Do water savings persist? Using survival models to plan for long-term responses to extreme drought

Bolorinos, Jose; Rajagopal, Ram; Ajami, Newsha K.

doi:10.1088/1748-9326/ac8b22

Cited by 4 publications

(5 citation statements)

References 43 publications

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“…In 2015 Costa Mesa enforced restricted irrigation schedules, which is likely to explain the presence of over 90% SB customers in this profile. This behavior is consistent with previous findings (Bolorinos et al 2020(Bolorinos et al , 2022, though, our analysis additionally suggests that those restrictions had a long-lasting effect on the water consumption behavior, as no rebound effect is visible for Drought Savers.…”

Section: Impact Of Hydroclimatic Economic and Pandemic Stressors On W...supporting

confidence: 92%

Fast in the pandemic, durable after droughts, inequal during economic downturn. A 20 year multi-dimensional retrospective analysis of water demand change in Southern California

Gross,

Ajami,

Cominola

2023

Environ. Res. Lett.

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Determining changes in water consumption behavior due to recurring external stressors (e.g. droughts and socio-economic fluctuations) and previously unseen shocks like the COVID-19 pandemic can support future demand-side management (DSM) programs and identifying vulnerable social groups. Yet, most studies analyzing external drivers of water consumption change are noncomparative as they examine only one stressor at the time, mainly droughts. Here we develop a multi-dimensional retrospective analysis (MDRA) to quantify residential water consumption changes in Southern California over the last two decades under compound hydroclimatic, economic, and pandemic stressors. We then uncover what socio-economic groups relate to predominant behavioral changes under each stressor. We observe a long-lasting decreasing water consumption trend for more than 76% of the analyzed households. Socio-economically vulnerable households were more likely to reduce water consumption during the economic and pandemic stressors. Differently, affluent neighborhoods tended to increase water consumption during or after droughts and the pandemic. Our MDRA supports utilities and policy makers to discern the impacts of different stressors on water demand and helps to identify social and economic sensitivities across a service area to develop adaptive DSMs and assistance programs.

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Section: Impact Of Hydroclimatic Economic and Pandemic Stressors On W...supporting

confidence: 92%

Fast in the pandemic, durable after droughts, inequal during economic downturn. A 20 year multi-dimensional retrospective analysis of water demand change in Southern California

Gross,

Ajami,

Cominola

2023

Environ. Res. Lett.

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“…where Q 0 (t) is the measured annual runoff volume, m 3 . Q p (t) denotes the predicted annual runoff volume, m 3 . n represents the number of years in the test period.…”

Section: Evaluation Of the Modelmentioning

confidence: 99%

“…In recent years, the frequent occurrence of extreme climate events has exerted a profound influence on the global water cycle [1]. Extreme precipitation [2], extreme drought [3], and extreme flooding [4] pose a great threat to human lives, property, and safety. An accurate runoff forecast plays a vital role in water resource management.…”

Section: Introductionmentioning

confidence: 99%

Research on Annual Runoff Prediction Model Based on Adaptive Particle Swarm Optimization–Long Short-Term Memory with Coupled Variational Mode Decomposition and Spectral Clustering Reconstruction

Wang,

Chang,

Jin

et al. 2024

Water

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Accurate medium- and long-term runoff prediction models play crucial guiding roles in regional water resources planning and management. However, due to the significant variation in and limited amount of annual runoff sequence samples, it is difficult for the conventional machine learning models to capture its features, resulting in inadequate prediction accuracy. In response to the difficulties in leveraging the advantages of machine learning models and limited prediction accuracy in annual runoff forecasting, firstly, the variational mode decomposition (VMD) method is adopted to decompose the annual runoff series into multiple intrinsic mode function (IMF) components and residual sequences, and the spectral clustering (SC) algorithm is applied to classify and reconstruct each IMF. Secondly, an annual runoff prediction model based on the adaptive particle swarm optimization–long short-term memory network (APSO-LSTM) model is constructed. Finally, with the basis of the APSO-LSTM model, the decomposed and clustered IMFs are predicted separately, and the predicted results are integrated to obtain the ultimate annual runoff forecast results. By decomposing and clustering the annual runoff series, the non-stationarity and complexity of the series have been reduced effectively, and the endpoint effect of modal decomposition has been effectively suppressed. Ultimately, the expected improvement in the prediction accuracy of the annual runoff series based on machine learning models is achieved. Four hydrological stations along the upper reaches of the Fen River in Shanxi Province, China, are studied utilizing the method proposed in this paper, and the results are compared with those obtained from other methods. The results show that the method proposed in this article is significantly superior to other methods. Compared with the APSO-LSTM model and the APSO-LSTM model based on processed annual runoff sequences by single VMD or Wavelet Packet Decomposition (WPD), the method proposed in this paper reduces the RMSE by 40.95–80.28%, 25.26–57.04%, and 15.49–40.14%, and the MAE by 24.46–80.53%, 16.50–59.30%, and 16.58–41.80%, in annual runoff prediction, respectively. The research has important reference significance for annual runoff prediction and hydrological prediction in areas with data scarcity.

