An integrated statistical-machine learning approach for runoff prediction
Nowadays, great attention has been attributed to the study of runoff and its fluctuation over
space and time. There is a crucial need for a good soil and water management system to …
space and time. There is a crucial need for a good soil and water management system to …
Application of innovative machine learning techniques for long-term rainfall prediction
Rainfall forecasting is critical because it is the componen t that has the strongest link to
natural disasters such as landslides, floods, mass movements, and avalanches. The present …
natural disasters such as landslides, floods, mass movements, and avalanches. The present …
Forecasting of stage-discharge in a non-perennial river using machine learning with gamma test
Abstract Knowledge of the stage-discharge rating curve is useful in designing and planning
flood warnings; thus, develo** a reliable stage-discharge rating curve is a fundamental …
flood warnings; thus, develo** a reliable stage-discharge rating curve is a fundamental …
Modeling of soil moisture movement and wetting behavior under point-source trickle irrigation
The design and selection of ideal emitter discharge rates can be aided by accurate
information regarding the wetted soil pattern under surface drip irrigation. The current field …
information regarding the wetted soil pattern under surface drip irrigation. The current field …
A novel hybrid AIG-SVR model for estimating daily reference evapotranspiration
Reference evapotranspiration (ETo) simulation is of great importance for various procedures
of the hydrological cycle, irrigation, agronomic management, and planning and …
of the hydrological cycle, irrigation, agronomic management, and planning and …
Multi-ahead electrical conductivity forecasting of surface water based on machine learning algorithms
The present research work focused on predicting the electrical conductivity (EC) of surface
water in the Upper Ganga basin using four machine learning algorithms: multilayer …
water in the Upper Ganga basin using four machine learning algorithms: multilayer …
Daily suspended sediment yield estimation using soft-computing algorithms for hilly watersheds in a data-scarce situation: a case study of Bino watershed …
Water erosion creates adverse impacts on agricultural production, infrastructure, and water
quality across the world, especially in hilly areas. Regional-scale water erosion assessment …
quality across the world, especially in hilly areas. Regional-scale water erosion assessment …
Evaluation of CatBoost method for predicting weekly Pan evaporation in subtropical and sub-humid regions
Pan evaporation modeling and forecasting are needed to provide timely, continuous, and
valuable information to support water management. This study aimed to overcome the …
valuable information to support water management. This study aimed to overcome the …
Analysis of spatio-temporal trend in groundwater elevation data from arsenic affected alluvial aquifers–Case study from Murshidabad district, West Bengal, Eastern …
Fluctuation in groundwater level is a time-dependent stochastic process. It is also a function
of various inflow and outflow components to and from the hydrologic system concerned …
of various inflow and outflow components to and from the hydrologic system concerned …
Use of gene expression programming to predict reference evapotranspiration in different climatic conditions
Evapotranspiration plays a pivotal role in the hydrological cycle. It is essential to develop an
accurate computational model for predicting reference evapotranspiration (RET) for …
accurate computational model for predicting reference evapotranspiration (RET) for …