A review of drought monitoring with big data: Issues, methods, challenges and research directions

H Balti, AB Abbes, N Mellouli, IR Farah, Y Sang… - Ecological …, 2020 - Elsevier
Over recent years, the frequency and intensity of droughts have increased and there has
been a large drying trend over many parts of the world. Consequently, drought monitoring …

A review of drought monitoring using remote sensing and data mining methods

R Inoubli, AB Abbes, IR Farah, V Singh… - … for Signal and …, 2020 - ieeexplore.ieee.org
Today, drought has become part of the identity as well as the fate of many countries. In fact,
drought is considered among the most damaging natural disasters. The severe …

Soil temperature estimation with meteorological parameters by using tree-based hybrid data mining models

MT Sattari, A Avram, H Apaydin, O Matei - Mathematics, 2020 - mdpi.com
The temperature of the soil at different depths is one of the most important factors used in
different disciplines, such as hydrology, soil science, civil engineering, construction …

The investigation of the applicability of data-driven techniques in hydrological modeling: The case of seyhan basin

E Turhan, MK Keleş, A Tantekin… - Rocznik Ochrona …, 2019 - yadda.icm.edu.pl
Hydrology science is described as the life cycle of water. It is a fact that rainfall-runoff
modeling and the other data-driven techniques are significant events in this cycle …

[HTML][HTML] Drought Monitoring Using MOWCATL Data Mining Algorithm in Aras Basin, Turkey

E Topçu - Earth Sciences Research Journal, 2022 - scielo.org.co
Drought is a natural phenomenon that occurs frequently and has some adverse effects on
the ecosystem and humanity. Determination of drought beforehand is vital for optimal …

Meteorological Drought Assessment and Prediction in Association with Combination of Atmospheric Circulations and Meteorological Parameters via Rule Based …

FS Sureh, MT Sattari, H Rostamzadeh… - Journal of Agricultural …, 2024 - dergipark.org.tr
The development of data-driven models in conjunction with the advances in technologies
regarded as remote sensing in generating recorded data from satellites has guided water …

Evaluation of the Decision Tree Model in Precipitation Prediction (Case study: Yazd Synoptic Station)

MT Dastourani, A Habibipoor, MR Ekhtesasi… - Iran-Water Resources …, 2013 - iwrr.ir
Undesirable effects of droughts on the agricultural and economical sectors and especially
on the natural resources are intense. Different methods have been presented to predict the …

A binary granular algorithm for spatiotemporal meteorological data mining

H Wang, J Yang, Z Wang… - 2015 2nd IEEE …, 2015 - ieeexplore.ieee.org
This paper introduces the binary granule into the algorithm in computing and mining
meteorological data. By redefining the binary algorithm, matching operators, convergence …

Estimation procedures for the GEV distribution for the minima

JA Raynal-Villasenor, ME Raynal-Gutierrez - Journal of Hydrology, 2014 - Elsevier
The biased and unbiased moments (MOM1 and MOM2), maximum likelihood (ML), sextiles
(SEX1 and SEX2) and probability weighted moments (PWM) methods for the estimation the …

Analysis of urban water consumption in Babol County using data mining methods

M AhangarCani, SH Khasteh - Scientific-Research Quarterly of …, 2019 - sepehr.org
Extended Abstract Introduction and Objective Due to the location of Iran in dry regions of the
Middle East, and also because of the rapid increase in its urban population and water …