# Presentation: 513487

## Simulating the Value of El Niño Forecasts

**Simulating the Value of El Niño Forecasts**
**for the Panama Canal**
- Nicholas Graham and Konstantine Georgakakos
- Hydrologic Research Center
- San Diego, CA
- Carlos Vargas and Modesto Echevers
- Meteorology and Hydrology Section,
- Panama Canal Authority
- Panama Canal Zone, Panama

*CDPW BOULDER, OCT. 2006*

## FACTS

_**FACTS**_
- The Panama Canal requires a _supply of fresh water_ for operations.
- Canal fresh water storage has an _operational time constant of months_.
- _El Niño variability strongly modulates rainfall_ and water supply for the Canal.
- _El Niño variability is somewhat predictable_ at lead times of 9-12 months.
- _Canal inflow is modestly predictable_ at lead times of months.
_**QUESTION**_
- Can routine El Niño predictions be used assist in Canal operational planning?

## Slide 3

## OUTLINE

- _OUTLINE_
- DATA
- PROJECT DESIGN
- 	HOW TO EVALUATE THE VALUE OF EL NINO FORECASTS
- CLIMATOLOGY AND PREDICTABILIY
- 		CANAL INFLOW CLIMATOLOGY
- 		RELATIONSHIPS BETWEEN EL NINO AND INFLOW
- RESULTS

## DATA

- _DATA_
- 1) CLIMATE
- 	* NATURAL INFLOW INTO GATUN LAKE (1906-2000)
- 	* NIÑO3 SST (1906-2000; Smith and Reynolds, 2004)
- 	* PREDICTED NIÑO3 (NCEP; 1981-97; MONTHLY)
- 		(this is the pre-CFS 1-forecast per month system)
- 2) CANAL CHARACTERISTICS (PCA)

## PROJECT DESIGN AND GOALS (1)

_**PROJECT DESIGN AND GOALS (1)**_
- Build a _basic, monthly timestep model of the Canal system_, embodying:
- Management objectives
**Reliable passage of ships (lockage)**
- Additional income through hydro-power generation
- Low risk
- 	  b)	Physical constraints
- 		i)     Gatun Lake capacity, vol. / stage, level requirements
- 		ii)    Lockage, hydropower, spillage discharge capacities
- 		iii)   Lockage and hydropower income
- 	  c)	Inflow predictability ( 3 models, each with variable uncertainty )
- 		i)     **CLIMATE** - _Inflow outlook => mean monthly climatology + rmse_
- 		ii)   ** ****PERFECT** - I_nflow outlook => observations + small error_
- 		iii)  ** ****FORECAST** - _Inflow outlook => El Nino forecasts + fcst. rmse_

## PROJECT DESIGN AND GOALS (2)

_**PROJECT DESIGN AND GOALS (2)**_
- Build a _basic, monthly timestep, model of the Canal system_, embodying:
- Management objectives
- 	  b)	Physical constraints
- 	  c)	Inflow predictability ( 3 models, each with variable uncertainty )
- _Operate the model using probabilistic inflow outlooks_ (i, ii, iii) using an
- 	optimizer to simulate management with objective forecast information.
- _Evaluate performance of simulated system_ in terms of added value and operational reliability afforded by El Nino forecast information and formal inclusion of uncertainty.

## CLIMATOLOGY AND PREDICTABILITY

**CLIMATOLOGY AND PREDICTABILITY**
- CANAL INFLOWS HAVE A STRONG ANNUAL CYCLE
- EL NIÑO VARIABILITY MODULATES CANAL REGION RAINFALL AND INFLOWS.
- THE STRENGTH OF THE RELATIONSHIP BETWEEN EL NIÑO AND FLOW VARIES FROM STRONG TO VERY WEAK DURING THE YEAR.

