Probabilistic monitoring of meteorological drought impacts on water quality of major rivers in South Korea using copula models.

The impacts of drought range from water supply for humans to ecosystems. Drought affects river water quality by disturbing the hydrological regime in a variety of ways, and can degrade water quality by reducing surface and groundwater availability. In particular, drought-induced low flows, reduced nutrient dilution, and extreme increases in water temperature affect various water quality parameters in streams. Furthermore, the effects of drought on stream water quality may vary from season to season and from stream segment to stream segment, which requires careful investigation. In this study, Environmental Drought Condition Index - water quality (EDCI-wq) is proposed using a bivariate copula joint probability model between meteorological drought index and river water quality. Using this, environmental drought with respect to water quality is defined, and it is confirmed that environmental drought with respect to water quality can be routinely monitored through time series analysis and mapping of the proposed EDCI-wq. In addition, in order to express the environmental drought condition more explicitly to the general public, the environmental drought condition is graded into four classes based on the EDCI-wq. Furthermore, the sensitivity of river water quality to meteorological drought was estimated using the copula joint probability model, which allowed us to identify river segments that are relatively more sensitive to meteorological drought events.

Ecohydrologic model with satellite-based data for predicting streamflow in ungauged basins.

Information on water availability in basins can be crucial for making decisions for effective water resource management in basins. As the operation of hydrometric stations in Korea is mainly focused on flood season and large rivers, most basins have lack or no observed data. Consequently, this complicates water resource planning and management. Remote sensing data is emerging as a powerful alternative to hydrological information in ungauged basins. This study investigated the applicability of Satellite-Remote Sensed Data (SRSD) as a source for model calibration in Prediction in Ungauged Basins (PUB) through modeling. Remote sensed leaf area index (LAI), actual evapotranspiration, and soil moisture data were used. Each SRSD was used alone to calibrate a hydrologic model to predict the daily streamflow for 28 basins in Korea. A vegetation module was added to the existing hydrologic model to use LAI. Among the SRSDs tested, the model calibrated with LAI had the most robust performance, predicting streamflow with acceptable accuracy compared to the traditional calibration based on streamflow. In particular, since the model account for vegetation actively interacting with evapotranspiration and soil moisture in the season of low flow, the LAI-calibrated model showed an advantage in improving the flow prediction performance. Although further research is required to utilize evapotranspiration and soil moisture data, the overall results of the LAI-based calibration were promising for predicting streamflow in ungauged basins where observations are scarce or absent, given that the satellite-derived LAI data were used alone without any preprocessing such as a bias correction. However, the prediction performance of the LAI-calibrated model was found to have a statistically significant relationship with local conditions. Therefore, by evaluating and improving the potential of SRSD in different region and climatic conditions, it is expected that the application of the SRSD-only calibration method can be extended to various ungauged basins.

A copula model to identify the risk of river water temperature stress for meteorological drought.

Drought is a natural phenomenon that can occur in all climatic zones, and is persistent and regionally widespread. Extreme drought caused by climate change can have serious consequences for freshwater ecosystems, which can have significant social and economic impacts. In this study, the effect of meteorological drought on river water temperature was analyzed probabilistically in order to identify the risk of river water temperature stress experienced by the aquatic ecosystem when a meteorological drought occurs. Meteorological drought is divided into a situation in which moisture is insufficiently supplied from the atmosphere and a situation in which the atmosphere requires excessive moisture from the earth's surface. Using the copula theory, a joint probabilistic model between the river water temperature and each meteorological drought caused by two causes is proposed. In order to consider the propagation time from meteorological drought to river water temperature, the optimal time-scale meteorological drought index is adopted through correlation analysis between the meteorological drought index calculated at various time-scales and the river water temperature. The optimal copula function of the drought index and river water temperature is determined using AIC analysis. Using the proposed model, a risk map is drawn for the river water temperature stress experienced by the aquatic ecosystem under the user-defined meteorological drought severity. The risk map identifies the stream sections where the river water temperature is relatively more sensitive to meteorological drought. The identified stream sections appear differently depending on the cause of the meteorological drought, the region, and the season.

A copula model integrating atmospheric moisture demand and supply for vegetation vulnerability mapping.

