# Presentation: 911639

## Turkey Creek Critical Zone ObservatoryProposal

- NSF rfp for two watershed scale observatories to examine role of earth surface zone (top of plant canopy to basement rock) on water, chemicals, and living material.

**Notes:**
NSF has issued an RFP for critical zone observatories. The sources in the NSF RFP define this zone as layer of earth from top of vegetation to unweathered rock.  Do we want to have a Turkey creek proposal.

## Hypothesis

- The phenol-oxidase “latch” mechanism (Freeman et al. 2001) hypothesized that when the active layer of soil becomes saturated to the point where is oxygen availability is limiting, the activity of the microbial exoenzyme phenol oxidase, which degrades soluble phenolics released during lignin decomposition, is inhibited. Consequently, the soluble phenolics in the soil solution will be accumulated and inhibit the activities of hydrolytic enzymes associated with organic matter breakdown (i.e., the inhibition of decomposition)
- “Latch” is only important if soil saturation, O2 depletion, and phenolic build up are common on a watershed in both space and time.

**Notes:**
Freeman suggests this latch holds soil carbon. If it is released there is a cascade of CO2 and DOC release is begun. Serious problem as it is a positive feed back in global CO2.  Wetland forested areas are CO2 sinks due to this latch. Know that latch works in lab but how important is it in environment.

## How does this look on a real world 3d model of topography?

- The most important aspect of wetland forested watersheds is the relation of the
- land surface to the equilibrium slope of the water table.  When P>ET the excess
- must move laterally by subsurface flow.  The slope of the water table is an
- equilibrium of P-ET and the Hydraulic Conductivity of the aquifer.  In the
- LOW COUNTRY that slope exceeds the land slope.  So saturation not only
- occurs near the stream but also near the watershed divide.  Therefore, soil
- saturation, O2 depletion and phonolic oxidase “latch” could be important and
- active across the watershed.
- How does that influence “latch” and DOC transport?

**Notes:**
Wetland forested watersheds are unique in that water table slope is greater than land slope and saturation occurs far from streams.  How do these watersheds function in real 3d world.  How does this influence the latch and DOC transport?

## MIKE SHE is an advanced integrated hydrological modeling system. It simulates water flow in the entire land based phase of the hydrological cycle from rainfall to river flow, via various flow processes such as, overland flow, infiltration into soils, evapotranspiration from vegetation, and groundwater flow.

**Notes:**
We propose a linked MIKE-SHE Forest DNDC model 

## MIKE -SHE

- Produces a 3d grid of predicted water movements which is placed on the watershed.  Each grid cell has individual water balance and predicted degree of saturation. Provides input to------------

**Notes:**
MIKE_SHE predicts a 3d water movement and water balance. Allowing modeling of saturation in time and space. It feeds hydrology data to 

**Notes:**
Forest DNDC model which models both latch and other decomposition dynamics.  Allowing an estimate of NO-N2O-NO3, DOC, Fe, Mn, CH4, H2O as dissolved or gaseous output.  

## Forest - DNDC

- Bioegeochemical model that uses the environment to predict C decomposition includes not only “latch” and O2 but other electron acceptor pathways; denitirfication, Fe, Mn reduction, methanogenesis

## Methods 

- Watershed scale: Turkey creek 5000 hectares.  Weather stations , Eddy Flux towers.  Runoff quantity, geochemical- isotope ratio water source tracing
- Sub-watershed scale: 2x2 factorial of watershed incision 10m vs < 4m and soil texture clay loam to clay vs sandy to sandy clay loam.

