temporal disaggregations, daily flows were computed by computing disaggregation
fractions for all flows (total and local inflows) using the historic dataset. In principal, the disaggregation
factors are applied to the Maurer observed and HDe monthly and HDe traces to obtain flows (temporal
disaggregation). However, because HDe adjustments are monthly and the adjustment vary month to
month, disaggregated daily flows can produce transition issues between months. A smoothing process
was developed consisting of following steps:
1. Disaggregate Maurer observed trace
2. Apply interpolated monthly HDe adjustment factors to compute initial daily HDe flows.
3. Adjust initial daily HDe flows to maintain consistency with monthly HDe flow.
The Pecos Basin is really dry. The median flow of most tributaries and local inflows was zero. These
data were problematic for doing bias corrections. Therefore another approach was developed to compute
HDe flows for these cases. This approach is to compute the HDe flow as a function of the historic flow
relative to the next downstream station’s historic and HDe flow. For instance:
Tributary HDe flow = Downstream HDe flow * Tributary historic flow / Downstream historic flow.
This was done on a monthly basis. Daily disaggregations for tributaries were done the same as
mainstem flow nodes.
16
Figure 9. Hydrology Data Pathways.
17
RiverWare Model Modifications
Although not part of TSC work scope, sufficient resources were available to create a version of the PBRM
and rules, data management interfaces (DMI’s), associated workbooks, and a data manager that could be
used to support the PBS. The workbooks and data manager were adopted from the Milk Basin Study.
The following modifications were made to the model and rules:
1. Added data object slots and initialization rules for all slots of previous initialization DMI. This was
necessary to accommodate difference between historic (1940 through 2009) and climate change
(1951 through 1998) periods. This also removed the need for an initialization DMI.
2. Modified return flow lagging initialization from routed returns after the starting timestep to
unrouted flows before the starting timestep, then created an initialization rule for original return
flow lagging initialization. This corrected an error in the original setup which produced incorrect
routed return flows during first year and warning messages.
3. Changed CID water user object and supply rule to enable use of evapotranspiration as an input.
This consisted of setting up the water user object to compute depletion requested from
evapotranspiration rate and area and to compute diversion requested from depletion requested
and efficiency. The water supply rule was changed to populate the “Incoming Available Water”
slot after unlinking it from Avalon Reservoir.
4. Changed UpperFSID and LowerFSID supply rules to populate the “Incoming Available Water”
slots instead of the “Diversion Requested” slots because the computed “Diversion Requested”
caused a conflict with the original rule setup under some climate change scenarios.
5. Created six DMI’s to import climate change or historic irrigation requirements, evaporation, and
hydrology. A separate DMI exist for each parameter and data source to facilitate data
management by the manager.
6. Created DMI “Standard Output” to post a standard set up of output for each model run.
7. Created a manager (workbook PecosRiverWareManager.xlsm discussed in next section) that
sets up batch operation of RiverWare model using historic data, Maurer observed or one HDe
trace, or all HDe traces.
18
Applications
Data for the PBS were developed using several applications. The applications can be categorized as
generalized and specialized where the generalized applications were developed to support similar studies
west-wide and the specialized applications were developed specifically for the Pecos Basin. The
generalized applications consist of VIC, the Penman Monteith model and data manager written using
Excel Visual Basic For Applications (VBA). The specialized applications consist of scripts and VBA data
managers.
The Hargreaves Samani and Penman Monteith models and documentation are available from:
ftp://ftp.usbr.gov/tsc/jrieker/utilities/HargraevesSamani/hs4.0Install.zip
ftp://ftp.usbr.gov/tsc/jrieker/utilities/PenmanMonteith/pm4.0Install.zip
The generalized data managers used to support the PBS include NetCDFBCSDManager.xlsm,
ClimateChangeAdjustmentsManager.xlsm (HDe Met data manager),
ClimateChangeHDeFlowsManager.xlsm, HargraevesSamaniManager.xlsm, and
PenmanMonteithManager.xlsm. Pecos versions of each of these were created. The source applications
and documentation (ClimateChangeDataManagers.docx) are available at:
ftp://ftp.usbr.gov/tsc/jrieker/utilities/climatechange/
Specialized applications are PecosRiverWareManager.xlsm, PecosCCHydrologyManager.xlsm,
PecosEvapHSRefETManager.xlsm and PecosEvapHSEvaorationManager.xlsm. The
PecosRiverWAreManager.xlsm is used to manage RiverWare historic and climate change data and
model runs. The Pecos CCHydrologyManager.xlsm is used to compute HDe daily flows from HDe
monthly flows. The Pecos EvapHSRefETManager.xlsm is used to compute the historic reference ET that
was used to develop evaporation to reference ET regressions. The
PeocsEvapHSEvaporationManager.xlsm is used to compute evaporation as a function of reference ET
for Maurer observed and HDe traces. Instructions for these applications exist within the applications.
The applications are available upon request.
List of Acronyms
BCSD – Bias Corrected Spatially Downscaled.
CC – Climate Change.
CDF - Cumulative density function.
DMI - Data management interface.
ET – Evapotranspiration.
HS – Hargraeves-Samani ET Model.
HDe – Hybrid Delta Ensemble.
MRGCD – Middle Pecos Conservancy District.
PM – Penman Monteith ET Model.
PBS - Pecos Impacts Assessment.
PBRM – Upper Pecos Simulation Model.
PBRM – Upper Pecos Water Operation Model.
RiverWare – River and reservoir modeling system used to develop operation models.
VIC - Variable Infiltration Capacity.
WaterSmart – Sustain and Manage America’s Resources For Tomorrow.
WWCRA – West-wide Climate Risk Assessment.
19
20