Implications of Conceptual Channel Representation on SWAT Streamflow and Sediment Modeling

Hydrologic modeling outputs are influenced by how a watershed system is represented. Channel routing is a typical example of the mathematical conceptualization of watershed landscape and processes in hydrologic modeling. We investigated the sensitivity of accuracy, equifinality, and uncertainty of Soil and Water Assessment Tool (SWAT) modeling to channel dimensions to demonstrate how a conceptual representation of a watershed system affects streamflow and sediment modeling. Results showed the amount of uncertainty and equifinality strongly responded to channel dimensions. On the other hand, the model performance did not significantly vary with the changes in the channel representation due to the degree of freedom allowed by the conceptual nature of hydrologic modeling in the parameter calibration. Such findings demonstrated good modeling performance statistics do not necessarily mean small output uncertainty, and partial improvements in the watershed representation may neither increase modeling accuracy nor reduce uncertainty. We also showed the equifinality and uncertainty of hydrologic modeling are case‐dependent rather than specific to models or regions, suggesting great caution should be used when attempting to transfer uncertainty analysis results to other modeling studies, especially for ungauged watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

A comparison study on high-temperature water–gas shift reaction over Fe/Al/Cu and Fe/Al/Ni catalysts using simulated waste-derived synthesis gas

A comparative study on Fe/Al, Fe/Al/Cu, and Fe/Al/Ni catalysts in high-temperature water–gas shift reaction (HT–WGS) using simulated waste-derived synthesis gas has been carried out. The metal oxide (Cu and Ni) and aluminum incorporated Fe catalysts were designed to get highly active HT–WGS catalysts. Despite the high CO concentration in the simulated waste-derived synthesis gas, Fe/Al/Cu catalyst exhibited the highest CO conversion (84 %) and 100 % selectivity to CO₂ at a very high gas hourly space velocity (GHSV) of 40,057 h^?1. The outstanding catalytic performance is mainly due to easier reducibility, the synergy effect of Cu and Al, and the stability of the magnetite.     

Numerical simulation on multi-scale diffusion of CO2 injected in the deep ocean in a practical scenario

The direct injection of CO₂ into the deep ocean is one of the ways for the mitigation of the global warming. There is, however, a concern about its environmental impact near the injection point. To minimize its biological impact, it is necessary to make CO₂ disperse as fast as possible and it is thought that injection with pipes towed by moving-ships is effective for this purpose. Because the injection ships are planned to move in the site, the order of magnitude of which is 10² km, a mesoscale model is required to predict CO₂ fate in seawater. At the same time, it is required to predict the concentration precisely near the injection points, which move with the ships in the mesoscale domain. In this study, a multi-scale ocean model was developed to analyze the dispersion of CO₂ in the deep ocean: the model consists of a fixed mesoscale domain and 5 small-scale domains nesting in the mesoscale domain. Each small-scale domain involves 6 pipes and moves along with the trajectories of the injection ships. From the results of the present numerical simulation, the developed technique demonstrated its applicability as a tool to optimise the system to dilute CO₂ below some criterion of biological impact.     

A contribution of brown carbon aerosol to the aerosol light absorption and its radiative forcing in East Asia

Brown carbon aerosols were recently found to be ubiquitous and effectively absorb solar radiation. We use a 3-D global chemical transport model (GEOS-Chem) together with aircraft and ground based observations from the TRACE-P and the ACE-Asia campaigns to examine the contribution of brown carbon aerosol to the aerosol light absorption and its climatic implication over East Asia in spring 2001. We estimated brown carbon aerosol concentrations in the model using the mass ratio of brown carbon to black carbon (BC) aerosols based on measurements in China and Europe. The comparison of simulated versus observed aerosol light absorption showed that the model accounting for brown carbon aerosol resulted in a better agreement with the observations in East Asian-Pacific outflow. We then used the model results to compute the radiative forcing of brown carbon, which amounts up to ?2.4 W m^?2 and 0.24 W m^?2 at the surface and at the top of the atmosphere (TOA), respectively, over East Asia. Mean radiative forcing of brown carbon aerosol is ?0.43 W m^?2 and 0.05 W m^?2 at the surface and at the TOA, accounting for about 15% of total radiative forcing (?2.2 W m^?2 and 0.33 W m^?2) by absorbing aerosols (BC + brown carbon aerosol), having a significant climatic implication in East Asia.     

