Anil Kumar’s Post

Latest publication in Journal of Hydrometeorology: https://lnkd.in/gjb9sv4S Majority of flash flood research is concentrated on predicting discharge and timing of floods. But the receding period of floods is vital for disaster relief, community recovery, public health etc and attracts little attention in comparison. Generally, we use Recession curves for this, but they can be difficult to use from an operational point of view. Here, we propose a new metric called 'Recoveriness', based on the physical definition of floods by an operational agency. And mapped it across the country using machine learning. Because the metric is based on operational definitions of floods and flash floods, it has the potential for wide usage for both climatology and events. Led by Principal Project Scientist of HydroSense Lab: Anil Kumar. In collaboration with Prof. Pierre-Emmanuel Kirstetter.

📢🌍 Excited to share my latest publication 📚"Deciphering spatial-temporal dynamics of flood exposure in the United States" is now published in Sustainable Cities and Society journal (Cite Score: 22; Impact Factor: 11.7). 🎉💡 In this paper, we evaluated county-wide #flood_exposure 🌊 in the United States and unraveled its #spatial_temporal dynamics from 2001 to 2019. At present, comprehensive, long-term spatial-temporal flood exposure research in the United States is #lacking. In this study, we identified three #research_gaps and tried to answer three research questions via #hypothesis testing. I had the privilege to #lead the paper under the guidance and supervision of my #PhD advisor, Dr. Lei Zou whose invaluable mentorship and support were instrumental throughout the process. A heartfelt appreciation goes out to Dr. Robert Rohli, Dr. Yi Qiang, and Dr. Heng Cai for their invaluable contributions to revising and enhancing the final version of the manuscript. I extend my sincere appreciation to my co-authors, colleagues #Mingzheng_Yang, Debayan Mandal, and #GEAR_Lab team. The paper can be accessed at the following link: https://lnkd.in/ghmGJ4MZ #FloodExposure #UrbanDevelopment #GIScience #SpatialAnalysis #UnitedStates

Our study titled 'Drought monitoring in Burdur Lake, Turkey using multi-sensor remote sensing data sets' has been published in 'Advances in Geodesy and Geoinformation'. You can find it at the link below. https://lnkd.in/dcVf7x7Z

I am pleased to share our recently published research article "Event-based flood estimation in un-gauged sub-basins: a comparative assessment of SCS-UH, CWC-UH and Nash-GIUH based rainfall-runoff models in Shilabati River, Eastern India" in Natural Hazards journal (SCIE, IF 3.3). 🌧🌊 The study explores the performances of three different synthetic unit hydrograph models for routing the excess rainfall into direct runoff. A single storm event is used to simulate direct surface runoff (DSRO) hydrographs in ten un-gauged sub-basins. 🔍 It is observed that the Gemorphologic Instantaneous Unit Hydrograph coupled with Nash two parameter gamma distribution (Nash-GIUH) model outperforms the soil conservation service unit hydrograph and the central water commission unit hydrograph models. 📝 Therefore, results reveal the efficiency of the Nash-GIUH model in estimating the accurate shape of DSRO hydrographs and flood-susceptible un-gauged sub-basins. https://lnkd.in/gs6H97gP

🌊💧 Exploring the Depths: Coastal vs. Continental Hydrology 💧🌊 Dive into the dynamic world of hydrology as we navigate the contrasting landscapes of coastal and continental regions. From the rhythmic tides of the ocean to the vast networks of rivers and streams, the differences in hydrological processes between these two environments are both fascinating and critical to understand. In this post (see first comment for the link), we'll unravel the unique characteristics of coastal hydrology, shaped by the ebb and flow of saltwater, and contrast it with the intricate workings of continental hydrology, driven by freshwater sources and terrestrial ecosystems. Join us as we explore the implications of these differences on water resource management, ecosystem dynamics, and environmental sustainability. Stay tuned for insights that will broaden your understanding of hydrological systems and their profound impact on our world. Don't miss out on this enlightening weekend read! #Hydrology #CoastalHydrology #ContinentalHydrology #WaterManagement #EnvironmentalScience 🌍💦

Latest publication in Journal of Hydrometeorology: https://lnkd.in/gjb9sv4S Code and dataset freely released: https://lnkd.in/gpi2fSfW Majority of flash flood research is concentrated on predicting discharge and timing of floods. But the receding period of floods is vital for disaster relief, community recovery, public health etc and attracts little attention in comparison. Generally, we use Recession curves for this, but they can be difficult to use from an operational point of view. Here, we propose a new metric called 'Recoveriness', based on the physical definition of floods by an operational agency. And mapped it across the country using machine learning. Because the metric is based on operational definitions of floods and flash floods, it has the potential for wide usage in both flood management planning and real-time usage. Led by Principal Project Scientist of HydroSense Lab: Anil Kumar. In collaboration with Prof. Pierre-Emmanuel Kirstetter. HydroSense Lab: https://lnkd.in/dhpmaVr

1/2 I have decided that from today I will be raising the awareness on the land cover and land use change in some "PROTECTED AREAS" and/or "FOREST RESEVES in West Africa. I will be using unsupervised classification (NDVI) of satellite images for the time been but you can leave a comment if you want more details and numbers for a specific area of your interest. If you do not know the meaning of NDVI please take a moment and read this extract below from Google. "NDVI stands for Normalized Difference Vegetation Index, a mathematical calculation that measures the amount and health of vegetation on land. It's based on how plants reflect different parts of the electromagnetic spectrum, particularly near-infrared (NIR) and visible (VIS) light. NDVI values range from -1.0 to 1.0, with negative values indicating clouds and water, and positive values indicating vegetation: *Very low: 0.1 and below, indicating barren areas like rock, sand, or snow *Moderate: 0.2 to 0.3, indicating shrub and grassland *High: 0.6 to 0.8, indicating temperate and tropical rainforests *Close to zero: No vegetation *Close to +1: 0.8 to 0.9, indicating the highest possible density of green leaves." I will be using NDVI to develop images from different time periods for the purposes of understanding vegetation density and changes in plant health in the aforementioned areas.

