Critical Zone Observatory - University of Arizona

The Jemez River Basin (NM) &
Santa Catalina Mountains (AZ)
Critical Zone Observatory
(JRB‐SCM CZO)
Principal Investigators (all at University of Arizona):
Jon Chorover (SWES) – Soil Biogeochemistry* †
Peter Troch (HWR) Catchment Hydrology* †
Peter Troch (HWR) – Catchment Hydrology* †
Paul Brooks (HWR) – Catchment Biogeochemistry †
Jon Pelletier (GEOS) – Geomorphology †
Craig Rasmussen (SWES) – Pedology †
g gy
David Breshears (SNRE) – Terrestrial Ecology
Travis Huxman (EEB/B2) – Physiological Ecology
Kathleen Lohse (SNRE) – Soil and Watershed Biogeochemistry
Shirley (Kurc) Papuga (SNRE) – Ecohydrology
Jennifer McIntosh (HWR) – Aqueous Geochemistry
Thomas Meixner (HWR) – Catchment Hydrochemistry
Marcel Schaap (SWES) – Soil Physics
*Lead PIs
† Executive Committee

What is the Critical Zone?
The external terrestrial terrestrial layer extending from the outer limits
of vegetation to the lower boundary of groundwater,
inclusive of all liquid, gas, mineral and biotic components.
Brantley et al., 2007
As defined by
the National
Research
Council in the
“BROES” BROES
Report (2001).
CZ = f hydrologic
geochemical
geomorphic
pedologic
ecologic

NSF 06‐588: Critical Zone Observatories
(CZO)
• “Processes occurring g at and near the Earth’s surface f do not
operate independently, but the extent to which they are
coupled, and at what temporal and spatial scales, remains
largely g yunknown.”
• Need for natural laboratories, where terrestrial processes
and systems can be studied through detailed field
observations and in situ measurements.
• Techniques from several disciplines must be coordinated
to collect data sets that are spatially dense and
temporally extended extended.
• Address the integration and coupling of earth surface
processes as mediated by the presence and flux of fresh
water.

Transformative Behavior of Energy, Water and Carbon in
the Critical Zone:
An Observatory to Quantify Linkages among
Ecohydrology, Biogeochemistry, and Landscape Evolution
• Builds ld on success of f the h SA SAHRA A ecohydrological
h d l l
observatory (JRB) and seed‐funded CZ research (SCM).
• Collaborators from LANL, NCAR, VCNP, NMT, ASU,
UCSD UCSD, UCLA, UCLA INRS, INRS NAU NAU, CU, CU UIUC
• The CZO is organized around broad climate‐water
questions relevant to arid and semi‐arid systems that
require i an iintegrated, t t d multi‐disciplinary lti di i li approachh
– How does variability in energy input and related mass flux
influence CZ structure and function?
– How do feedbacks between landscape evolution and the cycling of
water and carbon alter short‐ and long‐term CZ development?
• Project duration 9/1/09 – 8/31/14

JRB-SCM CZO research integrates
four cross-cutting g science themes
(each linked by CZ process coupling and mass transfers)
Hillslope water flux
Mass transport
Erosion
Ecohydrology/
Hydrologic Partitioning
(EHP)
Landscape Water Org Litho
Evolution
(LSE)
CZ evolution,
transmissivity/
Water, Org, Litho
Pools and Fluxes
storage g
Subsurface
Biogeochemistry
(SSB)
Evapotranspiration
Water transit time
Soil storage
Surface
W Water
Dynamics
(SWD)
Solute, DOM, H + , e- flux
Flow Paths
Soil/Rock Weathering Rx.

Jemez River Basin (NM) and Santa Catalina Mountains (AZ)

Santa Catalina Mountains (SCM)
Valles Caldera (JRB)

Conceptual Model of the CZ:
Open, non-equilibrium, dissipative system
EEnvironmental i t l E Energy and d Mass M TTransfer f (EEMT)
EEMT
=
E
NPP
Energy Source
Solar Radiation
Mass Mass, Momentum
Momentum,
and Heat
+ E
PPT
+
∑ E
i
i
ENPP = NPP⋅Ebio E =ΔT⋅c ⋅P
∑
Critical Zone
PPT w eff
E
EEMT
We postulate that
critical zone structure
EEM
Catchment
and Chemical C e ca function Energy e gy follow
Structural organization
(e.g., carbon and water)
• Vegetation structure
trends in EEMT. • Soil catena
Gravitational Energy
• Drainage networks
(e.g., sediment and water)
• Topography
i
:
additional energy/mass fluxes
Energy Sink
Products passed
external of Critical
Zone
Climatic forcing is in a single energy term with units kJ m -2 s -1