## Slide 9

## CORRELATIONS: 

- CORRELATIONS:
- WATER YEAR GATUN INFLOW vs NINO3 SST
- 1915-1999

## Slide 11

## Slide 12

## EL NIÑO VARIABILITY IS PREDICTABLE

- EL NIÑO VARIABILITY IS PREDICTABLE
- OPERATIONAL (PRE-CFS) NINO3 SST FORECAST SKILL
- (CORRELATIONS x 100) 1981-1998

## EL NINO PREDICTIONS REDUCE UNCERTIAINTY

**EL NINO PREDICTIONS REDUCE UNCERTIAINTY**
**IN INFLOW OUTLOOKS**
_**FRACTIONAL REDUCTIONS IN INFLOW UNCERTAINTY (RMSE)**_** **
- RATIO WITH CLIMATOLOGICAL RMSE (x 100)
- USING OPERATIONAL NINO3 SST PREDICTIONS
- 1981-1998

## CANAL SIMULATION SYSTEM

- _CANAL SIMULATION SYSTEM_
- INITIAL STATE (GATUN LAKE VOLUME)
- GATUN LAKE CAPACITY – LEVEL / VOLUME RELATIONSHIP
- LOCKAGE REQUIREMENTS, WATER USE
- HYDROPOWER REQUREMENTS, WATER USE
- SPILL LEVEL, POSSIBLE RANGES
- EVAPORATION, MUNICIPAL WATER REQUIREMENTS
- EXISTING RULE CURVE
- LOCKAGE INCOME
- HYDROPOWER INCOME
- PROBABILISTIC INFLOW PROJECTIONS (6 MONTH HORIZON)
- OPTIMIZER and VIRTUAL MANAGER

## PANAMA CANAL SIMULATION SYSTEM

## PARAMETERS FOR SIMULATED PANAMA CANAL SYSTEM

- _GATUN LAKE PARAMETERS_
- Useful volume (VU) – 766 Mm3
- Lowest useful level (HL) – 24.84 m
- Maximum (spill) level (HU) – 26.67 m
- Evaporation and Municipal withdrawal (E) 6.16 Mm3 month-1
- Maximum spill rate (RUS) – 13358.30 Mm3 month-1
- Actual spill rate per month (RS) Mm3
- Rule curve level for a particular month (H*m) m
- Actual level for a particular month (H*m) m
- _CANAL PARAMETERS_
- Volume required per unit ship passage (VL) – 196,820 m3 ship-1
- Maximum number of ships per month (SU) – 1200 ships month-1
- Maximum lockage volume per month (RUL) – 236.18 Mm3 month-1
- Actual lockage volume per month (RL)
- Volume required per unit MWH hydropower production (VH) – 19,114 m3 MWH-1
- Maximum hydropower production per month – 17,280 MWH month-1
- Maximum hydropower volume per month (RUH)– 330.29 Mm3 month-1
- Actual hydropower volume per month (RH)
- INCOME PARAMETERS
- Income per ship passage (iL) – $US 50,000
- Maximum lockage income per month (IUL) - $US 60M
- Actual lockage income per month (IL)
- Income per MWH (iH) - $US 50
- Maximum hydropower income per month (IUH)- $US 864,000
- Actual hydropower production per month (IH)
- Maximum possible total income per month (IMAX) - $US 60.864M

## ASSESSING PERFORMANCE OF “OPTIMIZED” POLICIES

- _Start with initial state_ at time t (Gatun Lake volume)
- _Use inflow outlook _(probabilistic) for next 6 months
- _Derive optimal feasible policy_ (lockage, hydropower, spill) for next 6 months.
- _Execute optimal feasible policy for __ONE__ month_ (to t+1)
- Tabulate results with respect to objectives
- _Update state_ (Gatun Lake volume) with OBSERVED inflow
- Repeat

## ASSESSING PERFORMANCE OF CANAL SIMULATIONS

## RESULTS

_**RESULTS**_
- 3 SETS OF SIMULATIONS
_**PERFECT**_ – PERFECT FORESIGHT.
- 		NOMINAL UNCERTAINTY:  ~ZERO
_**FORECAST**_ – USE INFLOWS DERIVED FROM EL NIÑO FORECASTS.
- 		NOMINAL UNCERTAINTY:  MEAN-SQUARE FORECAST ERROR.
_**CLIMATE**_ – INFLOWS ARE FROM LONG-TERM CLIMATOLOGY.
- 		NOMINAL UNCERTAINTY: MEAN-SQUARE CLIMATOLOGY ERROR
- EACH SET OF SIMULATIONS IS ASSIGNED THE NOMINAL UNCERTAINTY,
- 	AND ALSO VALUES RANGING FROM SMALL TO LARGE.
- THIS ALLOW US TO SEE THE _SENSIVITY_ TO CHANGES IN:
- 	A) FORECAST SKILL (i.e., IN THE DETERMINISTIC FORECAST)
- 	B) THE ASSOCIATED UNCERTAINTY
- 	C) DEMAND (HOW MANY SHIPS)

