Bivariate Frequency Analysis of Extreme Sea Level with Rainfall and Temperature in New York City
Journal Title: Water Harvesting Research - Year 2024, Vol 7, Issue 2
Abstract
Climate change negatively impacts hydrologic patterns, affecting rainfall, temperature extremes, and sea level rise. Long-term averages of these variables may shift over time due to climate change effects. This study conducted trend analysis on rainfall, maximum and minimum temperature, and water level data from Manhattan, Central Park, and Battery Park stations to identify significant changes in means. The Partial Mann-Kendall test was employed for trend analysis. Frequency analysis utilized common probability distribution functions, including Generalized Extreme Value (GEV), normal, log-normal, and Log-Pearson distributions, with goodness-of-fit tests like Kolmogorov-Smirnov to identify the most suitable distributions. While flood frequency analysis typically examines rainfall and water levels separately, their combination can significantly influence floodplain delineation. This study aimed to enhance flood frequency analysis by considering joint probability distributions for rainfall and storm surge. The correlations between variables and joint probabilities of extreme water levels and temperatures were explored to assess the potential impacts of global warming on sea level flooding. Copula functions determined the joint probabilities of water levels with rainfall and temperature across various recurrence intervals. The trend analysis results indicated an increase in long-term averages due to climate change. The GEV distribution emerged as the most appropriate function for extreme climate variables. This joint probability distribution analysis underscored the necessity of incorporating both rainfall and water level data in flood frequency assessments.
Authors and Affiliations
Ali Razmi,Emad Mahjoobi,Heydar Ali Mardani-Fard,Zahra Zahmatkesh,
Keywords
Related Articles
- EP ID EP759860
- DOI -
- Views 24
- Downloads 0
A Quantitative Strategic Planning Framework for Artificial Groundwater Recharge in Iran Based on Fuzzy AHP
This article studies the Artificial Groundwater Recharge (AGR) of the Esfarayen aquifer, in Iran, from the perspective of the strategic planning process. For this purpose, a SWOT systematic analysis was performed for the...
Assessment of Re-Forecast Data in the Modeling of Extreme Rainfall-Runoff Events (Case Study: Floods in the Bakhtiari Basin, Iran, March-April 2019)
Predicting inflow into reservoirs is essential for their operation during floods, particularly in mountainous watersheds characterized by snow-rain regimes. The objective of this research is to evaluate the GEFSv12 re-fo...
Advancing Sustainable Agriculture: Renewable Energy Integration and Policy Implications for Irrigation in Nigeria – A Systematic Review
This research review explores the application of renewable energy sources, such as solar, wind, and biomass, in irrigation practices throughout Nigeria. Following the PRISMA (Preferred Reporting Items for Systematic Revi...
Comparative Analysis of Machine Learning Algorithms for Forecasting Effluent Chemical Oxygen Demand in Wastewater Treatment Plants
Accurate prediction of wastewater effluent parameters is crucial for evaluating the performance of wastewater treatment plants, as it significantly contributes to reducing time, energy, and costs. This study employed thr...
Investigating the Performance of Metal Surfaces Modified by Laser on the Efficiency of Water Harvesting from Humid Air
The population growth and consequently lack of fresh water resources, are the main concerns of developed communities. Providing water from air humidity is an efficient, clean, and sustainable solution that can supply swe...