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Abstract New York City (NYC) faces many challenges in the coming decades due to climate change and its interactions with social vulnerabilities and uneven urban development patterns and processes. This New York City Panel on Climate Change (NPCC) report contributes to the Panel's mandate to advise the city on climate change and provide timely climate risk information that can inform flexible and equitable adaptation pathways that enhance resilience to climate change. This report presents up‐to‐date scientific information as well as updated sea level rise projections of record. We also present a new methodology related to climate extremes and describe new methods for developing the next generation of climate projections for the New York metropolitan region. Future work by the Panel should compare the temperature and precipitation projections presented in this report with a subset of models to determine the potential impact and relevance of the “hot model” problem. NPCC4 expects to establish new projections‐of‐record for precipitation and temperature in 2024 based on this comparison and additional analysis. Nevertheless, the temperature and precipitation projections presented in this report may be useful for NYC stakeholders in the interim as they rely on the newest generation of global climate models. 

Abstract Large dams degrade the river’s health by heavily regulating the natural flows. Despite a long history of research on flow regulation due to dams, most studies focused only on the impact of a single dam and ignored the combined impact of flow regulation on a river network. We propose a new Dynamic Flow Alteration Index (DFAI) to quantify the local and cumulative degree of regulation by comparing the observed controlled flows with the naturalized flows based on a moving time horizon for the highly regulated Colorado River Basin. The proposed DFAI matches closely to dam’s localized regulation for headwater gages and starts to diverge as we move downstream due to increase in cumulative impact of the dams. DFAI considers the impact of dam operations on flow characteristics such as shifting of peak flow occurrence and dampening of peak flows. DFAI estimates the degree of regulation to be small for upstream dams and finds the maximum network regulation to be 2.52 years at Glen Canyon reservoir. DFAI also successfully captures the reduction in cumulative regulation when dam operations (e.g., Hoover Dam) bring the altered flow in synchronization with natural regime due to downstream flow requirements. The impact of San Juan River Basin Recovery Implementation Program is also captured by DFAI as the reduction in network regulation drops by 1.5 years for Navajo Dam. Our findings using DFAI suggest the need to develop naturalized flows for major river basins to quantify the flow alteration under continually changing climate and human influences. 

Abstract Large dams are a leading cause of river ecosystem degradation. Although dams have cumulative effects as water flows downstream in a river network, most flow alteration research has focused on local impacts of single dams. Here we examined the highly regulated Colorado River Basin (CRB) to understand how flow alteration propagates in river networks, as influenced by the location and characteristics of dams as well as the structure of the river network—including the presence of tributaries. We used a spatial Markov network model informed by 117 upstream‐downstream pairs of monthly flow series (2003–2017) to estimate flow alteration from 84 intermediate‐to‐large dams representing >83% of the total storage in the CRB. Using Least Absolute Shrinkage and Selection Operator regression, we then investigated how flow alteration was influenced by local dam properties (e.g., purpose, storage capacity) and network‐level attributes (e.g., position, upstream cumulative storage). Flow alteration was highly variable across the network, but tended to accumulate downstream and remained high in the main stem. Dam impacts were explained by network‐level attributes (63%) more than by local dam properties (37%), underscoring the need to consider network context when assessing dam impacts. High‐impact dams were often located in sub‐watersheds with high levels of native fish biodiversity, fish imperilment, or species requiring seasonal flows that are no longer present. These three biodiversity dimensions, as well as the amount of dam‐free downstream habitat, indicate potential to restore river ecosystems via controlled flow releases. Our methods are transferrable and could guide screening for dam reoperation in other highly regulated basins.