Central Composite Design Optimization of Biological Dye Removal in the Presence of Macroalgae Chara sp.

Response surface methodology (RSM) was employed to investigate the effects of different operational parameters on the biological decolorization of a dye solution containing malachite green (MG) in the presence of macroalgae Chara sp. The investigated variables were the initial pH, initial dye concentration, algae amount, and reaction time. Central composite design (CCD) was used for the optimization of biological decolorization process. Predicted values were found to be in good agreement with experimental values (R² = 0.982 and Adj‐R² = 0.966), which indicated suitability of the employed model and the success of RSM. The results of optimization predicted by the model showed that maximum decolorization efficiency was achieved at the optimum condition of the initial pH 6.8, initial dye concentration 9.7 mg/L, algae amount 3.9 g, and reaction time 75 min. UV–VIS spectra and FT‐IR analysis showed degradation of MG.     

δ53Cr values of catchment runoff exhibit seasonality regardless of bedrock Cr concentrations: Role of periodically changing chromium export fluxes

One pre-requisite for the construction of a global chromium isotope mass balance is detailed understanding of Cr isotope systematics in the critical zone where redox-processes can modify the isotope signature of geogenic Cr input into the hydrosphere. A Cr isotope inventory of bedrock, soil, and runoff was performed in a Central European headwater catchment underlain by amphibolite, situated in the vicinity of two previously studied catchments underlain by different bedrock types (serpentinite and leucogranite). Fresh bedrock in the amphibolite catchment NAZ contained ~300 mg/kg Cr, serpentinite at PLB contained ~800 mg/kg Cr, and leucogranite at LYS contained ~2 mg/kg Cr. Monthly hydrochemical monitoring at all three sites revealed higher Cr(VI) export fluxes in winter than in summer. NAZ was characterized by a distinct seasonality in the δ⁵³Cr values, with minima during winter/spring snowmelts (−0.35‰) and maxima during dry summers (0.40‰). Similar seasonality in δ⁵³Cr values had been reported from PLB and LYS. Bedrock at all three sites had similar Cr isotope composition close to −0.10‰, a value indistinguishable from the δ⁵³Cr value of bulk silicate Earth (BSE). Positive mean δ⁵³Cr value of NAZ runoff indicated Cr-isotope fractionations during weathering of geogenic Cr(III), combined with adsorption of the resulting Cr(VI) on soil particles during pedogenesis. However, the mass-weighted mean δ⁵³Cr of NAZ runoff was lower (−0.08‰), indistinguishable from the Cr isotope signature of bedrock. The same pattern of lower mass-weighted mean δ⁵³Cr values of runoff, compared to arithmetic mean δ⁵³Cr values of runoff, were observed also at PLB and LYS. We suggest that elevated Cr runoff fluxes in winter remove some of the residual isotopically light Cr that accumulated in the soil during summer. Seasonality in runoff δ⁵³Cr values appears to be a relatively widespread phenomenon, de-coupled from Cr availability for chemical weathering.     

Bioreduction of Hexavalent Chromium by Live and Active Phanerochaete chrysosporium: Kinetics and Modeling

In this work the potential of live and active Phanerochaete chryosporium, a white rot fungi, to remove lower Cr(VI) concentration from aqueous solutions was reported for the first time. A medium pH had significant effect on the growth of the fungus and bioremoval of Cr(VI). Substrate inhibition on the growth of Phanerochaete chrysosporium was evident beyond 20 g L^?1 of dextrose concentration. A maximum biomass concentration of 15.64 g L^?1 was obtained for an initial dextrose concentration of 20 g L^?1 in metal free medium at pH 6.0. An increase in Cr(VI) concentration beyond 10 mg L^?1 inhibited the growth of the fungi, thereby, reducing the chromium bioremoval efficiency. A maximum reduction efficiency of 98.92% was reported for an initial metal concentration of 10 mg L^?1. A mathematical expression for the bioreduction of Cr(VI) considering the organic compounds in the cells was proposed.     

