Artificial intelligence for suspended sediment load prediction: a review

D Gupta, BB Hazarika, M Berlin, UM Sharma… - Environmental earth …, 2021 - Springer
The estimation of sediment yield concentration is crucial for the development of stream
ventures, watershed management, toxins estimation, soil disintegration, floods, and so on. In …

[HTML][HTML] Flood risk management in arid and semi-arid areas: a comprehensive review of challenges, needs, and opportunities

S Nabinejad, H Schüttrumpf - Water, 2023 - mdpi.com
Despite water shortages and infrequent rainfall in arid and semi-arid areas, their recent
floods show that flooding tends to be more severe and life-threatening. However, flooding is …

Forecast of rainfall distribution based on fixed sliding window long short-term memory

C Chen, Q Zhang, MH Kashani, C Jun… - Engineering …, 2022 - Taylor & Francis
Applying data mining techniques for rainfall modeling because of a lack of sufficient memory
components may increase uncertainty in rainfall forecasting. To solve this issue, in this …

[PDF][PDF] Al-Biruni Based Optimization of Rainfall Forecasting in Ethiopia.

ESM El-Kenawy, AA Abdelhamid… - … Systems Science & …, 2023 - researchgate.net
Rainfall plays a significant role in managing the water level in the reservoir. The
unpredictable amount of rainfall due to the climate change can cause either overflow or dry …

A novel machine learning-based approach for the risk assessment of nitrate groundwater contamination

F Sajedi-Hosseini, A Malekian, B Choubin… - Science of the total …, 2018 - Elsevier
This study aimed to develop a novel framework for risk assessment of nitrate groundwater
contamination by integrating chemical and statistical analysis for an arid region. A standard …

River suspended sediment modelling using the CART model: A comparative study of machine learning techniques

B Choubin, H Darabi, O Rahmati… - Science of the Total …, 2018 - Elsevier
Suspended sediment load (SSL) modelling is an important issue in integrated
environmental and water resources management, as sediment affects water quality and …

Predicting uncertainty of machine learning models for modelling nitrate pollution of groundwater using quantile regression and UNEEC methods

O Rahmati, B Choubin, A Fathabadi, F Coulon… - Science of the Total …, 2019 - Elsevier
Although estimating the uncertainty of models used for modelling nitrate contamination of
groundwater is essential in groundwater management, it has been generally ignored. This …

Modeling monthly pan evaporation using wavelet support vector regression and wavelet artificial neural networks in arid and humid climates

SN Qasem, S Samadianfard, S Kheshtgar… - Engineering …, 2019 - Taylor & Francis
Evaporation rate is one of the key parameters in determining the ecological conditions and it
has an irrefutable role in the proper management of water resources. In this paper, the …

Precipitation forecasting using classification and regression trees (CART) model: a comparative study of different approaches

B Choubin, G Zehtabian, A Azareh… - Environmental earth …, 2018 - Springer
Interest in semiarid climate forecasting has prominently grown due to risks associated with
above average levels of precipitation amount. Longer-lead forecasts in semiarid watersheds …

Deep learning model for daily rainfall prediction: case study of Jimma, Ethiopia

D Endalie, G Haile, W Taye - Water Supply, 2022 - iwaponline.com
Rainfall prediction is a critical task because many people rely on it, particularly in the
agricultural sector. Rainfall forecasting is difficult due to the ever-changing nature of weather …