A. H. Matonse

Examination of change factor methodologies for climate change impact assessment

[1] A variety of methods are available to estimate values of meteorological variables at future times and at spatial scales that are appropriate for local climate change impact assessment. One commonly used method is Change Factor Methodology (CFM), sometimes referred to as delta change factor methodology. Although more sophisticated methods exist, CFM is still widely applicable and used in impact analysis studies. While there are a number of different ways by which change factors (CFs) can be calculated and used to estimate future climate scenarios, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. In this study several categories of CFM (additive versus multiplicative and single versus multiple) for a number of climate variables are compared and contrasted. The study employs several theoretical case studies, as well as a real example from Cannonsville watershed, which supplies water to New York City, USA. Results show that in cases when the frequency distribution of Global Climate Model (GCM) baseline climate is close to the frequency distribution of observed climate, or when the frequency distribution of GCM future climate is close to the frequency distribution of GCM baseline climate, additive and multiplicative single CFMs provide comparable results. Two options to guide the choice of CFM are

Investigating the impact of climate change on New York City’s primary water supply

Future climate scenarios projected by three different General Circulation Models and a delta-change methodology are used as input to the Generalized Watershed Loading Functions – Variable Source Area (GWLF-VSA) watershed model to simulate future inflows to reservoirs that are part of the New York City water supply system (NYCWSS). These inflows are in turn used as part of the NYC OASIS model designed to simulate operations for the NYCWSS. In this study future demands and operation rules are assumed stationary and future climate variability is based on historical data to which change factors were applied in order to develop the future scenarios. Our results for the West of Hudson portion of the NYCWSS suggest that future climate change will impact regional hydrology on a seasonal basis. The combined effect of projected increases in winter air temperatures, increased winter rain, and earlier snowmelt results in more runoff occurring during winter and slightly less runoff in early spring, increased spring and summer evapotranspiration, and reduction in number of days the system is under drought conditions. At subsystem level reservoir storages, water releases and spills appear to be higher and less variable during the winter months and are slightly reduced during summer. Under the projected future climate and assumptions in this study the NYC reservoir system continues to show high resilience, high annual reliability and relatively low vulnerability.

A Seasonal Shift in the Frequency of Extreme Hydrological Events in Southern New York State

AbstractThe recent sequence of extreme hydrological events across the eastern United States (e.g., Hurricane Irene in August 2011, Tropical Storm Lee in September 2011, and Hurricane Sandy in October 2012), which led to unprecedented flooding including in various parts in the study region, the Catskill Mountains, and Hudson River Valley in southern New York State, have raised the question of whether the frequency of extreme events across the region is changing. In this study variations in the frequency of extreme precipitation and streamflow events available from historical records are analyzed. This study finds that there has been a marked increase in the frequency of warm season (June–October) extreme hydrologic events during the last two decades, with an accelerated rate of increase since the mid-1990s. The most recent decade has the highest frequency of extreme warm season events in the last 100 years across the study region. No such trend is observed between November and May; in fact the frequency of...

The Seasonal Nature of Extreme Hydrological Events in the Northeastern United States

AbstractRecent analyses of extreme hydrological events across the United States, including those summarized in the recent U.S. Third National Climate Assessment (May 2014), show that extremely large (extreme) precipitation and streamflow events are increasing over much of the country, with particularly steep trends over the northeastern United States. The authors demonstrate that the increase in extreme hydrological events over the northeastern United States is primarily a warm season phenomenon and is caused more by an increase in frequency than magnitude. The frequency of extreme warm season events peaked during the 2000s; a secondary peak occurred during the 1970s; and the calmest decade was the 1960s. Cold season trends during the last 30–50 yr are weaker. Since extreme precipitation events in this region tend to be larger during the warm season than during the cold season, trend analyses based on annual precipitation values are influenced more by warm season than by cold season trends. In contrast, t...

The New York City Operations Support Tool (OST): Managing Water for Millions of People in an Era of Changing Climate and Extreme Hydrological Events

With an average daily delivery of 1.1 billion gallons (∼4.2×106m3) of drinking water to approximately nine million people in New York City (NYC) and four upstate counties, the NYC Water Supply is among the world’s largest unfiltered systems. In addition to reliably supplying water in terms of quantity and quality, the city has to fulfill other flow objectives to serve downstream communities. At times, such as during extreme hydrological events, water quality issues may restrict water usage from parts of the system; the city is proactively implementing a number of programs to monitor and minimize the impact. To help guide operations and planning, NYC has developed the Operations Support Tool (OST), a decision support system that utilizes ensemble forecasts provided by the National Weather Service (NWS) Hydrologic Ensemble Forecast Service (HEFS). This paper provides an overview of OST and shows two operations case studies to illustrate how OST is used to support risk-based water supply management. As the modeling uncertainty is strongly impacted by the forecast skill, we also discuss how changes in patterns of hydrological extreme events elevate the challenge faced by water supply managers and the role of the scientific community to integrate non-stationarity approaches in hydrologic forecasting.