Filters








51 Hits in 11.1 sec

The Development of a Hybrid Wavelet-ARIMA-LSTM Model for Precipitation Amounts and Drought Analysis

Xianghua Wu, Jieqin Zhou, Huaying Yu, Duanyang Liu, Kang Xie, Yiqi Chen, Jingbiao Hu, Haiyan Sun, Fengjuan Xing
2021 Atmosphere  
Wavelet transformation (WT), autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM) methods were utilized to depict the time series, and a new hybrid model wavelet-ARIMA-LSTM  ...  Therefore, a case study at three meteorological sites which represent three different climate types was explored, and we used time series analysis of monthly precipitation and the grey theory methods for  ...  Long short-term memory (LSTM) is a type of time-cyclic neural network, that is specifically used to solve the long-term correlation problem of general RNN.  ... 
doi:10.3390/atmos12010074 fatcat:zrkbs6mne5c4xjithnf53u7iyy

Estimation of Drought by Streamflow Drought Index (SDI) and Artificial Neural Networks (ANNs) in Ankara-Nallihan Region

Tülay Akkurt Eroğluer, Halit Apaydin
2020 Turkish Journal of Agriculture: Food Science and Technology  
In this study, it is aimed to predict drought in Nallihan region by using streamflow drought index and artificial neural network method which is a part of artificial intelligence approaches.  ...  The use of 6-month drought data for the streamflow drought index is expected to be useful in predicting future drought.  ...  Agana and Homaifar (2017) examined the use of deep learning algorithms in drought predictions. Katip (2018) determined the meteorological drought in Bursa province by SPI index and ANN method.  ... 
doi:10.24925/turjaf.v8i2.348-357.3045 fatcat:twcyfcn6qzdx7dckor3fbgyd4m

Prediction of drought-induced reduction of agricultural productivity in Chile from MODIS, rainfall estimates, and climate oscillation indices

Francisco Zambrano, Anton Vrieling, Andy Nelson, Michele Meroni, Tsegaye Tadesse
2018 Remote Sensing of Environment  
A B S T R A C T Global food security is negatively affected by drought. Climate projections show that drought frequency and intensity may increase in different parts of the globe.  ...  multi-layer feedforward neural network architecture, often called deep learning (DL), where all predictors for all units were combined in a single spatiotemporal model.  ...  Acknowledgements Francisco Zambrano was funded by the CONICYT, Chile Scholarship/National Ph.D. 21141028.  ... 
doi:10.1016/j.rse.2018.10.006 fatcat:rvcrqmjtmfbhlj6uva5kanms5y

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

Demeke Endalie, Getamesay Haile, Wondmagegn Taye
2021 Water Science and Technology : Water Supply  
We proposed a Long Short-Term Memory (LSTM)-based prediction model capable of forecasting Jimma's daily rainfall.  ...  In this study, we carry out a rainfall predictive model for Jimma, a region located in southwestern Oromia, Ethiopia.  ...  ACKNOWLEDGEMENTS This study was performed by three academic staff at Jimma Institute of Technology, Jimma University, Ethiopia.  ... 
doi:10.2166/ws.2021.391 fatcat:7o7s5dwrjvfdxftk426fkrhnem

Analysis of hydrological data with correlation matrices: technical implementation and possible applications

Johannes Christoph Haas, Matthew Switanek, Steffen Birk
2018 Environmental Earth Sciences  
This is done by first standardizing the data using different drought indices and, subsequently, visualization of correlation matrices or plots of data on maps.  ...  This wealth of data, however, poses new challenges in effectively making use of it.  ...  Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creat iveco mmons .org/licen ses/by/4.0/), which permits unrestricted use,  ... 
doi:10.1007/s12665-018-7469-4 fatcat:ntnn5cnrnfaedmzju2ilebfmry

Evidence for Intensification in Meteorological Drought Since the 1950s and Recent Dryness–Wetness Forecasting in China

Ruting Yang, Bing Xing
2022 Atmosphere  
The standardized precipitation evapotranspiration index (SPEI) with a 12-month timescale was adopted to monitor dry–wet status over China from 1951 to 2021.  ...  The results indicate that the dry–wet climate in China overall exhibits interannual variability characterized by intensified drought.  ...  The commonly used meteorological drought indices include the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) [33] .  ... 
doi:10.3390/atmos13050745 fatcat:vft5own64jalnh5r6nir7lnzna

A Review on Interpretable and Explainable Artificial Intelligence in Hydroclimatic Applications

Hakan Başağaoğlu, Debaditya Chakraborty, Cesar Do Lago, Lilianna Gutierrez, Mehmet Arif Şahinli, Marcio Giacomoni, Chad Furl, Ali Mirchi, Daniel Moriasi, Sema Sevinç Şengör
2022 Water  
These AI models can transform into XAI models when they are coupled with the explanatory methods such as the Shapley additive explanations and local interpretable model-agnostic explanations.  ...  The review concludes with a proposed XAI framework to enhance the interpretability and explainability of AI models for hydroclimatic applications.  ...  Precipitation (P) is a discontinuous hydroclimatic variable, especially in arid and semi-arid regions.  ... 
doi:10.3390/w14081230 doaj:dd344c65604e4ca582d8c55c4bf8eb01 fatcat:2dc6gr3t5zd6hou734ujrrsv6e

