Identifying and Evaluating a Suitable Index for Agricultural Drought Monitoring in the Texas High Plains

Drought is a complex and highly destructive natural phenomenon that affects portions of the United States almost every year, and severe water deficiencies can often become catastrophic for agricultural production. Evapotranspiration (ET) by crops is an important component in the agricultural water budget; thus, it is advantageous to include ET in agricultural drought monitoring. The main objectives of this study were to (1) conduct a literature review of drought indices with a focus to identify a simple but simultaneously adequate drought index for monitoring agricultural drought in a semiarid region and (2) using the identified drought index method, develop and evaluate time series of that drought index for the Texas High Plains. Based on the literature review, the Standardized Precipitation‐Evapotranspiration Index (SPEI) was found to satisfy identified constraints for assessing agricultural drought. However, the SPEI was revised by replacing reference ET with potential crop ET to better represent actual water demand. Data from the Texas High Plains Evapotranspiration network was used to calculate SPEIs for the major irrigated crops. Trends and magnitudes of crop‐specific, time‐series SPEIs followed crop water demand patterns for summer crops. Such an observation suggests that a modified SPEI is an appropriate index to monitor agricultural drought for summer crops, but it was found to not account for soil water stored during the summer fallow period for winter wheat.     

Chronotype differences in Drosophila are enhanced by semi-natural conditions

Morning and evening chronotypes of sleep/wake cycles in humans are often metaphorically termed as ‘larks’ and ‘owls’. We derived Drosophila populations early and late, displaying lark- and owl-like emergence chronotypes by imposing selection for adult emergence during morning and evening hours. Preference for morning and evening emergence in these populations was accompanied by divergence in their circadian period (τ) and photic phase response curve. To test if lark- and owl-like emergence chronotypes displayed by these flies under weak environmental cycles of the laboratory would also persist in nature where several zeitgebers are present in the strongest form, we examined the emergence rhythm of early and late flies under semi-natural conditions. The early and late flies not only continued to exhibit divergent emergence waveforms under semi-natural conditions, the differences became even more prominent. However, phases of early and late emergence waveforms did not match natural morning and evening transitions, unlike that observed under laboratory conditions. These results thus provide evidence consistent with the notion that chronotypes are the result of interactions between circadian clocks and natural environmental cycles.     

COMPARING SOME METHODS OF ESTIMATING MEAN AREAL RAINFALL1

ABSTRACT: A comparison of 13 different methods of estimating mean areal rainfall was made on two areas in New Mexico, U.S.A., and one area in Great Britain. Daily, monthly and yearly rainfall data were utilized. All methods, in general, yielded comparable estimates, especially for yearly values. This suggested that a simpler method would be preferable for estimating mean areal rainfall in these areas.     

DERIVATION OF THE GAMMA DISTRIBUTION BY USING THE PRINCIPLE OF MAXIMUM ENTROPY (POME)1

The principle of maximum entropy (POME) was used to derive the two-parameter gamma distribution used frequently in synthesis of instantaneous or finite-period unit hydrographs. The POME yielded the minimally prejudiced gamma distribution by maximizing the entropy subject to two appropriate constraints which were the mean of real values and the mean of the logarithms of real values of the variable. It provided a unique method for parameter estimation. Experimental data were used to compare this method with the methods of moments, cumulants, maximum likelihood estimation, and least squares.     

Identification and leaching characteristics of sludge generated from metal pickling and electroplating industries by Toxicity Characteristics Leaching Procedure (TCLP)

One of India's major concerns is the increasing level of land pollution largely due to the uncontrolled disposal of industrialsolid and hazardous waste. With rapid industrialization, thegeneration of industrial solid and hazardous waste has increasedappreciably and the nature of waste generated has become complex.Their impacts on the ecological bodies are noticeable. The article describes the details of studies conducted using Toxicity Characteristics Leaching Procedure, to estimate the toxicity effects of the metals viz., chromium, zinc, manganese,iron, nickel, cobalt and copper by the Zero Headspace Extractorfor the sludges generated from effluent treatment plant of steeltube, wire and plating industries on environment constituentslike groundwater, surface water and land. Toxicity Characteristics Leaching Procedure determines the mobility of organic and inorganic analytes of liquid, solid or multiphase waste from hazardous solid wastes in the form of primary and secondary extracts. These extracts are mixed in equal volumeproportion and analyzed by Direct Reading 2000 spectrophotometer.The amount of heavy metals observed during the studies in theleachates were found and the results were compared with HazardousWaste categories as per Indian Standards, TCLP regulatory limitsgiven by United States Environment Protection Agency (USEPA) andGermany Leachate Quality Standards and it was observed that theywere on higher side, needing a proper preventive concept of sludge management including handling, treatment, recovery and disposal.     

