Variations in Hillslope Runoff as Detected Using Geological Strata Coupled with Vegetation Patterns- Implications on Spatially Distributed Desert Runoff Agriculture

Abstract

Sparsely vegetated bedrock slopes in deserts coincide with slope parameters, thus they have important implications on biological, chemical, hydrological and geomorphological processes. Spatial variations in these vegetation patterns, density and communities indicates on relatively humid habitats, which correspond with sinks for high runoff. Relations between the bedrock runoff generation and vegetation patterns may imply on the spatial locations of Byzantine – Early Muslim (400-1000 C.E.; 1600-1000 y BP) agriculture installations. These installations are widespread in the Negev Desert, Israel, utilized sophisticated runoff harvesting techniques by the ancient farmers. Applying a multi-disciplinary approach, we tested vegetation patterns as a precursor for runoff generation along bedrock slopes in the Negev Desert Highlands, and correlated them to the spatial distribution of the Byzantine – Early Muslim runoff agriculture installations. Integrating vegetation patterns, geological substrate data and bedrock-runoff generation data on a GIS model on a large scale (160 km2) of the Negev Highlands yields a synthetic potential runoff map. This map is a unique new product conducted for the first time during this study. Basing on it, runoff yield can be predicted for different scales, ranging from that of a single lithology slope to that of a basin of varying lithologies. Utilizing this methodology, we show that high correlation (80 %) exists between vegetation patterns and spatially located Byzantine – Early Muslim runoff-farming installations. This correlation turns the vegetation coverage as a reliable marker for predicting runoff yield in arid bedrock slopes and imply for stable arid climate in the past 1600 years in the Negev Desert.

Keywords

• desert
• ancient runoff agriculture
• rain-bedrock-runoff relations
• vegetation patterns
• southern levant
• climate variability
• gis