Determination of spatiallydistributed irrigation water requirements at scheme level using soilwater

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Determination of spatially-distributed
irrigation water requirements at scheme level
using soil-water balance model and GIS

• Term Project CEE 6440 GIS in Water Resources
• Tuesday, November 30th 2004
• Prepared by
• Daniel Zaccaria
• Graduate student
• Department of Irrigation Engineering
• Utah State University

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OBJECTIVES

• General
• Develop and test a tentative methodology for
  mapping I.W.R for large-scale agricultural areas,
  under different climatic scenarios
• Evaluate spatial variability and
  time-distribution of I.W.R. along irrigation
  season
• Specific
• Getting a better knowledge of main factors
  related to irrigated agricultural systems
• Identifying major sources of errors and
  uncertainties in large-scale estimations of
  irrigation requirements

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Long-term purposes

• Carrying out preliminary studies in order to come
  up with a better irrigation water management plan
  for the study area
• Carry out a performance analysis of distribution
  networks and eventually identify re-engineering
  options for low-performing systems or sub-systems

OVERALL Show usefulness of coupling GIS
environment and models capabilities to provide
irrigation managers with operational tools to
support decision-making processes
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Background on the study area
The study area is part of a large-scale irrigated
area located in Southern Italy and managed by a
local Water Users Association. The whole WUA
scheme covers an area of 142,905 Ha
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• The study area is served by three large-scale
  irrigation schemes
• whose physical features and operational rules are
  different

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Cropping pattern
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Why this study area?

• Several problems
• High number of small land-holdings (average farm
  size 1.5 -2.5 ha)
• Market-oriented horticulture, which is strongly
  depending on irrigation
• Irrigation networks are operated with rotation
  delivery schedule
• Water distribution to farms is too restrictive
  and is not timely matching crop water
  requirements
• Resulting consequence
• As a result of all the above factors, during the
  last 10 years a large number of farmers started
  developing their private water sources and
  refused to take water from large-scale irrigation
  networks.
• This led to a very large number of unlicensed
  irrigation wells, to over-pumping from
  groundwater, to sea-water intrusion and salt
  accumulation in the soil

ENVIRONMENTAL AND ECONOMIC HAZARDS
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. AND MOREOVER

• An alarming message is being continuously spread
  out

There is a serious water deficit in the area
But before spreading such a message we have to be
able to come up with reliable numbers from
application of sound methodologies
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Therefore

• A good estimate of actual water demand is
  strongly needed at whole scheme level in order to
  identify
• Existence and potential magnitude of water
  deficit
• Total volume of water seasonally withdrawn from
  groundwater
• Existence and magnitude of environmental hazards
• Re-engineering options (modernization and/or
  rehabilitation of irrigation systems) aiming at
  improving irrigation systems performances and
  efficiency of water use

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Applied methodology
1st step) Identification of 3 climatic scenarios
(Average, Demanding, Very-high demanding)
7 Climatic stations, monthly values for 35 years
of observation (1959-1994)
Areal Clim. Deficit SUM (ETo Reff) x Station
Weight
ETo computed on a montly basis by Hargreaves-
Samani method ETo 0.0023 Ra (Tmax Tmin)0.5
(Ta 17.8)
Tmax and Tmin in hot-dry situation are quite
different
35 annual values of Areal Climatic Deficit
Probability of non-exceedance
50 , 75 and 90 Probabilities
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Probability Analysis
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Methodology
Climatic parameters gt Evapotranspiration (ETo)
Crop Irrigation Requirements and their
time-distribution depend on
Crop characteristics gt Crop coefficient (Kc)
Soil characteristics gt WHC o AW (FC PWP)
Soil-Water Balance gt accounting for all water
inflows and outflows Di D(i-1) ETc (P
SRO) Iinf DP - GW
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Soils polygons (13 different soil types)


Crops polygons (8 different crops)
MeteoStations polygons

Intersect utility in ArcGIS
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Identification of Simulation Units
Simulation units are polygons having the same
crop-soil-climatic area combinations
153 unique soil-crop-clim.area combinations 153
ID.Codes
(153 x 3 climatic scenarios) 459 Runnings of
the Soil-Water Balance model
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Soil-Water Balance algorithm in terms of depletion
Di Di-1 ETc - (P - SRO) - Irr DP - GW

• Assumptions
• irrigation aiming at maximum yield 2) No
  groundwater contribution 3) No restriction
  imposed
• 4) Soils at F.C. at irrig. season starting

Time to irrigate when Di gt MAD Wa Rz
How much to irrigate? The amount necessary to
replenish the root-zone to the F.C.
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Results Map of Net Irrigation requirements
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Superimposing layer of irrigation districts
boundaries
Aggregation of IWR at district level for
different time-scales
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Sources of errors and uncertainties in up-scaling
IWR

• Spatial variability of soils
• Spatial variability of crops gt different crops
  age and cultivars
• Spatial variability of climatic conditions
  (Thiessen method enables rough estimation)
• Spatial variability of land elevation (not taken
  into account)
• Spatial variability of conveyance, distribution
  and application efficiencies

Bottom line I.W.R. are very close to what
farmers give to crops in the area
Further check the time-distribution of seasonal
IWR values
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• Aknowledgements
• G. H. HARGREAVES
• Stornara Tara Water Users Association
• Technical University of Lisbon (PT) Instituto
  Superior de Agricultura

QUESTIONS, COMMENTS OR SUGGESTIONS ??
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Evaluating NIR and their spatial and time
distribution

• Basic information for
• Water allocation plan
• Water distribution plan (time of deliveries)
• Indirect quantification of withdrawals from
  groundwater
• Investigation on available water supply and time
  distribution
• Comparing water supply with water demand enables
  identification of deficit periods and areas
• Performance analysis of irrigation networks based
  on
• Water demand flow hydrographs
• Physical capability of the network
• Identify critical areas
• Simulate re-engineering option and evaluating
  their effectiveness