We’re funding Arizona State University conducted research that explores Phoenix’s water availability and where that water comes from. These findings will help us better prepare for a more reliable future.
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Our preprint for the 𝐈𝐧𝐯𝐢𝐭𝐞𝐝 𝐑𝐞𝐯𝐢𝐞𝐰 paper on 𝐒𝐨𝐢𝐥 𝐌𝐨𝐢𝐬𝐭𝐮𝐫𝐞 𝐌𝐞𝐦𝐨𝐫𝐲 can be accessed via this link in the 𝐄𝐒𝐒 𝐎𝐩𝐞𝐧 𝐀𝐫𝐜𝐡𝐢𝐯𝐞 before the official publication in 𝐑𝐞𝐯𝐢𝐞𝐰𝐬 𝐨𝐟 𝐆𝐞𝐨𝐩𝐡𝐲𝐬𝐢𝐜𝐬. We have already received the reviewers' reports, revised the paper based on their comments, and sent the revised version back to the journal. We hope that the paper will soon be accepted and officially published. Here is the feedback from one of our reviewers: "𝑂𝑣𝑒𝑟𝑎𝑙𝑙, 𝑡ℎ𝑖𝑠 𝑖𝑠 𝑎 𝑤𝑒𝑙𝑙-𝑤𝑟𝑖𝑡𝑡𝑒𝑛 𝑟𝑒𝑣𝑖𝑒𝑤 𝑝𝑎𝑝𝑒𝑟 𝑡ℎ𝑎𝑡 𝑝𝑟𝑜𝑣𝑖𝑑𝑒𝑠 𝑎 𝑐𝑜𝑚𝑝𝑟𝑒ℎ𝑒𝑛𝑠𝑖𝑣𝑒 𝑠𝑢𝑚𝑚𝑎𝑟𝑦 𝑜𝑓 𝑟𝑒𝑠𝑒𝑎𝑟𝑐ℎ 𝑡ℎ𝑎𝑡 𝑖𝑛𝑣𝑒𝑠𝑡𝑖𝑔𝑎𝑡𝑒𝑑 𝑡ℎ𝑒 𝑟𝑜𝑙𝑒 𝑜𝑓 𝑠𝑜𝑖𝑙 𝑚𝑜𝑖𝑠𝑡𝑢𝑟𝑒 𝑖𝑛 𝑡ℎ𝑒 𝑐𝑙𝑖𝑚𝑎𝑡𝑒 𝑠𝑦𝑠𝑡𝑒𝑚 𝑢𝑠𝑖𝑛𝑔 𝑖𝑛-𝑠𝑖𝑡𝑢 𝑜𝑏𝑠𝑒𝑟𝑣𝑎𝑡𝑖𝑜𝑛𝑠, 𝑙𝑎𝑛𝑑 𝑠𝑢𝑟𝑓𝑎𝑐𝑒 𝑚𝑜𝑑𝑒𝑙𝑖𝑛𝑔, 𝑟𝑒𝑚𝑜𝑡𝑒 𝑠𝑒𝑛𝑠𝑖𝑛𝑔, 𝑐𝑜𝑢𝑝𝑙𝑒𝑑 𝑐𝑙𝑖𝑚𝑎𝑡𝑒 𝑚𝑜𝑑𝑒𝑙𝑠, 𝑎𝑛𝑑 𝑒𝑣𝑒𝑛 𝑟𝑒𝑐𝑒𝑛𝑡 𝑚𝑎𝑐ℎ𝑖𝑛𝑒 𝑙𝑒𝑎𝑟𝑛𝑖𝑛𝑔 𝑚𝑒𝑡ℎ𝑜𝑑𝑠. 𝐹𝑜𝑟 𝑠𝑡𝑢𝑑𝑒𝑛𝑡𝑠 𝑎𝑛𝑑 𝑟𝑒𝑠𝑒𝑎𝑟𝑐ℎ𝑒𝑟𝑠 𝑤ℎ𝑜 𝑎𝑟𝑒 𝑖𝑛𝑡𝑒𝑟𝑒𝑠𝑡𝑒𝑑 𝑖𝑛 𝑡ℎ𝑖𝑠 𝑡𝑜𝑝𝑖𝑐, 𝑡ℎ𝑖𝑠 𝑝𝑎𝑝𝑒𝑟 𝑐𝑎𝑛 𝑠𝑒𝑟𝑣𝑒 𝑎𝑠 𝑎 𝑔𝑜𝑜𝑑 𝑝𝑙𝑎𝑐𝑒 𝑡𝑜 𝑠𝑡𝑎𝑟𝑡 𝑎 𝑙𝑖𝑡𝑒𝑟𝑎𝑡𝑢𝑟𝑒 𝑟𝑒𝑣𝑖𝑒𝑤, 𝑡𝑜 𝑢𝑛𝑑𝑒𝑟𝑠𝑡𝑎𝑛𝑑 𝑡ℎ𝑒 𝑠𝑡𝑎𝑡𝑒-𝑜𝑓-𝑡ℎ𝑒-𝑎𝑟𝑡 𝑏𝑒𝑓𝑜𝑟𝑒 𝑑𝑒𝑙𝑣𝑖𝑛𝑔 𝑖𝑛𝑡𝑜 𝑝𝑎𝑟𝑡𝑖𝑐𝑢𝑙𝑎𝑟 𝑠𝑡𝑢𝑑𝑖𝑒𝑠 𝑎𝑛𝑑 𝑒𝑥𝑝𝑎𝑛𝑑𝑖𝑛𝑔 𝑓𝑟𝑜𝑚 𝑡ℎ𝑒𝑚." https://lnkd.in/euVfzgHn Many thanks to all my colleagues for their great collaboration on this paper: Wulf Amelung Cosimo Brogi Jacopo Dari Alessia Flammini Heye Bogena Luca Brocca @Hao Chen Jannis Groh @Randel D. Koster Kaighin McColl Carsten Montzka Shirin Moradi Arash Rahi Farnaz Sharghi Harry Vereecken
Soil Moisture Memory: State-of-the-art and the way forward
essopenarchive.org
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As I near the completion of my Ph.D. journey, I am excited to share a key part of my research with you: a modified column test crucial for predicting landslides induced by heavy rainfall. 🌧️🏔️🔬 This test allows us to measure pore water pressure, volumetric water content, and air pressure in unsaturated soils. The goal? To develop predictive models that can save lives and protect infrastructure by foreseeing landslides before they occur. This research is more than an academic pursuit; it's a potential lifesaver in regions frequently facing these natural disasters. Stay tuned as I continue to share insights and breakthroughs from my research journey. #LandslidePrediction #GeotechnicalEngineering #EnvironmentalImpact
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Our recent study (https://lnkd.in/euwH_ccw) examined the role of biophysical conductances in diagnostic and prognostic evaporation models under arid conditions. We found that the extent of water stress, different functional forms of conductances, and the strength of coupling of these conductances to surface temperature significantly affect the models' responses to soil and atmospheric drought. Our analysis highlights the need for a consensus on theories and models that capture the sensitivity of biophysical conductances to the interplay of soil and atmospheric drought to improve plant water use predictions in complex environments.