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“…In contrast, other parts of the world deal with more frequent water scarcity events, such as Australia, the United States and Brazil, where optimization of water usage is a constant goal of local utilities. While Fielding et al (2012) observed in some places in Australia that previous drought experience is crucial in determining the water conservation culture of residents, as well as other demographic, psychosocial, behavioral, and infrastructure variables, Bolorinos et al (2022) revealed that drought severity experience and income are not as determinant as consumers' age and political inclination on the persistence of conservation behavior after drought events in California. In Brazil, the Jaguaribe Basin experienced an intense drought between 2012 and 2017, when the system of reservoirs, built during the 20th century, was crucial to increase water security (Nunes and Medeiros, 2020).…”

Section: Discussionmentioning

confidence: 93%

“…One possible validation of our results could be to collect a substantial amount of data regarding individual end-users. Examples such as Bolorinos et al (2022); Brühl and Visser (2021) statistically assessed the role of drivers of consumption in times of water scarcity. Additionally, the evaporation is embedded on the water balance variables of the reservoirs (inflow, outflow and storage).…”

Section: Discussionmentioning

confidence: 99%

Spatial and time scales of human-water feedbacks facing drought risk in megacities: a socio-hydrological approach in São Paulo

Souza

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During my master and doctorate dedication, life has guided me to meet people that played an important role in the construction of the ideas I will present in this thesis. First in 2016, Professor Mario Mendiondo, the person who reached out to my ideas, accepted to advise my master and doctorate research projects at the University of São Paulo. Later in 2018, the organizers of the Santa Fe Institute on Socio-Hydrological Dynamics, Christa Brelsford and Marion Dumas, put me in contact to the socio-hydrology thoughts and introduced me to my great references, Murugesu Sivapalan, and Margaret Garcia. In 2019, professors Fuqiang Tian, Gunter Bloschl and Siva organized the six-weeks Summer Institute on Sociohydrology and Transboundary Rivers, what gave me the opportunity to learn how science is made under the lens of the most renowned researchers of sociohydrology. Therefore, I would like to express my special thanks to all these researchers for the opportunity to learn how to think, do research and communicate.Besides the scientific life, some other people are stronger correlated to the accomplishment of this thesis because they have shaped my personal life during these years. First, the researchers from the WADI lab, who are my scientific co-workers that shared insights, conference trips and the friendship I will always remember. Second, the friends I made in São Carlos and in China. They are people who shared apartment, joined me at the university parties, had coffee breaks at the Hydraulics Department, invited me to be groomsman, backpacked in South America countries and had many other unforgettable moments. Finally, my great gratitude goes to my family for their comprehension of the obstacles that academic life imposes and their support to achieve the PhD qualification.

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Do water savings persist? Using survival models to plan for long-term responses to extreme drought

Cited by 4 publications

References 43 publications

Fast in the pandemic, durable after droughts, inequal during economic downturn. A 20 year multi-dimensional retrospective analysis of water demand change in Southern California

Fast in the pandemic, durable after droughts, inequal during economic downturn. A 20 year multi-dimensional retrospective analysis of water demand change in Southern California

Research on Annual Runoff Prediction Model Based on Adaptive Particle Swarm Optimization–Long Short-Term Memory with Coupled Variational Mode Decomposition and Spectral Clustering Reconstruction

Spatial and time scales of human-water feedbacks facing drought risk in megacities: a socio-hydrological approach in São Paulo

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