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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Original research questions from project brief:
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
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 2012
Optimizing rainfall partitioning and quantifying rainfall-runoff processes
Unproductive water use
TARGET/Productive water use
Proportion of Rainfall Contributing to Major Hydrologic Components (Climate Forecast System Reanalysis, 31 year mean - Wet Season )
Hydrological Units are defined by a coincidence of soil type and landuse
So runoff here is calculated the same..
but we know this is not the case
Dams / Reservoirs
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)
Primary HH data gathered at Jeldu, Diga, Fogera
ECOSAUT populated for Jeldu and Fogera
Preliminary analysis completed for Jeldu
‘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
Analysis of policy implications of basin scale implementation of RMS
No output so far……..