Lakes have an important role in storing water for drinking, producing hydroelectric power, and environmental, agricultural, industrial uses. In order to optimize the use of lakes, precise prediction lake level (LWL) is a main issue resources management. Due existence nonlinear relations, uncertainty, characteristics time series variables, exact difficult. this study hybrid support vector regression (SVR) grey wolf algorithm (GWO) are used predict fluctuations. Also, three types data...

Evapotranspiration estimation and forecasting is a key step in water management projects, especially water-scarce countries such as Iran. Seasonal autoregressive integrated moving average (SARIMA), support vector machine (SVM), group method of data handling (GMDH) models were developed assessed to find an appropriate model for short long-term monthly reference evapotranspiration the Guilan Plain, northern Monthly meteorological gathered from four weather stations (Anzali, Astara, Manjil,...

Precipitation deficit can affect different natural resources such as water, soil, rivers and plants, cause meteorological, hydrological agricultural droughts. Multivariate drought indexes theoretically show the severity weakness of various types simultaneously. This study introduces an approach for forecasting joint index (JDI) multivariate standardized precipitation (MSPI) by using machine–learning methods entropy theory. JDI MSPI were calculated 1–12 months’ time window (JDI1–12 MSPI1–12),...

Finding an efficient and reliable streamflow forecasting model has always been important challenge for managers planners of freshwater resources. The current study, based on adaptive neuro-fuzzy inference system (ANFIS) model, was designed to predict the Warta river (Poland) 1 day, 2 days, 3 days ahead a data set from period 1993-2013. ANFIS additionally combined with ant colony optimization (ACO) algorithm employed as meta-heuristic ANFIS-ACO which is novelty in prediction studies....

Abstract Water scarcity is the most obstacle faced by irrigation water requirements, likewise, limited available meteorological data to calculate reference evapotranspiration. Consequently, focal aims of investigation are assess potential machine learning models in forecasting requirements (IWR) snap beans evolving multi-scenarios inputs parameters figure out impact meteorological, crop, and soil on IWR. Six were applied, support vector regressor (SVR), random forest (RF), deep neural...

Snow is one of the essential factors in hydrology, freshwater resources, irrigation, travel, pastimes, floods, avalanches, and vegetation. In this study, snow cover northern southern slopes Alborz Mountains Iran was investigated by considering two issues: (1) Estimating area (2) effects droughts on cover. The data were monitored images obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. meteorological (including precipitation, minimum maximum temperature, global solar...

The temperature of river water (TRW) is an important factor in ecosystem predictions. This study aims to compare two different types numerical model for predicting daily TRW the Warta River basin Poland. implemented models were stochastic type—Autoregressive (AR), Moving Average (MA), Autoregressive (ARMA) and Integrated (ARIMA)—and artificial intelligence (AI) type—Adaptive Neuro Fuzzy Inference System (ANFIS), Radial Basis Function (RBF) Group Method Data Handling (GMDH). ANFIS RBF had...

A simultaneous survey of several types droughts, such as meteorological, hydrological, agricultural, economic, and social is possible by using the multivariate standardized precipitation index (MSPI). In this study, accuracy four artificial intelligence (AI) methods, including generalized regression neural network (GRNN), least-square support vector machine (LSSVM), group method data handling (GMDH), adaptive neuro-fuzzy inference systems with fuzzy C-means clustering (ANFIS-FCM), were...

Precipitation deficit causes meteorological drought, and its continuation appears as other different types of droughts including hydrological, agricultural, economic, social droughts. Multivariate Standardized Index (MSPI) can show the drought status from perspective simultaneously. Forecasting multivariate provide good information about future a region will be applicable for planners water divisions. In this study, MLP model hybrid form with Imperialistic Competitive Algorithm (MLP‐ICA)...

One of the most important parts hydrological cycle is evapotranspiration (ET). Accurate estimates ET in irrigated regions are critical to planning, control, and regulation agricultural natural resources. estimation necessary for irrigation scheduling. a nonlinear complex process that cannot be calculated directly. Reference (RET) potential (PET) two primary forms ET. The ideas, equations, application areas PET RET different. These terms have been confused used interchangeably by researchers....

Evapotranspiration represents the water requirement of plants during their growing season, and its accurate measurement at farm is essential for agricultural planners managers. Field measurements evapotranspiration have always been associated with many difficulties that led researchers to seek a way remotely measure this component in horticultural areas. This study aims investigate an indirect approach daily rice crop (ETc) by machine learning (ML) techniques least available climatic...

Abstract Evapotranspiration is one of the most important hydro-climatological components which directly affects agricultural productions. Therefore, its forecasting critical for water managers and irrigation planners. In this study, adaptive neuro-fuzzy inference system (ANFIS) model has been hybridized by differential evolution (DE) optimization algorithm as a novel approach to forecast monthly reference evapotranspiration (ET0). Furthermore, compared with classic stochastic time series...

Evaporation is one of the main components hydrological cycle, and its estimation crucial important for water resources management issues. Access to a reliable estimator tool evaporation simulation in arid semi-arid areas such as Iran, which lose more than 70% their received precipitation by evaporation. Current research employs Bayesian Regularization (BR) Scaled Conjugate Gradient (SCG) algorithms training Multilayer Perceptron (MLP) model (as MLP-BR MLP-SCG) comparing performance with...