Daniel Nover

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.

Nutrient and particle load estimates to Lake Tahoe (CA-NV, USA) for Total Maximum Daily Load establishment.

The Lake Tahoe Total Maximum Daily Load (TMDL) requires detailed methodologies to identify sources of flows and pollutants (particles and nutrients) for estimating time-variant loads as input data for the Lake Tahoe clarity model. Based on field data and a modeling study, the major sources of pollutant loads include streams (three subdivisions of this category are urban, nonurban, and stream channel erosion), intervening zones (IZs) (two subdivisions of this category are urban and nonurban), atmosphere (wet and dry), groundwater and shoreline erosion. As Lake Tahoe remains well oxygenated year-round, the contribution of internal loading from the bottom sediments was considered minor. A comprehensive quantitative estimate for fine particle number (< 16 μm diameter) and nutrient (nitrogen and phosphorus) loading is presented. Uncertainties in the estimation of fine particle numbers and nutrients for different sources are discussed. Biologically available phosphorus and nitrogen were also evaluated. Urban runoff accounted for 67% of the total fine particle load for all sources making it the most significant contributor although total urban runoff was only 6%. Non-urban flows accounted for 94% of total upland runoff, but the nitrogen, phosphorus and fine sediment loadings were 18%, 47% and 12%, respectively of the total loadings. Atmospheric nitrogen, phosphorus, and fine particle loadings were approximately 57%, 20%, and 16%, respectively of the total loading. Among streams and IZs, IZ 8000, Upper Truckee River, Trout Creek, Blackwood Creek, and Ward Creek are the top fine particle, nitrogen and phosphorus contributors. The relative percentage contribution of inorganic fine particles from all sources based on annual average for the period 1994-2008 on size classes 0.5-1, 1-2, 2-4, 4-8, and 8-16 μm are 73%, 19%, 5%, 2%, and 1%, respectively. These results suggest clear priorities for resource managers to establish TMDL on sources and incoming pollutants and preserving lake clarity.

Impact of forest maintenance on water shortages: Hydrologic modeling and effects of climate change

The importance of water quantity for domestic and industrial water supply, agriculture, and the economy more broadly has led to the development of many water quantity assessment methods. In this study, surface flow and soil water in the forested upper reaches of the Yoshino River are compared using a distributed hydrological model with Forest Maintenance Module under two scenarios; before and after forest maintenance. We also examine the impact of forest maintenance on these variables during extreme droughts. Results show that surface flow and soil water increased after forest maintenance. In addition, projections of future water resources were estimated using a hydrological model and the output from a 20km mesh Global Climate Model (GCM20). River discharge for the near-future (2015-2039) is similar to that of the present (1979-2003). Estimated river discharge for the future (2075-2099) was found to be substantially more extreme than in the current period, with 12m3/s higher peak discharge in August and 7m3/s lower in July compared to the discharges of the present period. Soil water for the future is estimated to be lower than for the present and near future in May. The methods discussed in this study can be applied in other regions and the results help elucidate the impact of forests and climate change on water resources.

Environmental heterogeneity and community structure of the Kobuk River, Alaska, in response to climate change

The Kobuk River runs west along the southern Brooks Range from Gates of the Arctic National Park in Alaska, USA, to the Chukchi Sea. It is highly vulnerable to changes in climate due to its sub-Arctic location, unique geography, and permafrost foundation. Combined with its pristine condition, these qualities make the Kobuk an ideal system upon which to build a conceptual model for predicting ecosystem effects of climate change. We constructed a conceptual ecosystem model for the Kobuk River synthesizing surveyed baseline hydrologic, geomorphic and biotic conditions with literature on Arctic rivers. While the mainstem Kobuk has limited biological productivity, it provides spawning habitat and connectivity for large resident and migratory fish that rely upon off-channel habitat for food resources. System function is dependent largely on intermittent pulse flows that connect riverine habitats, allowing periods of late summer high productivity in off-channel habitat. Spring break-up and hill slope processes are critically important for maintaining habitat complexity and inter-connectivity. Climate change models predict the region will experience a disproportionate increase in average winter air temperature relative to summer temperatures, in the number of ice-free days, and in annual rainfall. Our conceptual model predicts that changes to fish and invertebrate populations on the Kobuk River will result not from physiological responses to increased temperatures, but rather to shifts in two main physical drivers: 1) spring break-up intensity, resulting in changes to scour rate and sediment deposition; and 2) discontinuous permafrost melt, resulting in widespread heterogeneous zones of active layer thickening and thermokarsting. The interaction of these two drivers offers four potential scenarios of geomorphic change in the system and four dramatically different biological outcomes. This model should help managers and scientists evaluate the magnitude and direction of ecosystem changes as they occur within the Kobuk system and potentially other sub-Arctic river systems.