Verification of land surface evapotranspiration estimation from remote sensing spatial contextual information

Estimation of evapotranspiration (ET) is of great significance in modeling the water and energy interactions between land and atmosphere. Negative correlation of surface temperature (T_s) versus vegetation index (VI) from remote sensing data provides diagnosis on the spatial pattern of surface soil moisture and ET. This study further examined the applicability of T_s–VI triangle method with a newly developed edges determination technique in estimating regional evaporative fraction (EF) and ET at MODIS pixel scale through comparison with large aperture scintillometer (LAS) and high‐level eddy covariance measurements collected at Changwu agro‐ecological experiment station from late June to late October, 2009. An algorithm with merely land and atmosphere products from MODIS onboard Terra satellite was used to estimate the surface net radiation (R_n) and soil heat flux. In most cases, the estimated instantaneous R_n was in good agreement with surface measurement with slight overestimation by 12 W/m². Validation results from LAS measurement showed that the root mean square error is 0.097 for instantaneous EF, 48 W/m² for instantaneous sensible heat flux, and 30 W/m² for daily latent heat flux. This paper successfully presents a miniature of the overall capability of T_s–VI triangle in estimating regional EF and ET from limited number of data. For a thorough interpretation, further comprehensive investigation needs to be done with more integration of remote sensing data and in‐situ surface measurements. Copyright © 2011 John Wiley & Sons, Ltd.     

Removal of Cr(VI) by Zero‐valent,Iron‐encapsulated Alginate Beads

Zero‐valent, iron‐encapsulated alginate beads were synthesized and were applied for the removal of Cr(VI) from aqueous solutions. The effects of several important parameters including solution pH, contact time, initial concentration and reaction temperature on Cr(VI) removal levels were investigated in batch studies. An initial solution pH of 1.0 was seen to be most favorable for Cr(VI) removal. The removal process was quick and almost 80% of the removal was attained within 60 min. The kinetic data followed the second‐order equation well. The Cr(VI) removal was almost reaction temperature‐independent and decreased with an increase in Cr(VI) initial concentration. The removal of Cr(VI) by iron‐encapsulated alginate beads was found to be significantly higher than that of non‐encapsulated alginate beads.     

Removal of Chromium from Synthetic Effluent using Nymphaea rubra

In the present work, biosorption of Cr(VI) by Nymphaea rubra was investigated in batch studies. Batch experiments were conducted to study the effect of initial sorbent dosage, solution pH and initial Cr(VI) concentration. The results showed that the equilibrium uptake capacity was increased with decrease in biomass dosage. The Cr(VI) removal was influenced by the initial chromium compound concentration. Langmuir and Freundlich adsorption isotherm models were used to represent the equilibrium data. The Freundlich isotherm model was fitted very well with the equilibrium data when compared to Langmuir isotherm model. The sorption results were analyzed for pseudo‐first order and pseudo‐second order kinetic model. It was observed that the kinetic data fitted very well with the pseudo‐second order rate equation when compared to the pseudo‐first order rate equation. Fourier transform infrared spectrum showed the presence of different functional groups in the biomass. The surface morphology of the sorbent was exemplified by SEM analysis. Aquatic weeds seem to be a promising biosorbent for the removal of chromium ions from water environment. This paper reports the research findings of a laboratory‐based study on the removal of Cr(VI) from the synthetic solution using the dried stem of N. rubra as a biosorbent.     

Bioremediation of Chlorinated Pesticides in Field‐Contaminated Soils and Suitability of Tenax Solid‐Phase Extraction as a Predictor of Its Effectiveness