## UNCERTAINTY vs TOTAL CANAL INCOME (1981-1997)

_**UNCERTAINTY vs TOTAL CANAL INCOME (1981-1997)**_
**DOES EL NI****ÑO FORECAST INFORMATION HELP?**
**NOTICE THE EFFECT ON INCORRECTLY SPECIFIED UNCERTAINTY**

- CLIMATOLOGY

- FORECAST

- PERFECT

**LOW UNCERTAINTY**

**HIGH  UNCERTAINTY**

## $329M

- COMPARISON OF TOTAL INCOME (1981-1997)
- CLIMATOLOGY - DETERMINISTIC
- FORECAST – UNCERTAINTY 0.4
- PERFECT - DETERMINISTIC

## EXAMPLE OF MONTHLY INCOMES:

- PERFECT AND FORECAST MODELS
- IN GENERAL, THE CANAL PERFORMS ROBUSTLY

## NORMALIZED HYDRO-POWER INCOME

- CLIMATOLOGY

- FORECAST

- PERFECT

## AVERAGE SPILL

- CLIMATOLOGY

- FORECAST

- PERFECT

## TEST BEHAVIOR OF CANAL TO INCREASED LOCKAGE DEMAND

**TEST BEHAVIOR OF CANAL TO INCREASED LOCKAGE DEMAND**
- 40 SHIPS PER DAY
- 48 SHIPS PER DAY
- 56 SHIPS PER DAY
- EFFECT IS TO **INCREASE THE SENSITIVITY TO UNCERTAINTY** SPECIFICATION

## TEST BEHAVIOR OF CANAL TO INCREASED LOCKAGE DEMAND

**TEST BEHAVIOR OF CANAL TO INCREASED LOCKAGE DEMAND**
- N = 40 , 48, 56 SHIPS PER DAY
- AS FRACTION OF MAXIMUM POSSIBLE INCOME FOR N SHIPS DAY-1

## Slide 28

##       JUST APPROVED CANAL EXPANSION

-       _JUST APPROVED CANAL EXPANSION_
- DEEPEN / WIDEN ATLANTIC APPROACH
- NEW APPROACH TO NEW ATL. LOCKS
- NEW POST-PANMAX ATL. LOCKS
- RAISE MAXIMUM LEVEL OF LAKE GATUN
- DEEPEN / WIDEN CHANNEL
- NEW APPROACH TO NEW PAC. LOCKS
- NEW POST-PANMAX PAC. LOCKS
- DEEPEN/WIDEN PACIFIC APPROACH
- WATER-SAVING BASINS FOR NEW LOCKS
-        RESULT IN 7% WATER SAVINGS
- DEEPENING GATUN CHANNEL RESULTS
- 	IN INCREASED VOLUME.
- -	LARGER SHIPS, MORE SHIPS

## TEST BEHAVIOR OF EXPANDED CANAL

- AS FRACTION OF MAXIMUM POSSIBLE INCOME
- NOTE IMPORTANCE OF FORECAST RELIABILITY

- NEW MODEL INCLUDES:
- - HIGHER LOCKAGE DEMAND
- - INCREASED POTABLE DEMAND
- - WATER SAVING BASINS
- - DEEPENED CHANNEL
- - MADDEN LAKE

## SUMMARY

_**SUMMARY**_
- ROUTINE EL NIÑO FORECASTS CAN BE USED TO REDUCE THE UNCERTAINTY IN GATUN INFLOW PROJECTIONS AT LEAD TIMES OF MONTH.
- 2)  THE USE OF THIS INFORMATION INCREASES SIMULATED CANAL INCOME IN COMPARISON TO CLIMATOLOGICAL EXPECTATIONS. VALUE = $322M.
- 3)  THE VALUE OF FORECAST INFORMATION INCREASES AS THE DEMANDS ON CANAL RESOURCES ARE INCREASED.
- OPTIMAL CANAL OPERATION IS VERY SENSITIVE TO CORRECT SPECIFICATION OF UNCERTAINTY.
- 	**INACCURATE FORECASTS WITH CORRECT UNCERTAINTY**
**BETTER THAN**
** ****ACCURATE FORECASTS WITH INCORRECT UNCERTAINTY**

## - THANK YOU -

*- THANK YOU -*

*Graham, Georgakakos, Vargas, Echevers, 2006:*
*Advances in Water Resources, 29, 1665-1677.*