Mapping Basin Level Water Productivity Using Remote Sensing and Secondary Data in the Karkheh River Basin Iran

Mapping Basin Level Water Productivity Using Remote Sensing and Secondary Data in the Karkheh River Basin Iran

Mobin-ud Din Ahmad Md. Aminul Islam

Ilyas MasihLal MuthuwattaPoolad KarimiHugh Turral

Presentation made at XIII IWRA World Water Congress on Global Changes and Water Resources: confronting the expanding and diversifying pressures, held on September 1-4, 2008, at Montpellier, France.

Introduction

• Rapid increase in agricultural production will be required to keep pace with future food and fiber demands.

– This can be achieved by bringing more area under agriculture or– by increasing the yields using similar or even reduced water resources

(e.g., increasing productivity of water).

• Considering that:– Land and water resources are already reached their exploitation limits or are

over exploited in many river basins; and – There is increasing competition for water among sectors.

• The option of increasing agricultural production using same or less water resources is the most appropriate one.

The case of Iran• Iran is land abundant and water short country.

– Average Precipitation of 240 mm/year (Dinpashoh et al. 2004)• less than 200 mm/year over 50 % area • less than 300 mm/year over 75 % area. • more than 500 mm/year over 8 %,

– Annual renewable water resources: 135 Km3/year (Vakili et al. 1995)

• Strategic goal of achieving food self-sufficiency need more water resources development, hence will increase pressures on scarce water resources

• Addressing these challenges require discovering ways to more effectively utilize existing resources.

• Unavailability of information on water use performance (e.g., water productivity) is yet another bottleneck

The case of Karkheh basin

• Very limited information on water productivity– Field scale estimates exists (e.g. Keshavarz et al., 2003, Moayeri et al.,

2007). – water productivity estimates beyond field scale are non-existent.

• The major goal of this component of the CPWF’s Karkheh Basin Focal Project was to fill these information gaps

– The specific objectives are:

• to estimate physical water productivity of major rainfed and irrigated crops and evaluate the spatial variability in Karkheh basin; and

• to estimate the economic water productivity at sub-catchment to basin scale both in terms of vegetative areas as well as inclusive of livestock.

METHODOLOGY

The Karkheh basin

• Drainage area: 50, 764 Km2

• Population: 4 Million-2/3 rural

• Mediterranean climate– precipitation 450

mm/year, range: 150 mm to 750 mm

• Renewable water resources: 8.5 * 109

m3/year• distributed among seven

provinces and 32 districts.• Hydrologically divided

into five main catchments (sub-basins).

Water productivity mapping:Sub-catchment to basin scale

nConsumptioBenefitWP =

MODIS-TERRA 1000m

MODIS-TERRA 250m NDVI time series

SRTM 90m DEMSub-catchmentBoundaries

Land Use Land CoverMap

Estimation of Actual Evapotranspiration ETa

Administrative/districtmaps and agricultural statistics

Meteorological Data

Image Classification

Topographic/ GIS Analysis

Energy Balance Analysis

Land use wise sub-catchment Actual Evapotranspiration ETa

Land use wise sub-catchment Gross Value of Production (GVP)

Sub-catchment level Land use type

Water Productivity(GVP/ETa)

MODIS-TERRA 1000m

MODIS-TERRA 250m NDVI time series

SRTM 90m DEMSub-catchmentBoundaries

Land Use Land CoverMap

Estimation of Actual Evapotranspiration ETa

Administrative/districtmaps and agricultural statistics

Meteorological Data







Land use wise sub-catchment Actual Evapotranspiration ETa

Land use wise sub-catchment Gross Value of Production (GVP)

Sub-catchment level Land use type

Water Productivity(GVP/ETa)

(Molden 1997)

Water productivity mapping:Field and farm scale

nConsumptioBenefitWP =

Villages: 110

Farmers: 298

Small: 37 Medium: 173 Large: 88

Rainfed: 97Small (11)

Medium (45)Large (41)

Irrigated: 120Small (26)

Medium (62) Large (32)

Mixed: 81


Villages: 110

Farmers: 298

Small: 37 Medium: 173 Large: 88

Rainfed: 97Small (11)


Irrigated: 120Small (26)

Medium (62) Large (32)

Mixed: 81


(Molden 1997)

RESULTS

Field to Farm Analysis

Field to Farm Analysis

Variability in land and water productivity-Example of irrigated wheat

0

1000

2000

3000

4000

5000

6000

Gamas

iab

Qaras

ou

Kashka

nSay

mareh

Lower Kark

hehKark

heh bas

in

Yiel

d (K

g/ha

)

00.10.20.30.40.50.60.7

WP

(Kg/

m3 o

f gro

ss in

flow

)

Field to Farm Analysis:The case of Irrigated farms

0

1000

2000

3000

4000

5000

6000

7000

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 106 111 116 121 126 131 136 141 146 151 156 1610.00

0.20

0.40

0.60

0.80

1.00

1.20Yield Water Productivity

Yiel

d (k

g/ha

)

Wat

er P

rodu

ctiv

ity (k

g/m

3 )

Gamasiab Qarasou Kashkan Lower Karkheh Saymareh

Field to Farm Analysis:The case of Rainfed farms

0

500

1000

1500

2000

2500

3000

3500

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 106 111 116 121 126 131 136 141 1460.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60Yield Water Productivity

Yiel

d (k

g/ha

)

Wat

er P

rodu

ctiv

ity (k

g/m

3 )

Gamasiab Qarasou Kashkan Lower Karkheh Saymareh

Field to Farm Analysis:Main observations

• Large variability and presence of closable gaps.

