Open AccessCN Modeling for Predicting Discharge in Lesti Sub-watershed
Author(s) -
Abdul Azis Hoesein*,
Mohammad Bisri,
Lily Montarcih Limantara,
Ery Suhartanto
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.l3544.1081219
Subject(s) - watershed , hydrology (agriculture) , environmental science , cover (algebra) , land cover , time of concentration , watershed management , land use , computer science , engineering , civil engineering , geotechnical engineering , machine learning , mechanical engineering
This research intends to accurately mapping the Curve Number (CN) that is as the function of cover type, land use treatment, hydrology condition, and hydrologic soil group in the Lesti sub-watershed,. The methodology consists of to build the suitable CN modeling for predicting discharge in the Lesti sub-watershed and then to evaluate the result accurately. The value of CN is obtained from the mathematical formula with the input is rainfall depth and discharge. The result of CN modeling for the Lesti sub-watershed is accurate enough as is made by the United States Department of Agriculture (USDA) in USA. In addition, the CN mapping can be directly used by the engineers of the manager and designer on the water resources structures in Lesti sub-watershed