APPLICATION OF GREY MODEL AND ARTIFICIAL NEURAL NETWORKS TO FLOOD FORECASTING1

The main focus of this study was to compare the Grey model and several artificial neural network (ANN) models for real time flood forecasting, including a comparison of the models for various lead times (ranging from one to six hours). For hydrological applications, the Grey model has the advantage that it can easily be used in forecasting without assuming that forecast storm events exhibit the same stochastic characteristics as the storm events themselves. The major advantage of an ANN in rainfall‐runoff modeling is that there is no requirement for any prior assumptions regarding the processes involved. The Grey model and three ANN models were applied to a 2,509 km² watershed in the Republic of Korea to compare the results for real time flood forecasting with from one to six hours of lead time. The fifth‐order Grey model and the ANN models with the optimal network architectures, represented by ANN1004 (34 input nodes, 21 hidden nodes, and 1 output node), ANN1010 (40 input nodes, 25 hidden nodes, and 1 output node), and ANN1004T (14 input nodes, 21 hidden nodes, and 1 output node), were adopted to evaluate the effects of time lags and differences between area mean and point rainfall. The Grey model and the ANN models, which provided reliable forecasts with one to six hours of lead time, were calibrated and their datasets validated. The results showed that the Grey model and the ANN1010 model achieved the highest level of performance in forecasting runoff for one to six lead hours. The ANN model architectures (ANN1004 and ANN1010) that used point rainfall data performed better than the model that used mean rainfall data (ANN1004T) in the real time forecasting. The selected models thus appear to be a useful tool for flood forecasting in Korea.     

Removal of organic matter and nitrogen from river water in a model floodplain

A significant improvement in river water quality cannot be expected unless nonpoint-source contaminants are treated in addition to the further treatment of point-source contaminants. If river water is sprayed over a floodplain, the consequent water filtration through the sediment profile can simultaneously remove organic matter and nitrogen in the water through aerobic and denitrifying reactions. This hypothesis was tested using lysimeters constructed from polyvinyl chloride (PVC) pipe (150 cm long, 15 cm in diameter) packed with loamy sand floodplain sediment. Water was applied to the top of the lysimeters at three different flow rates (48, 54, and 68 mm d(-1)). Concentrations of NO3 and dissolved oxygen (DO), chemical oxygen demand (COD), and redox potential (Eh) in the water were measured as functions of depth after the system reached steady states for both water flow and reactions. At the rate of 68.0 mm d(-1), a reducing condition for denitrification developed below the 5-cm depth due to the depletion of O2 by organic matter degradation in the surface oxidizing layer; Eh and DO were below 205 mV and 0.4 mg L(-1), respectively. At a depth of 70 cm, COD and NO3-N concentration decreased to 5.2 and 3.8 mg L(-1) from the respective influent concentrations of 17.1 and 6.2 mg L(-1). Most biodegradable organic matter was removed during flow and further removal of NO3 was limited by the lack of an electron donor (i.e., organic matter). These results indicate that the floodplain filtration technique has great promise for treatment of contaminated river water.     

Polychlorinated dibenzo-p-dioxins and dibenzofurans from food salt samples processed by heat treatment in Korea

Eight samples of processed food salt collected from five plants in Korea were analyzed for 2,3,7,8-substituted polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) using liquid-liquid extraction, clean-up procedures, and high resolution gas chromatography-high resolution mass spectrometry. The study included the analyses of two kinds of salt product sample: bamboo-salt and parched salt. The levels of toxic PCDD/Fs found in the salt product samples were extremely low: the results revealed TEQ levels ranging between the sub pg TEQ/g and sub fg TEQ/g. The differences in the TEQ values of toxic PCDD/F were observed between the salt product samples, which were treated with different frequency of baking using four different fuels (firewood, pine wood, pine resin, and indirect heating by gas) at temperatures from 300 to 2000 degrees C. In bamboo-salt samples, the concentrations and TEQ values of toxic PCDD/Fs ranged between 0.57-66 pg/g and 5.7x10(-5)-0.64 pg TEQ/g, respectively. PCDD/Fs levels in bamboo-salts baked by firewood were found to be higher than those baked by pinewood or pine resin. In parched salt samples, the concentrations and TEQ values of toxic PCDD/Fs ranged between 0.97-3.7 pg/g and 0.0097-0.017 pg TEQ/g, respectively. The data was discussed regarding the concentration and the distribution pattern of congeners.     

Development of the Spatial Rainfall Generator (SRGEN) for the Agricultural Policy/Environmental Extender Model

Accurate spatial representation of climatic patterns is often a challenge in modeling biophysical processes at the watershed scale, especially where the representation of a spatial gradient in rainfall is not sufficiently captured by the number of weather stations. The spatial rainfall generator (SRGEN) is developed as an extension of the “weather generator” (WXGEN), a component of the Agricultural Policy/Environmental eXtender (APEX) model. SRGEN generates spatially distributed daily rainfall using monthly weather statistics available at multiple locations in a watershed. The spatial rainfall generator as incorporated in APEX is tested on the Cowhouse watershed (1,178 km²) in central Texas. The watershed presented a significant spatial rainfall gradient of 2.9 mm/km in the lateral (north‐south) directions based on four rainfall gages. A comparative analysis between SRGEN and WXGEN indicates that SRGEN performs well (PBIAS = 2.40%). Good results were obtained from APEX for streamflow (NSE = 0.99, PBIAS = 8.34%) and NO₃‐N and soluble P loads (PBIAS ≈ 6.00% for each, respectively). However, APEX underpredicted sediment yield and organic N and P loads (PBIAS: 24.75‐27.90%) with SRGEN, although its uncertainty in output was lower than WXGEN results (PBIAS: ?13.02 to ?46.13%). The overall improvement achieved in rainfall generation by SRGEN is demonstrated to be effective in the improving model performance on flow and water quality output.