Sungwook Wi

Expanded decision-scaling framework to select robust long-term water-system plans under hydroclimatic uncertainties

AbstractThis paper presents a decision-scaling based framework to determine whether one or more preselected planning alternatives for a multiobjective water-resources system are robust to a variety of nonstationary hydroclimatic conditions and modeling uncertainties. The decision-scaling methodology is advanced beyond previous applications with an efficient procedure to select realizations of climate variability and Bayesian methods to assess the effects of hydrologic uncertainty. Monte Carlo simulations are used to identify long-term planning alternatives that are robust despite the hydroclimatic uncertainties. A new metric is proposed to define robustness in this context. The framework is coupled with a host of long-term projections to understand the likelihood of potential future changes and provide useful guidance for planning. The effects of climate model downscaling and credibility on the decision process are discussed. The approach is demonstrated in a case study for a dual-purpose surface water re...

Non-stationary frequency analysis of extreme precipitation in South Korea using peaks-over-threshold and annual maxima

The conventional approach to the frequency analysis of extreme precipitation is complicated by non-stationarity resulting from climate variability and change. This study utilized a non-stationary frequency analysis to better understand the time-varying behavior of short-duration (1-, 6-, 12-, and 24-h) precipitation extremes at 65 weather stations scattered across South Korea. Trends in precipitation extremes were diagnosed with respect to both annual maximum precipitation (AMP) and peaks-over-threshold (POT) extremes. Non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with model parameters made a linear function of time were applied to AMP and POT respectively. Trends detected using the Mann–Kendall test revealed that the stations showing an increasing trend in AMP extremes were concentrated in the mountainous areas (the northeast and southwest regions) of South Korea. Trend tests on POT extremes provided fairly different results, with a significantly reduced number of stations showing an increasing trend and with some stations showing a decreasing trend. For most of stations showing a statistically significant trend, non-stationary GEV and GPD models significantly outperformed their stationary counterparts, particularly for precipitation extremes with shorter durations. Due to a significant-increasing trend in the POT frequency found at a considerable number of stations (about 10 stations for each rainfall duration), the performance of modeling POT extremes was further improved with a non-homogeneous Poisson model. The large differences in design storm estimates between stationary and non-stationary models (design storm estimates from stationary models were significantly lower than the estimates of non-stationary models) demonstrated the challenges in relying on the stationary assumption when planning the design and management of water facilities. This study also highlighted the need of caution when quantifying design storms from POT and AMP extremes by showing a large discrepancy between the estimates from those two approaches.

The Effects of Climate Change on Seasonal Snowpack and the Hydrology of the Northeastern and Upper Midwest United States

AbstractThe potential effects of climate change on the snowpack of the northeastern and upper Midwest United States are assessed using statistically downscaled climate projections from an ensemble of 10 climate models and a macroscale hydrological model. Climate simulations for the region indicate warmer-than-normal temperatures and wetter conditions for the snow season (November–April) during the twenty-first century. However, despite projected increases in seasonal precipitation, statistically significant negative trends in snow water equivalent (SWE) are found for the region. Snow cover is likely to migrate northward in the future as a result of warmer-than-present air temperatures, with higher loss rates in northern latitudes and at high elevation. Decreases in future (2041–95) snow cover in early spring will likely affect the timing of maximum spring peak streamflow, with earlier peaks predicted in more than 80% of the 124 basins studied.

A user-friendly software package for VIC hydrologic model development

The Variable Infiltration Capacity (VIC) hydrologic and river routing model simulates the water and energy fluxes that occur near the land surface and provides useful information regarding the quantity and timing of available water within a watershed system. However, despite its popularity, wider adoption is hampered by the considerable effort required to prepare model inputs and calibrate the model parameters. This study presents a user-friendly software package, named VIC-Automated Setup Toolkit (VIC-ASSIST), accessible through an intuitive MATLAB graphical user interface. VIC-ASSIST enables users to navigate the model building process through prompts and automation, with the intention to promote the use of the model for practical, educational, and research purposes. The automated processes include watershed delineation, climate and geographical input set-up, model parameter calibration, sensitivity analysis, and graphical output generation. We demonstrate the packages utilities in various case studies. We introduce VIC-Automated Setup Toolkit (VIC-ASSIST).VIC-ASSIST framed within a MATLAB GUI aids building and calibrating the VIC model.VIC-ASSIST helps users navigate the model building processes through automation.We demonstrate the packages utilities in various case studies.

Guiding Groundwater Policy in the Indus Basin of Pakistan Using a Physically Based Groundwater Model

AbstractThe exponential increase in groundwater usage over the past few decades in the Punjab province in Pakistan is responsible for the significant groundwater table decline in many parts of the province, leading to an urgent need for policy measures to better manage groundwater use. A better understanding of the underground water balance is necessary for drafting informed groundwater management plans. With limited data, this study develops the first physically-based groundwater model for the entire Punjab province. Using the calibrated provincewide model, simulations are performed to evaluate groundwater dynamics in the future under different scenarios. These scenarios comprise controls on groundwater pumping, canal infrastructure improvements, and precipitation changes. The impacts of these scenarios are highlighted with the mapping of changes in water table, pumping cost, and waterlogged area. The results show that changes in both groundwater abstraction and seepage from the canal system into the aqu...