Data Package Metadata View Summary

Data for Lake Mendota Phosphorus Cycling Model

General Information

Data Package:
Local Identifier:	edi.141.2
Title:	Data for Lake Mendota Phosphorus Cycling Model
Alternate Identifier:	DOI PLACE HOLDER
Abstract:	There is an opportunity to advance both prediction accuracy and scientific discovery for phosphorus cycling in Lake Mendota (Wisconsin, USA). Twenty years of phosphorus measurements show patterns at seasonal to decadal scales, suggesting a variety of drivers control lake phosphorus dynamics. Our objectives are to produce a phosphorus budget for Lake Mendota and to accurately predict summertime epilimnetic phosphorus using a simple and adaptable modeling approach. We combined ecological knowledge with machine learning in the emerging paradigm, theory-guided data science (TGDS). A mass balance model (PROCESS) accounted for most of the observed pattern in lake phosphorus. However, inclusion of machine learning (RNN) and an ecological principle (PGRNN) to constrain its output improved summertime phosphorus predictions and accounted for long term changes missed by the mass balance model. TGDS indicated additional processes related to water temperature, thermal stratification, and long term changes in external loads are needed to improve our mass balance modeling approach.
Publication Date:	2019-02-28

Time Period

Begin:

1995-05-09

End:

2015-12-31

People and Organizations
Contact:	Hanson, Paul C (University of Wisconsin-Madison, Center for Limnology) [ email ]
Creator:	Hanson, Paul C (University of Wisconsin-Madison, Center for Limnology)
Creator:	Stillman, Aviah B (University of Wisconsin-Madison, Center for Limnology)

Data Entities
Data Table Name:	Lake Mendota chemical properties through time
Description:	Lake Mendota chemical properties through time
Data Table Name:	Lake water surface levels through time
Description:	Lake water surface levels through time
Data Table Name:	Chemical and physical properties of Pheasant Branch inflow through time
Description:	Chemical and physical properties of Pheasant Branch inflow through time
Data Table Name:	Chemical and physical properties of Yahara River inflow through time
Description:	Chemical and physical properties of Yahara River inflow through time
Data Table Name:	Thermocline depth, epilimnetic temperature, and hypolimnetic temperature for Lake Mendota through time
Description:	Thermocline depth, epilimnetic temperature, and hypolimnetic temperature for Lake Mendota through time
Data Table Name:	Atmospheric data for Madison through time
Description:	Atmospheric data for Madison through time
Data Table Name:	Hypsometry factors for various lakes
Description:	Hypsometry factors for various lakes
Data Table Name:	Driving data for PROCESS
Description:	Driving data for PROCESS
Data Table Name:	The observed epilimnetic phosphorus and the corresponding modeled output for epilimnetic phosphorus from PROCESS
Description:	The observed epilimnetic phosphorus and the corresponding modeled output for epilimnetic phosphorus from PROCESS
Data Table Name:	The observed hypolimnetic phosphorus and the corresponding modeled output for hypolimnetic phosphorus from PROCESS
Description:	The observed hypolimnetic phosphorus and the corresponding modeled output for hypolimnetic phosphorus from PROCESS
Data Table Name:	The PROCESS model outputs for epilimnetic phosphorus and hypolimnetic phosphorus at the daily time scale
Description:	The PROCESS model outputs for epilimnetic phosphorus and hypolimnetic phosphorus at the daily time scale
Data Table Name:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 1
Description:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 1
Data Table Name:	Modeled outputs of lake phosphorus from PGRNN when the ecological principal loss function was not included
Description:	Modeled outputs of lake phosphorus from PGRNN when the ecological principal loss function was not included
Data Table Name:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 2
Description:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 2
Data Table Name:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 3
Description:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 3
Data Table Name:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 4
Description:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 4
Data Table Name:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 5
Description:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 5
Data Table Name:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 6
Description:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 6
Data Table Name:	Modeled outputs of lake phosphorus from RNN when validated on segment 1
Description:	Modeled outputs of lake phosphorus from RNN when validated on segment 1
Data Table Name:	Modeled outputs of lake phosphorus from RNN when validated on segment 2
Description:	Modeled outputs of lake phosphorus from RNN when validated on segment 2
Data Table Name:	Modeled outputs of lake phosphorus from RNN when validated on segment 3
Description:	Modeled outputs of lake phosphorus from RNN when validated on segment 3
Data Table Name:	Modeled outputs of lake phosphorus from RNN when validated on segment 4
Description:	Modeled outputs of lake phosphorus from RNN when validated on segment 4
Data Table Name:	Modeled outputs of lake phosphorus from RNN when validated on segment 5
Description:	Modeled outputs of lake phosphorus from RNN when validated on segment 5
Data Table Name:	Modeled outputs of lake phosphorus from RNN when validated on segment 6
Description:	Modeled outputs of lake phosphorus from RNN when validated on segment 6

