Weili Duan

Spatial and temporal trends in estimates of nutrient and suspended sediment loads in the Ishikari River, Japan, 1985 to 2010.

Nutrients and suspended sediment in surface water play important roles in aquatic ecosystems and contribute strongly to water quality with implication for drinking water resources, human and environmental health. Estimating loads of nutrients (nitrogen and phosphorus) and suspended sediment (SS) is complicated because of infrequent monitoring data, retransformation bias, data censoring, and non-normality. To obtain reliable unbiased estimates, the Maintenance of Variance-Extension type 3 (MOVE. 3) and the regression model Load Estimator (LOADEST) were applied to develop regression equations and to estimate total nitrogen (TN), total phosphorus (TP) and SS loads at five sites on the Ishikari River, Japan, from 1985 to 2010. Coefficients of determination (R(2)) for the best-fit regression models for loads of TN, TP, and SS for the five sites ranged from 71.86% to 90.94%, suggesting the model for all three constituents successfully simulated the variability in constituent loads at all studied sites. Estimated monthly average loads at Yishikarikakou-bashi were larger than at the other sites, with TN, TP, and SS loads ranging from 8.52×10(3) to 2.00×10(5) kg/day (Apr. 1999), 3.96×10(2) to 5.23×10(4) kg/ day (Apr. 1999), and 9.21×10(4) to 9.25×10(7) kg/day (Sep. 2001), respectively. Because of variation in river discharge, the estimated seasonal loads fluctuated widely over the period 1985 to 2010, with the greatest loads occurring in spring and the smallest loads occurring in winter. Estimated loads of TN, TP, and especially SS showed decreasing trends during the study period. Accurate load estimation is a necessary goal of water quality monitoring efforts and the methods described here provide essential information for effectively managing water resources.

Impact assessment of rainfall scenarios and land-use change on hydrologic response using synthetic Area IDF curves

In combination with land use change, climate change is increasingly leading to extreme weather conditions and consequently novel hydrologic conditions. Rainfall Area intensity-duration-frequency (IDF) curves, commonly used tools for modeling hydrology and managing flood risk can be used to assess hydrologic response under extreme rainfall conditions. We explore the influence of land use change on hydrologic response under designed extreme rainfall over the period 1976 to 2006 in the Kamo River basin. Run-off for all six designed rainfall shapes under 2006 land use is higher than that under 1976 land use, but the timing of peak discharge under 2006 land use occurs at roughly the same time as that under 1976 land use. Results indicate that run-off under 2006 land use yielded higher discharge than under 1976 land use, and rainfall shape six leads to the most extreme hydrologic response and most dangerous conditions from the perspective of urban planning and flood risk management. Future hydrologic response will differ from present due both to changes in land cover and changes in extreme rainfall patterns requiring modification to Area IDF curves for catchments.

Emergency Response System for Pollution Accidents in Chemical Industrial Parks, China

In addition to property damage and loss of lives, environment pollution, such as water pollution and air pollution caused by accidents in chemical industrial parks (CIPs) is a significant issue in China. An emergency response system (ERS) was therefore planned to properly and proactively cope with safety incidents including fire and explosions occurring in the CIPs in this study. Using a scenario analysis, the stages of emergency response were divided into three levels, after introducing the domino effect, and fundamental requirements of ERS design were confirmed. The framework of ERS was composed mainly of a monitoring system, an emergency command center, an action system, and a supporting system. On this basis, six main emergency rescue steps containing alarm receipt, emergency evaluation, launched corresponding emergency plans, emergency rescue actions, emergency recovery, and result evaluation and feedback were determined. Finally, an example from the XiaoHu Chemical Industrial Park (XHCIP) was presented to check on the integrality, reliability, and maneuverability of the ERS, and the result of the first emergency drill with this ERS indicated that the developed ERS can reduce delays, improve usage efficiency of resources, and raise emergency rescue efficiency.

