Predicting Debris Yield From Burned Watersheds: Comparison of Statistical and Artificial Neural Network Models1

Abstract: Alluvial fans in southern California are continuously being developed for residential, industrial, commercial, and agricultural purposes. Development and alteration of alluvial fans often require consideration of mud and debris flows from burned mountain watersheds. Accurate prediction of sediment (hyper‐concentrated sediment or debris) yield is essential for the design, operation, and maintenance of debris basins to safeguard properly the general population. This paper presents results based on a statistical model and Artificial Neural Network (ANN) models. The models predict sediment yield caused by storms following wildfire events in burned mountainous watersheds. Both sediment yield prediction models have been developed for use in relatively small watersheds (50‐800 ha) in the greater Los Angeles area. The statistical model was developed using multiple regression analysis on sediment yield data collected from 1938 to 1983. Following the multiple regression analysis, a method for multi‐sequence sediment yield prediction under burned watershed conditions was developed. The statistical model was then calibrated based on 17 years of sediment yield, fire, and precipitation data collected between 1984 and 2000. The present study also evaluated ANN models created to predict the sediment yields. The training of the ANN models utilized single storm event data generated for the 17‐year period between 1984 and 2000 as the training input data. Training patterns and neural network architectures were varied to further study the ANN performance. Results from these models were compared with the available field data obtained from several debris basins within Los Angeles County. Both predictive models were then applied for hind‐casting the sediment prediction of several post 2000 events. Both the statistical and ANN models yield remarkably consistent results when compared with the measured field data. The results show that these models are very useful tools for predicting sediment yield sequences. The results can be used for scheduling cleanout operation of debris basins. It can be of great help in the planning of emergency response for burned areas to minimize the damage to properties and lives.     

Highly siliceous MCM-48 from rice husk ash for CO2 adsorption

Mesoporous MCM-48 silica was synthesized using a cationic-neutral surfactant mixture as the structure-directing template and rice husk ash (RHA) as the silica source. The MCM-48 samples were characterized by X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), N₂ physisorption and SEM. X-ray diffraction pattern of the resulting MCM-48 revealed typical pattern of cubic Ia3d mesophase. BET results showed the MCM-48 to have a surface area of 1024 m²/g and FT-IR revealed a silanol functional group at about 3460 cm⁻¹. Breakthrough experiments in the presence of MCM-48 were also carried out to test the material's CO₂ adsorption capacity. The breakthrough time for CO₂ was found to decrease as the temperature increased from 298 K to 348 K. The steep slopes observed shows the CO₂ adsorption occurred very quickly, with only a minimal mass transfer effect and very fast kinetics. In addition, amine grafted MCM-48, APTS-MCM-48 (RHA), was prepared with the 3-aminopropyltriethoxysilane (APTS) to investigate the effect of amine functional group in CO₂ separation. An order of magnitude higher CO₂ adsorption capacity was obtained in the presence of APTS-MCM-48 (RHA) compared to that with MCM-48 (RHA). These results suggest that MCM-48 synthesized from rice husk ash could be usefully applied for CO₂ removal.     

Residual Perchloroethylene in Dry-Cleaned Acetate: The Effect of Pressing and Extent of Inter-Dry-Cleaner Variability

ABSTRACT

Measurements of residual perchloroethylene (PCE), a dry-cleaning solvent associated with human health effects, were made in dry-cleaned acetate cloth to enable improved characterizations of both occupational and environmental exposure. A limited sample size (25 acetate cloths) was used to explore the extent of inter-dry-cleaner variability in residual PCE and to characterize the effect of the pressing operation on residual PCE. A new method, which uses carbon-disulfide as the direct extracting agent, proved effective in the analysis of residual PCE, with a recovery-efficiency ≈ 75%. Inter-dry-cleaner variability of residual PCE, although marginally statistically significant, was relatively low, showing only a fourfold range compared to a 5-order-of-magnitude range obtained from Kawauchi and Nishiyama¹. Pairwise comparison of residual PCE in nonpressed versus pressed acetate samples revealed a statistically significant reduction (p < 0.008), which amounted to a consistent (among dry-cleaners) pressing-related removal efficiency of 75 ± 4%. A preliminary assessment of the source term associated with the pressing operation (mass PCE liberated per kg cloth dry-cleaned, S_PCE ≈ 30 mg/kg) indicates a minor contribution to the average ambient air concentrations within dry-cleaning establishments.     

