Drought assessment and prediction for Gidra river, Slovakia

Abstract

Climate change is affecting every aspect of the world including water resources and water scarcity. Drought is one of many big problems associated with climate change that could occur all over the world. Moreover, hydrological drought is one form of drought that relates to decreased river discharges, below-normal groundwater level, declining the area of wetlands and low water level in lakes or reservoirs. In this study, an assessment of hydrological drought in Gidra river is conducted to characterize dry and normal hydrological years according to Slovak Hydrometeorological Institute (SHMI) Methodology. Furthermore, making benefit of machine learning and artificial intelligence in this field is applicable now, as data of many types are being recorded every day. Deploying machine learning algorithms for the purpose of drought prediction is one way to regulate many operations of water management to prevent irrigation problems. By catching patterns through historical data and deploying machines to learn from those patterns, it is possible to use the values of daily average discharges for January, February, March, and April to correctly predict the hydrological situation in Gidra river whether it is dry or normal, knowing that normal situation refers to wet or normal hydrologically assessed years as the optimal goal in this study is drought assessment and prediction of Gidra river.