Jemez River Basin (JRB) Elevation Gradient
MAT: 11 to 3 °C
MAP: 0.4 to 0.8 m y-1 : 0.4 to 0.8 y

Santa Catalina Mountains (SCM) Elevation Gradient
MAT: 18 to 11 °C
MAP: 0.4 to 0.8 m y-1 4 y
Soil MRT = 10-20 ky
Parallel lithologies
Granite and Schist
Upper Sonoran
Pinyon-Juniper
Woodland-Grassland
White Fir-
P. Pine
Ponderosa Pine
Parallel lithology
Granite and Schist
Elev. (1000 m)
2.6
23 2.3
2.0
1.7
14 1.4
1.1
0.8

Research Approach: Model Measure
• Critical Zone Modeling
– Empirical (Energy/Climate Based, EEMT)
– Process coupled (hydrology‐biogeochemistry‐geomorphology)
• Synoptic sampling l along l EE EEMT gradients d at bboth h JRB
and SCM
– Vegetation (ANPP, community structure/composition)
– Soil (morphology, mineralogy, chemistry, microbiology, SOM)
– Bedrock (morphology, mineralogy, chemistry)
– Surface water (element/isotope p chemistry, y DCOM)
• Installation of nested hillslope and catchment
observatory instrumentation
– Eddy flux towers
– Soil solution samplers (spatially‐distributed chemistry, isotopes
at sub‐catchment scale)
– Soil oi moisture, oi u e, water ae po potential e ia aand temperature e pe a u epo probes e
– Flumes and ISCO samplers

Field site
instrumentation follows a
nested catchment
approach:
Rain, , stream, , temperature p
gages, snow lysimeters
Soil moisture, temperature,
and solution samplers
Eddy Flux towers
Emphasis on hillslope-scale
Emphasis on hillslope scale
process coupling

EHP
Aspect controls water TTD
Hypothesis: MTT
increases from southern to
northern aspect due to
increasing water availability
(E PPT), which leads to
development of deeper soils,
larger storage, longer water
residence time.
Broxton et al. (2009)

LSE
Regolith/soil thickness can be
modeled using sparse calibration data, LiDAR
ddata, t and d an EEMT model d l f for weathering. th i
Tested in the SCM site (Pelletier and Rasmussen,
WRR 2009).

LSE EHP
Pelletier and Rasmussen (in rev.)
Kostrzewskietal,
Brooks,
Meixner et al.
How does soil
production affect
catchment h water
transit time?
Broxton, Troch et al. (2009)
H How does d variability i bili
in catchment water
transit time influence
hydrochemical
response?
SWD

LLa JJara
EHP
USGS
Redondo
1983
Redondo
UA 2005
SWD
Kostrzewskietal, Brooks,
Meixner et al. (2009)
How do catchment
wetting dynamics
influence redox
processes in soil?
How do soil pore- pore
scale redox
processes affect
catchment
carbon b release? l ?
SSB
Thompson, Chorover, et al. (2007)

Development of
coupled process
model
EHP SWD
LSE SSB

EHP
Evapotranspiration,
primary production,
water transit time
LSE
DDenudation, d ti
pedogenesis,
structural
organization g
SWD
SSB
Weathering,
rootmicrobeorganicmetalinteractions
Catchment
hydrochemical
response, end
member mixing

0 25 50 100 Meters 0 125 250 500Meters
0 25 50 100Meters
meters
GC4 GC
EHP
GC1
GC2
GC3
GC5
GRANITE
SCHIST
N
SC4
SC1
SC2
SC3
SC5

LSE
Valley density (channel per unit
area) ) can be related to a balance between soil
production on hillslopes (a function of climate
and rock type) and incision in channels.
Testing in SCM (Pelletier and Rasmussen, JGRF).

Evolving
Integrated Conceptual
Modeling of Watershed Model
Coupled Time and space p
Processes
Combine
hydrologic‐
hydrologic
pedologic‐
geomorphic‐
theory at the
hillslope scale to
link process
measurements t and d
interpret/guide
distributed
observations
b
distribution of EEMT
drives CZ processing
of f energy, gy, water and
carbon.
Field Activities
Coordinated,
interdisciplinary,
process‐based b d
measurements &
experimentation
among cross‐cutting
science themes
Hypothesis‐
Driven
EExperimental e i e tal
Design
Instrumented
hillslopes nested
in subcatchments
as f(elevation) f( ) to
capture variation
in EEMT and to
identify
biogeophysical
controls

Geology Soils
Topography Vegetation
VCNP
GIS