Probability-based classifications for spatially characterizing the water temperatures and discharge rates of hot springs in the Tatun Volcanic Region,Taiwan

Accurately classifying the spatial features of the water temperatures and discharge rates of hot springs is crucial for environmental resources use and management. This study spatially characterized classifications of the water temperatures and discharge rates of hot springs in the Tatun Volcanic Region of Northern Taiwan by using indicator kriging (IK). The water temperatures and discharge rates of the springs were first assigned to high, moderate, and low categories according to the two thresholds of the proposed spring classification criteria. IK was then used to model the occurrence probabilities of the water temperatures and discharge rates of the springs and probabilistically determine their categories. Finally, nine combinations were acquired from the probability-based classifications for the spatial features of the water temperatures and discharge rates of the springs. Moreover, various combinations of spring water features were examined according to seven subzones of spring use in the study region. The research results reveal that probability-based classifications using IK provide practicable insights related to propagating the uncertainty of classifications according to the spatial features of the water temperatures and discharge rates of the springs. The springs in the Beitou (BT), Xingyi Road (XYR), Zhongshanlou (ZSL), and Lengshuikeng (LSK) subzones are suitable for supplying tourism hotels with a sufficient quantity of spring water because they have high or moderate discharge rates. Furthermore, natural hot springs in riverbeds and valleys should be developed in the Dingbeitou (DBT), ZSL, Xiayoukeng (XYK), and Macao (MC) subzones because of low discharge rates and low or moderate water temperatures.     

Combustion characteristics of paper mill sludge in a lab-scale combustor with internally cycloned circulating fluidized bed

After performing a series of batch type experiments using a lab-scale combustor, consideration was given to the use of an internally cycloned circulating fluidized bed combustor (ICCFBC) for a paper mill sludge. Operation parameters including water content, feeding mass of the sludge, and secondary air injection ratio were varied to understand their effects on combustion performance, which was examined in terms of carbon conversion rate (CCR) and the emission rates of CO, C(x)H(y) and NO(x). The combustion of paper mill sludge in the ICCFBC was compared to the reaction mechanisms of a conventional solid fuel combustion, characterized by kinetics limited reaction zone, diffusion limited reaction zone, and transition zone. The results of the parametric study showed that a 35% water content and 60 g feeding mass generated the best condition for combustion. Meanwhile, areal mass burning rate, which is an important design and operation parameter at an industrial scale plant, was estimated by a conceptual equation. The areal mass burning rate corresponding to the best combustion condition was approximately 400 kg/hm(2) for 35% water content. The secondary air injection generating swirling flow enhanced the mixing between the gas phase components as well as the solid phase components, and improved the combustion efficiency by increasing the carbon conversion rate and reducing pollutant emissions.     

Model for Prioritizing Best Management Practice Implementation: Sediment Load Reduction

Understanding the best way to allocate limited resources is a constant challenge for water quality improvement efforts. The synoptic approach is a tool for geographic prioritization of these efforts. It uses a benefit-cost framework to calculate indices for functional criteria in subunits (watersheds, counties) of a region and then rank the subunits. The synoptic approach was specifically designed to incorporate best professional judgment in cases where information and resources are limited. To date, the synoptic approach has been applied primarily to local or regional wetland restoration prioritization projects. The goal of this work was to develop a synoptic model for prioritizing watersheds within which suites of agricultural best management practices (BMPs) can be implemented to reduce sediment load at the watershed outlets. The model ranks candidate watersheds within an ecoregion or river basin so that BMP implementation within the highest ranked watersheds will result in the most sediment load reduction per conservation dollar invested. The model can be applied anywhere and at many scales provided that the selected suite of BMPs is appropriate for the evaluation area’s biophysical and climatic conditions. The model was specifically developed as a tool for prioritizing BMP implementation efforts in ecoregions containing watersheds associated with the USDA-NRCS conservation effects assessment project (CEAP). This paper presents the testing of the model in the little river experimental watershed (LREW) which is located near Tifton, Georgia, USA and is the CEAP watershed representing the southeastern coastal plain. The application of the model to the LREW demonstrated that the model represents the physical drivers of erosion and sediment loading well. The application also showed that the model is quite responsive to social and economic drivers and is, therefore, best applied at a scale large enough to ensure differences in social and economic drivers across the candidate watersheds. The prioritization model will be used for planning purposes. Its results are visualized as maps which enable resource managers to identify watersheds within which BMP implementation would result in the most water quality improvement per conservation dollar invested.     