Spatiotemporal patterns and source attribution of nitrogen pollution in a typical headwater agricultural watershed in Southeastern China

Excessive nitrogen (N) discharge from agriculture causes widespread problems in aquatic ecosystems. Knowledge of spatiotemporal patterns and source attribution of N pollution is critical for nutrient management programs but is poorly studied in headwaters with various small water bodies and mini-point pollution sources. Taking a typical small watershed in the low mountains of Southeastern China as an example, N pollution and source attribution were studied for a multipond system around a village using the Hydrological Simulation Program-Fortran (HSPF) model. The results exhibited distinctive spatio-seasonal variations with an overall seriousness rank for the three indicators: total nitrogen (TN) > nitrate/nitrite nitrogen (NOx−-N) > ammonia nitrogen (NH3-N), according to the Chinese Surface Water Quality Standard. TN pollution was severe for the entire watershed, while NOx−-N pollution was significant for ponds and ditches far from the village, and the NH3-N concentrations were acceptable except for the ponds near the village in summer. Although food and cash crop production accounted for the largest source of N loads, we discovered that mini-point pollution sources, including animal feeding operations, rural residential sewage, and waste, together contributed as high as 47% of the TN and NH3-N loads in ponds and ditches. So, apart from eco-fertilizer programs and concentrated animal feeding operations, the importance of environmental awareness building for resource management is highlighted for small farmers in headwater agricultural watersheds. As a first attempt to incorporate multipond systems into the process-based modeling of nonpoint source (NPS) pollution, this work can inform other hydro-environmental studies on scattered and small water bodies. The results are also useful to water quality improvement for entire river basins.

Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China

Comprehensive understanding of the long-term trends and seasonality of water quality is important for controlling water pollution. This study focuses on spatio-temporal distributions, long-term trends, and seasonality of water quality in the Yangtze River basin using a combination of the seasonal Mann-Kendall test and time-series decomposition. The used weekly water quality data were from 17 environmental stations for the period January 2004 to December 2015. Results show gradual improvement in water quality during this period in the Yangtze River basin and greater improvement in the Uppermost Yangtze River basin. The larger cities, with high GDP and population density, experienced relatively higher pollution levels due to discharge of industrial and household wastewater. There are higher pollution levels in Xiang and Gan River basins, as indicated by higher NH4-N and CODMn concentrations measured at the stations within these basins. Significant trends in water quality were identified for the 2004–2015 period. Operations of the three Gorges Reservoir (TGR) enhanced pH fluctuations and possibly attenuated CODMn, and NH4-N transportation. Finally, seasonal cycles of varying strength were detected for time-series of pollutants in river discharge. Seasonal patterns in pH indicate that maxima appear in winter, and minima in summer, with the opposite true for CODMn. Accurate understanding of long-term trends and seasonality are necessary goals of water quality monitoring system efforts and the analysis methods described here provide essential information for effectively controlling water pollution.

Assessment of hydrological extremes in the Kamo River Basin, Japan

ABSTRACT A suite of extreme indices derived from daily precipitation and streamflow was analysed to assess changes in the hydrological extremes from 1951 to 2012 in the Kamo River Basin. The evaluated indices included annual maximum 1-day and 5-day precipitation (RX1day, RX5day), consecutive dry days (CDD), annual maximum 1-day and 5-day streamflow (SX1day, SX5day), and consecutive low-flow days (CDS). Sen’s slope estimator and two versions of the Mann-Kendall test were used to detect trends in the indices. Also, frequency distributions of the indices were analysed separately for two periods: 1951–1981 and 1982–2012. The results indicate that quantiles of the rainfall indices corresponding to the 100-year return period have decreased in recent years, and the streamflow indices had similar patterns. Although consecutive no rainfall days represented by 100-year CDD decreased, continuous low-flow days represented by 100-year CDS increased. This pattern change is likely associated with the increase in temperature during this period. EDITOR D. Koutsoyiannis ASSOCIATE EDITOR E. Gargouri

Numerical Assessment of Shallow Landslide Using the Distributed Hydrological–Geotechnical Model in a Large Scale

Kyushu is the third largest island of Japan. The natural hazards accompanied with geomorphic changes like landslides and debris flows occur at many places in Kyushu region. In this study, a hydrological–geotechnical modelling system was applied in Kyushu using observed rainfall for a regional shallow landslide prediction system. The physically based distributed landslide model has been developed by integrating a grid-based distributed kinematic wave rainfall-runoff model with an infinite slope stability approach. The resulting time-invariant landslide susceptibility map shows good agreement with the spatial patterns of observed landslides in Kyushu region. Application of the model to calculate the shallow landslides shows that the model can successfully simulate the effect of rainfall movement and intensity on the spatiotemporal dynamic of hydrological variables that trigger shallow landslides. The results of this study can be used to develop the potential applicability of the modelling system for shallow landslide disaster predictions and warnings.