Bioremediation is intensively studied today as a treatment method for soil contaminated with chlorinated pesticides, chemicals counted among persistent organic pollutants. In the presented work, results of desorption kinetics study using consecutive Tenax TA solid phase extraction (SPE) were tested as predictors of 3‐wk anaerobic soil bioremediation effectiveness for chlorinated pesticides γ‐HCH, DDT, and methoxychlor. Field‐contaminated samples were used in these experiments, and conditions of bioremediation tests were based on previous research. Amounts of pesticides removed during bioremediation (43–98% of initial concentrations) were in most cases much larger (average ratio 1.37) than rapidly desorbing fractions estimated in SPE using two‐compartment model of desorption kinetics. The scatter of results was also considerable (standard deviation 0.45). However, there was a statistically significant correlation between amounts removed and rapidly desorbing fractions (R² = 0.64), indicating a relationship between degradability and desorbability. Nonetheless, determination of rapidly desorbing fractions was considered rather a poor indicator of soil bioremediation efficiency for chlorinated pesticides. The total amounts of pesticides desorbed by Tenax in 72 h performed better in this respect (R² = 0.73, fraction removed/desorbed = 1.10 ± 0.20, average ± standard deviation). Disappearance of DDT during bioremediation was accompanied by DDD formation but this was considerably lower than results expected from stoichiometry.     

Seasonal Short‐Term Prediction of Dissolved Oxygen in Rivers via Nature‐Inspired Algorithms

This study challenges the use of three nature‐inspired algorithms as learning frameworks of the adaptive‐neuro‐fuzzy inference system (ANFIS) machine learning model for short‐term modeling of dissolved oxygen (DO) concentrations. Particle swarm optimization (PSO), butterfly optimization algorithm (BOA), and biogeography‐based optimization (BBO) are employed for developing predictive ANFIS models using seasonal 15 min data collected from the Rock Creek River in Washington, DC. Four independent variables are used as model inputs including water temperature (T), river discharge (Q), specific conductance (SC), and pH. The Mallow's Cp and R² parameters are used for choosing the best input parameters for the models. The models are assessed by several statistics such as the coefficient of determination (R²), root‐mean‐square error (RMSE), Nash–Sutcliffe efficiency, mean absolute error, and the percent bias. The results indicate that the performance of all‐nature‐inspired algorithms is close to each other. However, based on the calculated RMSE, they enhance the accuracy of standard ANFIS in the spring, summer, fall, and winter around 13.79%, 15.94%, 6.25%, and 12.74%, respectively. Overall, the ANFIS‐PSO and ANFIS‐BOA provide slightly better results than the other ANFIS models.     

Optimization and Modeling of the Photocatalytic Degradation of the Insect Repellent DEET in Aqueous TiO2 Suspensions

Response surface methodology (RSM) and artificial neural networks (ANNs) based on a multivariate central composite design (CCD) were applied to model and optimize the photocatalytic degradation of N,N‐diethyl‐m‐toluamide (DEET). The individual and interaction effects of three main operating factors (mass of TiO₂, initial DEET concentration, and irradiation intensity) on process efficiency were estimated, proving their important effect on % DEET removal. Among the independent variables, TiO₂ concentration displayed the highest effect on DEET degradation followed by initial DEET concentration and UV intensity. The optimization and prediction capabilities of ANNs and RSM were compared on the basis of root mean squared error, mean absolute error, absolute average deviation, and correlation coefficient values. Results proved the usefulness and capability of the experimental design strategy for successful investigation and modeling of the photocatalytic process. Moreover, the selected ANN gave better estimation capabilities throughout the range of variables than RSM. Based on the models and the related experimental conditions, the optimal values of each parameter were determined. Under optimum conditions, DEET and total organic carbon (TOC) followed pseudo‐first order kinetics. Nearly complete degradation of DEET took place within 15 min whereas high TOC removal percentages (>85%) was achieved after 90 min irradiation time.     

Electrochemical Treatment of Dye Solution by Oxalate Catalyzed Photoelectro‐Fenton Process Using a Carbon Nanotube‐PTFE Cathode: Optimization by Central Composite Design

Decolorization of C.I. Basic Blue 3 (BB3) by oxalate catalyzed photoelectro‐Fenton process based on carbon nanotube‐polytetrafluoroethylene (CNT‐PTFE) electrode as cathode under visible light was studied. A comparison of electro‐Fenton, photoelectro‐Fenton, and photoelectro‐Fenton/oxalate processes for decolorization of the solution containing BB3 has been performed. The results showed that color removal follows the decreasing order: photoelectro‐Fenton/oxalate > photoelectro‐Fenton > electro‐Fenton. Response surface methodology (RSM) was employed to assess individual and interactive effects of the four main independent parameters on the decolorization efficiency. A central composite design (CCD) was employed for optimization of photoelectro‐Fenton/oxalate treatment of BB3. The analysis of variance (ANOVA) showed a high coefficient of determination value (R² = 0.958) and satisfactory prediction second‐order regression. This study clearly showed that RSM was one of the suitable methods to optimize the operating conditions.     