Documentary data and the study of past droughts: a global state of the art

Rudolf Brázdil, Andrea Kiss, Jürg Luterbacher, David J. Nash, Ladislava Řezníčková
2018 Climate of the Past  
Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers  ...  </strong> The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades.  ...  SPI (Standardized Precipitation Index; McKee et al., 1993) is one of those frequently employed in examinations of meteorological drought.  ... 
doi:10.5194/cp-14-1915-2018 fatcat:t2anoycbfvdzrmfqkbj4wf2o2m

A changing Arctic - dialogues from the North

Dragana Bojovic, Marta Terrado, Isadora Christel, Francisco Javier Doblas-Reyes, Halldór Jóhannsson, Luisa Cristini, Thomas Jung
2018 Zenodo  
Proceedings of the 5th International Climate Change Adaptation Conference, Cape Town, South Africa, 18 -21 June 2018  ...  Acknowledgements Acknowledgements This work was carried out under the Adaptation at Scale in Semi-Arid Regions project (ASSAR).  ...  Proceedings Report by the African Climate and Development Initiative (ACDI), the National Research Foundation (NRF) and the Adaptation Network.  ... 
doi:10.5281/zenodo.2590955 fatcat:6nibfwoohrh63igcehy3m2dgg4

Relationship between the tropical Pacific and Indian Ocean sea-surface temperature and monthly precipitation over the central highlands, Vietnam

Tinh Dang Nguyen, Cintia Uvo, Dan Rosbjerg
2007 International Journal of Climatology  
of droughts using the standardized precipitation index (SPI) in Karoon river basin, Iran M. Mohseni Saravi*, A. A. Safdari & A.  ...  A useful index for drought monitoring, based only on monthly precipitation, is the Standardized Precipitation Index (SPI); here we assume that it properly describes the climatic condition of a particular  ...  ; simulation and modelling of water resource systems; forecasting and control of quantity and quality of water; economic and social aspects of water use; legislation and water resources protection.  ... 
doi:10.1002/joc.1486 fatcat:b7u5rdyrkjcpnd4vp63hhkocbe

A process-based typology of hydrological drought

A. F. Van Loon, H. A. J. Van Lanen
2011 Hydrology and Earth System Sciences Discussions  
The occurrence of hydrological drought types is determined by climate and catchment characteristics.  ...  A general framework is proposed to identify drought type occurrence in relation to climate and catchment characteristics.  ...  Part of the funding was provided by the European Union (FP7) project DROUGHT-R & SPI (contract no. 282769).  ... 
doi:10.5194/hessd-8-11413-2011 fatcat:oua5btcctvb7dpbpmxwricvzaa

A process-based typology of hydrological drought

A. F. Van Loon, H. A. J. Van Lanen
2012 Hydrology and Earth System Sciences  
The occurrence of hydrological drought types is determined by climate and catchment characteristics.  ...  A general framework is proposed to identify drought type occurrence in relation to climate and catchment characteristics.</p>  ...  Part of the funding was provided by the European Union (FP7) project DROUGHT-R & SPI (contract no. 282769).  ... 
doi:10.5194/hess-16-1915-2012 fatcat:mtvvpmjc4ra3xeeujjr7vx7t4e

ITIKI: bridge between African indigenous knowledge and modern science of drought prediction

Muthoni Masinde, Antoine Bagula
2011 Knowledge Management for Development Journal  
Declaration This thesis is a presentation of my original research work.  ...  Short Term (1), Medium Term (2) or Long Term 3); Lead-Timeranging from 1 to 14 days for Short Term, 1 to 12 months for Medium Term and 1 to 4 years for Long Term Example:Df;HKEM;2,2 -A request for Medium-Term  ...  They have no learning capability or memory.  ... 
doi:10.1080/19474199.2012.683444 fatcat:zkhefk7kgjdadasijz26yag3m4

Extreme Drought Affects Visitation and Seed Set in a Plant Species in the Central Chilean Andes Heavily Dependent on Hummingbird Pollination

Mary T. K. Arroyo, Valeria Robles, Ítalo Tamburrino, Jaime Martínez-Harms, René D. Garreaud, Paola Jara-Arancio, Patricio Pliscoff, Ana Copier, Jonás Arenas, Joaquín Keymer, Kiara Castro
2020 Plants  
Central Chile experienced a mega drought between 2010 and 2020 which reached an extreme in the austral summer of 2019–2020.  ...  Rising temperatures and increasing drought in Mediterranean-type climate areas are expected to affect plant–pollinator interactions, especially in plant species with specialised pollination.  ...  We appreciate the useful suggestions supplied by the reviewers.  ... 
doi:10.3390/plants9111553 pmid:33198222 fatcat:6ttcjrlyt5gszc44ep4ansj52u

A review of machine learning applications in wildfire science and management [article]

Piyush Jain, Sean C P Coogan, Sriram Ganapathi Subramanian, Mark Crowley, Steve Taylor, Mike D Flannigan
2020 arXiv   pre-print
There exists opportunities to apply more current ML methods (e.g., deep learning and agent based learning) in wildfire science.  ...  Finally, we stress that the wildfire research and management community plays an active role in providing relevant, high quality data for use by practitioners of ML methods.  ...  Acknowledgments The motivation for this paper arose from the "Not the New Normal" BC AI Wildfire Symposium held in Vancouver, BC, on 12 October 2018.  ... 
arXiv:2003.00646v1 fatcat:5ufhtbwlsvd2rdk3ogbmqpnxuu
« Previous Showing results 1 — 15 out of 51 results