Agricultural water interventions for sustainable intensification –

upstream downstream trade-offs and opportunities

“Agricultural Research Towards Sustainable Development Goals ”

Yihun Dile and Louise Karlberg

Stockholm Environment Institute

Stockholm Resilience Centre

Two sister projects on AWI

EthiopiaScattered pondsSubsistence agricultureImplications of potential AWIDSS location + size of dams

IndiaWatershed dev. prog.Commercial farmingActual changesLivelihoods

SWAT tool used for analysisImplications on downstream water availability

Research Area

WH suitability studyUpper Blue Nile Basin

Hydrological ModellingLake Tana Basin

Understanding implicationsMeso-scale

Total area: 10 sq.km Subbasin size: 1-6ha

Water harvesting implementation

Ponds dimension size that can store water for ONSEASON and OFFSEASON irrigation size determined for combination of different climatic years & nutrient application

Crop rotation is applied ONSEASON (July-Dec) – TEFF OFFSEASON (Jan-April) – Onion

Suitability class HRUs of slope: <8%; Soil: Luvisols, and vertisols; and agricultural land. Area = 3.79km2 (38% of watershed)

Water Harvesting Implementation Scenarios

Nutrient scenarios

TEFF Current nutrient application rate (WH + BaselineN)

TEFF – 1st stage: UREA - 15kg/ha and DAP – 30kg/ha 2nd stage: UREA – 15kg/ha

Blanket Nutrient Recommendation (WH + BNR1) TEFF – 1stage: UREA – 50kg/ha, and DAP – 30kg/ha 2nd stage: UREA – 50kg/ha

Blanket Nutrient Recommendation (WH + BNR2) TEFF – 1st stage: UREA – 85kg/ha, and DAP – 30kg/ha 2nd stage: UREA – 85kg/ha

ONION Onion – 1st stage: UREA – 85kg/ha, and DAP – 30kg/ha 2nd stage: UREA – 85kg/ha

Crop growth constraints

Scenarios Percent change in teff yield2.5th percentile Median 97.5th percentile

WH+Baseline Nutrient

15 57.2 667.3

WH+BNR1 94.7 134.3 674.5WH+BNR2 148.56 217.4 363.6

2.5th percentile median 97.5th percentileOnion yield (ton/ha) 1.33 7.66 8.22

Crop production

Change in Teff yield (%)

Change in crop yield (%)

Onion production (ton/ha)

Water Productivity

Water productivity2.5th Median 97.5th

Baseline 0.14 0.17 0.20WH + Baseline N 0.17 0.27 1.12WH + BNR1 0.29 0.40 1.13WH + BNR2 0.38 0.45 0.75

Year IRR Vol (m3) WYLD (m3) Percentage1995 532,486 1,839,334 292001 309,326 7,063,383 3.95

The Kothapally Case, India

Implications on livelihoods

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Conclusions• Total annual runoff reduced by 5 - 30% (Eth) and around 60% (In). At the meso-scale level the total runoff reduction was 30% (In).

• Peak flows reduce and low flows increase – flooding problems, bank ersion and channel sedimentation reduce + more water available during dry seasons.

• Sediment loss reduction

• Crop yield and biomass increase upstream, in particular when combined with nutrient management – food availability and material flow will improve (upstream + downstream)

• Drought proofing? Only for some farms during dry seasons, but significantly higher incomes with WDP during normal and wet years

• DSS tool for location and size of dams

Thanks for the attention

Basin Area: 15129 km2

Total No subbasins: 959 Subasin sizes: 500-3000ha Total No HRUs: 9963 Flow calibrated at 3 gauging stations

Climate data rainfall, Max & Min - 1990-2011 Global weather data – weather genrator

Evapotranspiration Hargreaves’s method

Surface runoff estimation Curve number method

Stream routing Variable storage method

Hydrological data 1990-2007

Model setup and simulation

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Management

Two reserviorsPrincipal spillway Emergency spillway

Elevation* Area(km2) Volume(Mm3)

Elevation Area(km2) Volume(Mm3)

Lake Tana 1784 2,766 20,300 1787 2983 29,100AngerebReservior

2135 0.5 3.53 2138 0.6 5.16

Tillage operations

depth of till of 15cm, and mixing efficiency of 0.3 tillage frequency of 4

Fertilizer application

Pescticide application 2.4.D amine weed killer 1 liter/ha ~ 0.379kg/ha

Subbasins No.: 482 HRUs No.: 786 Total area: 10 sq.km Subbasin size: 1-6ha

Climate data rainfall, Max & Min - 1990-2011

Evapotranspiration Hargreaves’s method Global weather data – weather genrator

Surface runoff estimation Curve number method

Stream routing Variable storage method

Model setup and simulations

Pond

Model Calibration and Validation at Megech

NSE=0.76PBIAS=4.0%

NSE=0.74PBIAS=40.2%