Detailed Metadata

Data Entities

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/f417d5bc6975fefea10bdc76fc4a44ea
Name:	Lake Mendota chemical properties through time
Description:	Lake Mendota chemical properties through time
Number of Records:	9443
Number of Columns:	9

Table Structure

Object Name:

chemphys.csv

Size:

293193 byte

Authentication:

721cc6c72292480b731a0bb07bbb4aa8 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

\r\n

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

lakeid

year4

daynum

sampledate

depth

totpf

totpuf

totpuf_sloh

drp_sloh

Definition:

Lake identification

Year the sample was taken

Day of year

Day the sample was taken

Depth at which the sample was taken

Total dissolved phosphorus or a filtered sample

Total phosphorus unfiltered

Total phosphorus unfiltered from WI State Laboratory of Hygiene

Dissolved reactive phosphorus from WI State Laboratory of Hygiene

Storage Type:

string

date

float

date

float

Measurement Type:

nominal

dateTime

ratio

dateTime

ratio

Measurement Values Domain:

Definition

Lake identification

Format	YYYY
Precision

Unit	number
Type	natural
Min	3
Max	340

Format	MM/DD/YYYY
Precision

Unit	meter
Type	real
Min	0
Max	25.2

Unit	microgramsPerLiter
Type	real
Min	0
Max	521

Unit	microgramsPerLiter
Type	real
Min	0
Max	600

Unit	milligramsPerLiter
Type	real
Min	0.01
Max	1.52

Unit	milligramsPerLiter
Type	real
Min	0
Max	1.65

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/08dda6201227efa32362e7e8908eaaee
Name:	Lake water surface levels through time
Description:	Lake water surface levels through time
Number of Records:	8396
Number of Columns:	5

Table Structure

Object Name:

LakeLevel.csv

Size:

304976 byte

Authentication:

75f33f299568a0cd394eac14aa4112c4 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

Date

Lake_Kegonsa

Lake_Mendota

Lake_Monona

Lake_Waubesa

Definition:

Date the sample was taken

Lake elevation of Lake Kegonsa

Lake elevation of Lake Mendota

Lake elevation of Lake Monona

Lake elevation of Lake Waubesa

Storage Type:

date

float

Measurement Type:

dateTime

ratio

Measurement Values Domain:

Format	MM/DD/YYYY
Precision

Unit	foot
Type	real
Min	842.04
Max	851.41

Unit	foot
Type	real
Min	842.94
Max	1021

Unit	foot
Type	real
Min	842.49
Max	1337

Unit	foot
Type	real
Min	838.6
Max	1279

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/5fb78deb53e1c1fc63d4f7ce2bb1ef4c
Name:	Chemical and physical properties of Pheasant Branch inflow through time
Description:	Chemical and physical properties of Pheasant Branch inflow through time
Number of Records:	13513
Number of Columns:	15

Table Structure

Object Name:

Mendota_pheasant_branch_30year2xP.csv

Size:

1621674 byte

Authentication:

4227f94534b60c687146bbcdbe97e3a2 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

\r\n

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

time

FLOW

SALT

TEMP

PHS_frp

PHS_frp_ads

OGM_dop

OGM_pop

OGM_don

NIT_amm

NIT_nit

OGM_docr

CAR_dic

CAR_pH

SIL_rsi

Definition:

Date the sample was taken

Stream flow

Stream salinity

Water temperature

Filterable reactive phosphorus concentration

Filtered reactive phosphorus, absorbed

Dissolved organic phosphorus

Particulate organic phosphorus

Dissolved organic nitrogen concentration

Ammonium concentration

Nitrate concentration

Recalcitrant dissolved organic carbon concentration

Dissolved inorganic carbon concentration

Soluble reactive silica

Storage Type:

date

float

Measurement Type:

dateTime

ratio

Measurement Values Domain:

Format	YYYY-MM-DD
Precision

Unit	cubicMetersPerSecond
Type	real
Min	0
Max	15.58

Unit	milligramsPerLiter
Type	whole
Min	0
Max	0

Unit	celsius
Type	real
Min	0.51
Max	23.91

Unit	millimolesPerMeterCubed
Type	real
Min	0.24
Max	8.23

Unit	millimolesPerMeterCubed
Type	real
Min	0.79
Max	27.31

Unit	millimolesPerMeterCubed
Type	real
Min	0.31
Max	10.65

Unit	millimolesPerMeterCubed
Type	real
Min	0.24
Max	8.43

Unit	millimolesPerMeterCubed
Type	real
Min	2.01
Max	57.19

Unit	millimolesPerMeterCubed
Type	real
Min	30.22
Max	193.24

Unit	millimolesPerMeterCubed
Type	real
Min	20.14
Max	571.85

Unit	millimolesPerMeterCubed
Type	real
Min	583.33
Max	583.33

Unit	millimolesPerMeterCubed
Type	natural
Min	5000
Max	5000

Unit	dimensionless
Type	real
Min	7.7
Max	7.7

Unit	millimolesPerMeterCubed
Type	natural
Min	190
Max	190

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/2e4baf1ecca69ca29bc1f48c1663cf1c
Name:	Chemical and physical properties of Yahara River inflow through time
Description:	Chemical and physical properties of Yahara River inflow through time
Number of Records:	13513
Number of Columns:	15

Table Structure

Object Name:

Mendota_yahara_30year2xP.csv

Size:

1637274 byte

Authentication:

f135a93b25a201d060da3d4b3dac14e3 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

\r\n

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

time

FLOW

SALT

TEMP

PHS_frp

PHS_frp_ads

OGM_dop

OGM_pop

OGM_don

NIT_amm

NIT_nit

OGM_docr

CAR_dic

CAR_pH

SIL_rsi

Definition:

Date the sample was taken

Stream flow

Stream salinity

Water temperature

Filterable reactive phosphorus concentration

Filtered reactive phosphorus, absorbed

Dissolved organic phosphorus

Particulate organic phosphorus

Dissolved organic nitrogen concentration

Ammonium concentration

Nitrate concentration

Recalcitrant dissolved organic carbon concentration

Dissolved inorganic carbon concentration

Soluble reactive silica

Storage Type:

date

float

Measurement Type:

dateTime

ratio

Measurement Values Domain:

Format	YYYY-MM-DD
Precision

Unit	cubicMetersPerSecond
Type	real
Min	0.11
Max	88.07

Unit	milligramsPerLiter
Type	whole
Min	0
Max	0

Unit	celsius
Type	real
Min	-1.39
Max	29.1

Unit	millimolesPerMeterCubed
Type	real
Min	0.44
Max	4.47

Unit	millimolesPerMeterCubed
Type	real
Min	0.93
Max	9.51

Unit	millimolesPerMeterCubed
Type	real
Min	0.36
Max	3.71

Unit	millimolesPerMeterCubed
Type	real
Min	0.13
Max	1.33

Unit	millimolesPerMeterCubed
Type	real
Min	16.23
Max	404.02

Unit	millimolesPerMeterCubed
Type	real
Min	0.31
Max	719.83

Unit	millimolesPerMeterCubed
Type	real
Min	162.34
Max	4040.17

Unit	millimolesPerMeterCubed
Type	real
Min	583.33
Max	583.33

Unit	millimolesPerMeterCubed
Type	natural
Min	5000
Max	5000

Unit	dimensionless
Type	real
Min	7.7
Max	7.7

Unit	millimolesPerMeterCubed
Type	natural
Min	190
Max	190

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/f2e56a9f305b9cc590a9592b44a61094
Name:	Thermocline depth, epilimnetic temperature, and hypolimnetic temperature for Lake Mendota through time
Description:	Thermocline depth, epilimnetic temperature, and hypolimnetic temperature for Lake Mendota through time
Number of Records:	7542
Number of Columns:	4

Table Structure

Object Name:

Modeled_thermocline_daily.csv

Size:

425385 byte

Authentication:

11ac79a9c0cb30d9d7c53d51480fcf92 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

datetime

thermo_depth

EpiTemp

HypoTemp

Definition:

Date the sample was taken

Depth to the thermocline from the surface of the lake

Water temperature in the epilimnion

Water temperature in the hypolimnion

Storage Type:

date

float

Measurement Type:

dateTime

ratio

Measurement Values Domain:

