caribbean coastal scenarios project ccsp l.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Caribbean Coastal Scenarios Project (CCSP): PowerPoint Presentation
Download Presentation
Caribbean Coastal Scenarios Project (CCSP):

Loading in 2 Seconds...

play fullscreen
1 / 35

Caribbean Coastal Scenarios Project (CCSP): - PowerPoint PPT Presentation


  • 184 Views
  • Uploaded on

Caribbean Coastal Scenarios Project (CCSP):. Hydrological and Water quality Modeling using SWAT Assefa Melesse Florida International University. Outline. Modeling protocol SWAT overview and Data requirement Pilot watershed selection Data collection Calibration, validation and verification.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Caribbean Coastal Scenarios Project (CCSP):' - Audrey


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
caribbean coastal scenarios project ccsp

Caribbean Coastal Scenarios Project (CCSP):

Hydrological and Water quality Modeling using SWAT

Assefa Melesse

Florida International University

outline
Outline
  • Modeling protocol
  • SWAT overview and Data requirement
  • Pilot watershed selection
  • Data collection
  • Calibration, validation and verification
model
Model
  • Model = simplification of reality
    • Purpose: To reduce a complex system to its essential processes, so that system behavior may be simulated under different conditions.
  • Model = software + data
    • A modeling program + data specific to that watershed
      • Climate, topography, hydrography, soils, and land use
model cont
Model cont.
  • A program to determine the cause of water quality problems and aquatic ecosystem disturbances
  • Sediment and nutrient load modeling require:
    • Soil loss data
    • Field operations and fertilizer/pesticide application data
    • Human impact activities – LULC change.
  • Max. daily sediment/nutrient loads for evaluating watershed management strategies
  • Recommend BMPs
model cont5
Model cont.
  • Problem
  • Information
  • What questions need to be answered
  • Simplest model with acceptable accuracy
  • Question whether increased accuracy is worth the increased effort
slide6

Define the problem

Field data

Conceptual Model

Mathematical Model

Computer Program

Yes

Code Verified?

NO

Model Design

Field data

Calibration

Compare

with Field data

Verification

Field data

Postaudit

Modeling

Protocol

research questions
Research questions
  • What are the major sources of the coastal and aquatic ecosystem degradation?
  • How much runoff, nutrient and sediment loading?
  • How much nutrient loads aquatic ecosystem sustain?
  • What BMPs will help reduce the sediment, nutrient and solute laden?
swat soil water assessment tool
SWAT (Soil water Assessment Tool)

Some figures are taken from SWAT Manual

about swat
About SWAT
  • SWAT (USDA/ARS)
    • Objective: “...to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use and management conditions over long periods of time.”
    • Strengths
      • Best at NPS-pollution loads from agricultural practices;
      • improving routines for urban loads
      • Good interface with GIS software (ArcView)
swat features cont
SWAT features cont.

MODEL OPERATION:

  • simulates hydrology, pesticide and nutrient cycling, erosion and sediment transport
  • spatially distributed
  • Daily time step with long term simulations
  • Basins subdivided to account for differences in soils,   land use, crops, topography, weather, etc.
  • Basins of several thousand square miles can be studied
  • SWAT accepts measured data & point sources
  • Windows Interface
pilot watershed selection
Pilot Watershedselection
  • Data availability and continuity
  • Significance to water quality problems
  • Accessibility for possible visit and data collection
watershed selection suggestions
Watershedselection: Suggestions?
  • Jamaica: Kingston Basin (Hope River watershed)
  • Purteo Rico: Loiza Basin
  • Cuba: Guama`@Hoyo de Guama`
  • DR: Haina Basin
watershed selection jamaica17
Watershedselection: Jamaica
  • Kingston Basin (Hope River watershed)
  • Home of the 25% of the island’s population
  • Urban discharge to the Kingston Harbour has been a concern 
  • Better data
  • But no agricultural areas

Rio Cobre Basin

  • Sugar cane agriculture and urban areas
  • Data? 
data collection
Data Collection

Geospatial/Physical

  • Land cover:
    • Detailed land-cover map from existing sources
    • Level I or higher land-cover classes
  • Soil: FAO or other sources
    • 1:250K or better scale
  • Elevation
    • DEM 90-m or better
data collection cont
Data Collection cont.

Weather

  • Rainfall
  • air temperature (monthly min and max)
  • solar radiation
  • wind speed and
  • relative humidity
    • Location of weather station
data collection cont21
Data Collection cont.

Hydrological

  • Stream flow
  • Sediment and
  • Nutrient delivery
    • Continuous data
data collection cont22
Data Collection cont.
  • Non-point and point source pollution data
    • Fertilizer and pesticide application data
      • Type, rate and characteristics (absorption, half-life
    • Point source of pollution, if any
      • Location and amount
calibration validation and verification
Calibration, validation and verification
  • Calibration
    • Model adjustment by changing parameters using known input and output data
  • Validation
    • Comparison of the model with a different input dataset
  • Verification
    • Examining the numerical technique represents the conceptual model and no numerical problems
calibration validation and verification24
Calibration, validation and verification

Calibration/validation periods

  • Enough time to adjust
  • Similar condition

Calibration validation

calibration validation and verification25
Calibration, validation and verification

Calibration/validation steps

  • Hydrology
  • Sediment
  • Water quality/nutrients
calibration validation and verification26
Calibration, validation and verification

Calibration/validation common problems

  • Little data
  • Small range of conditions
    • Only small storms
    • Data discontinuity
  • Calibration can change the physical representation of the processes by the model
calibration validation and verification27
Calibration, validation and verification

Calibration/validation evaluation

  • Mean and SD, errors of prediction
  • Regression coefficient, intercept, slope
  • RMSE, MAD, MAPE
  • Nash and Sutcliffe efficiency
calibration validation and verification28
Calibration, validation and verification

Calibration/validation key considerations

  • Water balance
    • Total amount
    • Partitioning to other hydrologic components
  • Storm sequence
    • Time shift or lag
      • Time of concentration, travel time
    • Shape of hydrograph
      • Peak, time to peak and recession
calibration validation and verification hydrology
Calibration, validation and verification : Hydrology

Possible scenarios for hydrology

  • Model failed to simulate some peaks
  • Rain gage location
  • Prblem with rain gage
  • Use rainfall from representative rain gage
  • Examine the rainfall and flow data
calibration validation and verification hydrology31
Calibration, validation and verification : Hydrology

Possible scenarios

  • Consistent over prediction
  • High surface flow, base flow
  • Less evapotranspiration
  • Decrease CN
  • Increase soil available water
  • Increase deep percolation loss
  • Increase GW revap coeff.
calibration validation and verification hydrology32
Calibration, validation and verification : Hydrology

Possible scenarios

  • Time lag
  • Long time of concentration
  • High Surface roughness
  • Less slope
  • Increase slope
  • Lower Manning’s coeff
calibration validation and verification hydrology33
Calibration, validation and verification: Hydrology

Possible scenarios

  • Model consistently over predicts peaks and under predicts at other parts
  • Less base flow
  • High overland flow
calibration validation and verification sediment
Calibration, validation and verification: Sediment

Sediment calibration possible scenarios

  • Model consistently under predicts sediment
    • Low sediment yield
    • Adjust
      • Crop management factor
      • soil erodabiliy factor
      • USLE slope length factor
      • Channel cover factor