This video showcases our analysis of the Huaihe River Basin, China, featuring NDVI, LST, and TVDI. March 2016, August 2016, and December 2016 represent the end of the 2015 drought season, the Humid season in the area, and the mid-drought season of 2016, respectively. This project highlights seasonal vegetation dynamics, surface temperatures, and drought patterns, providing valuable insights for environmental monitoring and sustainable resource management. If you want Professional Geospatial Services feel free to contact us at metagis2rs@gmail.com. #RemoteSensing #GIS #NDVI #LST #TVDI #GeospatialAnalysis #EnvironmentalMonitoring #SustainableDevelopment #HuaiheRiver #DataVisualization #ClimateChange #EarthObservation #SatelliteImagery #VegetationIndex #LandSurfaceTemperature #DroughtMonitoring #SpatialAnalysis #GeoSpatial #SmartAgriculture #NaturalResources #Hydrology #ClimateScience #SustainableEcosystems #GeoTech #GeoData #GeospatialIntelligence #Mapping #LocationIntelligence #LandUse #ForestManagement #AgriculturalMonitoring #SoilMoisture #SpatialData #SatelliteData #WaterResources #Biodiversity #DataScience #EnvironmentalProtection #InnovationInGIS #ClimateAdaptation #EnvironmentalScience #UrbanPlanning #SmartMapping #EarthAnalytics #GeoVisualization #VegetationHealth #DigitalMapping #ConservationScience #EcosystemServices #TechForGood

Exciting news: our paper about 𝗖𝗼𝗮𝘀𝘁𝗮𝗹 𝗙𝗹𝗼𝗼𝗱𝗶𝗻𝗴 𝗶𝗻 𝗔𝘀𝗶𝗮𝗻 𝗠𝗲𝗴𝗮𝗱𝗲𝗹𝘁𝗮𝘀: 𝗥𝗲𝗰𝗲𝗻𝘁 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝘀, 𝗣𝗲𝗿𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀, 𝗮𝗻𝗱 𝗖𝗮𝗹𝗹 𝗳𝗼𝗿 𝗔𝗰𝘁𝗶𝗼𝗻𝘀 𝗔𝗺𝗶𝗱𝘀𝘁 𝗟𝗼𝗰𝗮𝗹 𝗮𝗻𝗱 𝗚𝗹𝗼𝗯𝗮𝗹 𝗖𝗵𝗮𝗻𝗴𝗲𝘀 got published open-access in 𝗥𝗲𝘃𝗶𝗲𝘄𝘀 𝗼𝗳 𝗚𝗲𝗼𝗽𝗵𝘆𝘀𝗶𝗰𝘀 today! The paper is open accessible here: https://lnkd.in/e6A8_grT Based on an extensive literature review of the #GangesBrahmaputraMeghna, #Irrawaddy, #ChaoPhraya, #Mekong, and #RedRiver #deltas, we provide an overview of what is known about #coastal #flood-related #hazards in these deltas, their environmental and biophysical drivers, how they interact from short- to long-term changes, including extreme events, and how human activities contribute to coastal #flooding. Through a systems perspective, we assess the current state of the deltaic systems and give insights for shaping their #sustainable #future trajectories to meet the challenges of coastal flooding. 𝗞𝗲𝘆 𝗽𝗼𝗶𝗻𝘁𝘀 are that …urgent action is needed to address data gaps in monitoring coastal flooding in Asian megadeltas …integrated approaches, including in situ data, remote sensing and advanced modeling, are needed to understand coastal flooding impacts …unprecedented changes in Asian megadeltas call for integrated studies; decisions made today shape deltaic sustainability for decades Feel free to #spread the word and #share with anyone who is interested! May this review paper be the starting point for many more research projects on the Asian deltas and inspire also beyond! A big thank you to the great teamwork! @Mélanie Becker, Amelie Paszkowski, @Marta Marcos, @Fabrice Papa, @Rafael Almar, Professor Paul Bates CBE FRS, @Christian France-Lanord, @Md Sarwar Hossain, @Jamal Khan, Makan A. Karegar, Mikhail Karpytchev, @Nathalie Long, Philip Minderhoud, Jeffrey Neal, Robert Nicholls and Jaia Syvitski

We got a great #review #paper out in Reviews of Geophysics on #Coastal #Flooding in #Asian #Megadeltas. Find it open access here: https://lnkd.in/e7QgkeMt The review is build by the #interdisciplinary #ISSI #Megadeltas team in which we bring together the growing issue of #coastal #flooding in megadeltas from #different #sources: #upstream, #downstream and #within the deltas, from #physical towards #anthropogenic. We hope it is a great resource to boost further study and policymaking.