Format	YYYY-MM-DD
Precision

Unit	meter
Type	real
Min	0.67
Max	22.04

Unit	celsius
Type	real
Min	0.07
Max	30.35

Unit	celsius
Type	real
Min	0.09
Max	13.92

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/99f3d1c88464f1cdee86bbfdb6612a28
Name:	Atmospheric data for Madison through time
Description:	Atmospheric data for Madison through time
Number of Records:	7856
Number of Columns:	5

Table Structure

Object Name:

NLDAS_daily.csv

Size:

605195 byte

Authentication:

3d47e09273004faeb654315ed7368870 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

day

AirTemp_C

ShortWave_W_m2

Rain_m

WindSpeed_m_s

Definition:

Date the sample was taken

Air temperature

Shortwave radiation

Precipitation

Windspeed

Storage Type:

date

float

Measurement Type:

dateTime

ratio

Measurement Values Domain:

Format	YYYY-MM-DD
Precision

Unit	celsius
Type	real
Min	-31.95
Max	35.5

Unit	wattPerMeterSquared
Type	real
Min	0
Max	334.89

Unit	meter
Type	real
Min	0
Max	0.12

Unit	metersPerSecond
Type	real
Min	0.83
Max	11.44

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/c7ab02fbaf8529280cfd32fbb20a6600
Name:	Hypsometry factors for various lakes
Description:	Hypsometry factors for various lakes
Number of Records:	306
Number of Columns:	3

Table Structure

Object Name:

ntl301_hypso.csv

Size:

5700 byte

Authentication:

be263c8dc4510bdd04ca6fa2a5406e47 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

\r\n

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

lakeid

depth

hp_factor

Definition:

Lake identification

Depth below the lake surface

Hypsometry factor (volume percent for that layer)

Storage Type:

string

float

Measurement Type:

nominal

ratio

Measurement Values Domain:

Allowed Values and Definitions

Enumerated Domain

Code Definition

Code	AL
Definition	Allequash Lake
Source

Code Definition

Code	BM
Definition	Big Muskellunge Lake
Source

Code Definition

Code	CB
Definition	Bog 27-2 (Crystal Bog)
Source

Code Definition

Code	CR
Definition	Crystal Lake
Source

Code Definition

Code	LRN
Definition	Unknown
Source

Code Definition

Code	LRS
Definition	Unknown
Source

Code Definition

Code	SP
Definition	Sparkling Lake
Source

Code Definition

Code	TB
Definition	Bog 12-15 (Trout Bog)
Source

Code Definition

Code	TR
Definition	Trout Lake
Source

Code Definition

Code	ME
Definition	Lake Mendota
Source

Code Definition

Code	MO
Definition	Lake Monona
Source

Code Definition

Code	L1
Definition	Unknown
Source

Code Definition

Code	L2
Definition	Unknown
Source

Unit	meter
Type	real
Min	0
Max	35.7

Unit	dimensionless
Type	real
Min	0
Max	0.54

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/61b0a871e7311027fd623766455b1854
Name:	Driving data for PROCESS
Description:	Driving data for PROCESS
Number of Records:	7542
Number of Columns:	9

Table Structure

Object Name:

P_Drivers.csv

Size:

814379 byte

Authentication:

613e41c4611aa7cb6d5acc0f91c516ef Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

SampleDate

EpiTemp

HypoTemp

Stratified

Thermocline

EpiVolume

HypoVolume

Discharge

PLoad

Definition:

Date the sample was taken

Water temperature of epilimnion

Water temperature of hypolimnion

Whether the lake was stratified or not on that day

Thermocline depth measured from lake surface

Volume of the epilimnion

Volume of the hypolimnion

Overland flow into the lake

Lake phosphorus load

Storage Type:

date

float

string

float

Measurement Type:

dateTime

ratio

nominal

ratio

Measurement Values Domain:

Format	YYYY-MM-DD
Precision

Unit	celsius
Type	real
Min	0.07
Max	30.35

Unit	celsius
Type	real
Min	0.09
Max	13.92

Allowed Values and Definitions

Enumerated Domain

Code Definition

Code	FALSE
Definition	Not stratified
Source

Code Definition

Code	TRUE
Definition	Stratified
Source

Unit	meter
Type	real
Min	0.67
Max	22.04

Unit	cubicMeter
Type	real
Min	46837162.21
Max	548147842.4

Unit	cubicMeter
Type	real
Min	3364223.6
Max	504674903.79

Unit	cubicMetersPerDay
Type	real
Min	26912.29
Max	15658057.73

Unit	gramsPerSecond
Type	real
Min	0.01
Max	1.96

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/36ab1c3f6ef72402030d5aea6df5ffb0
Name:	The observed epilimnetic phosphorus and the corresponding modeled output for epilimnetic phosphorus from PROCESS
Description:	The observed epilimnetic phosphorus and the corresponding modeled output for epilimnetic phosphorus from PROCESS
Number of Records:	322
Number of Columns:	3

Table Structure

Object Name:

P_EpilimnionP.csv

Size:

11426 byte

Authentication:

c6f544804f3f58d291db3c06df25b9c6 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

SampleDate

obsEpiP

modelEpiP

Definition:

Date the sample was taken

Observational epilimnetic phosphorus concentration

Model predictions for epilimnetic phosphorus concentrations

Storage Type:

date

float

Measurement Type:

dateTime

ratio

Measurement Values Domain:

Format	YYYY-MM-DD
Precision

Unit	gramsPerCubicMeter
Type	real
Min	0.01
Max	0.21

Unit	gramsPerCubicMeter
Type	real
Min	0.01
Max	0.17

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/0770b927f6206bd5f1f5b4e37bbab13b
Name:	The observed hypolimnetic phosphorus and the corresponding modeled output for hypolimnetic phosphorus from PROCESS
Description:	The observed hypolimnetic phosphorus and the corresponding modeled output for hypolimnetic phosphorus from PROCESS
Number of Records:	121
Number of Columns:	3

Table Structure

Object Name:

P_HypolimnionP.csv

Size:

4841 byte

Authentication:

7c3111452e073fbb67af929e1908b09b Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

SampleDate

obsHypoP

modelHypoP

Definition:

Date the sample was taken

Observational hypolimnetic phosphorus concentration

Model predictions for hypolimnetic phosphorus concentrations

Storage Type:

date

float

Measurement Type:

dateTime

ratio

Measurement Values Domain:

Format	YYYY-MM-DD
Precision

Unit	gramsPerCubicMeter
Type	real
Min	0.05
Max	0.47

Unit	gramsPerCubicMeter
Type	real
Min	0.07
Max	0.31

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/c06f1ebc0b6ee62575ff703f82bc3b98
Name:	The PROCESS model outputs for epilimnetic phosphorus and hypolimnetic phosphorus at the daily time scale
Description:	The PROCESS model outputs for epilimnetic phosphorus and hypolimnetic phosphorus at the daily time scale
Number of Records:	7542
Number of Columns:	5

Table Structure

Object Name:

P_ModelOutput.csv

Size:

613395 byte

Authentication:

1a259186e64b488024dfc23be62b94f6 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

SampleDate

EpiP

EpiPConc

HypoP

HypoPConc

Definition:

Time series for model evaluation

Model predictions for epilimnetic phosphorus load

Model predictions for epilimnetic phosphorus concentrations

Model predictions for hypolimnetic phosphorus load

Model predictions for hypolimnetic phosphorus concentrations

Storage Type:

date

float

Measurement Type:

dateTime

ratio

Measurement Values Domain:

Format	YYYY-MM-DD
Precision

Unit	gram
Type	real
Min	1337309.6
Max	69426372.49

Unit	gramsPerCubicMeter
Type	real
Min	0.01
Max	0.17

Unit	gramsPerCubicMeter
Type	real
Min	307489.63
Max	86359584.71

Unit	gramsPerCubicMeter
Type	real
Min	0.07
Max	0.4

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/ea8841e29393eaecef08aff834aaa8aa
Name:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 1
Description:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 1
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

PGRNN_1.csv

Size:

60542 byte

Authentication:

336f22b9a03271350f2a6d8d85b06a3d Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Process-guided recursive neural network model predicted lake phosphorus concentrations when validated on segment 1

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	0.01
Max	0.16

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/55e5abeb63c9e8b1e526ce61b02e9085
Name:	Modeled outputs of lake phosphorus from PGRNN when the ecological principal loss function was not included
Description:	Modeled outputs of lake phosphorus from PGRNN when the ecological principal loss function was not included
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

PGRNN_10.csv

Size:

187200 byte

Authentication:

b7afbcadb083a7cf1ade122761d4d55c Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

\r\n

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Process-guided recursive neural network model predicted lake phosphorus concentrations when ecological principal loss function was not included

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	0.01
Max	0.18

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/d434bcd71abba4515d70b825ed899766
Name:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 2
Description:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 2
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

PGRNN_2.csv

Size:

61180 byte

Authentication:

9b77865a18e8cae203fd1e728e166828 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Process-guided recursive neural network model predicted lake phosphorus concentrations when validated on segment 2

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	0.02
Max	0.16

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/5d24677c007f5655ed53fdb745968673
Name:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 3
Description:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 3
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

PGRNN_3.csv

Size:

60429 byte

Authentication:

4899f440d89e644451adeac7bc4539eb Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Process-guided recursive neural network model predicted lake phosphorus concentrations when validated on segment 3

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	0.03
Max	0.15

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/f03ab050558314ca18ff24ffca990e28
Name:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 4
Description:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 4
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

PGRNN_4.csv

Size:

60413 byte

Authentication:

9722a6353d2dab96e28689e238eacb32 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Process-guided recursive neural network model predicted lake phosphorus concentrations when validated on segment 4

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	0.01
Max	0.16

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/3dede28017188789409374e8fe38c0da
Name:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 5
Description:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 5
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

PGRNN_5.csv

Size:

60402 byte

Authentication:

d9d1ea12e41dfbc11f536d7f534d1d08 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Process-guided recursive neural network model predicted lake phosphorus concentrations when validated on segment 5

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	0.01
Max	0.16

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/98f912d639c4490923f6fd310df6fc68
Name:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 6
Description:	Modeled outputs of lake phosphorus from PGRNN when validated on segment 6
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

PGRNN_6.csv

Size:

60207 byte

Authentication:

6dbfb9534dafbb66fe70f3d13fe4721d Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Process-guided recursive neural network model predicted lake phosphorus concentrations when validated on segment 6

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	0.01
Max	0.15

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/3b6177f2b596f936a66dacb811a647c0
Name:	Modeled outputs of lake phosphorus from RNN when validated on segment 1
Description:	Modeled outputs of lake phosphorus from RNN when validated on segment 1
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

RNN_1.csv

Size:

60322 byte

Authentication:

e19caa484832835a4a0ad07f6d092176 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Recursive neural network model predicted lake phosphorus concentrations when validated on segment 1

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	0.02
Max	0.19

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/588b97ca0669d899ece8969b8f89a743
Name:	Modeled outputs of lake phosphorus from RNN when validated on segment 2
Description:	Modeled outputs of lake phosphorus from RNN when validated on segment 2
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

RNN_2.csv

Size:

60685 byte

Authentication:

828687caad53984aa868f2d7ebf12cc0 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Recursive neural network model predicted lake phosphorus concentrations when validated on segment 2

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	-0.01
Max	0.2

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/6bc95318ca7624b39caaf014449d9bca
Name:	Modeled outputs of lake phosphorus from RNN when validated on segment 3
Description:	Modeled outputs of lake phosphorus from RNN when validated on segment 3
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

RNN_3.csv

Size:

60387 byte

Authentication:

f8552e29905a39ac75163254b9d49541 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Recursive neural network model predicted lake phosphorus concentrations when validated on segment 3

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	-0.01
Max	0.21

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/285dd21f796a191ab18b05afafad7846
Name:	Modeled outputs of lake phosphorus from RNN when validated on segment 4
Description:	Modeled outputs of lake phosphorus from RNN when validated on segment 4
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

RNN_4.csv

Size:

60160 byte

Authentication:

30bfacb30975398ce840c508ed90ef6c Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Recursive neural network model predicted lake phosphorus concentrations when validated on segment 4

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	-0.01
Max	0.19

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/74b0b7dce8424be975edf5cd944cd10f
Name:	Modeled outputs of lake phosphorus from RNN when validated on segment 5
Description:	Modeled outputs of lake phosphorus from RNN when validated on segment 5
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

RNN_5.csv

Size:

60370 byte

Authentication:

ba382c8237f6661ff1b474607a5ea91d Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Recursive neural network model predicted lake phosphorus concentrations when validated on segment 5

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	0
Max	0.18

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/141/2/7a20b1db5c86401d9a583afbc45f4bae
Name:	Modeled outputs of lake phosphorus from RNN when validated on segment 6
Description:	Modeled outputs of lake phosphorus from RNN when validated on segment 6
Number of Records:	7199
Number of Columns:	1