## Slide 9

## South Carolina Coastal Plain soils characterized by drainage and subsurface material

| 
Drainage | Sand  | Sandy Loam | Sandy Clay Loam >40”  | Sandy Clay Loam 20-40”  | Sandy Clay Loam <20” | Silt Loams | Sandy Clay   
Clay loam  | Clay |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| excessively | Foxworth    Kershaw
Lakeland     Fripp          Crevasse      Kureb
Newhan       Candor
Cainhoy       Alpin
Rminii | Eustis |  |  |  |  |  |  |
| somewhat
excessively  | Wakulla     Alga
Tarboro |  | Pocalla
 Troup |  |  |  |  |  |
| well  | Wando | Conetoe
Autryville
Kennansville
Foreston
Blanton | Brogden
Eddings 
Fuquay | Suffolk      Hockley 
Ailey         Blaney
Lucy
Wagram | Naboco     Cowarts
Norfolk     Orangeburg
Dothan       Kalamia
Red bay      Cahaba
Altavista     Wickham
Poindexter   Vaucluse
Barnwell | Riverview   Nason
Congaree   
Badin
Georgeville
Hiwassee | Emporia    Caroline
Faceville   Greenville
Marlboro   Kinston
Nankin       Neeses
Sunsweet    Varina | Summerton
Clayham |
| moderately
 well  | Chipley      Seabrook
Centenary
Echaw     Pactocluus | Barth  Tomahawk
Nansemond
Olanta       Bertie
Charleston |  | Bonneau
Chisolm
Coosaw | Goldsboro    Onslow
Clarendon   Yauhannah
Eunola         Johns | Chenneby 
Craven | Angie   Pelion
Exum    Gilead
Duplin  Izagora
Hornsville | Nemours
Persanti   
Wicksburg 
Eulonia |
| somewhat poorly   | Scranton
Kiawah
Witherbee
Sewee | Stallings | Albany
Mirand 
Ocilla 
Edisto | Seagate | Ardilla
Lynchburg
Yemassee
Quitman | Chewacla Jedburg
Tawcaw | Augusta  Uchee
Dunbar
Wahee
Nahunta | Lenoir
Oketee
Smithboro |
| poorly | Osier
Ridgland
Leon
Baratari
St. John’s | Bibb
Elloree
Woodington Plummer |  | Grifton
Pelham
Williman | Rains         Wehadkee
Tomotley   Wadmalaw
Ogeechee    Younges 
Mouzon      Lumbee  | Myatt 
Leaf | Coxville
Gourdin | Bladen     Argent
Meggett    Grady
Cantey     Chastain
Bethera     Rembert
McColl |
| very poorly | Rutledge LynnHaven
Rosedu Dawhoo
Pickney
Torhuunta | Pocomoke
Johnston
Paxville
Stono |  | Nakina 
Portsmouth | Pantego
Deloss
Hobcaw | Hyde | Santee | Cape Fear   Bayboro
Brookman   Byars    
Levy (m)  Capers (m)
Bohicket (m)
Hansboro (m) |
| very poorly
mucks | Hobbony   Dorovan
Pamlico
Ponzer
Pungo |  |  |  |  |  |  |  |

## Clay in river valleys, deltas, lagoons.

- Old beaches are sand,
- Sandy clay loam, old marshes
- Very little Silt, only in valleys, only above Talbot Terrace
- Organic, younger marshes

## Qimby Creek

- Turkey Creek

**Notes:**
Close up showing the Wicomico terrace with well drained sandy loam, Penholway with sandy scarp clayey sediments as water continues to fall. Talbot scarp with sandy soil, even excessively well drained dunes.  Talbot marsh sediments now sandy caly loam soils. Cooper river dissecting all the way to the Wicomico terrace, East cooper into Penholway and Talbot.  These dissected valleys are filled with marsh sediment with later stands of sea level.

**Notes:**
Second look to NW  to show flat land near Talbot scarp.   Note the ability of new technology to represent geomorphology and soils with elevation. The ability to  visualize data is an important aspect of communication the complexity of the critical zone. Dr. Bo Song ( specializing in visualization techniques)  is interested in this proposal although she was unable to attend our meeting 

## Sub - watershed

- Four sub watersheds labeled A ,B ,C,D
- A,B dissected 10 m total relief
- C,D flat above erosion <4m relief
- A,D heavy subsoil
- B,C sandy subsoil
- Each sub-watershed sampled like large watershed.
- Eddy flux tower moved during study to different areas

## Within watershed

- Transect of topography high-low-high
- Deep piezometer, multiple shallow piezometers, water table wells
- Within soil and groundwater DOC analysis, phenloic oxidase, other “inhibited” oxidases, phenolic compounds.
- Grids of rusty rods to calibrate and test WT predictions.
- Geo-statistical planning of locations to maximize information.

## Strengths

- Unique but common hydrology, no other CZO has land slope less that WT.
- Good mix of young, mid career, and senior scientists with expertise needed to test hypothesis.
- Clear hypothesis and simple tests.
- Hydrology, geochemistry, useful for many other hypotheses.

## WeaknessesWhere is the watershed

## Where is the watershed

**Notes:**
DEM done QUAD by QUAD not edge matched SHulerville is flat with numerous numerical artifacts from rasterization. The land does not have 300m wide 1 deep straight east west furrows.  If you let the GIS wander along these numerical hills you may not get a very good watershed. Similarly if you follow the AP road you may get screwed by a culvert you missed.  LIDAR is badly needed. 

## Equifinality

- Mike She ≈10-15 unknown parameters
- Forest DNDC ≈ 20 unknown parameters
- 5000 hectare = 5x106 10x10m grid cells
-                       = 5 x 108 m2 grid cells
-                       = 1-1.5 x 1010 unknown parameters
- If we measure 1 million data points we still have 10,000 correct parameter sets. To fit a parameter set with 99% confidence it would require in the neighborhood of 1.5 quadrillion data points.
- How large a grid cell does one well represent?
- We can get pretty good model fits without knowing where the watershed boundary is.

**Notes:**
A few thoughts about limitation of modeling.  And groundwater hydrology