78 citations as recorded by crossref.

1. Efficacy of statistical algorithms in imputing missing data of streamflow discharge imparted with variegated variances and seasonalities Y. Gao et al.
2. Closure to the discussion of Ebtehaj et al. on “Comparative assessment of time series and artificial intelligence models to estimate monthly streamflow: A local and external data analysis approach” S. Mehdizadeh et al.
3. The Empirical Test on the Impact of Climate Volatility on Tourism Demand: A Case of Japanese Tourists Visiting Korea Y. Hwang et al.
4. Uncertainty analysis of hydrological processes based on ARMA-GARCH model H. Wang et al.
5. The role of anthropogenic activities in karst spring discharge volatility J. Wu et al.
6. Big Data for Cybersecurity: Vulnerability Disclosure Trends and Dependencies M. Tang et al.
7. Characterizing and forecasting climate indices using time series models T. Lee et al.
8. A prediction of future flows of ephemeral rivers by using stochastic modeling (AR autoregressive modeling) M. Malakoutian et al.
9. Impacts of the Three Gorges Dam on the streamflow fluctuations in the downstream region S. Guo et al.
10. Flood forecasting for heteroscedastic streamflow processes F. Pianosi & L. Raso
11. Hybrid Forecasting of Daily River Discharges Considering Autoregressive Heteroscedasticity E. Szolgayová et al.
12. AR-GARCH with Exogenous Variables as a Postprocessing Model for Improving Streamflow Forecasts X. Zha et al.
13. Bivariate Simulation of Potential Evapotranspiration Using Copula-GARCH Model M. Nazeri-Tahroudi et al.
14. Crytic period analysis model of hydrological process and its application H. Wang et al.
15. The Impact of Climate Change on Stochastic Variations of the Hydrology of the Flow of the Indus River M. Yonus & S. Hassan
16. Forecasting Wind Speed in Peninsular Malaysia: An Application of ARIMA and ARIMA-GARCH Models N. Hussin et al.
17. Comparison of forecasting performance of nonlinear models of hydrological time series J. Komorník et al.
18. Annual, seasonal, and monthly baseflow trend in an arid area in Loss Plateau, China Y. Sun et al.
19. Impact of EMD decomposition and random initialisation of weights in ANN hindcasting of daily stream flow series: An empirical examination G. Napolitano et al.
20. Monthly Simulation of Pan Evaporation Using Copula-Based Models Considering the Effect of Heteroscedasticity A. Lalehpour et al.
21. Statistical simulation of flood variables: incorporating short‐term sequencing Y. Cai et al.
22. Bivariate simulation of river flow using hybrid intelligent models in sub-basins of Lake Urmia, Iran V. Eslamitabar et al.
23. Updating urban design floods for changes in central tendency and variability using regression J. Hecht & R. Vogel
24. A nonstationary extreme value distribution for analysing the cessation of karst spring discharge Y. Liu et al.
25. Trivariate Flood Frequency Analysis Using Discharge Time Series with Possible Different Lengths: Cuyahoga River Case Study L. Zhang & V. Singh
26. Estimating weak periodic vector autoregressive time series Y. Boubacar Maïnassara & E. Ursu
27. Hidden Markov and Semi-Markov Models with Multivariate Leptokurtic-Normal Components for Robust Modeling of Daily Returns Series A. Maruotti et al.
28. Development of resistance to sarcoptic mange in ibex J. Pérez et al.
29. Management strategies for run-of-river hydropower plants: an optimal switching approach M. Olofsson et al.
30. Enhancing the Prediction Accuracy of Data-Driven Models for Monthly Streamflow in Urmia Lake Basin Based upon the Autoregressive Conditionally Heteroskedastic Time-Series Model N. Attar et al.
31. Modeling streamflow time series using nonlinear SETAR-GARCH models F. Fathian et al.
32. The multi temporal/multi-model approach to predictive uncertainty assessment in real-time flood forecasting S. Barbetta et al.
33. The application of the hybrid copula-GARCH approach in the simulation of extreme discharge values M. Nazeri Tahroudi et al.
34. Para Politikası Uygulamalarının Gelişmekte Olan Ülkelerin Ülke Kredi Riski Üzerindeki Yayılma Etkisi F. DURAL & Z. SEÇME
35. Enhancing decadal snowfall forecasts in the Mediterranean mountains through informed atmospheric variability and climate data N. Diodato et al.
36. Is the volatility and non-stationarity of the Atlantic Multidecadal Oscillation (AMO) changing? O. Beyraghdar Kashkooli & R. Modarres
37. Multi-step SETARMA predictors in the analysis of hydrological time series A. Amendola et al.
38. Reducing the uncertainty of time-varying hydrological model parameters using spatial coherence within a hierarchical Bayesian framework Z. Pan et al.
