A Statistical Sediment Yield Prediction Model Incorporating the Effect of Fires and Subsequent Storm Events1

Abstract: Alluvial fans are continuously being developed for residential, industrial, commercial, and agricultural uses in southern California. Development and alteration of alluvial fans need to consider the possibility of mud and debris flows from upstream mountain watersheds affected by fires. Accurate prediction of sediment yield (or hyper‐concentrated sediment yield) is essential for the design, operation, and maintenance of debris basins to safeguard properly the general populace. This paper presents a model for the prediction of sediment yields that result from a combination of fire and subsequent storm events. The watersheds used in this analysis are located in the foothills of the San Gabriel Mountains in southern California. A multiple regression analysis is first utilized to establish a fundamental statistical relationship for sediment yield as a function of relief ratio, drainage area, maximum 1‐h rainfall intensity and fire factor using 45 years of data (1938‐1983). In addition, a method for multi‐sequence sediment yield prediction under fire conditions was developed and calibrated using 17 years of sediment yield, fire, and precipitation data for the period 1984‐2000. After calibration, this model was verified by applying it to provide a prediction of the sediment yields for the 2001‐2002 fire events in southern California. The findings indicate a strong correlation between the estimated and measured sediment yields. The proposed method for sequence sediment yield prediction following fire events can be a useful tool to schedule cleanout operations for debris basins and to develop an emergency response strategy for the southern California region where plentiful sediment supplies exist and frequent fires occur.     

A conceptual framework for Jatropha seed yield estimation using adaptive neuro-fuzzy inference system (ANFIS) modelling

Jatropha seed yield prediction is one of the most important influencing factors for developing a supply chain modelling of Jatropha seed. The oil from this Jatropha seed is used to blend with diesel to obtain biofuel (Hiromi, Yamamoto, Junichi Fujino, and Kenji Yamaji. 2001. “Evaluation of Bioenergy Potential with a Multi-regional Global-Land-Use-and-Energy Model.” Biomass and Bioenergy 21: 185–203). The Jatropha plant is easy to cultivate and produces high yield if properly maintained. The main focus of this study is to utilize uncultivable wastelands for cultivating Jatropha seeds. As suggested by Liu et al. (Liu, Xiaohong, David B. Grant, Alan C. McKinnon, and Yuanhua Feng. 2010. “An Empirical Examination of the Contribution of Capabilities to the Competitiveness of Logistics Service Providers: A Perspective from China.” International Journal of Physical Distribution & Logistics Management 40 (10): 847–866), the effectiveness of prediction affects the functional characteristics of a supply chain network design. The yield prediction of Jatropha seeds has two important roles which include (i) the identification of external parameters that affects the yield and (ii) the detection of internal attributes that changes the growth characteristics of the Jatropha plant. The development of the fuzzy inference system is characterized by a large number of input variables (Dobrila Petrovic. 2001. International Journal of Production Economics 71: 429–438). A Matlab programming software was used to integrate an adaptive neuro-fuzzy inference system. This approach gave the numerical as well as graphical output that was used to interpret the final result. The root mean square error values were identified for the given inputs which were then compared with the trained input variables to select the best input among the given alternative variables.     

Influence of crop residues on trifluralin mineralization in a silty clay loam soil

Trifluralin is typically applied onto crop residues (trash, stubble) at the soil surface, or onto the bare soil surface after the incorporation of crop residues into the soil. The objective of this study was to quantify the effect of the type and amount of crop residues in soil on trifluralin mineralization in a Wellwood silty clay loam soil. Leaves and stubble of Potato (Solanum tuberosum) (P); Canola (Brassica napus) (C), Wheat (Triticum aestivum) (W), Oats (Avena sativa), (O), and Alfalfa (Medicago sativa) (A) were added to soil microcosms at rates of 2%, 4%, 8% and 16% of the total soil weight (25 g). The type and amount of crop residues in soil had little influence on the trifluralin first-order mineralization rate constant, which ranged from 3.57E-03 day^?1 in soil with 16% A to 2.89E-02 day^?1 in soil with 8% W. The cumulative trifluralin mineralization at 113 days ranged from 1.15% in soil with 16% P to 3.21% in soil with 4% C, again demonstrating that the observed differences across the treatments are not of agronomic or environmental importance.     

Investigation on the Chemical Structure of Nonextractable Residues of the Fungicide Cyprodinil in Spring Wheat Using 13C-C1-Phenyl-Cyprodinil on 13C-Depleted Plants—An Alternative Approach to Investigate Nonextractable Residues

Abstract

¹³C-labelled cyprodinil was applied on ¹³C-depleted wheat plants with 27-fold field application rate. A control experiment applying same amounts of ¹⁴C-cyprodinil showed that main portions of the residues were detected in the cellulose (15% NER), hemicellulose (28.3% NER), and lignin fraction (23.3% NER). 16.7% were detected in water soluble polymers, 6% in both, pectin and protein fraction, and 4% in the starch containing fraction. Free cyprodinil was detectable by TLC in all fractions except lignin. A direct characterization of the residues in vivo by CP-MAS was not successful. Cell wall fractions were further analysed by liquid state NMR to determine the structure of the mobilized highly polymer/polar residues: Within lignin, where most of the residues were located at field application rate, neither intact cyprodinil nor its metabolites could not be detected. The ¹³C-label introduced was probably incorporated in the polymer as natural lignin monomers and thus are not considered as bound residues according to IUPAC definition.     