Soil and Atmospheric Drought Explain the Biophysical Conductance Responses in Diagnostic and Prognostic Evaporation Models Over Two Contrasting European Forest Sites
agupubs.onlinelibrary.wiley.com
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Ph.D. in Watershed Management | Prediction in Ungauged Basin (PUB) | Extreme Events Analysis | Climate Change
💪😇📢 Happy to share our third paper published for year 2024 in “Water Resources Management” of Springer (IF = 4.4, Q1, Top 15%) entitled “A Comparative Assessment of Decision Tree Algorithms for Index of Sediment Connectivity Modelling” Our study evaluated five decision tree-based machine learning (ML) models (i.e., M5P, RT, RF, AMT, and REPT) using geomorphic and climatic factors. We focused on 50 watersheds in Queensland, Australia, and validated our models against calculated values. The random forest (RF) model emerged as the most robust, especially for smaller subsections of watersheds. These findings have significant implications for implementing watershed and soil and water resources management measures. By leveraging machine learning, we enable informed decisions on sediment yield and transfer. I would like to express my heartfelt appreciation to Dr. Haniyeh Asadi, Prof. Dastorani, and Prof. Roy C. Sidle. Paper link: https://lnkd.in/df_Ds-Tc #WatershedManagement #SedimentTransport #MachineLearning #DataDrivenInsights
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Sonoma Technology scientists authored the journal article “Projected smoke impacts from increased prescribed fire activity in California's high wildfire risk landscape,” published in Atmospheric Environment. To understand and characterize the impacts of increased prescribed burning in California, Sonoma Technology scientists conducted a novel, large-scale modeling study covering the state for a 10-year historical baseline period and a projection of 8 annual cycles to compare the relative air quality impacts and smoke exposure between (1) historical wildfires and prescribed fires, and (2) the historical baseline to a target prescribed fire scenario. This work was funded by the CAL FIRE Forest Health Research Program and performed in collaboration with an interdisciplinary team, including the California Department of Public Health, The Sequoia Foundation, U.S. EPA, Michigan Technological University and the U.S. Forest Service.” Congratulations to authors Samantha Kramer, ShihMing Huang, Crystal D. McClure, Melissa Chaveste, and Fred Lurmann! The full article can be found on Science Direct: https://bit.ly/45tUaMf #Airquality #Wildfire #ForestManagement #DispersionModeling #Projections #PrescribedFires
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The final report from the Workshop on Open Data and Reuse in Social Science Weather Research is now available! https://lnkd.in/e_q2FNCi The workshop was hosted by the Natural Hazards Center and brought together program administrators and researchers from NOAA and the Natural Hazards Center, program directors from the National Science Foundation (NSF), representatives from data repositories and data governance experts, and social science and interdisciplinary researchers. The workshop sought to gather insights and recommendations on ethical publication and reuse of social, behavioral, and economic science data in the context of weather-related research. The impetus for the workshop was the recent OSTP memorandum (https://lnkd.in/eajtFDGs) that delivered guidance for federal departments and agencies to update their public access policies as soon as possible. Here's a link to all of the workshop materials (following the recommendations of the report, we will be publishing all of these materials in an appropriate repository...DOIs forthcoming!): https://lnkd.in/epVrPE9s And for those attending AMS 2024 in Baltimore, we will be having a listening session to discuss the report: https://lnkd.in/ejbR-EwB #NOAA #openscience #sciencepolicy #socialscience #opendata
OpenDataReport_Final_2023.pdf
hazards.colorado.edu
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📢 Check out this peer-reviewed article, authored by BRAC JPGSPH researcher, on modeling and characterization of shallow aquifer water based on ion concentrations to salinity variations using multivariate statistical approach, published in the Discover Water journal. 👉 Click to read: https://lnkd.in/g6T_95ak
Modeling and characterization of shallow aquifer water based on ion concentrations to salinity variations using multivariate statistical approach - Discover Water
link.springer.com
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