N4 activity update may 2012
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N4 Activity update, May 2012. Original research questions from project brief: How can the consequences of improved rainwater management (RMS) systems be anticipated ( and measured) ? What methods are appropriate under different circumstances?

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N4 Activity update, May 2012

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N4 activity update may 2012

N4 Activity update, May 2012

Original research questions from project brief:

  • How can the consequences of improved rainwater management (RMS) systems be anticipated (and measured)? What methods are appropriate under different circumstances?

  • How can the contribution of improved RMS be assessed relative to the contributions of other factors?

  • How can research on performance be used to further improve RMS design?


N4 activity update may 20121

N4 Activity update, May 2012

N4 team (9 staff; 4 consultants; 10 students):

TL/hydrology/modelling:Charlotte MacAlister

Hydrology/modelling:Solomon Seyoum, Dan Fuka, Zach Easton, Tammo Steenhuis, Francisco Flores

Soils/crop productivity:Teklu Erkossa

Livestockproductivity: Amare Haileslassie, Don Peden

Economics/Livelihoods:Kinde Getnet, Nancy Johnston

Economic data review: Gerba Leta

Spatial Analysis/data:Yenenesh Abebe

Students:

MSc - BedasaEba (also N2), Ayele Abebe (also N2), AlemayehuWudneh, Bamlaku Desalegn, Getnet Taye, Negasa Bane, AddisuAsfaw, Nurelegn Mekuriaw.

PhD - Abeyou Wale, HaimanoteBayabil

2012 budget: $359K reducing to $319K


N4 activity update may 20122

N4 Activity update, May 2012

*Biophysical *Socio-economic

N4 ‘themes’:

  • Developing hydrological (process based) and water resource models of the BNB to anticipate the impact of (large scale) RMS implementation

  • Assessing sediment and nutrient transport, loss and contamination

  • Investigating crop-water and livestock-water productivity > relating to RMS potential

  • Livelihoods and poverty impact analysis

  • Economic assessment of the water, sediment and agronomic components of the primary farming approaches, and modelling anticipated impacts of potential RMS on livelihoods in the BNB

  • Linking to N3 targeting for recommendation of appropriate ‘development domains’ for RMS

  • Analysis of policy implications of basin scale implementation of RMS


Biophysical impacts of rms

Biophysical Impacts of RMS

N4 Activity update, May 2012

  • Improvements in RMS optimize distribution of rainfall amongst different hydrologic components to:

    • increase water availability > less loss and more water storage (soil, surface, GW)

    • reduce evaporation and increase transpiration i.e. crop water productivity = fodder availability and improved livestock water productivity

    • improve soil conditions (reduce sediment loss) and reverse land degradation

  • Evaluate current status of hydrologic components in relation to rainfall from global data

  • Initialize hydrologic and water resource models to evaluate impacts of RMS on water availability, sediment load, soil moisture (and groundwater recharge)


N4 activity update may 2012

N4 Activity update, May 2012

  • Challenges:

  • Properly describing hydro-physical processes e.g. runoff

  • Parameterizing hydrological components (P, ET, soil moisture etc)

  • Representing RMS practices in the process based model (SWAT)

  • Accurate representation of plant water use at large scale (LU-LC)

  • Reliable sediment data

  • Sediment routing in reservoirs within WEAP model

  • Definition of RMS scenarios for impact modelling

  • Linking hydrological, water resource and economic models


N4 activity update may 2012

Optimizing rainfall partitioning and quantifying rainfall-runoff processes

Rainfall

Evaporation

Transpiration

Canopy Evaporation

Soil Evaporation

Vegetation

Land Surface

Water Body

Throughfall

Infiltration

Overland flow

Capillary Rise

Minimize:

Unproductive water use

Soil

Stream

Interflow

Maximize:

TARGET/Productive water use

Capillary Rise

Baseflow

Percolation

Optimize:

Aquifer

Watershed discharge

Transfers


N4 activity update may 2012

Proportion of Rainfall Contributing to Major Hydrologic Components (Climate Forecast System Reanalysis, 31 year mean)


N4 activity update may 2012

Proportion of Rainfall Contributing to Major Hydrologic Components (Climate Forecast System Reanalysis, 31 year mean - Wet Season )


N4 activity update may 2012

Traditional SWAT

Soils

Hydrological Units are defined by a coincidence of soil type and landuse

Landuse

Hydrological

Response Units

So runoff here is calculated the same..

…as here

but we know this is not the case


N4 activity update may 2012

Incorporating Topographic Index in the SWAT model


N4 activity update may 2012

‘Automating’ the Topographic Index in ArcGIS


N4 activity update may 2012

TI


N4 activity update may 2012

Global Soil – to be replaced by Masterplan soil coverage


N4 activity update may 2012

HRU’s


Swat weap interface weap schema

SWAT-WEAP Interface (WEAP schema)

SWAT sub-catchments

Dams / Reservoirs

Irrigation demands

River Networks


N4 activity update may 2012

Next: how to parameterize the RMS in the SWAT process model…..


Anticipating rms impacts on crop water productivity on and off site

Anticipating RMS impacts on Crop Water Productivity – on and off site


N4 activity update may 2012

N4 Activity update, May 2012

Anticipating economic impacts of RMS on households and catchments:

Establish a baseline of current situation using HH, hydrological/sediment and secondary data (at hydrological unit scale or HRU)

Done:

Primary HH data gathered at Jeldu, Diga, Fogera

ECOSAUT populated for Jeldu and Fogera

Preliminary analysis completed for Jeldu

Challenges:

‘Validating’ the model and analysis

Incorporating crop, sediment and runoff data from 3 sites

Scenario development with N2, N3 and stakeholders

Extrapolation of economic impacts of RMS scenarios to larger scale


N4 activity update may 2012

Analysis of policy implications of basin scale implementation of RMS

No output so far……..


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