Table Structure

Object Name:

RNN_6.csv

Size:

59818 byte

Authentication:

3c3b25e8a732fd6666db0ec8f7b567ee Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

Orientation:

column

Simple Delimited:

Field Delimiter:

Table Column Descriptions

Column Name:

output

Definition:

Recursive neural network model predicted lake phosphorus concentrations when validated on segment 6

Storage Type:

float

Measurement Type:

ratio

Measurement Values Domain:

Unit	gramsPerCubicMeter
Type	real
Min	0
Max	0.17

Missing Value Code:

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Package Usage Rights

This data package is released to the “public domain” under Creative Commons CC0 1.0 “No Rights Reserved” (see: https://creativecommons.org/publicdomain/zero/1.0/). It is considered professional etiquette to provide attribution of the original work if this data package is shared in whole or by individual components. A generic citation is provided for this data package on the website https://portal.edirepository.org (herein “website”) in the summary metadata page. Communication (and collaboration) with the creators of this data package is recommended to prevent duplicate research or publication. This data package (and its components) is made available “as is” and with no warranty of accuracy or fitness for use. The creators of this data package and the website shall not be liable for any damages resulting from misinterpretation or misuse of the data package or its components. Periodic updates of this data package may be available from the website. Thank you.

Keywords

By Thesaurus:
(No thesaurus)	Lake Mendota, phosphorus, models, modeling, lakes

Methods and Protocols

These methods, instrumentation and/or protocols apply to all data in this dataset:

Methods and protocols used in the collection of this data package

Description:

The analytical approach blends an ecosystem process model (PROCESS) with the machine learning technology, recurrent neural networks (RNN). When combined, they are an implementation of TGDS that we term a process-guided recurrent neural network (PGRNN). PROCESS is a mass-balance model that tracks three different pools of phosphorus (P) within the lake system: epilimnetic P, hypolimnetic P, and sediment P. The RNN maps pattern in the response variable to a suite of driving variables as a "black box" model. PGRNN includes the output of PROCESS as an input to the neural network, unlike RNN, which uses only the observational data as an input. PGRNN weights the PROCESS predictions along with other drivers, allowing for the possibility of adjusting or eliminating PROCESS as a driver. PGRNN also includes the ecological principle of power scaling across the time domain in its loss function to constrain its predictions to ecologically reasonable values. The loss function penalizes PGRNN predictions when daily deviations exceed 80% of the deviations at the ~bi-weekly scale in the observed data and penalizes large discrepancies between the power spectra of the predicted and observed values. We fit all models to epilimnetic P concentration, which was sampled approximately monthly for 20 years. The observed time series was divided into six equal segments. Models were validated with one segment and were fit independently to the other five segments.

People and Organizations

Creators:

Individual:

Paul C Hanson

Organization:

University of Wisconsin-Madison, Center for Limnology

Email Address:

pchanson@wisc.edu

Id:

https://orcid.org/0000-0001-8533-6061

Individual:

Aviah B Stillman

Organization:

University of Wisconsin-Madison, Center for Limnology

Email Address:

aviah.stillman@gmail.com

Contacts:

Individual:

Paul C Hanson

Organization:

University of Wisconsin-Madison, Center for Limnology

Email Address:

pchanson@wisc.edu

Id:

https://orcid.org/0000-0001-8533-6061

Temporal, Geographic and Taxonomic Coverage

Temporal, Geographic and/or Taxonomic information that applies to all data in this dataset:

Time Period

Begin:

1995-05-09

End:

2015-12-31

Project

Parent Project Information:

Title:

CNH-L: Linking Land-Use Decision Making, Water Quality, and Lake Associations to Understand Human-Natural Feedbacks in Lake Catchments

Personnel:

Individual:

Paul Hanson

Email Address:

pchanson@wisc.edu

Id:

https://orcid.org/0000-0001-8533-6061

Role:

Principal Investigator

Funding:

National Science Foundation (NSF): 1517823

Maintenance

Maintenance:

Description:	completed
Frequency:

Other Metadata

Additional Metadata

additionalMetadata
        |___text '\n    '
        |___element 'metadata'
        |     |___text '\n      '
        |     |___element 'unitList'
        |     |     |___text '\n        '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'millimolesPerMeterCubed'
        |     |     |     |  \___attribute 'multiplierToSI' = '0.001'
        |     |     |     |  \___attribute 'name' = 'millimolesPerMeterCubed'
        |     |     |     |  \___attribute 'parentSI' = 'molesPerMeterCubed'
        |     |     |     |  \___attribute 'unitType' = 'amountOfSubstanceDensity'
        |     |     |     |___text '\n          '
        |     |     |     |___element 'description'
        |     |     |     |     |___text 'millimoles per meter cubed'
        |     |     |     |___text '\n        '
        |     |     |___text '\n        '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'wattPerMeterSquared'
        |     |     |     |  \___attribute 'multiplierToSI' = '1'
        |     |     |     |  \___attribute 'name' = 'wattPerMeterSquared'
        |     |     |     |  \___attribute 'parentSI' = 'wattPerMeterSquared'
        |     |     |     |  \___attribute 'unitType' = 'arealEnergyFlux'
        |     |     |     |___text '\n          '
        |     |     |     |___element 'description'
        |     |     |     |     |___text 'watts per meter squared'
        |     |     |     |___text '\n        '
        |     |     |___text '\n        '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'cubicMetersPerDay'
        |     |     |     |  \___attribute 'multiplierToSI' = '0.00001157407'
        |     |     |     |  \___attribute 'name' = 'cubicMetersPerDay'
        |     |     |     |  \___attribute 'parentSI' = 'cubicMetersPerSecond'
        |     |     |     |  \___attribute 'unitType' = 'volumetricRate'
        |     |     |     |___text '\n          '
        |     |     |     |___element 'description'
        |     |     |     |     |___text 'cubic meters per day'
        |     |     |     |___text '\n        '
        |     |     |___text '\n        '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'gramsPerSecond'
        |     |     |     |  \___attribute 'multiplierToSI' = '0.00000001157407'
        |     |     |     |  \___attribute 'name' = 'gramsPerSecond'
        |     |     |     |  \___attribute 'parentSI' = 'kilogramsPerSecond'
        |     |     |     |  \___attribute 'unitType' = 'massRate'
        |     |     |     |___text '\n          '
        |     |     |     |___element 'description'
        |     |     |     |     |___text 'grams per day'
        |     |     |     |___text '\n        '
        |     |     |___text '\n        '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'gramsPerCubicMeter'
        |     |     |     |  \___attribute 'multiplierToSI' = '0.001'
        |     |     |     |  \___attribute 'name' = 'gramsPerCubicMeter'
        |     |     |     |  \___attribute 'parentSI' = 'kilogramsPerCubicMeter'
        |     |     |     |  \___attribute 'unitType' = 'density'
        |     |     |     |___text '\n          '
        |     |     |     |___element 'description'
        |     |     |     |     |___text 'grams per cubic meter'
        |     |     |     |___text '\n        '
        |     |     |___text '\n      '
        |     |___text '\n    '
        |___text '\n  '

Copyright 2024 Environmental Data Initiative. This material is based upon work supported by the National Science Foundation under grants #2223103 and #2223104. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Please contact us with questions, comments, or for technical assistance regarding this web site or the Environmental Data Initiative. Please read our privacy policy to know what information we collect about you and to understand your privacy rights.

EDI is a collaboration between the University of New Mexico and the University of Wisconsin – Madison, Center for Limnology:

Data Package Metadata View Summary

Data for Lake Mendota Phosphorus Cycling Model

Data Entities

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Package Usage Rights

Keywords

Methods and Protocols

These methods, instrumentation and/or protocols apply to all data in this dataset:

People and Organizations

Temporal, Geographic and Taxonomic Coverage

Project

Parent Project Information:

Maintenance

Additional Metadata

Recently Added

Recently Updated

Data Package Metadata View Summary

Data for Lake Mendota Phosphorus Cycling Model

+/- Data Entities

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

Data Table

+/- Data Package Usage Rights

+/- Keywords

+/- Methods and Protocols

These methods, instrumentation and/or protocols apply to all data in this dataset:

+/- People and Organizations

+/- Temporal, Geographic and Taxonomic Coverage

+/- Project

Parent Project Information:

+/- Maintenance

+/- Additional Metadata

Data Entities

Data Package Usage Rights

Keywords

Methods and Protocols

People and Organizations

Temporal, Geographic and Taxonomic Coverage

Project

Maintenance

Additional Metadata