1 Innovations in SLM, decision support and up-scaling at local and national level WOCAT Share Fair Pretoria, South Africa, May 2013 Feras Ziadat, Mohammed Karrou, Theib Oweis, Tarek Kandakji International Center for Agricultural Research in the Dry Areas (ICARDA) Similarity and suitability analysis to assist the out-scaling of SLM at national and regional levels in West Asia and North Africa

About ICARDA Vision: Improved livelihoods of the resource-poor in the dry areas Geographic Mandate: non tropical dry areas Partners: National Agricultural Research Systems Advanced Research Institutes Development organizations Rural communities One of 15 CGIAR centres (Consultative Group on International Agricultural Research)

Motivation for out-scaling … Technologies are being developed and tested in the Benchmark and satellite sites to improve productivity and livelihood Examples: Rainfed Benchmark: supplemental irrigation Rangeland Benchmark: water harvesting Irrigated Benchmark: raised bed techniques Out-scaling of proved technologies and best bet practices (SLM) to other larger areas 3

4 RB BB IB Rainfed Benchmark – Morocco Irrigated Benchmark – Egypt Badia (Rangeland) Benchmark – Jordan Concept of Benchmarks and Satellite sites For West Asia and North Africa (WANA or MENA)

Supplemental irrigation: addition of small amounts of water, to rain- fed crops, during the critical stages of crop growth in order to provide sufficient moisture for normal (optimal) plant growth. Rainfed Benchmark and Satellite sites Supplemental irrigation Deficit SI and improved crop management package (such as early sowing) increased wheat yield by 33% compared to farmer management; The improved package almost doubled water productivity; The package saved 28% of irrigation water.

Water-saving irrigation techniques, such as the raised bed system, reduces drastically irrigation water consumption without any significant loss in crop yields.. Irrigated Benchmark and Satellite sites Raised-bed technology The raised bed machine helped the growers to: save the applied water by 20%, reduce seed rate by 50%, decrease farming cost by 25%, reduce planting time by 88% Increase crops yields by 15-25%.

Valerrani mechanized water harvesting system: direct runoff water from collection area and concentrate it in the cultivated areas.. Badia (Rangeland) Benchmark and Satellite sites Valerrani water harvesting The system helped in: Improving shrub production compared with farmers practice (Barley). reduce runoff and soil losses Without water harvesting (Farmers Practice) With water harvesting intervention Soil erosion assessment

8 Other SLM options Continuous contour ridges Contour Stone bunds (continuous) Semi-circular stone bunds Intercropping with cover crops Reduced tillage or no-tillage Contour tillage Addition of organic manure Check dams in dry areas

9 However, adoption rate by farmers is still un-satisfactory Technical options to suit various biophysical conditions are known and available Adoption by farmers Out-scaling of these technologies to enhance adoption and uptake by farmers Decision makers need guidance to target potential areas for out-scaling

How to out-scale ? Similarity analysis: identifying similar areas with potential for successful implementation of SLM practices 10 Define key expert criteria for each Benchmark Identify data needed Produce similarity maps at regional level Verification of similarity maps using detailed data at national level Revise the criteria and similarity maps Provide maps for decision-making process (Research and Development

Similarity criteria Preliminary criteria and similarity maps verified by national experts Supplemental Irrigation package Raised-bed Package Valerrani Water Harvesting package

12 Data collection and analysis at regional level RainfallLand use Soil DepthSoil Type / texture

13 Similarity maps for three agro-ecosystems Regional level Coarse maps at regional level & verification at country level

14 Similarity maps for three agro-ecosystems National level Use same criteria at regional level but with more detailed data

15 Compare similarity results at national level with regional level for fine-tunning Produce final similarity maps for out-scaling of the technologies

16 Detailed Suitability maps for similar areas Use detailed data within country, but Out-scalable to other countries with similar bio-physical conditions

17 Concluding remarks Similarity and suitability analysis are promising tools to facilitate out-scaling of sustainable land management Provide means to facilitate within and among countries collaboration to provide regional coverage of data and information needed for sustainable land management