Maryam Hafezparast Mavadat; Seiran Marabi
Abstract
Surface water quality is of particular importance due to its drinking, industrial, and agricultural water sources. Changes in rainfall, temperature and river discharge can affect surface water quality. In this study, the effect of CANESM2, FIO, GFDL, MIROC climate models and weight composition model ...
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Surface water quality is of particular importance due to its drinking, industrial, and agricultural water sources. Changes in rainfall, temperature and river discharge can affect surface water quality. In this study, the effect of CANESM2, FIO, GFDL, MIROC climate models and weight composition model of CMIP5 (Coupled Model Intercomparison Project) under representative concentration pathways (RCP) of 4.5, 6, 8.5 scenarios on rainfall and temperature were investigated and then monthly discharge of the Aran river in Iran during 2020-2052 and 2053-2085 is predicted using the IHACRES runoff model. Next, the LSTM (Long Short-Term Memory network)-RNN (Recurrent Neural Networks) model were used to predict the total dissolved solids (TDS), sodium adsorption ratio (SAR) for the period 2020-2030. The results showed that the long-term monthly rainfall under the RCP8.5 scenario reported a further decrease compared to the RCP4.5 and RCP6, and the rainfall fluctuations were higher than the other two scenarios. Temperature changes in the second period are higher than the first period, so that in the first period under the scenarios of RCP4.5, RCP6 and RCP8.5 showed respectively 1, 1.5 and 2 degrees Celsius increase, while in the second period, 2, 3 and 4 degrees Celsius is predicted. The average discharge shows by 15.8 % and 20.97 % respectively decrease under the RCP4.5 scenario in the first and second periods, while by 8.51 % and 27.55 % under the RCP6 scenario and 6.38 % and 39.89 % under the RCP8.5 scenario compared to the observed discharge. The mean, maximum, and minimum TDS parameters under RCP4.5 scenario are, respectively, 295, 410, and 263, and 302, 410, and 257 under RCP6 scenario while 292, 410, and 257 mg, for RCP8.5 scenario. These changes are, respectively, 0.42, 0.93 and 0.14 for the SAR parameter in RCP4.5 scenario, and equal to 0.44, 0.94 and 0.1 in scenario 6, while 0.42, 0.93 and 0.15, respectively, for RCP8.5 scenario in Khorramrood river.
Hamidreza Babaali; Zohreh Ramak; Reza Sepahvand
Abstract
Predicting the river discharge is one of the important subjects in water resourcesengineering. This subject is of utmost importance in terms of planning,management, and policy of water resources with the aim of economic andenvironmental development, especially in a country like Iran with limited waterresources. ...
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Predicting the river discharge is one of the important subjects in water resourcesengineering. This subject is of utmost importance in terms of planning,management, and policy of water resources with the aim of economic andenvironmental development, especially in a country like Iran with limited waterresources. Awareness of the relation between rainfall and runoff of basins is aninseparable past of water design studies. Lack of sufficient data on rainfall-runoffdue to the absence of appropriate hydrometric stations reveals the importanceof using indirect methods and heuristic algorithms for estimating the basins'runoff more than before. In the present research, the genetic programmingmodel has been employed to simulate the rainfall-runoff process ofKhorramabad River basin, and in order to introduce the patterns and identify thebest pattern dominating the nature of flow, all statistical data were divided intotwo groups of training and experiment (52 percent training and 48 percentexperiment) and the program was implemented for 1000 replications using fittingfunctions and going through replication and developmental processes so as tofind the optimal replication. Moreover, in order to evaluate the relations obtainedfrom the simulator model, Root Mean Square Error (RMSE) and Mean SquaredError (MSE) indexes and Coefficient of Determination (R2) have been used. Theinvestigations demonstrate that the employed equation 3 has the greatestrelevance with the observational data. Therefore, it is recommended that the saidequation be used for the rainfall-runoff studies of the abovementioned basin.Based on the results, the genetic programming model is an accurate directmethod for predicting the discharge of Khorramabad River basin.
