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(2023, January) Stochastic Environmental Research and Risk Assessment Vol. 37 (1) Springer Science and Business Media LLC

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Reference TypeJournal (issue)
JournalStochastic Environmental Research and Risk AssessmentISSN1436-3240
Year2023 (January)Volume37
Issue1   >
PublisherSpringer Science and Business Media LLC
Mindat Ref. ID15672611Long-form Identifiermindat:1:5:15672611:7
GUID0
Full Reference(2023, January) Stochastic Environmental Research and Risk Assessment Vol. 37 (1) Springer Science and Business Media LLC
Plain Text(2023, January) Stochastic Environmental Research and Risk Assessment Vol. 37 (1) Springer Science and Business Media LLC
In(2023) Stochastic Environmental Research and Risk Assessment Vol. 37. Springer Science and Business Media LLC

Contains

Khan, Muhammad Fawad, Sulaiman, Muhammad, Alshammari, Fahad Sameer (2023) A hybrid heuristic-driven technique to study the dynamics of savanna ecosystem. Stochastic Environmental Research and Risk Assessment, 37 (1) 1-25 doi:10.1007/s00477-022-02270-7
Mathew, Micky, Sreelash, K., Jacob, Amala Anie, Mathew, Merin Mariam, Padmalal, D. (2023) Diverging monthly rainfall trends in south peninsular India and their association with global climate indices. Stochastic Environmental Research and Risk Assessment, 37 (1) 27-48 doi:10.1007/s00477-022-02272-5
Moayedi, Hossein, Khasmakhi, Mohammad Ali Salehi Amin (2023) Wildfire susceptibility mapping using two empowered machine learning algorithms. Stochastic Environmental Research and Risk Assessment, 37 (1) 49-72 doi:10.1007/s00477-022-02273-4
Ji, Juan, Chen, Junfei, Ding, Tonghui, Gu, Yan (2023) Security assessment and obstacle factors diagnosis of water-energy-food nexus based on pressure-state-response framework in Northwest China. Stochastic Environmental Research and Risk Assessment, 37 (1) 73-88 doi:10.1007/s00477-022-02274-3
Tongal, Hakan, Booij, Martijn J. (2023) Simulated annealing coupled with a NaĂŻve Bayes model and base flow separation for streamflow simulation in a snow dominated basin. Stochastic Environmental Research and Risk Assessment, 37 (1) 89-112 doi:10.1007/s00477-022-02276-1
Elbeltagi, Ahmed, Kumar, Manish, Kushwaha, N. L., Pande, Chaitanya B., Ditthakit, Pakorn, Vishwakarma, Dinesh Kumar, Subeesh, A. (2023) Drought indicator analysis and forecasting using data driven models: case study in Jaisalmer, India. Stochastic Environmental Research and Risk Assessment, 37 (1) 113-131 doi:10.1007/s00477-022-02277-0
Wan, Xinyu, Wu, Qingyang, Cao, Zhenyu, Wu, Yan (2023) Real-time flood forecasting based on a general dynamic neural network framework. Stochastic Environmental Research and Risk Assessment, 37 (1) 133-151 doi:10.1007/s00477-022-02271-6
Liu, Song, She, Dunxian, Zhang, Liping, Xia, Jun (2023) A hybrid time- and signature-domain Bayesian inference framework for calibration of hydrological models: a case study in the Ren River basin in China. Stochastic Environmental Research and Risk Assessment, 37 (1) 153-173 doi:10.1007/s00477-022-02282-3
Rashidi, Rajab, Khaniabadi, Yusef Omidi, Sicard, Pierre, De Marco, Alessandra, Anbari, Khatereh (2023) Ambient PM2.5 and O3 pollution and health impacts in Iranian megacity. Stochastic Environmental Research and Risk Assessment, 37 (1) 175-184 doi:10.1007/s00477-022-02286-z
Pansa, Alessandro, Butera, Ilaria, Gómez-Hernández, J. Jaime, Vigna, Bartolomeo (2023) Predicting discharge from a complex karst system using the ensemble smoother with multiple data assimilation. Stochastic Environmental Research and Risk Assessment, 37 (1) 185-201 doi:10.1007/s00477-022-02287-y
Baysal, Asli, Saygin, Hasan (2023) An assessment of ecological and possible human health risks from Cr and Ni in sediments affected by the industrial marine area in Tuzla Aydinli Bay, Istanbul, Turkey between 2016–2020. Stochastic Environmental Research and Risk Assessment, 37 (1) 203-217 doi:10.1007/s00477-022-02289-w
Pereira, F. Catarina, Gonçalves, A. Manuela, Costa, Marco (2023) Short-term forecast improvement of maximum temperature by state-space model approach: the study case of the TO CHAIR project. Stochastic Environmental Research and Risk Assessment, 37 (1) 219-231 doi:10.1007/s00477-022-02290-3
