Faculty of New Sciences and Technologies, University of TehranIranian journal of Ecohydrology2423-60987320200922Forecasting Hydrological Regime Based on Rainfall Regime Using
Two-dimensional Markov Chain in Anzali WatershedForecasting Hydrological Regime Based on Rainfall Regime Using
Two-dimensional Markov Chain in Anzali Watershed6636747757210.22059/ije.2020.299814.1308FAFahimehRaziGraduated Ph.D. Student, Water Engineering Department, Faculty of Agriculture and Natural Resources, Imam Khomeini International University, Qazvin, IranAlirezaShokoohiProfessor of Water Engineering Department, Faculty of Agriculture and Natural Resources, Imam Khomeini International University, Qazvin, Iran0000-0001-8310-8866AlirezaEslamiAssistant professor, Agricultural Research, Education and Extension Organization, Soil Conservation and Watershed Management Research Institute, Tehran, IranJournal Article20200302Despite the need to predict the flow regime in rivers, especially in hydrological drought conditions, little progress has been made in this area; so meteorological situation of basins in general, and meteorological drought in particular, have been used for these purposes. In this study, the prediction of hydrological conditions in rivers based on the basin condition in terms of rainfall is done using Markov chain concepts for the case study of Anzali Wetland catchment with 9 meteorological stations and 20 hydrometric stations over the years. The data from 1985 to 2015 have been used. Two-dimensional Markov probability matrix was used to predict the hydrological status of the rivers by observing the meteorological condition of the basin. The two-dimensional transition probability matrix is different from what has been customary so far, using two different phases of moisture flow in hydrometeorological processes in a matrix so that its columns represent the meteorological state and its rows represent the hydrological conditions. Evaluation of Anzali catchment conditions showed that meteorological and hydrological conditions are the same in each month by the probability of higher than 50%. Based on the results of the 2D matrix of the probability of transfer, the probability of being in normal, wet and dry hydrologic conditions, if these conditions occur in a step ahead in the meteorological phase, is 80, 50 and 40%, respectively. Based on the achieved results, with the expected value of the pertinent discharges in the forecasted hydrological condition concerning the former step climatological state, the probable discharge in the river is predicted.Despite the need to predict the flow regime in rivers, especially in hydrological drought conditions, little progress has been made in this area; so meteorological situation of basins in general, and meteorological drought in particular, have been used for these purposes. In this study, the prediction of hydrological conditions in rivers based on the basin condition in terms of rainfall is done using Markov chain concepts for the case study of Anzali Wetland catchment with 9 meteorological stations and 20 hydrometric stations over the years. The data from 1985 to 2015 have been used. Two-dimensional Markov probability matrix was used to predict the hydrological status of the rivers by observing the meteorological condition of the basin. The two-dimensional transition probability matrix is different from what has been customary so far, using two different phases of moisture flow in hydrometeorological processes in a matrix so that its columns represent the meteorological state and its rows represent the hydrological conditions. Evaluation of Anzali catchment conditions showed that meteorological and hydrological conditions are the same in each month by the probability of higher than 50%. Based on the results of the 2D matrix of the probability of transfer, the probability of being in normal, wet and dry hydrologic conditions, if these conditions occur in a step ahead in the meteorological phase, is 80, 50 and 40%, respectively. Based on the achieved results, with the expected value of the pertinent discharges in the forecasted hydrological condition concerning the former step climatological state, the probable discharge in the river is predicted.https://ije.ut.ac.ir/article_77572_7c191c49a6e4f6eabc9ed19b044cc7b3.pdf