21st Century Management Solutions

for Water Supply and Demand

Bill Szafranski

Roger Wolvington

AWRA Annual Conference

November 9, 2017

Abstract

Water supply planning in the Western US is critical for managing limited resources

Conventional approaches such as using spreadsheets are being abandoned for more modern modeling approaches

We will discuss these modern approaches centered around our model CRAM

These models need to meet the following requirements:• A good user interface

• Perform rapid calculations

• Represent real-life features (reservoirs, inflows, demands, etc.)

• Optimize a system

• Preserve mass balance

• Provide insights for analysts, water managers, utilities, planners, etc.

Water Allocation Models

Applications• Long term supply planning

• Demand build-out

• Firm yield analysis

• What if scenario analysis• Drought, climate change, new capital improvement projects

What Can They Do?

• OASIS• HydroLogics model

• Uses linear programming

• MODSIM• CSU model run by John

Labadie

• RELAX flow optimization algorithm

• PACSIM• Platte and Colorado Simulation

Model

• Model owned by and run internally by Denver Water (FORTRAN)

A Few Models

• StateMod• Colorado’s large basin water

rights modeling system

• CalSim or WRIMS• California’s State Water

Project/ Central Valley Project simulation model

• Uses linear programming

• CRAM• Lynker Technologies model

• Out of Kilter network optimization algorithm

CRAM

Central Resources Allocation Model

1. Bosque del Apache Decision Support Tool (BdADST)

• Managing water rights for the US Fish and Wildlife Service

• Used at the Bosque del Apache National Wildlife Refuge

2. Llandegfedd Reservoir Operations Model

• Optimization of a reservoir guide curve

Case Studies

Source: US Fish and Wildlife

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Reservoir Guide Curves

• Bosque del Apache National Wildlife Refuge in New Mexico serves as habitat for migratory birds

• 57,000 acres of land (89 mi2) includes wetlands, crops and riparian forests

• Rio Grande passes through the Refuge

Case Study 1 – Bosque del Apache

Background

US Fish and Wildlife needed a better way to administer their water rights.

1. Decision support tool for annual water planning

2. Scenario analysis for droughts

3. Prove and quantify historical water use

4. Minimize groundwater use in Refuge

Bosque del Apache

Purpose

Bosque del Apache

CRAM Modeling Outline

Build System Model (CRAM)

Run Annual Planning Scenarios

Run Drought Simulations

In order to maintain habitat, the refuge manages irrigation water through a complex system that includes return flows and wells

• 4 surface sources

• 12 supplemental wells

• 123 management units (MU)

• 32 miles of canals

Bosque del Apache

Build model to

System Specifications

Bosque del Apache CRAM setup

• Specify land use type for 123 MUs for each month of the year

• Ponded, small grains, corn/alfalfa, fallow, etc.

• Specify GW pumping

• Run Model

Output: Solve for water used (water required)

Bosque del Apache

1. Annual Water Planning (Demand Driven Analysis)

Scenario Analysis

Delete farm field diversion

Month Land Use

Consumptive

Irrigation Use (ft.)

Diversion

(AF)

Jan Fallow 0.00 0.0

Feb Fallow 0.00 0.0

Mar Corn/Alfalfa 0.06 10.2

Apr Corn/Alfalfa 0.19 32.0

May Corn/Alfalfa 0.31 52.7

Jun Corn/Alfalfa 0.44 74.4

Jul Corn/Alfalfa 0.47 79.5

Aug Corn/Alfalfa 0.35 60.2

Sep Corn/Alfalfa 0.19 33.0

Oct Corn/Alfalfa 0.08 13.3

Nov Fallow 0.00 0.0

Dec Fallow 0.00 0.0

Month Land Use

Consumptive

Irrigation Use (ft.)

