Quantifying the Influences of Land Use and Rainfall Dynamics on Probable Flood Hazard Zoning

Flooding is Pakistan's most common natural hazard, and it exacerbated by increased rainfall urbanization. Khyber Pakhtunkhwa (KPK), Pakistan flood-prone zones were determined superimposing six flood parameters in an ArcGIS environment: elevation, slope, accumulation, land cover, soil geometry, gap/buffer from water channel. Cellular automata based on artificial neural network (CA-ANN) along QGIS plugin module of Land Use Change Simulations (MOLUSCE) was used for predicting year 2050 use, with a kappa value 0.83. The results indicated that the 75775 km2 area covered this research region, 3.37% (2553.62 km2) falls extremely high risk, 18.44% (13972.91 11.26% (8532.27 moderate 0.51% (386.45 low just 66.42% (50329.76 very risk areas. In KPK, like any other place, multi-criteria risk-vulnerability assessment consequently necessary preparation post-hazard planning. Without doubt, outcomes reported here are crucial assessments hazard management decision-making.
 Key words: disasters; floods; remote sensing; geographic information system, evaluation; weighted overlay.