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Understanding the nature of climatic change impacts on spatial and temporal hydroclimatic patterns is important to the development of timely and spatially explicit adaptation options. However, regime-switching behavior of hydroclimatic variables complicates the modelling process as many traditional time series methods do not capture this behavior. Accurately representing spatial correlation across hydroclimatic regimes is particularly important for water resources planning in large watersheds such as the Colorado River, and regions where interbasin transfers and shared demand nodes link multiple watersheds. Here, we developed a hidden Markov model (HMM) with covariates that generates an ensemble of plausible future regional scenarios of the Palmer modified drought index (PMDI) for any projected temperature sequence. The resulting spatially explicit scenarios represent the historical spatial and temporal patterns of the training data while incorporating non-stationarity by conditioning on temperature. These ensembles can aid water resources managers, infrastructure planners, and government policymakers tasked with building of more resilient water systems. Moreover, these ensembles can be used to generate streamflow ensembles, which, in turn, will be a valuable input to study the impact of climate change on regional hydrology. 

This repository contains R scripts for implementing a computationally efficient 4-state Hidden Markov Model (HMM) that uses temperature as a covariate to generate ensembles of plausible Palmer Modified Drought Index (PMDI) scenarios across the Western U.S. The model uses paleo PMDI data, which spans from 1500 to 1980 with a matrix grid of 1823 x 481 (e.g., 1823 grid-cells and 481 years). Similarly, paleo temperature data covers the same period, arranged in a matrix grid of 1637 grid cells by 481 years. To address the high dimensionality of the datasets, Principal Component Analysis (PCA) is applied to each variable, and the first six principal components (PCs) from both PMDI and temperature are retained as input to the HMM. The trained HMM is then used to simulate future PMDI scenarios by leveraging bias-corrected CMIP6 temperature projections under the Shared Socioeconomic Pathway (SSP) 2–4.5 scenario. The HMM framework is designed to capture the spatiotemporal variability and regime-shifting behavior of hydroclimatic patterns. It provides critical insights into the spatial correlation of wet and dry conditions across the Western U.S., supporting regional drought risk assessment and long-term water resource planning. For a more detailed description of the model, please refer to the following paper: Tezcan, B., & Garcia, M. (2025). Training a hidden Markov model with PMDI and temperature to create climate informed scenarios. Frontiers in Water, 7, Article 1472695. https://doi.org/10.3389/frwa.2025.1472695 

This dataset contains: Values for 42 variables related to topography, climate, vegetation, geology, and anthropogenic activities collected from 2001 to 2020. These variables were used to assess the drivers of streamflow drought deficit and duration across 2,550 stream gauges in the contiguous United States, including both natural and human-impacted sites. The computation method for each factor is detailed in Table 1. The dataset also includes trend analyses of drought duration and deficit from 1980 to 2020, performed using the Mann-Kendall test under three conditions: independence, short-term persistence, and long-term persistence. The complete analysis and findings are presented in Vicario, S.A., Hornberger, G.M., Mazzoleni, M., Garcia, M. (2025), "Drivers and trends of streamflow droughts in natural and human-impacted basins across the contiguous United States," Journal of Hydrology, DOI: https://doi.org/10.1016/j.jhydrol.2025.132908. 

The 1922 Colorado River Compact started the long history of water governance in the Colorado River Basin. Over the last century, the institutional structure has shaped water governance in the basin. However, an understanding of the long-term evolution is lacking. This study examines how water management strategies have evolved at the basin scale by incorporating institutional, temporal, and network structure analysis methods to examine long-term changes. Content analysis was employed to systematically investigate encouraged and/or discouraged water management actions at different rule levels. The water governance network was examined at four points in time to map the institutional structure, actors, and governance level at which rules are issued and targeted. Using institutional analysis, we found constitutional, operational, and collective-choice level rules for water supply, storage, movement, and use have been altered via layering of new governance rules without major rule or responsibility alteration. The network analysis results indicate that key decision-making positions have remained and actors who issue and are targeted by the rules lack significant change. We found original positions of power have been maintained, potentially stagnating the space for problem-solving and management strategy renegotiation. Our results indicate that path dependency has shaped water governance and who is able to influence decision-making. 

This resource contains 49 factors categorized into five groups: climatic (14), topographic (11), vegetation-related (5), anthropogenic (12), and geologic (7) factors, concerning 383 watersheds within the GAGES-II gages dataset (https:// water.usgs.gov/GIS/metadata/usgswrd/XML/gagesII_Sept2011.xml) across the contiguous United States (CONUS). The selection of the 383 watersheds out of the 9067 (in the CONUS) from GAGES-II was determined by the availability of daily streamflow data from 1990 to 2020 and its anthropogenic influence. For further details, refer to section 2.1 of https://doi.org/10.1016/j.jhydrol.2024.130984. The factors represent average values for each watershed spanning 1990 to 2020, calculated using publicly available data. Detailed information on these factors, including their sources and calculation methods, is provided in Tables 1 and 2 of the PDF document (Methodology_factors.pdf). The Excel file (Factors.xlsx) contains the classification of the gages and their associated factor values. The computation of these factors was conducted for the manuscript authored by Sara Alonso Vicario, George M. Hornberger, Maurizio Mazzoleni, and Margaret Garcia, titled "The Importance of Climate and Anthropogenic Influence in Precipitation Partitioning in the Contiguous United States," published in the Journal of Hydrology, Volume 633 (2024). The manuscript is accessible at https://doi.org/10.1016/j.jhydrol.2024.130984. 

Abstract A useful theoretical lens that has emerged for understanding urban resilience is the four basic types of interdependencies in critical infrastructures: the physical, geographic, cyber, and logical types. This paper is motivated by a conceptual and methodological limitation—althoughlogicalinterdependencies (where two infrastructures affect the state of each other via human decisions) are regarded as one of the basic types of interdependencies, the question of how to apply the notion and how to quantify logical relations remains under‐explored. To overcome this limitation, this study focuses on institutions (rules), for example, rules and planned tasks guiding human interactions with one another and infrastructure. Such rule‐mediated interactions, when linguistically expressed, have a syntactic form that can be translated into a network form. We provide a foundation to delineate these two forms to detect logical interdependence. Specifically, we propose an approach to quantify logical interdependence based on the idea that (1) there are certainnetwork motifsindicating logical relations, (2) such network motifs can be discerned from the network form of rules, and that (3) the higher the frequency of these motifs between two infrastructures, the greater the extent of logical interdependency. We develop a set of such motifs and illustrate their usage using an example. We conclude by suggesting a revision to the original definition of logical interdependence. This rule‐focused approach is relevant to understanding human error in risk analysis of socio‐technical systems, as human error can be seen as deviations from constraints that lead to accidents. 

Abstract Urban water management is increasingly challenged by the need to balance cost-effectiveness with equity considerations. This study presents a multi-objective approach to water conservation within the Las Vegas valley water district, analyzing a comprehensive dataset of water consumption and socioeconomic indicators across all single-family residences. We assess policy scenarios under two primary objectives: maximizing water savings to enhance economic efficiency and improving water affordability to promote equity. Our analysis reveals that while strategies focused on water savings reduce water use more efficiently, they tend to favor higher-income, predominantly white neighborhoods whereas prioritizing water affordability shifts resources towards lower-income, communities of color. The analysis of intermediate policy scenarios reveals the trade-offs and potential synergies between water savings and affordability. Our findings suggest that local water sustainability can be achieved by allocating resources to both high-demand and socioeconomically disadvantaged households. Highlighting the importance of integrating equity considerations into water management policies, this study provides insights for policymakers in crafting more inclusive and sustainable urban water management practices.