不同氮源对常中温条件下麦秆厌氧发酵的影响

通过自行设计的厌氧发酵装置,研究不同氮源对常温（20℃）和中温（35℃）条件下麦秆厌氧发酵的影响。结果表明,在常温和中温条件下进行麦秆沼气厌氧发酵时,适量添加外部氮源可加快产气速率,增加产气量,缩短产气停滞时间,其中添加牛粪效果最好,分别在182 d和84 d时发酵完全,总累积产气3 486.80 mL和4 210.70 mL,干物质累积产气量为217.93 mL/g和263.17 mL/g,且在实验期间未出现产气停滞。添加尿素处理次之,分别在累积产气215.70 mL和238.00 mL时进入61 d和20 d的产气停滞期,在196 d和143 d时发酵完全,在实验结束时,累积产气2 784.20 mL和3 454.00 mL,干物质累积产气量为174.01 mL/g和215.88 mL/g。可见,在以秸秆为原料的沼气发酵过程中,可通过添加适量的外部氮源和提高发酵温度来提高沼气产量,而且在条件允许的情况下,应尽量添加畜禽粪便等有机氮源。     

江西省气候变化的特征及其对水稻产量的贡献——基于“气候-经济”模型

采用气候倾向率和M-K突变检验,分析1951~2012年江西省气候和温度的变化趋势和突变特征;构建"气候-经济"新模型,研究气候因子对水稻产量的影响,最后借助BP神经网络模型预测未来10a气候因子对水稻产量的贡献。结果表明:过去60多年来气温平均每10a升高0.172℃,而降水的线性倾向不显著;气温突变开始的时间约为1997年,降水的突变趋势不明显;不同阶段气候因素的贡献率及作用方向存在差异,1978~1997年气候因子贡献率为5.97%,其中温度和降水贡献率分别为1.51%、4.46%。1998~2013年气候因子贡献率为8.98%,温度和降水贡献率分别为4.63%、4.35%。物质要素在不同阶段的贡献率均为70%以上,其中播种面积和化肥的影响程度较大;未来10a气温对江西水稻产量的贡献为1.48,降水量对水稻产量的贡献为2.22。     

长江中下游冬小麦春季湿渍害灾损风险评估

春季湿渍害对南方冬小麦生长发育和产量形成影响很大。选取能较好反映冬小麦湿渍害特征的降雨量、日照和作物需水量构建湿渍害气象判别指数,从春季湿渍害产量实际损失的角度,对受灾频率、因灾减产频率、产量损失风险强度进行分析,基于减产频率和产量灾损风险强度建立风险评估模型,并依据风险值大小进行分区。结果表明:沿江江南地区冬小麦春季湿渍害受灾频率最高,为风险高值区,约占全区台站27%;风险中值区范围较大,约占47%,分布在江淮东部、淮北大部、江汉平原以及鄂东南地区;低风险区约占全区16%,主要分布在湖北北部和淮北局部地区。     

Dimer formation during UV photolysis of diclofenac

Dimer formation was observed during ultraviolet (UV) photolysis of the anti-inflammatory drug diclofenac, and confirmed with mass spectrometry, NMR and fluorescence analysis. The dimers were combinations of the two parent molecules or of the parent and the product of photolysis, and had visible color. Radical formation during UV exposure and dissolved oxygen photosensitized reactions played a role in dimer formation. Singlet oxygen formed via photosensitization by photolysis products of diclofenac. It reacted with diclofenac to form an epoxide which is an intermediate in some dimer formation pathways. Quantum yield of photolysis for diclofenac was 0.21 ± 0.02 and 0.19 ± 0.02 for UV irradiation from medium pressure and low pressure mercury vapor lamps, respectively. Band pass filter experiments revealed that the quantum yield is constant at wavelengths >200 nm. The same dimers formed in laboratory grade water when either of the two UV sources was used. Dimers did not form in wastewater effluent matrix, and diclofenac epoxide molecules may have formed bonds with organic matter rather than each other Implications for the importance of dimer formation in NOM are discussed.     

添加秸秆对废橡胶/塑料共热解制油特性的影响

针对难降解类垃圾资源化处理的难题,利用固定床系统对废弃橡胶/塑料以不同比例掺混进行了共热解制油实验,研究掺混燃料中添加少量秸秆对共热解特性的影响。结果表明,橡胶和塑料共热解,较各自热解的得油率和油发热量增加,橡胶/塑料比例2∶3~3∶2时,制油收益率最佳;添加秸秆,能够促进热解反应提前进行,进一步提高得油率和油发热量同时提高了固体残渣的热值,则制取热解油的收益率明显提高。橡胶/塑料比例4∶1的混合燃料,添加秸秆共热解获得了最高得油率,油发热量为39.93 MJ/kg。     

Optimization of a methodology for the simultaneous determination of deltamethrin,permethrin and malathion in stored wheat samples using dispersive liquid–liquid microextraction with solidification of floating organic drop and HPLC-UV

The purpose of this study was to investigate common pesticides in stored wheat at Kermanshah province's silos in Iran. A simple, inexpensive, reliable and environmentally friendly method based on dispersive liquid–liquid microextraction with solidification of floating organic drop was developed. The analytical characteristics of the method were determined. Also, various parameters such as the materials of the silos, types of ownerships of the silos, geographic orientation of silo locations and climatic conditions of silo locations on pesticide residues in studied wheat samples were investigated. Among all the studied parameters, the climatic conditions of silo locations showed the highest influence on pesticide residues in wheat samples. Generally, 61.2% of the samples had pesticide levels below the method detection limits and 38.8% of the total samples had at least one of the understudied pesticides. Also, 13.9% of the samples had deltamethrin residues, 16.7% of the samples had permethrin, 22.2% of the samples had malathion, 11.1% of the samples had both permethrin and malathion and 2.8% of the samples had both deltamethrin and malathion. The results revealed that the residues of deltamethrin and malathion were lower than the standard level announced by European Union regulation and only three samples contained permethrin higher than Europe standard level.