List of articles (by subject) Hydrology
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Open Access Article
1 - Analysis of meander evolution of Dez River in agricultural and mountainous areas by Google Earth Engine (GEE) and GIS
Ladan Khedri GharibvandBackground and objective:The rivers are vital natural resources for human activities. Knowledge of the structure and dynamics of rivers is important to understand river characteristics. Differences due to the season in river flow lead to unsteady sediment transport capa MoreBackground and objective:The rivers are vital natural resources for human activities. Knowledge of the structure and dynamics of rivers is important to understand river characteristics. Differences due to the season in river flow lead to unsteady sediment transport capacities that cause riverside erosion and the development of meandering channels. Channel migration might produce a crucial problem for water supply and hydraulic structures. Therefore, the study of a stream channel dynamical is necessary. In this research, we investigate the meander evolution of the Dez River in agricultural and mountainous areas by GEE and Geographical Information System (GIS) during 1995 - 2021.Materials and methods:To study the meander evolution of the Dez River, the Sinuosity Index (SI) of the river in the mountainous and agricultural areas was calculated. Then the slope and The Digital Elevation Model (DEM) maps were prepared using NASA SRTM. Also, the soil texture map was derived from the U.S. Department of Agriculture (USDA) system and the monthly runoff map was prepared in GEE.Results and conclusion:The results showed that SI in the mountainous area was constant (2.10), but it changed in agricultural areas (2.10-2.14). Also, the slope in agricultural areas was 1-4 degrees, the elevation was 30-36 meters, and the soil type was loam and clay loam. Due to the increase in runoff in recent years and the erodibility of the riverbed, it seems that the meander evolution of the Dez River is due to soil type and runoff increase. Manuscript profile -
Open Access Article
2 - Monitoring annual precipitation changes in Dezful plain with statistical analysis and time series
Yaser Sabzevari Saeid Eslamian Keyvan MoradalivandBackground and objective:Predicting and studying the trend of climate variables in the future plays an important role in the optimal management of water resources. Different methods are used to determine the trend of change. One of the most common methods of trend chang MoreBackground and objective:Predicting and studying the trend of climate variables in the future plays an important role in the optimal management of water resources. Different methods are used to determine the trend of change. One of the most common methods of trend change analysis is time series analysis. Time series is a set of observations about a variable that is measured at discrete points in time, usually at equal distances, and arranged in chronological orderMaterials and methods:In the present study, the trend of precipitation changes in Dezful plain during 32 years was investigated and by selecting the appropriate time series model, a forecast was made for the next ten years. Man-Kendall’s non-parametric test was used to investigate the trend of precipitation changes.Results and conclusion:The result of this test showed that the annual precipitation of Dezful had a decreasing trend due to having a Man-Kendall statistic of -1.6. To select the appropriate time series model, data preparation (trend elimination and normalization) was performed first. Data stagnation was assessed with autocorrelation (ACF) and partial autocorrelation (PACF) charts. Using the differentiation method, the data became static (eliminating the mean trend) by applying one-time differentiation. By static data, random models were used to predict the average annual precipitation. Then, by fitting different Arima models and considering the criteria of T, P-VALUE less than 0.05 and Bayesian information criterion (BIC), the Arima model (3,1,1) was selected as the most appropriate model and to verify this the model was predicted for the period 2011 to 2018. The validation results showed that the prediction of this model is acceptable according to the actual values. Then, based on this model, a forecast was made for the next ten years from 2019 to 2028, which is predicted that the precipitation trend will decrease for the next period. Manuscript profile