Advances and Challenges in Hydro-Climatological Modeling and Uncertainty Analysis

Dear Colleagues,

Climate change (CC) and anthropogenic land use land cover (LULC) activities have heightened the risk that hydro-climatological extremes pose to the ecosystem, society (including human health/mortality), and the economy (e.g., infrastructure/agriculture). When multiple hydro-climatological extreme or nonextreme events (such as floods; drought; precipitation; extreme temperatures, humidity, and wind speed; heatwaves; etc.) occur simultaneously or successively, the compound effect amplifies the overall stress level compared to their individual consideration. Also, because of CC and/or LULC, the methods used to identify, attribute, and measure their frequency of occurrence or severity must be reviewed, as these processes are no longer stationary or time-invariant. Statistical methods have a long history of analysing such complex hydro-climatological data for designing, planning, infilling, and forecasting. Time–frequency analysis, hydrological modelling, multivariate statistical techniques, uncertainty analysis, artificial intelligence, etc., are powerful tools for the stationary and nonstationary modelling of hydro-climatological events in static and dynamic settings. We are particularly interested in and welcome contributions from a diverse community of studies related to innovative stochastic and statistical model development in climatology and hydrology, as well as their uncertainty analysis using historical and/or future projected datasets for different climate models (i.e., the CIMP5 and CIMP6 datasets under different scenarios). We focus on both the local and regional estimation of extreme hydro-climatological events, hydro-climatological forecasting, the design of measurement networks, analyses of the spatial and temporal variability of hydro-climatological datasets, modelling the impact of climate change on hydro-climatological variables, the homogenization of data-series flood damage estimation, and the evolution of hydrological regimes. Potential topics include, but are not limited to, the following:

• Developing statistical, numerical, and physical modelling tools as well as deterministic and stochastic hydro-climatological models;
• Modelling compounded hydro-climatological events;
• Applications of time-invariant and time-varying copulas or extreme dependence models with historical or future projected datasets for hydro-climatic extremes;
• Applications of Bayesian approaches in hydro-climatological modelling;
• Advances in nonparametric function estimation in developing multidimensional models for hydro-climatological events;
• Statistical downscaling, water quality management, and thermal modelling in rivers;
• Statistical model development in investigating the impact of hydro-climatological extremes on agriculture crop yield, risks of forest fires, health-related issues, etc.;
• The interplay between climate variability and changes;
• Complicated interactions between precipitation, temperature, groundwater, surface water, wind speed, temperature, and other climatic variables;
• Hydrological design and risk assessment under static and dynamic frameworks;
• Stationary and nonstationary, local and regional, and univariate and multivariate frequency analyses of hydro-climatological variables;
• Uncertainty assessments in hydrological and climatological projections and observations;
• Adaption and mitigation strategies;
• Innovative methods for hazard risk assessments;
• Climate models (regional and global scales);
• Regional flood and drought frequency analyses;
• The spatio-temporal variation and characterization of recent extreme hazards, i.e., floods, drought, wildfire risks, etc.;
• Addressing uncertainty in understanding hydro-climatology and hydrology across scales;
• Nonparametric time-series models and stochastic generation;
• Advancements in urban inundation forecasting techniques;
• Reviews of previous studies on hydroclimatological hazards and risk assessment.

Dr. Md Shahid Latif
Prof. Dr. Taha B. M. J. Ouarda
Guest Editors

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• statistical and stochastic hydro-climatology
• extreme events
• water resources
• precipitation
• evapotranspiration
• streamflow
• drought
• flood
• downscaling
• runoff
• heat wave
• wind speed
• modelling extreme hydrological and meteorological events
• uncertainty analysis
• risk hazard assessments
• climate change
• anthropogenic land use
• nonstationary hydro-climatological modelling
• artificial intelligence
• time-series analysis
• water quality
• non-parametric models