Spatially distributed long‐term hydrologic simulation using a continuous SCS CN method‐based hybrid hydrologic model

A continuous Soil Conservation Service (SCS) curve number (CN) method that considers time‐varied SCS CN values was developed based on the original SCS CN method with a revised soil moisture accounting approach to estimate run‐off depth for long‐term discontinuous storm events. The method was applied to spatially distributed long‐term hydrologic simulation of rainfall‐run‐off flow with an underlying assumption for its spatial variability using a geographic information systems‐based spatially distributed Clark's unit hydrograph method (Distributed‐Clark; hybrid hydrologic model), which is a simple few parameter run‐off routing method for input of spatiotemporally varied run‐off depth, incorporating conditional unit hydrograph adoption for different run‐off precipitation depth‐based direct run‐off flow convolution. Case studies of spatially distributed long‐term (total of 6 years) hydrologic simulation for four river basins using daily NEXRAD quantitative precipitation estimations demonstrate overall performances of Nash–Sutcliffe efficiency (E_NS) 0.62, coefficient of determination (R²) 0.64, and percent bias 0.33% in direct run‐off and E_NS 0.71, R² 0.72, and percent bias 0.15% in total streamflow for model result comparison against observed streamflow. These results show better fit (improvement in E_NS of 42.0% and R² of 33.3% for total streamflow) than the same model using spatially averaged gauged rainfall. Incorporation of logic for conditional initial abstraction in a continuous SCS CN method, which can accommodate initial run‐off loss amounts based on previous rainfall, slightly enhances model simulation performance; both E_NS and R² increased by 1.4% for total streamflow in a 4‐year calibration period. A continuous SCS CN method‐based hybrid hydrologic model presented in this study is, therefore, potentially significant to improved implementation of long‐term hydrologic applications for spatially distributed rainfall‐run‐off generation and routing, as a relatively simple hydrologic modelling approach for the use of more reliable gridded types of quantitative precipitation estimations.     

Nested‐Scale Nutrient Flux in a Mixed‐Land‐Use Urbanizing Watershed

To improve quantitative understanding of mixed‐land‐use impacts on nutrient yields, a nested‐scale experimental watershed study design (n = 5) was applied in a 303(d), clean water act impaired urbanizing watershed of the lower Missouri River Basin, USA. From 2010 to 2013, water samples (n = 858 sample days per site) were analysed for total inorganic nitrogen (TIN‐N), nitrite (NO₂–N) nitrate (NO₃–N), ammonia (NH₃–N), and total phosphorus (TP‐P). Annual, seasonal, and monthly flow‐weighted concentrations (FWCs) and nutrient yields were estimated. Mean nutrient concentrations were highest where agricultural land use comprised 58% of the drainage area (NH₃ = 0.111 mg/l; NO₂ = 0.045 mg/l; NO₃ = 0.684 mg/l, TIN = 0.840 mg/l; TP = 0.127 mg/l). Average TP‐P increased by 15% with 20% increased urban land use area. Highly variable annual precipitation was observed during the study with highest nutrient yields during 2010 (record setting wet year) and lowest nutrient yields during 2012 (extreme drought year). Annual TIN‐N and TP‐P yields exceeded 10.3 and 2.04 kg ha^?1 yr^?1 from the agricultural dominated headwaters. Mean annual NH₃–N, NO₂–N, NO₃–N, TIN‐N, and TP‐P yields were 0.742, 0.400, 4.24, 5.38, and 0.979 kg ha^?1 yr^?1, respectively near the watershed outlet. Precipitation accounted for the majority of the explained variance in nutrient yields (R² values from 0.68 to 0.85). Nutrient yields were also dependent on annual precipitation of the preceding year (R² values from 0.87 to 0.91) thus enforcing the great complexity of variable mixed‐land‐use mediated source‐sink nutrient yield relationships. Study results better inform land managers and best management practices designed to mitigate nutrient pollution issues in mixed‐land‐use freshwater ecosystems. Copyright © 2015 John Wiley & Sons, Ltd.     

