Search USGSSearch

Geology topics

Lulin Xue

Publications and source records attributed to Lulin Xue.

2 recordsLinked to original sources

Estimating the impact of climate and vegetation changes on runoff risk across the Hawaiian landscape

In Hawai’i, ecosystem conservation practitioners are increasingly considering the potential ecohydrological benefits from applied conservation action to mitigate the degrading impacts of runoff on native and restored ecosystems. One determinant of runoff is excess rainfall events where rainfall rates exceed the infiltration capacity of soils. To help understand runoff risks, we calculated the probability of excess rainfall events across the Hawaiian landscape by comparing the probability distributions of projected rainfall frequency and land-cover-specific infiltration capacity. We characterized soil infiltration capacity based on different land cover types (bare soil, grasses, and woody vegetation) and compared them to the frequency of large rainfall events under current and future climate scenarios. We then mapped the potential risk of excess rainfall across the main Hawaiian Islands. Our results show that land cover type has a very large effect on runoff risk as excess rainfall conditions are 234% more likely in bare soil and 75% more likely in grasslands compared to woody forests and shrublands. In contrast, projected shifts in rainfall intensity by end-of-century show little impact on these probabilities and thus, the risk of runoff. This indicates that the probability of excess rainfall is primarily driven by differences in land cover and not by current or potential shifts in rainfall patterns across the Hawaiian landscape. The ability to estimate the risk of potentially ecologically and economically costly runoff based on changes of land cover is useful for managers focused on invasive species control and restoration planning, especially for native and endemic ecosystems unique to the State of Hawai’i.

Hawaii

Bioclimatic variables dataset for baseline and future climate scenarios for climate change studies in Hawai'i

Gridded bioclimatic variables representing yearly, seasonal, and monthly means and extremes in temperature and precipitation have been widely used for ecological modeling purposes and in broader climate change impact and biogeographical studies. As a result of their utility, numerous sets of bioclimatic variables have been developed on a global scale (e.g., WorldClim) but rarely represent the finer regional scale pattern of climate in Hawai'i. Recognizing the value of having such regionally downscaled products, we integrated more detailed projections from recent climate models developed for Hawai'i with current climatological datasets to generate updated regionally defined bioclimatic variables. We derived updated bioclimatic variables from new projections of baseline and future monthly minimum, mean, and maximum temperature (T min , T mean , T max ) and mean precipitation (P mean ) data at 250 m resolution. We used the most up-to-date dynamically downscaled projections based on the Weather Research and Forecasting (WRF) model from the International Pacific Research Center (IPRC) and the National Center for Atmospheric Research (NCAR). We summarized the monthly data from these two climate projections into a suite of 19 standard bioclimatic variables that provide detailed information about annual and seasonal mean climatic conditions for the Hawaiian Islands. These bioclimatic variables are available for three climate scenarios: baseline climate (1990-2009) and future climate (2080-2099) under representative concentration pathway (RCP) 4.5 (IPRC projections only) and RCP 8.5 (both IPRC and NCAR projections) climate scenarios. The resulting dataset provides a more robust set of climate products that can be used for modeling purposes, impact studies, and management planning.

Hawaii