Diversion

(AF)

Jan Open Water/Flow Through 0.18 5.0

Feb Open Water/Flow Through 0.25 7.0

Mar Open Water/Flow Through 0.44 12.3

Apr Open Water/Flow Through 0.60 16.8

May Open Water/Flow Through 0.70 19.5

Jun Fallow 0.00 0.0

Jul Fallow 0.00 0.0

Aug Fallow 0.00 0.0

Sep Fallow 0.00 0.0

Oct Fallow 0.00 0.0

Nov Open Water/Flow Through 0.21 5.9

Dec Open Water/Flow Through 0.15 4.2

Bosque del Apache

1. Annual Water Planning (Demand Driven Analysis)

Scenario Analysis

Bosque del Apache

1. Annual Water Planning (Demand Driven Analysis)

Scenario Analysis

Purpose: Used to determine MU performance during years of low inflow.

• Specify inflows to Refuge

• Specify monthly GW pumping rates

• Specify land use/operations settings for the 123 MUs

Output:

Analyze water shortages for MUs by month

Bosque del Apache

2. Drought Analysis (Supply Driven Analysis)Scenario Analysis

Bosque del Apache

• GIS output of MUs

• Shortages for 1 month by MU

2. Drought Analysis

Scenario Analysis

• How can we change operations at a pumped reservoir to improve the river environmental flows without impacting municipal water supply (reliability)

Case Study 2: Llandegfedd Reservoir

Problem

1. River simulation:Synthetic daily streamflow to increase limited historical dataset

2. Reservoir rules optimization and simulation model:CRAM simulated reservoir operating rules, inflows and demands to determine supply reliability

Case Study 2: Llandegfedd Reservoir

Approach: 2-Part Solution

Synthetic Flow Data

• Empirical resampling (K-Nearest Neighbor)

• 500 simulations of 39 years at a daily time step = 19,500 years

• Simulated inflows represented the statistics of original 39-year daily dataset well (mean, variance, skew)

Demand Data

• Demand data was paired with its corresponding flow from the original 39-year dataset

River Simulation

Simulated Flow

Reservoir Simulation

CRAM Modeling Outline

Build System Model (CRAM)

Evaluate Proposed Operations

Evaluate Optimized Operations (GA-CRAM)

Optimize Reservoir Operating Rules

(GA-CRAM)

Step 1

Step 2

Step 3

System Model (CRAM)

Step 1:

Reservoir Simulation

Use Excel’s built-in genetic algorithm to determine ‘best’ reservoir guide curve (set of reservoir pool elevations)

Constraints• Min & max monthly pool

elevations• Max abstraction from river

Given Values• Set of inflows• Set of demands

Solve• Choose reservoir targets (pool

elevation)• Calculate total shortage

(demand-supply)• Objective function: Minimize

shortages

Step 2: Optimization (GA-CRAM)

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Reservoir Storage

High Storage Low Storage

Target Storage Maximum Contents

Reservoir Simulation

• Population size 50

• Mutation rate of 0.075

• Model tested 4,881 solutions

• End of simulation due to lack of improvement: 25 hours

• Total Simulation Time: 29 hours

• End of Model Run: Solver cannot improve current solution. All constraints are satisfied.

Optimization Detail (GA-CRAM)

Reservoir Simulation

1. Run Proposed Reservoir Operationsa. 39-years of historical inflow/demand data

b. 19,500-years of simulated inflow/demand data

2. Run GA-CRAM Created (Optimized) Reservoir Operations

a. 39-years of historical inflow/demand data

b. 19,500-years of simulated inflow/demand data

Step 3: Evaluate Operations

Reservoir Simulation

Results: GA-CRAM Operations (19,500-year simulation)

1% occurrence

Dead storage

Max storage

Reservoir Simulation

Results: Proposed Operations (19,500-year simulation)

1% occurrence

Dead storage

Max storage

Reservoir Simulation

River Analysis

20th percentile

Low flow months

No change in river

Client Proposed GA-CRAM

Summary

Water allocation models provide superior capabilities

for tracking and analyzing water supply and demand

within a system.

They allow fast scenario analysis to help answer

management questions.

CRAM Web Tool

Visit the CRAM Interactive Tool here:

https://lynkertech.shinyapps.io/cram/

CRAM Web Tool

Visit the CRAM Interactive Tool here:

https://lynkertech.shinyapps.io/cram/