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Abstract. Dams have proliferated along the Mekong, spurred by energy demands from economic development and capital from private companies. Swift dam evolution has rendered many databases outdated, in which mismatches arise from differing compilation methods. Without a comprehensive database, up-to-date spatial assessment of dam growth is unavailable. Looking at future development, hydropower potential specifically within the Mekong remains to be systematically evaluated. In this paper, we offer (1) an open-access and unified database of 1055 dams, (2) a spatiotemporal analysis of dams on a sub-basin and country level from the 1980s to the post-2020s, and (3) a grid-based assessment of the theoretical basin-wide hydropower potential using present-day discharge from the CaMa-Flood model (2011–2015, 0.05°) and future discharge from the WaterGAP2 model used for ISIMIP2b (2021–2040, 0.5°). The dam count of 1055 is more than twice the largest existing database, with 608 hydropower dams generating a boom in hydropower capacity from 1242 MW in the 1980s to 69 199 MW post-2020s. While China had the largest capacity increase from the 2000s to the 2010s (+16 854 MW), Laos has the most planned dams and the highest projected growth post-2020s (+18 223 MW). Based on present-day discharge, we estimate a basin-wide hydropower potential of 1 334 683 MW, where Laos is the highest at 514 887 MW. Based on future discharge modeled with climate change, hydropower potential could grow to over 2 000 000 MW. Laos and China are the highest at around 900 000 MW each, together forming over 80 % of the total potential. Our database facilitates research on dam-induced hydrological and ecological alterations, while spatiotemporal analysis of hydropower capacity could illuminate the complex transboundary electricity trade. Through both spatiotemporal and hydropower potential evaluation, we address the current and future vulnerability of countries to dam construction, highlighting the need for better planning and management in the future hydropower hotspot Laos. The Mekong dam database is publicly available at https://doi.org/10.21979/N9/ACZIJN (Ang et al., 2023). 

Despite the potential of autonomous vehicles (AV) to improve traffic efficiency and safety, many studies have shown that traffic accidents in a hybrid traffic environment where both AV and human-driven vehicles (HVs) are present are inevitable because of the unpredictability of HVs. Given that eliminating accidents is impossible, an achievable goal is to design AVs in a way so that they will not be blamed for any accident in which they are involved in. In this paper, we propose BlaFT Rules – or Blame-Free hybrid Traffic motion planning Rules. An AV following BlaFT Rules is designed to be cooperative with HVs as well as other AVs, and will not be blamed for accidents in a structured road environment. We provide proofs that no accidents will happen if all AVs are using a BlaFT Rules conforming motion planner, and that an AV using BlaFT Rules will be blame-free even if it is involved in a collision in hybrid traffic. We implemented a motion planning algorithm that conforms to BlaFT Rules called BlaFT. We instantiated scores of BlaFT controlled AVs and HVs in an urban roadscape loop in the SUMO simulator and show that over time that as the percentage of BlaFT vehicles increases, the traffic becomes safer even with HVs involved. Adding BlaFT vehicles increases the efficiency of traffic as a whole by up to 34% over HVs alone. 

Abstract Satellite‐based post‐tornado assessments have been widely used for the detection of tornado tracks, which heavily relies on the identification of vegetation changes through observations at visible and near‐infrared channels. During the deadly 10–11 December 2021 tornado outbreak, a series of violent tornadoes first touched down over northeastern Arkansas, an area dominated by cropland with rare vegetation coverage in winter. Through the examination of Moderate Resolution Imaging Spectroradiometer multi‐spectral observations, this study reveals significant scars on shortwave infrared channels over this region, but none are captured by visible and near‐infrared channels. The dominant soil type is aquert (one of vertisols), whose high clay content well preserves the severe changes in soil structure during the tornado passage, when the topmost soil layer was removed and underlying soil with higher moisture content was exposed to the air. This study suggests a quick post‐tornado assessment method over less vegetated area by using shortwave infrared channels.