AQUIFER SALINIZATION IN THE YUN‐LIN COASTAL AREA,TAIWAN1

ABSTRACT: This study analyzes possible causes of shallow ground water salinization in the coastal area of Yun‐Lin. The local hydro‐geologic setting is determined from geological drilling data and sea floor topography. Three possible causes (sea water intrusion, salt water percolation through wells, and infiltration of salty water from fish ponds) are evaluated. Chloride concentration is used as an index to measure ground water salinization. Sea water intrusion is modeled by the advective/dispersive equation, and salt water infiltration from wells and fish ponds is calculated by estimating the amount of water percolated. The determined local hydrogeologic setting suggests that the shallow aquifer may be connected to the sea water, resulting in salt water intrusion as a large amount of shallow ground water is withdrawn. The percent contributions of sea water intrusion, percolation through wells, and infiltration of water from fish ponds, to the salinization of the shallow aquifer at Ko‐Hu in the Yun‐Lin coastal area are approximately 27 percent, less than 1 percent and 73 percent, respectively. The results suggest that the vertical infiltration of salt water from fish ponds is the major cause of shallow ground water salinization in the coastal area of Yun‐Lin.     

Kinetic and mechanism studies of the adsorption of lead onto waste cow bone powder (WCBP) surfaces

This study examines the adsorption isotherms, kinetics and mechanisms of Pb2(+) sorption onto waste cow bone powder (WCBP) surfaces. The concentrations of Pb2(+) in the study range from 10 to 90 mg/L. Although the sorption data follow the Langmuir and Freundlich isotherm, a detailed examination reveals that surface sorption or complexation and co-precipitation are the most important mechanisms, along with possibly ion exchange and solid diffusion also contributing to the overall sorption process. The co-precipitation of Pb2(+) with the calcium hydroxyapatite (Ca-HAP) is implied by significant changes in Ca2(+) and PO?3? concentrations during the metal sorption processes. The Pb2(+) sorption onto the WCBP surface by metal complexation with surface functional groups such as ≡ POH. The major metal surface species are likely to be ≡ POPb(+). The sorption isotherm results indicated that Pb2(+) sorption onto the Langmuir and Freundlich constant q(max) and K( F ) is 9.52 and 8.18 mg g?1, respectively. Sorption kinetics results indicated that Pb2(+) sorption onto WCBP was pseudo-second-order rate constants K? was 1.12 g mg?1 h?1. The main mechanism is adsorption or surface complexation (≡POPb(+): 61.6%), co-precipitation or ion exchange [Ca?(.)?? Pb?(.)?? (PO?)? (OH): 21.4%] and other precipitation [Pb 50 mg L?1 and natural pH: 17%). Sorption isotherms showed that WCBP has a much higher Pb2(+) removal rate in an aqueous solution; the greater capability of WCBP to remove aqueous Pb2(+) indicates its potential as another promising way to remediate Pb2(+)-contaminated media.     

Potential application of sludge produced from coal mine drainage treatment for removing Zn(II) in an aqueous phase

Various analyses of physico-chemical characteristics and batch tests were conducted with the sludge obtained from a full-scale electrolysis facility for treating coal mine drainage in order to find the applicability of sludge as a material for removing Zn(II) in an aqueous phase. The physico-chemical analysis results indicated that coal mine drainage sludge (CMDS) had a high specific surface area and also satisfied the standard of toxicity characteristic leaching procedure (TCLP) because the extracted concentrations of certain toxic elements such as Pb, Cu, As, Hg, Zn, and Ni were much less than their regulatory limits. The results of X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) showed that the CMDS mainly consists of goethite (70%) and calcite (30%) as a weight basis. However, the zeta potential analysis represented that the CMDS had a lower isoelectric point of pH (pH(IEP)) than that of goethite or calcite. This might have been caused by the complexation of negatively charged anions, especially sulfate, which usually exists with a high concentration in coal mine drainage. The results of Fourier transform infrared (FT-IR) spectrometry analysis revealed that Zn(II) was dominantly removed as a form of precipitation by calcite, such as smithsonite [ZnCO?] or hydrozincite [Zn?(CO?)?(OH)?]. Recycling sludge, originally a waste material, for the removal process of Zn(II), as well as other heavy metals, could be beneficial due to its high and speedy removal capability and low economic costs.