Mark S. Zion

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

Modeling watershed-scale effectiveness of agricultural best management practices to reduce phosphorus loading

Planners advocate best management practices (BMPs) to reduce loss of sediment and nutrients in agricultural areas. However, the scientific community lacks tools that use readily available data to investigate the relationships between BMPs and their spatial locations and water quality. In rural, humid regions where runoff is associated with saturation-excess processes from variable source areas (VSAs), BMPs are potentially most effective when they are located in areas that produce the majority of the runoff. Thus, two critical elements necessary to predict the water quality impact of BMPs include correct identification of VSAs and accurate predictions of nutrient reduction due to particular BMPs. The objective of this research was to determine the effectiveness of BMPs using the Variable Source Loading Function (VSLF) model, which captures the spatial and temporal evolutions of VSAs in the landscape. Data from a long-term monitoring campaign on a 164-ha farm in the New York City source watersheds in the Catskills Mountains of New York state were used to evaluate the effectiveness of a range of BMPs. The data spanned an 11-year period over which a suite of BMPs, including a nutrient management plan, riparian buffers, filter strips and fencing, was installed to reduce phosphorus (P) loading. Despite its simplicity, VSLF predicted the spatial distribution of runoff producing areas well. Dissolved P reductions were simulated well by using calibrated reduction factors for various BMPs in the VSLF model. Total P losses decreased only after cattle crossings were installed in the creek. The results demonstrated that BMPs, when sited with respect to VSAs, reduce P loss from agricultural watersheds, providing useful information for targeted water quality management.

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.

Impacts of projected climate change on phosphorus and sediment loadings for a New York City water supply reservoir

Impacts of projected climate change on phosphorus and sediment loadings for a New York City water supply reservoir.