Yusuke Hiraga

The Probable Maximum Precipitation (PMP) estimation for long durations during winter and spring seasons is important to develop the Probable Maximum Flood for snowmelt-driven regions since extreme floods are often characterized by snow-accumulation and snowmelt processes rather than by a single rainstorm event. Although several studies have estimated the PMP for a single storm duration, little attention has been given to the PMP estimation for long durations on the order of several months. This

In recent years, there has been an increase in interest in estimating probable maximum precipitation (PMP) by numerical weather model (NWM)-based precipitation maximization methods, mainly, the moisture optimization method, storm transposition method, and their combination. This study addresses a quantitative comparison of the effectiveness of each precipitation maximization method regarding the increase in precipitation depths and a discussion on their functions for maximizing precipitation dep

• A novel model-based method to estimate PMP under climate change. • Maximizing Atmospheric River-induced heavy precipitation in Chile. • Maximum precipitation with shorter durations consistently increased with warming. This study proposes a novel dynamical model-based method to estimate Probable Maximum Precipitation (PMP) under climate change. The proposed method fundamentally builds on the Atmospheric Initial and Boundary condition shifting method to realize storm transposition and the pseudo

This study examined the sensitivity of cloud microphysics and planetary boundary layer (PBL) parameterization in the simulation of localized heavy rainfall in northern Japan such as the August 2022 event. Accurate simulation/forecast of such quasi-stationary line-shaped mesoscale convective systems is a pressing issue for the region. The sensitivities of 17 different cloud microphysics parameterization schemes, including single and double moments, and eight different PBL schemes, including nonlo

Abstract This study proposes a model‐based methodology to estimate design precipitation for long durations during the winter and spring seasons (October to June) through its application to the drainage areas of two dams in the Columbia River Basin, United States. For basins with large reservoir storage or snowpack, design precipitation and floods need to be estimated based on long‐duration processes rather than focusing only on flood peaks or single storm durations. This study used the advanced

US probable maximum precipitation (PMP) estimation guidance fundamentally relies on the assumption that any change in precipitable water is consistent with the change in precipitation. While this assumption is theoretically sound in extreme storms that are convective in nature with lifting so vigorous as to convert all available atmospheric water vapor into precipitation, this type of storm rarely occurs in the Pacific Northwest of the United States; the assumption may be invalid. This study inv

• Climate change impacts on PMP-magnitude extreme precipitation, explicitly including dynamic effects. • Warming scaling rate for PMP significantly exceeded C-C rate (>21 %/K). • The estimated PMP magnitude became more frequent under warming conditions. Understanding of the effects of climate change on Probable Maximum Precipitation (PMP)-like extreme precipitation is limited but urgently needed to update outdated design values. This study aims to quantify these effects through the application o

In the lower Mekong River Basin, the watershed development, such as reclamation, has been rapidly erence water index (NDWI) were defined as going on. The reclamation is expected to cause many problems on this important watershed environment. The objective of this research is to quantitatively clarify the impact of reclamation on the watershed environment of the lower Mekong River Basin. The locations of reclamation areas were extracted using MNDWI, NDVI and NDSI derived by Landsat data. As a res

This study examined the hydrological/meteorological controls on large wildfires > 10,000 acres (40.5 km2) during 2017–2020 in Northern California at spatial and temporal scales of the target wildfires’ occurrence or growth. This study used the following simple indices for analysis: Moisture Deficit Index (MDI) computed by dividing vapor pressure deficit by soil moisture, MDIWIND computed by multiplying MDI by horizontal wind speed, and MDIGUST computed by multiplying MDI by wind gust speed. T

In basins where disastrous floods are driven by long-duration processes, such as snow accumulation/melt and series of storm events, estimating maximum precipitation (MP) for not a single storm duration but long durations is necessary to estimate maximum flood. Although the model-based methodology to estimate MP for long durations was recently proposed, it is still required to better understand what characteristics of water years lead to higher increases in precipitation depths. To examine this i

Maipo River Basin (MRB) in Chile Aging infrastructures and climate-change emphasize an urgent need to improve extreme precipitation modeling and ultimately update Probable Maximum Precipitation (PMP) estimates. Motivated by this background, this study first examined the optimal physics parameterizations for modeling extreme precipitation. We then estimated PMP using the model-based method, which is compared with traditional methods-based PMP estimates. Finally, the exceedance probability of the

Nowadays, a deterioration of floodplain water quality in the Lower Mekong River Basin in Cambodia is expected because of urbanization/industrialization by landfilling. This study aimed to evaluate the impact of floodplain landfilling on basin water quality. Field observations of total phosphorus (TP), chemical oxygen demand and heavy metals were conducted in the Mekong River Basin in Cambodia and the Chao Phraya River Basin in Thailand. In the Mekong River Basin, TP was 2.05 mg/L in the floodpla