With the accelerated industrialisation and urbanisation in the Yangtze River Delta region,
shallow groundwater has also suffered some pollution. In order to clarify the current state of …

Rainfall hindcasting is one of the most challenging tasks in the hydrometeorological
forecasting community. The current ad hoc data-driven approaches appear to be insufficient …

Accurate estimation of precipitation over the Qinghai-Tibet Plateau (TP) remains a challenge
at high spatio-temporal scales. This research proposed a machine learning (ML) framework …

The objective function plays an important role in hydrological model calibrations/training,
since it largely determines the values of the model parameters and consequently influences …

This paper proposed a meta heuristic Particle Swarm Optimization to solve unequal area for
optimization problem at unstable demand of marNet. The paper proposed a reconfiguration …

This article proposes a new approach for determining the optimal parameter (β) in the
Inverse Distance Weighted Method (IDW) for spatial interpolation of hydrological data series …

A two-level modeling strategy is formulated to predict groundwater levels (GWL) within a
portion of Lake Urmia's aquifer in NW Iran during 14 years (2001–2015), which both aquifer …

A comparative study between classic linear and intelligent nonlinear time series approaches
for short-term maximum wave height forecasting is presented in this study. The applied …

Abstract In this study, Artificial Intelligence (AI) models along with ensemble techniques were
employed for predicting suspended sediment load (SSL) via single station and multi-station …

Seasonal precipitation forecasting is one of the most challenging tasks in stochastic
hydrology. This article proposes a new ensemble model, called EGP, to a season-ahead …