Cargando…
Predicting Urban Reservoir Levels Using Statistical Learning Techniques
Urban water supplies are critical to the growth of the city and the wellbeing of its citizens. However, these supplies can be vulnerable to hydrological extremes, such as droughts and floods, especially if they are the main source of water for the city. Maintaining these supplies and preparing for f...
Autores principales: | Obringer, Renee, Nateghi, Roshanak |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5980089/ https://www.ncbi.nlm.nih.gov/pubmed/29581520 http://dx.doi.org/10.1038/s41598-018-23509-w |
Ejemplares similares
-
Statistical Analysis of the Effectiveness of Seawalls and Coastal Forests in Mitigating Tsunami Impacts in Iwate and Miyagi Prefectures
por: Nateghi, Roshanak, et al.
Publicado: (2016) -
A multi-paradigm framework to assess the impacts of climate change on end-use energy demand
por: Nateghi, Roshanak, et al.
Publicado: (2017) -
Overemphasis on recovery inhibits community transformation and creates resilience traps
por: Rachunok, Benjamin, et al.
Publicado: (2021) -
Climate, weather, socio-economic and electricity usage data for the residential and commercial sectors in FL, U.S
por: Mukhopadhyay, Sayanti, et al.
Publicado: (2017) -
Data on major power outage events in the continental U.S.
por: Mukherjee, Sayanti, et al.
Publicado: (2018)