The Potential of Eleocharis acicularis for Phytoremediation: Case Study at an Abandoned Mine Site

Phytoremediation, a plant‐based and cost‐effective technology for the cleanup of contaminated soil and water, is receiving increasing attention. In this study, the aquatic macrophyte Eleocharis acicularis was examined for its ability to take up multiple heavy metals and its potential application for phytoremediation at an abandoned mining area in Hokkaido, Japan. Elemental concentrations were measured in samples of E. acicularis, water, and soil collected from areas of mine tailing and drainage. The results reveal that Pb, Fe, Cr, Cu, Ni, and Mn accumulation in the plants increased over the course of the experiment, exceeding their initial concentrations by factors of 930, 430, 60, 25, 10, and 6, respectively. The highest concentrations of Fe, Pb, Zn, Mn, Cr, Cu, and Ni within the plants were 59500, 1120, 964, 388, 265, 235, and 47.4 mg/kg dry wt., respectively, for plants growing in mine drainage after 11 months of the experiment. These results indicate that E. acicularis is a hyperaccumulator of Pb. We also found high Si concentrations in E. acicularis (2.08%). It is likely that heavy metals exist in opal‐A within cells of the plant. The bioconcentration factors (BCF: ratio of metal concentration in the plant shoots to that in the soil) obtained for Cr, Cu, Zn, Ni, Mn, and Pb were 3.27, 1.65, 1.29, 1.26, 1.11, and 0.82, respectively. The existence of heavy metals as sulphides is thought to have restricted the metal‐uptake efficiency of E. acicularis at the mine site. The results of this study indicate that E. acicularis shows great potential in the phytoremediation of mine tailing and drainage rich in heavy metals.     

Response Surface Approach for the Bisorption of Ag(I) by Macrofungus Pleurotus platypus

Response surface methodology (RSM) employing the three‐level Box–Behnken factorial design was used to optimize the biosorption of Ag(I) by the macrofungus Pleurotus platypus. The initial Ag(I) concentration (100–300 mg/L), pH (3.0–9.0), and biomass dosage (1.0–5.0 g/L) were chosen as the process variables for the optimization. A coefficient of determination (R²) value (0.99), model F value (234.18), and its low p‐value (F < 0.0001) along with the lower value of coefficient of variation (2.44%) indicated the fitness of response surface quadratic model during the present study. At the optimum pH (6.0), initial metal concentration (220 mg/L), and biomass dosage (3.0 g/L), the model predicted 46.7 mg/g Ag(I) uptake and an experimental 46.77 mg/g Ag(I) uptake by P. platypus was obtained. This is the first report on Ag(I) sorption by P. platypus using statistical experimental design employing RSM which may be helpful towards the treatment of industrial effluent containing silver.     

Speciation and spatial distribution of Cr in chromite ore processing residue site,Yunnan,China

Remediation of COPR sites requires the key information including chromium oxidation, speciation and spatial distribution. Samples were gathered from a COPR site in Luliang County in Qujing, Yunnan Province of China. The total Cr, Cr(VI) and chromium species were investigated. Results indicated the concentration of total Cr was between 110.5 and 21,774 mg/kg, and the concentration of Cr(VI) was between 0.1 and 1075 mg/kg. The map of total-Cr and ratio of Cr(VI)/total-Cr(%) showed that the maximum of total-Cr and Cr(VI) appeared in the layers near the surface. In the horizontal direction, the pollution was more serious in the middle and southeast part than that in the west. Additionally, acid extractable chromium increased in the layers at depth from-0.3 to-2.0 m, and it decreased in the deeper layers. There was a trend that the movable Cr(VI) migrated to the deeper layers, and then it turned into Cr(III). Water played an important role for the Cr distribution. Cr(VI) in COPR released to the soil solution after rainfall, and then gravity led the solution down to the deeper layers. After repeated rainfall and leaching,Cr(VI) moved to the deeper soil layers. Due to capillarity and evaporation, Cr(VI) migrated and was enriched at thesurface layer. Therefore, measures on controlling water movement should be taken in the remediation of the COPR site.     

Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data

Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non‐climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape‐scale soil moisture variation by utilizing high‐resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high‐latitude landscape of mountain tundra in north‐western Finland. We measured the plots three times during growing season 2016 with a hand‐held time‐domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R² = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R² = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R² = 0.47 and RMSE 9.34 VWC%, and for the latter R² = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high‐resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1 m² digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine‐scale soil moisture variation. In the temporal variation models, the strongest predictor was the field‐quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. Copyright © 2017 John Wiley & Sons, Ltd.     

Impact of draining hilly lands on runoff and on‐site erosion: a case study from humid Ethiopia

The use of drainage ditches on farmland has an impact on erosion processes both on‐site and off‐site, though their environmental impacts are not unequivocal. Here we study the runoff response and related rill erosion after installing drainage ditches and assess the effects of stone bunds in north Ethiopia. Three different land management systems were studied in 10 cropland catchments around Wanzaye during the rainy season of 2013: (1) the exclusive use of drainage ditches (locally called feses), (2) the exclusive use of stone bunds, and (3) a mixture of both systems. Stone bunds are an effective soil and water conservation technique, making the land more resistant against on‐site erosion, and allowing feses to be installed at a larger angle with the contour. The mean rill volumes for the 10 studied cropland catchments during the rainy season of 2013 was 3.73 ± 4.20 m³ ha^?1 corresponding to a soil loss of 5.72 ± 6.30 ton ha^?1. The establishment of feses causes larger rill volumes (R = 0.59, N = 10), although feses are perceived as the best way to avoid soil erosion when no stone bunds are present. The use of feses increases event‐based runoff coefficients (RCs) on cropland from c. 5% to values up to 39%. Also, a combination of low stone bund density and high feses density results in a higher RC, whereas catchments with a high stone bund density and low feses density have a lower RC. Peak runoff discharges decrease when stone bund density increases, whereas feses density is positively related to the peak runoff discharge. A multiple linear relation in which both feses and stone bund densities are used as explanatory variable, performs best in explaining runoff hydrograph peakedness (R² = 83%). Copyright © 2015 John Wiley & Sons, Ltd.     

The effects of initial soil moisture conditions on swale flow hydrographs

The effects of soil water content (SWC) on the formation of run‐off in grass swales draining into a storm sewer system were studied in two 30‐m test swales with trapezoidal cross sections. Swale 1 was built in a loamy fine‐sand soil, on a slope of 1.5%, and Swale 2 was built in a sandy loam soil, on a slope of 0.7%. In experimental runs, the swales were irrigated with 2 flow rates reproducing run‐off from block rainfalls with intensities approximately corresponding to 2‐month and 3‐year events. Run‐off experiments were conducted for initial SWC (SWC_ini) ranging from 0.18 to 0.43 m³/m³. For low SWC_ini, the run‐off volume was greatly reduced by up to 82%, but at high SWC_ini, the volume reduction was as low as 15%. The relative swale flow volume reductions decreased with increasing SWC_ini and, for the conditions studied, indicated a transition of the dominating swale functions from run‐off dissipation to conveyance. Run‐off flow peaks were reduced proportionally to the flow volume reductions, in the range from 4% to 55%. The swale outflow hydrograph lag times varied from 5 to 15 min, with the high values corresponding to low SWC_ini. Analysis of swale inflow/outflow hydrographs for high SWC_ini allowed estimations of the saturated hydraulic conductivities as 3.27 and 4.84 cm/hr in Swales 1 and 2, respectively. Such estimates differed from averages (N = 9) of double‐ring infiltrometer measurements (9.41 and 1.78 cm/hr). Irregularities in swale bottom slopes created bottom surface depression storage of 0.35 and 0.61 m³ for Swales 1 and 2, respectively, and functioned similarly as check berms contributing to run‐off attenuation. The experimental findings offer implications for drainage swale planning and design: (a) SWC_ini strongly affect swale functioning in run‐off dissipation and conveyance during the early phase of run‐off, which is particularly important for design storms and their antecedent moisture conditions, and (b) concerning the longevity of swale operation, Swale 1 remains fully functional even after almost 60 years of operation, as judged from its attractive appearance, good infiltration rates (3.27 cm/hr), and high flow capacity.     

