Quantifying water productivity in rainfed cropping systems: Limpopo Province, South Africa John Dimes CPWF PN17 Final Project Workshop June 2009, Univ of Witwatersrand, Johannesburg, South Africa

Impact target Smallholder farming systems in Limpopo Basin Largely Rainfed systems (highly variable) Perennial low productivity (poor fertility) Resource-poor farmers –Highly risk-averse –Poor market access Largely an issue of ‘Green Water’ productivity – near term and longer term

Purpose of Farmer-based research is to raise crop yields and water productivity of green water 680 kg/ha Av. Yield (298) Simulated maize yields, Bulawayo – WP of 1kg grain /mm/ha

Improved germplasm

Soil fertility to boosts yield

What about under farmer conditions? 1 bag No weeding 3 bags Weeded 1 bag Weeded

So where are the highest payoffs? Technology optionWUE (kg Grain /mm Rain) Traditional long season cultivar, no N 1.5 short season, no N1.8 short season, water conservation, no N 2.1 short season, N applied (17kg/ha) 3.2 Short season, N use, water cons. 4.5

CPWF PN17 Activity 1 year study ( ) 1.To measure crop water use (maize, cowpea, groundnut) 2.Evaluate APSIM performance 3.Use APSIM to extrapolate the field based results of crop water productivity (APSIM is a point-source model)

2 Issues: 1.Establish local credibility of model output (above & below ground) 2.Model outputs as information source for off-site impacts

Approach Did not initiate new experimentation Added value to existing field activities by monitoring soil water. Partnerships –Sasol Nitro/Univ Limpopo – NxP in Maize –ARC-GCI:- Gnut and Bambara variety trials –Venda Univ/ACIAR Project – P trial in Gnut

This Presentation Experimental data and simulation results from 1 site – Tafelkop, ARC-GCI –Higher potential ( > 1200masl, >500mm, Sekhukune District, 2007/08 = 717mm) –Sandy Loam Gnut and Bambara variety trial, on-farm Improved varieties of Maize and Cowpea Demonstration plots (30m x30m)

Exptn. Details Different Planting Dates: –Nov 14 th, 2007, Maize (29kgN ha -1 ) and Gnut –Dec 5 th, 2007, Cowpea Soil water measurements –0-10, 10-30, 30-60, 60-90cm, gravimetrically Dates Dec 12th 2007, Gnut and Bambara > 300mm, DUL for soil layers Feb 22nd, 2008, All crops almost 1 month without rain – Crop LL of soil layers Mar 29th, 2008, Mz, Cwp, Gnut Physiological Maturity – Mar rains 70mm, 30mm on 27 th – refilling of soil profile

Filling measurement gaps SOC 0-10cm = 0.51%, PAWC 0-90cm = 90mm : Oct-Nov14= 180mm, to Dec 12 th = 134mm

Total BiomassGrain yield Obs and Pred Yields Driver of crop water useAssessment of water productivity

Obs and Pred Soil Water

Water Balance Components Season rainfall – Oct 1 st 2007 to May 28 th 2008

Water Productivity (kg/mm/ha) WP1 = grain/ m 3 in_crop rainfall WP2 = kg grain/ (m 3 of rainfall +delta SW storage sowing to harvest – using model outputs) WP3 = kg grain/ m 3 of seasonal water balance (Oct 1st 2007 to May 28th 2008) Crops of different value($)

Simulation Analysis Tafelkop soil Groblersdal climate ( ) In Addis, Nov 2008 –Maize response to N (0N, 30N, Non-limiting N) –maize is the dominant crop grown by SHF’s Today Include legume options –Bag of LAN increased from R200 to > R500

Grain yield response

WP response (skip)

Rand returns

Deep Drainage (skip)

Deep Drainage

Conclusions Crop modelling (hydrological modelling AND Livestock modelling) are essential tools for systems analysis and WP assessment: –Caution: need to establish local credibility for these tools. Crop/soil simulation output can provide important data (drainage/runoff) to inform catchment level analysis for different crop management interventions (the green-blue interaction) Crop modelling adds value to field experimentation –Helps fill measurement gaps APSIM performed well in simulation of crop yields and soil water use in Limpopo Basin

Thank You

Some issues with Input data Marble Hall – 800masl – Tafelkop > 1200 masl Used Polokwane Temp data (1230 masl) to adequately simulate crop duration