Zonation and Prediction of Land Subsidence (Case Study-Kerman, Iran) *

摘要: Drought and Immethodical ground water withdrawal in recent years has caused numerous problems such as subsidence due to falling of subsurface table, the reduction quality, etc. cities across world. This research a case study deals with harmful effects city Kerman practical monitoring makes prediction land subsidence. The artificial neural network been used for modeling monitored results future A surveying more than 500 installed benchmarks an area 334 square kilometer measure area. Benchmarks were beginning 2004 at end 2004, 2006, 2007. For modeling, extra data obtained from Iranian Surveying Organization before 2004. resulting model showed that, varies between zero 15cm per year different parts City, which depends on subsurface-layered soils, their compressibility, manner withdrawal.