Modeling the Effects of Land Use Change and Climate Change on Stream Flow Using GIS and a Hydrological Model

This paper reports our research effort aiming to investigate the applicability of integrating a hydrological model and the Hydrological Predictions for the Environment (HYPE) model with a geographic information system (GIS) to examine the effect of land use change and climate change on stream-flows with the Kamo River basin (KRB) located in the central Honshu island, Japan as a case study. The goal of this study was to provide important information for understanding water discharge variations as a basis to guide water resource managers in environmental change decisions in this river basin. This goal was accomplished by two steps (i) comparing HYPE-generated hydrographs for various meteorological data from history to present at current land use (S1 and S2); and (ii) comparing HYPE-generated hydrographs for historical and current land use scenarios at current climate (S3 and S4). The calibration and validation results suggest that HYPE performs well in the case study site for daily simulations. The results of S1–S2 indicate that with the impact of climate change, the trend of annual and seasonal stream flows at the Kamo River Basin outlet would decrease. However, there is no evidence to indicate that the flood risk would be decreasing. The results of S3–S4 show that the conversion of forest, glass and agriculture (FGA) into urban area would induce high peak flows, a reduction in annual evaporation and an increase in annual surface runoff.

Modelling Shallow Landslide Risk Using GIS and a Distributed Hydro-geotechnical Model

GIS and distributed hydrological models are important tools for shallow landslide prediction, particularly as such disasters are exacerbated by global change driven changes in precipitation regimes. The main objective of this chapter is to outline a detailed methodology for shallow landslide risk assessment using GIS and a hydrological model. We have developed a method to assess shallow landslide risk using GIS tools and a distributed hydrological model and further used this method to analyze the probability of shallow landslides in a case study. The physically based distributed landslide model was developed by integrating a grid-based distributed kinematic wave rainfall-runoff model combined with an infinite slope stability module. Application of the model to assess shallow landslide risk using rainfall data for Kyushu Island shows that the model can successfully predict the effect of rainfall distribution and intensity on the driving variables that trigger shallow landslides. The modeling system has broad applicability for shallow landslide prediction and warning.

Climate Change Impacts on Wave Characteristics along the Coast of Japan from 1986 to 2012

ABSTRACT Duan, W.; He, B.; Takara, K.; Luo, P.; Hu, M.; Alias, N.E.; Ishihara, M., and Wang Y., 2014. Climate change impacts on wave characteristics along the coast of Japan from 1986 to 2012. With the effects of the earths climate change, ocean waves present various change trends in different areas. Using the linear trend method and the Mann-Kendall test, we analyzed the trends of the annual maximum significant wave height and period during the period of 1986–2012 on the basis of the 10 wave monitoring stations along the Sea of Japan coast. The correlation with climate change indexes including SST (sea surface temperature), MEI (Multivariate Enso Index), SOI (Southern Oscillation Index), AOI (Arctic Oscillation Index), PDOI (Pacific Decade Oscillation Index) and NPI (North Pacific Index) were also checked to fully understand the changes of wave characteristics. Generally, the annual maximum significant wave height and period increased at almost all stations along the Sea of Japan from 1986 to 2012. The Sakata station had the largest increase in the annual maximum significant wave height and period, which increased about 49.65 cm (approximately 1.84 cm yr-1) and 0.24 s (approximately 0.009s yr-1) from 1986 to 2012, respectively. The increasing tendency of the wave height and period was more apparent in the northeast areas along the Sea of Japan coast compared to the southwest areas. The annual maximum significant wave height and period had negative relationships with PDOI, SOI, MEI and AOI at most stations, while positive relationships with NPI and SST at most stations.