Drought caused by various meteorological factors negatively affects vegetation. Constructing a joint probability distribution between vegetation and drought information may be appropriate to understand the vulnerability of vegetation to drought. In this study, a copula-based trivariate joint probability model is proposed to investigate the effects of various aspects of meteorological drought on vegetation (vegetation drought). Because drought can be caused by insufficient precipitation or excessive evapotranspiration, the meteorological drought risk for vegetation was divided into two aspects (atmospheric moisture supply and moisture demand). The vulnerability of vegetation drought was mapped when two aspects of meteorological drought occurred separately or simultaneously at high spatial resolution using remote sensing data. The results revealed that the response of vegetation was significantly different depending on the climatic stressors. Although the sensitivity of vegetation to each drought condition varied from region to region, it was found that vegetation was more vulnerable to drought caused by atmospheric moisture demand in most regions of Far East Asia. It has also been shown that drought conditions, which overlapped with insufficient precipitation and excessive evapotranspiration, can drive vegetation to a far more lethal level. Meanwhile, through comparison with the existing VTCI, the proposed Normalized Vegetation Temperature Condition Index (nVTCI) was found to be able to more rationally monitor vegetation drought in the Far East Asian region.

Copula-based Joint Drought Index using SPI and EDDI and its application to climate change.

The drought index, which mainly focuses on the moisture supply side of the atmosphere, which has been mainly used in the field of drought monitoring, has limitations that cannot reflect drought caused by changes in various climate variables such as an increase in surface air temperature due to global warming. To overcome these limitations, various evaporation demand-based drought indices have been proposed, focusing on the aspect of atmospheric moisture demand. However, drought indices that consider only precipitation or the demand for atmospheric evaporation are difficult to comprehensively interpret drought caused by various climatic factors. The novelty of this study is to propose a new drought index to simultaneously monitor droughts occurring in terms of atmospheric moisture supply and demand. The proposed Copula-based Joint Drought Index (CJDI) combines the Standardized Precipitation Index and the Evaporative Demand Drought Index using copula. Since CJDI reflects the correlation between the two drought indices, it is shown that CJDI can better monitor Korea's past droughts than other drought indices. It is found that quantification of past drought using CJDI can be used to objectively recognize the level of drought currently in progress by combining with drought severity-duration-frequency curves derived from partial duration series. As a result of analyzing the future drought pattern in Korea, it was revealed that the drought would be alleviated by about 11% in the case of SPI and SPEI, but the drought would intensify by about 89% in the case of EDDI. In the case of CJDI, it is projected that the drought is likely to intensify to about 17%. From the perspective of better reproducing past droughts and projecting a more convincing future drought than other drought indices, CJDI is expected to be fully utilized as a drought index to monitor droughts and establish climate change adaptation policies.

Overflow risk analysis for designing a nonpoint sources control detention.

This paper presents a design method by which the overflow risk related to a detention for managing nonpoint pollutant sources in urban areas can be evaluated. The overall overflow risk of a nonpoint pollutant sources control detention can be estimated by inherent overflow risk and operational overflow risk. For the purpose of calculating overflow risk, the 3-parameter mixed exponential distribution is applied to describe the probability distribution of rainfall event depth. As a rainfall-runoff calculation procedure required for deriving a rainfall capture curve, the U.S. Natural Resources Conservation Service runoff curve number method is applied to consider the nonlinearity of the rainfall-runoff relation. Finally, the detention overflow risk is assessed with respect to the detention design capacity and drainage time. The proposed overflow risk assessment is expected to provide a baseline to determine quantitative parameters in designing a nonpoint sources control detention.

Fabrication of reliable semiconductor nanowires by controlling crystalline structure.