Masroor, Md, Razavi-Termeh, Seyed Vahid, Rahaman, Md Hibjur, Choudhari, Pandurang, Kulimushi, Luc Cimusa, Sajjad, Haroon (2023) Adaptive neuro fuzzy inference system (ANFIS) machine learning algorithm for assessing environmental and socio-economic vulnerability to drought: a study in Godavari middle sub-basin, India. Stochastic Environmental Research and Risk Assessment, 37 (1) 233-259 doi:10.1007/s00477-022-02292-1
Yang, Wenjing, Du, Juan, Jia, Bowen, Yang, Ling, Dong, Renze, Li, Xinyi (2023) $$\hbox {PM}_{2.5}$$ concentration prediction in Lanzhou, China, using hyperchaotic cuckoo search—extreme learning machine. Stochastic Environmental Research and Risk Assessment, 37 (1) 261-273 doi:10.1007/s00477-022-02293-0
Kocijan, Juš, Hvala, Nadja, Perne, Matija, Mlakar, Primož, Grašič, Boštjan, Božnar, Marija Zlata (2023) Surrogate modelling for the forecast of Seveso-type atmospheric pollutant dispersion. Stochastic Environmental Research and Risk Assessment, 37 (1) 275-290 doi:10.1007/s00477-022-02288-x
Shen, Lianfeng, Zeng, Jin, Guo, Erhui, Cheng, Yongxia, Li, Limei, Niu, Cunyang, Yuan, Yuan, Ma, Li (2023) Source apportionment and risk assessment of heavy metals in urban soils from a central China city by using positive matrix factorization model coupled with Monte Carlo simulation. Stochastic Environmental Research and Risk Assessment, 37 (1) 291-304 doi:10.1007/s00477-022-02297-w
Laha, Arnab Kumar, Majumdar, Sourav (2023) A multi-type branching process model for epidemics with application to COVID-19. Stochastic Environmental Research and Risk Assessment, 37 (1) 305-325 doi:10.1007/s00477-022-02298-9
Gabriel, Edith, Rodríguez-Cortés, Francisco, Coville, Jérôme, Mateu, Jorge, Chadœuf, Joël (2023) Mapping the intensity function of a non-stationary point process in unobserved areas. Stochastic Environmental Research and Risk Assessment, 37 (1) 327-343 doi:10.1007/s00477-022-02304-0
Sardar, Iqra, Akbar, Muhammad Azeem, Leiva, VĂ­ctor, Alsanad, Ahmed, Mishra, Pradeep (2023) Machine learning and automatic ARIMA/Prophet models-based forecasting of COVID-19: methodology, evaluation, and case study in SAARC countries. Stochastic Environmental Research and Risk Assessment, 37 (1) 345-359 doi:10.1007/s00477-022-02307-x
Cui, Xi, Ailijiang, Nuerla, Mamitimin, Yusuyunjiang, Zhong, Naifu, Cheng, Wenhu, Li, Nanxin, Zhang, Qiongfang, Pu, Miao (2023) Pollution levels, sources and risk assessment of polycyclic aromatic hydrocarbons in farmland soil and crops near Urumqi Industrial Park, Xinjiang, China. Stochastic Environmental Research and Risk Assessment, 37 (1) 361-374 doi:10.1007/s00477-022-02299-8
Böke Özkoç, Hülya, Arıman, Sema (2023) Contamination and risk assessment of heavy metals in coastal sediments from the Mid-Black Sea, Turkey. Stochastic Environmental Research and Risk Assessment, 37 (1) 375-394 doi:10.1007/s00477-022-02300-4
Wang, Jhih-Huang, Lin, Gwo-Fong, Huang, Yun-Ru, Huang, I-Hang, Chen, Chieh-Lin (2023) Application of hybrid machine learning model for flood hazard zoning assessments. Stochastic Environmental Research and Risk Assessment, 37 (1) 395-412 doi:10.1007/s00477-022-02301-3
Zhu, Wei, Zha, Xianbao, Luo, Pingping, Wang, Shuangtao, Cao, Zhe, Lyu, Jiqiang, Zhou, Meimei, He, Bin, Nover, Daniel (2023) A quantitative analysis of research trends in flood hazard assessment. Stochastic Environmental Research and Risk Assessment, 37 (1) 413-428 doi:10.1007/s00477-022-02302-2
Wu, Ziyi, Bhattacharya, Biswa, Xie, Ping, Zevenbergen, Chris (2023) Improving flash flood forecasting using a frequentist approach to identify rainfall thresholds for flash flood occurrence. Stochastic Environmental Research and Risk Assessment, 37 (1) 429-440 doi:10.1007/s00477-022-02303-1
Chen, Sam Li-Sheng, Jen, Grace Hsiao-Hsuan, Hsu, Chen-Yang, Yen, Amy Ming-Fang, Lai, Chao-Chih, Yeh, Yen-Po, Chen, Tony Hsiu-Hsi (2023) A new approach to modeling pre-symptomatic incidence and transmission time of imported COVID-19 cases evolving with SARS-CoV-2 variants. Stochastic Environmental Research and Risk Assessment, 37 (1) 441-452 doi:10.1007/s00477-022-02305-z

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