– The difference between the top 10% of cases and average water productivity is about 0.40 kg/m3.

• Increase yield by 1500kg/ha with no increase in water use.

– Reduce over irrigation: Farmers apply 2-8 irrigations to wheat crops. The highest yield can generally be attained by 3-4 irrigations in most cases.

– Interventions regarding improving field layouts, leveling, irrigation scheduling and fertilizer inputs are essentially required.

– For rainfed areas, exploring means of supplemental irrigation.

– In spatial terms more scope for land and water productivity improvements exists in the upper than lower Karkheh.

Sub-Basin to Basin Scale Analysis

Sub-Basin to Basin Scale Analysis:Land use and ETa

Sub-Basin to Basin Scale Analysis:Water Consumption and GVP

• Precipitation: 18.51×109 m3/year (Muttuwatte et al., 2008)

• Overall ETa: 16.68×109 m3/year

• Overall GVP:0.98×109 $/year

Sub-Basin to Basin Scale Analysis:WP of rainfed and irrigated crops

• Rainfed WP: 0.051$/m3;0.027 to 0.071$/m3

• Rainfed water productivity has a declining trend from upper to lower Karkheh.

• Irrigated WP: 0.22 $/m3 ;0.12 to 0.524 $/m3. • Higher irrigated WP values are concentrated

in middle and lower parts

• High performing areas are:

– Irrigated case; Jelogir, Pole Dokhtar, Ghore Baghestan, Doab, Abdul Khan and Hamedieh,

– Rainfed case; Dartoot, Holilan, GhoreBaghestan

Sub-Basin to Basin Scale Analysis:WP of vegetative and livestock

• Vegetative WP: 0.097 $/m3; 0.004 to 0.36 $/m3.

– The higher values are mainly due to higher proportion of irrigated lands

• WP vegetative and livestock: 0.129 $/m3

; 0.022 to 0.408 $/m3.

• Magnitude and distribution of agricultural economic water productivity changes substantially when livestock is included.

SUMMARY AND CONCLUSIONS

Summary and Conclusions

• The study shows that land and water productivity exhibit large inter-and intra-sub-basin variations.

– Indicating that considerable scope exists for farm scale productivity improvement both in irrigated and rainfed areas.

– Key interventions could be:

• Irrigated areas: improving field layouts, leveling and irrigation scheduling are essentially required, balanced use of fertilizer

• Rainfed areas: Tapping opportunities for providing additional water wherever possible

Summary and Conclusions (Cont.)

• The identified bright spots in upper (Jelogir, Pole Dokhtar, GhoreBaghestan and Doab) and lower Karkheh (Abdul Khan and Hamedieh). Similarly for rainfed areas Dartoot, Holilan, Ghore Baghestan could be help in interventions in the neighboring low performing areas

– The intervention focusing on reasons attributed to high performance such as irrigation, agronomic and markets in case of bright spots could be instructive to reduce productivity gap of low performing neighbors (Hot spots).

– Shifting to higher values crops could also contribute to increasing water productivity but might contradict national food sufficiency targets.

• Inclusion of livestock in economic water productivity estimates substantially changes the map of basin water productivity and the magnitude of results.

– This highlights the importance of fully accounting for all agricultural production systems in calculations, especially if they are to be used for the purpose of possible reallocation of water away from the rural sector.

• The approach presented in the paper exemplifies how the combineduse of freely available remote sensing data and routine secondary data/statistics coupled with advanced GIS techniques can be used to compute water productivity at different scales such as sub-catchment to river basin.

• This methodology provides essential information to water managers and policy makers on water use performance/water productivity helping them to identify high and low performing regions for better targeting resources reallocation and productivity enhancement campaigns within a river basin.

Summary and Conclusions (Cont.)

Acknowledgments:

Ministry of Jihad-e-Agriculture, Iran(AERO, Iran)

Statistical Department, IranMinistry of Water and Power, IranMeteorological Department, Iran

IWMI and CPWF colleagues

International Water Management Institute (IWMI)

PO Box 2075, Colombo, Sri Lanka

E-mail: [email protected]

Corresponding author: Dr. Mobin-ud Din Ahmad

E-mail: [email protected]; [email protected]

mailto:[email protected]



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Mapping Basin Level Water Productivity Using Remote Sensing and Secondary Data in the Karkheh River Basin Iran