One-dimensional SnO(2) nanomaterials with wide bandgap characteristics are attractive for flexible and/or transparent displays and high-performance nano-electronics. In this study, the crystallinity of SnO(2) nanowires was regulated by controlling their growth temperatures. Moreover, the correlation of the crystallinity of nanowires with optical and electrical characteristics was analyzed. When SnO(2) nanowires were grown at temperatures below 900 °C, they showed various growth directions and abnormal discontinuity in their crystal structures. On the other hand, most nanowires grown at 950 °C exhibited a regular growth trend in the direction of [100]. In addition, the low temperature photoluminescence measurement revealed that the higher growth temperatures of nanowires gradually decreased the 500 nm peak rather than the 620 nm peak. The former peak is derived from the surface defect related to the shallow energy level and affects nanowire surface states. Owing to crystallinity and defects, the threshold voltage range (maximum-minimum) of SnO(2) nanowire transistors was 1.5 V at 850 °C, 1.1 V at 900 °C, and 0.5 V at 950 °C, with dispersion characteristics dramatically decreased. This study successfully demonstrated the effects of nanowire crystallinity on optical and electrical characteristics. It also suggested that the optical and electrical characteristics of nanowire transistors could be regulated by controlling their growth temperatures in the course of producing SnO(2) nanowires.

Effects of land use change and water reuse options on urban water cycle.

The aim of this article was to study the effects of land use change and water reuse options on an urban water cycle. A water cycle analysis was performed on the Goonja drainage basin, located in metropolitan Seoul, using the Aquacycle model. The chronological effects of urbanization were first assessed for the land uses of the Goonja drainage basin from 1975 to 2005, where the ratio of impervious areas ranged from 43% to 84%. Progressive urbanization was identified as leading to a decrease in evapotranspiration (29%), an increase in surface runoff (41%) and a decrease in groundwater recharge (74%), indicating a serious distortion of the water cycle. From a subsequent analysis of the water reuse options, such as rainwater use and wastewater reuse, it is concluded that wastewater reuse seemed to have an advantage over rainwater use for providing a consistent water supply throughout the year for a country like Korea, where the rainy season is concentrated during the summer monsoon.

Hybrid nanowire-multilayer graphene film light-emitting sources.

We report a versatile hybrid device consisting of one-dimensional ZnS and Te-doped ZnS (ZnS:Te) nanowires (NWs) upon two-dimensional multilayer graphene films (MGFs). Single-crystalline ZnS and ZnS:Te NWs were grown directly on a MGF without a catalyst, and exhibited blue-green and blue emission peaks of ∼ 503 and ∼ 440 nm. A field emission light emitter using ZnS:Te NWs on a MGF was demonstrated, and it indicates excellent contact properties between the NWs and MGFs. The resulting hybrid devices are promising candidates for potential applications as building blocks for the development of highly functional and efficient electroluminescent devices and field-emitting devices including flexible and/or transparent display devices.

Tunable-white-light-emitting nanowire sources.

Tunable-white-light-emitting materials are developed by combining two single-crystal oxide nanowire materials-ZnO and SnO(2)-having different light emissions. The tuning of white-light emission from cool white to warm white is achieved for the first time by adjusting the growth sequence and growth time of the ZnO and SnO(2) nanowires. Combined ZnO:SnO(2) nanowire arrays yield a desired emission color from (0.30, 0.31) to (0.35, 0.37) and a white luminescence of approximately 100 cd m(-2), whose reproducibility can be controlled accurately. These results pave a new way to understand and generate a desired white-light emission, which is a key technology in large-area planar display devices, including flexible and/or transparent display devices.

Urban stormwater capture curve using three-parameter mixed exponential probability density function and NRCS runoff curve number method.

Most related literature regarding designing urban non-point-source management systems assumes that precipitation event-depths follow the 1-parameter exponential probability density function to reduce the mathematical complexity of the derivation process. However, the method of expressing the rainfall is the most important factor for analyzing stormwater; thus, a better mathematical expression, which represents the probability distribution of rainfall depths, is suggested in this study. Also, the rainfall-runoff calculation procedure required for deriving a stormwater-capture curve is altered by the U.S. Natural Resources Conservation Service (Washington, D.C.) (NRCS) runoff curve number method to consider the nonlinearity of the rainfall-runoff relation and, at the same time, obtain a more verifiable and representative curve for design when applying it to urban drainage areas with complicated land-use characteristics, such as occurs in Korea. The result of developing the stormwater-capture curve from the rainfall data in Busan, Korea, confirms that the methodology suggested in this study provides a better solution than the pre-existing one.