39. Diagnostic checking of periodic vector autoregressive time series models with dependent errors Y. Boubacar Maïnassara & E. Ursu
40. Improving Prediction Accuracy of Rainfall Time Series By Hybrid SARIMA–GARCH Modeling P. Pandey et al.
41. Asymptotic Properties of Weighted Least Squares Estimation in Weak PARMA Models C. Francq et al.
42. Generalized autoregressive conditional heteroscedasticity modelling of hydrologic time series R. Modarres & T. Ouarda
43. Application of copula-based and ARCH-based models in storm prediction Y. Ramezani et al.
44. Volatility modeling of rainfall time series F. Yusof & I. Kane
45. Time-Varying Effects of Precipitation and Temperature on Daily Streamflow Determined Using the DCC Model H. Wang et al.
46. Copula-based statistical refinement of precipitation in RCM simulations over complex terrain P. Laux et al.
47. Modeling Radar Rainfall Estimation Uncertainties: Random Error Model A. AghaKouchak et al.
48. Application of copula functions to construct confidence intervals of bivariate drought frequency curve J. Yoo et al.
49. Regional scale rainfall–runoff modeling using VARX–MGARCH approach F. Fathian et al.
50. Exploring the Regional Variance using ARMA-GARCH Models H. Xie et al.
51. Mevsimsel Değişkenliklerin Borsa İstanbul Üzerindeki Oynaklık Etkisi: Ramazan Ayı Örneği A. Yılmaz & Z. Can Ergün
52. Modeling the relationship between climate oscillations and drought by a multivariate GARCH model R. Modarres & T. Ouarda
53. Simulation of Nonstationary Spring Discharge Using Time Series Models Y. Liu et al.
54. The application of multiple linear regression method in reference evapotranspiration trend calculation N. Khanmohammadi et al.
55. Forecasting East Belitung Regency Rainfall Data by Reviewing Heteroscedasticity E. Kustiawan & . Adriyansyah
56. Conditional Heteroscedasticity in Streamflow Process: Paradox or Reality? M. Otache et al.
57. Modelling heteroscedasticty of streamflow times series R. Modarres & T. Ouarda
58. A farmer-centric agricultural decision support system for market dynamics in a volatile agricultural supply chain P. Tripathi et al.
59. Multiple streamflow time series modeling using VAR–MGARCH approach F. Fathian et al.
60. Machine learning for predicting pavement roughness and optimising maintenance M. Ghodratabadi et al.
61. Smoothing Variances Across Time: Adaptive Stochastic Volatility J. Cho & D. Matteson
62. Influence of whooping crane population dynamics on its recovery and management M. Butler et al.
63. Development of a partial copula-based algorithm for disclosing variability of dependence structures between hydro-meteorological factors under consideration of covariate-effect A. Guo et al.
64. Stochastic Volatility Modeling of Daily Streamflow Time Series H. Wang et al.
65. Copula-based assimilation of radar and gauge information to derive bias-corrected precipitation fields S. Vogl et al.
66. Testing for nonlinearity of streamflow processes at different timescales W. Wang et al.
67. Point and Interval Forecasting of Groundwater Depth Using Nonlinear Models T. Guo et al.
68. A review on missing hydrological data processing Y. Gao et al.
69. Rutting prediction using deep learning for time series modeling and K-means clustering based on RIOHTrack data J. Liu et al.
70. Addressing Volatility and Nonlinearity in Discharge Modeling: ARIMA-iGARCH for Short-Term Hydrological Time Series Simulation M. Khazaeiathar & B. Schmalz
71. Wavelets Based Artificial Neural Network Technique for Forecasting Agricultural Prices R. Paul & S. Garai
72. Streamflow Intervals Prediction Using Coupled Autoregressive Conditionally Heteroscedastic With Bootstrap Model B. Bickici et al.
73. Improving Forecasting Accuracy of Annual Runoff Time Series Using ARIMA Based on EEMD Decomposition W. Wang et al.
74. Combined deterministic – stochastic forecasting of monthly river flows for water management E. Peksova Szolgayova et al.
75. Returns and volatility of water investments R. Reza et al.
76. Clustering diagnosis of rolling element bearing fault based on integrated Autoregressive/Autoregressive Conditional Heteroscedasticity model G. Wang et al.
77. Applying time series models to estimate time lags between sap flux and micro-meteorological factors X. Zhao et al.
78. Genetic modeling for the optimal forecasting of hydrologic time-series: Application in Nestos River T. Koutroumanidis et al.