1. Original research questions from project brief: 1.How can the consequences of improved rainwater management (RMS) systems be anticipated (and measured)? What methods are appropriate under different circumstances? 2.How can the contribution of improved RMS be assessed relative to the contributions of other factors? 3.How can research on performance be used to further improve RMS design? N4 Activity update, May 2012

2. 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 Livestock productivity: Amare Haileslassie, Don Peden Economics/Livelihoods:Kinde Getnet, Nancy Johnston Economic data review: Gerba Leta Spatial Analysis/data:Yenenesh Abebe Students: MSc - Bedasa Eba (also N2), Ayele Abebe (also N2), Alemayehu Wudneh, Bamlaku Desalegn, Getnet Taye, Negasa Bane, Addisu Asfaw, Nurelegn Mekuriaw. PhD - Abeyou Wale, Haimanote Bayabil 2012 budget: $359K reducing to $319K

3. 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 N4 Activity update, May 2012 *Biophysical *Socio-economic

4. Biophysical Impacts of RMS 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

5. 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

6. Rainfall Vegetation Land Surface Water Body Soil Aquifer Stream Canopy Evaporation Soil Evaporation Evaporation Transpiration Watershed discharge Baseflow Overland flow Interflow Percolation Throughfall Infiltration Capillary Rise Optimizing rainfall partitioning and quantifying rainfall-runoff processes Unproductive water use TARGET/Productive water use Transfers Minimize: Maximize: Optimize:

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

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

9. Hydrological Units are defined by a coincidence of soil type and landuse Soils Landuse Hydrological Response Units Traditional SWAT So runoff here is calculated the same.. …as here but we know this is not the case

13. Incorporating Topographic Index in the SWAT model

14. ‘Automating’ the Topographic Index in ArcGIS

15. TI

16. Global Soil – to be replaced by Masterplan soil coverage

18. HRU’s

19. SWAT-WEAP Interface (WEAP schema) SWAT sub-catchments Dams / Reservoirs Irrigation demands River Networks

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

21. Anticipating RMS impacts on Crop Water Productivity – on and off site AimObjectiveActivitiesStatus 1. Estimate on-site effects Understand effect on crop water productivity Estimate crop water productivity (CWP) of Vertisols under current and alternative RMS scenarios Model baseline for major crops completed Vertisol areas suitable for different management alternatives identified and mapped Estimate CWP of other soils under selected RMS scenarios Assessment of current RMS at different landscape positions in the selected catchments completed Model baseline for CWP under way with MSc students Identify determinants of CWP Data analysis under way to identify determinant factors of CWP based on the above at the landscape level Quantify soil erosion as an indicator of land degradation Measure sediment and nutrient transport and loss at selected landscapes Sediment sampling and laboratory analysis completed Data preparation and analysis underway Relate nutrient loss to yield loss or replacement cost at landscape level Crop response functions for selected crops to nitrogen and phosphorus established at landscapes level Further analysis underway Extrapolate to larger / basin scale Method to be discussed and agreed upon 2. Estimate off-site effects a. Hydrology and water availability Estimate differential Crop Water Requirement under the RMS scenarios Estimate the impact on flow at sub- catchment levels Method to be discussed and agreed upon b. Water qualityMeasure sediment and nutrient load Sediment and nutrient concentration measured at sub- catchment level 3. Contribute to capacity building Support and supervise graduate students from partner institutions Provide research topics, financial support and guidance 6 students finalizing their thesis on two thematic areas: crop water productivity Sediment and nutrient loss

23. ActivitiesWho is responsibleStatusComment Livestock management practices and its implications on rain water use efficiencies Ayele/Amare/AlanData collected, cleaned, analyzed and draft report in progress Partly under revision Livestock feed sourcing and feeding strategies and its implications on rain water use efficiencies Bedasa/Amare/AlanData collected, cleaned, analyzed and draft report in progress Strategies to integrate livestock into agricultural rain water management Amare/Kebebe/AlanHypothesis developed, (data secured- from student), model selected and sample model run Econometrics models ( GLM, and Tobit)

24. Anticipating economic impacts of RMS on households and catchments: 1.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 2.Scenario development with N2, N3 and stakeholders 3.Extrapolation of economic impacts of RMS scenarios to larger scale N4 Activity update, May 2012

25. Analysis of policy implications of basin scale implementation of RMS No output so far……..