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.

Reconstruction assessment of historical land use: A case study in the Kamo River basin, Kyoto, Japan

Reconstruction assessment of historical land use can be useful for understanding historical conditions and the impact of long-term land-use change. This study establishes a new method to estimate historical land use based on a set of basic rules generated from the comparison of present land-use and historical documents. This method has been formalized in the paleo-land-use reconstruction (PLUR) program, allowing users to quickly reconstruct historical land use using historical information. The 1843, 1902 and 1927 historical land use conditions were generated using the PLUR model for the Kamo River basin (KRB). Our results show that between 1902 and 1976, three golf courses (Ohara Public course, Kamigamo course and Funayama course) replaced forest land in the KRB. As a result of agricultural development, the area occupied by paddy fields in 1843 was 2.48km^2 less than that in 1902. Urban areas increased from 1843 to 1976, mainly reflecting declining coverage of paddy fields after 1902. The approach presented in this study can be used to support land-use change analyses and reconstruction of paleo-hydrology. This study also provides a discussion of the major drivers of land use change.

Preparation of ureido-functionalized PVA/silica mesoporous fibre membranes via electrospinning for adsorption of Pb 2+ and Cu 2+ in wastewater

Ureido-functionalized mesoporous polyvinyl alcohol/silica composite nanofibre membranes were prepared by electrospinning technology and their application for removal of Pb2+ and Cu2+ from wastewater was discussed. The characteristics of the membranes were investigated by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, and N2 adsorption-desorption analysis. Results show that the membranes have long fibrous shapes and worm-like mesoporous micromorphologies. Fourier transform infrared spectroscopy confirmed the membranes were successfully functionalized with ureido groups. Pb2+ and Cu2+ adsorption behavior on the membranes followed a pseudo-second-order nonlinear kinetic model with approximately 30 minutes to equilibrium. Pb2+ adsorption was modelled using a Langmuir isotherm model with maximum adsorption capacity of 26.96 mg g-1. However, Cu2+ adsorption was well described by a Freundlich isotherm model with poor adsorption potential due to the tendency to form chelating complexes with several ureido groups. Notably, the membranes were easily regenerated through acid treatment, and maintained adsorption capacity of 91.87% after five regeneration cycles, showing potential for applications in controlling heavy metals-related pollution and metals reuse.

Estimating future temperature maxima in lakes across the United States using a surrogate modeling approach

A warming climate increases thermal inputs to lakes with potential implications for water quality and aquatic ecosystems. In a previous study, we used a dynamic water column temperature and mixing simulation model to simulate chronic (7-day average) maximum temperatures under a range of potential future climate projections at selected sites representative of different U.S. regions. Here, to extend results to lakes where dynamic models have not been developed, we apply a novel machine learning approach that uses Gaussian Process regression to describe the model response surface as a function of simplified lake characteristics (depth, surface area, water clarity) and climate forcing (winter and summer air temperatures and potential evapotranspiration). We use this approach to extrapolate predictions from the simulation model to the statistical sample of U.S. lakes in the National Lakes Assessment (NLA) database. Results provide a national-scale scoping assessment of the potential thermal risk to lake water quality and ecosystems across the U.S. We suggest a small fraction of lakes will experience less risk of summer thermal stress events due to changes in stratification and mixing dynamics, but most will experience increases. The percentage of lakes in the NLA with simulated 7-day average maximum water temperatures in excess of 30°C is projected to increase from less than 2% to approximately 22% by the end of the 21st century, which could significantly reduce the number of lakes that can support cold water fisheries. Site-specific analysis of the full range of factors that influence thermal profiles in individual lakes is needed to develop appropriate adaptation strategies.