Estimating forest aboveground biomass using HJ-1 Satellite CCD and ICESat GLAS waveform data

The ecosystem in northeastern China and the Russian Far East is a hotspot of scientific research into the global carbon balance. Forest aboveground biomass (AGB) is an important component in the land surface carbon cycle. In this study, using forest inventory data and forest distribution data, the AGB was estimated for forest in Daxinganlin in northeastern China by combining charge-coupled device (CCD) data from the Small Satellite for Disaster and Environment Monitoring and Forecast (HJ-1) and Geoscience Laser Altimeter System (GLAS) waveform data from the Ice, Cloud and land Elevation Satellite (ICESat). The forest AGB prediction models were separately developed for different forest types in the research area at GLAS footprint level from GLAS waveform parameters and field survey plot biomass in the Changqing (CQ) Forest Center, which was calculated from forest inventory data. The resulted statistical regression models have a R ²=0.68 for conifer and R ²=0.71 for broadleaf forests. These models were used to estimate biomass for all GLAS footprints of forest located in the study area. All GLAS footprint biomass coupled with various spectral reflectivity parameters and vegetation indices derived from HJ-1 satellite CCD data were used in multiple regression analyses to establish biomass prediction models (R ²=0.55 and R ²=0.52 for needle and broadleaf respectively). Then the models were used to produce a forest AGB map for the whole study area using the HJ-1 data. Biomass data obtained from forest inventory data of the Zhuanglin (ZL) Forest Center were used as independent field measurements to validate the AGB estimated from HJ-1 CCD data (R ²=0.71). About 80% of biomass samples had an error less than 20 t ha⁻¹, and the mean error of all validation samples is 5.74 t ha⁻¹. The pixel-level biomass map was then stratified into different biomass levels to illustrate the AGB spatial distribution pattern in this area. It was found that HJ-1 wide-swath data and GLAS waveform data can be combined to estimate forest biomass with good precision, and the biomass data can be used as input data for future carbon budget analysis.

     

Infiltration and runoff generation processes in fire‐affected soils

Post‐wildfire runoff was investigated by combining field measurements and modelling of infiltration into fire‐affected soils to predict time‐to‐start of runoff and peak runoff rate at the plot scale (1 m²). Time series of soil‐water content, rainfall and runoff were measured on a hillslope burned by the 2010 Fourmile Canyon Fire west of Boulder, Colorado during cyclonic and convective rainstorms in the spring and summer of 2011. Some of the field measurements and measured soil physical properties were used to calibrate a one‐dimensional post‐wildfire numerical model, which was then used as a ‘virtual instrument’ to provide estimates of the saturated hydraulic conductivity and high‐resolution (1 mm) estimates of the soil‐water profile and water fluxes within the unsaturated zone. Field and model estimates of the wetting‐front depth indicated that post‐wildfire infiltration was on average confined to shallow depths less than 30 mm. Model estimates of the effective saturated hydraulic conductivity, K_s, near the soil surface ranged from 0.1 to 5.2 mm h^?1. Because of the relatively small values of K_s, the time‐to‐start of runoff (measured from the start of rainfall), t_p, was found to depend only on the initial soil‐water saturation deficit (predicted by the model) and a measured characteristic of the rainfall profile (referred to as the average rainfall acceleration, equal to the initial rate of change in rainfall intensity). An analytical model was developed from the combined results and explained 92–97% of the variance of t_p, and the numerical infiltration model explained 74–91% of the variance of the peak runoff rates. These results are from one burned site, but they strongly suggest that t_p in fire‐affected soils (which often have low values of K_s) is probably controlled more by the storm profile and the initial soil‐water saturation deficit than by soil hydraulic properties. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.