Estimation and allocation of solid waste to bin through geographical information systems.

This study presents a geographical information system (GIS)-based procedure for the precise estimation of solid waste generation, computed using the local population density and income group distribution. Using a triangulated irregular network (TIN) in a GIS environment, the procedure further determines the command area for waste allocation to a particular bin which is generally located so the route slopes towards the collection points for ease of transportation by cart pullers. Computational results of bin location, type, size and the frequency of removal are presented for a typical urban area with known population density, income group distribution, road network and topology.     

An Assessment of U(VI) removal from groundwater using biochar produced from hydrothermal carbonization

The ever-increasing growth of biorefineries is expected to produce huge amounts of lignocellulosic biochar as a byproduct. The hydrothermal carbonization (HTC) process to produce biochar from lignocellulosic biomass is getting more attention due to its inherent advantage of using wet biomass. In the present study, biochar was produced from switchgrass at 300 °C in subcritical water and characterized using X-ray diffraction, fourier transform infra-red spectroscopy, scanning electron micrcoscopy, and thermogravimetric analysis. The physiochemical properties indicated that biochar could serve as an excellent adsorbent to remove uranium from groundwater. A batch adsorption experiment at the natural pH (~3.9) of biochar indicated an H-type isotherm. The adsorption data was fitted using a Langmuir isotherm model and the sorption capacity was estimated to be ca. 2.12 mg of U g(-1) of biochar. The adsorption process was highly dependent on the pH of the system. An increase towards circumneutral pH resulted in the maximum adsorption of ca. 4 mg U g(-1) of biochar. The adsorption mechanism of U(VI) onto biochar was strongly related to its pH-dependent aqueous speciation. The results of the column study indicate that biochar could be used as an effective adsorbent for U(VI), as a reactive barrier medium. Overall, the biochar produced via HTC is environmentally benign, carbon neutral, and efficient in removing U(VI) from groundwater.     

Assessment of water quality using cluster analysis in coastal region of Mumbai, India

The coastal water quality of Mumbai is deteriorating due to various point and non-point wastewater sources. Hence, it is desirable to monitor coastal water quality for various water-related activities like bathing, contact water sports, recreation, and commercial fishing. The objective of this paper is to assess the seasonal water quality on the basis of seawater standards. Based on water-quality analysis of 17 seafronts and beaches, most of the parameters were exceeding the standards. The statistical cluster analysis was carried out for evaluating impact of wastewater and sewage discharges. The hierarchical cluster analysis resulted into three clustered groups, namely less polluted, moderately polluted, and highly polluted sites with similar characteristics of water quality. Mahim was found to be worst-affected beach due to incoming organic load from the Mithi river in comparison to other seafronts and beaches. Unaccounted sources of sewage and wastewater should be identified and rerouted through sewerage system by improving collection efficiency, treatment, and proper disposal for achieving designated receiving water quality standards.     

Flood Forecasting Using Neural Computing Techniques and Conceptual Class Segregation

Various neural networks models are developed and applied for flood forecasting at Sangye station (no. 1) of the Bocheong Stream catchment, which is one of the International Hydrological Program's representative catchments, Republic of Korea. The neural networks models (NNMs) are multilayer perceptron‐neural networks model (MLP‐NNM), generalized regression neural networks model (GRNNM), and Kohonen self‐organizing feature maps neural networks model (KSOFM‐NNM). Data used for model training and testing are divided into two groups: such as floods and typhoon events. Single conventional application and class segregation implementation are applied to evaluate the neural networks models. KSOFM‐NNM forecasts flood discharge more accurately than do MLP‐NNM and GRNNM for the testing data of Methods I and II for single conventional application and class segregation implementation. This study shows that class segregation can capture the dynamics of different physical processes and overcome the difficulties using single conventional application of neural networks models.     

Studies on the Drying Characteristics of Zingiber Officinale Under Open Sun and Solar Biomass (Hybrid) Drying

Drying characteristics of Zingiber officinale (Ginger) under the open sun and direct type natural convection solar biomass (hybrid) drying were studied. It has been observed that under open sun drying conditions, the drying rate depends on the product thickness and climatic conditions. The results have been drawn for both the summer (April-May, 2004) and winter (November-January, 2003–04) months of Delhi, in India. In the hybrid drier, the ginger, with a thickness of 0.008 m, dried in 33 hours in comparison to 96 hours in open-sun drying. The overall drying efficiency of the hybrid drier was found to be 18% and 13% under summer and winter climatic conditions respectively. The loss of volatile oil content of the ginger is less in hybrid drier in comparison to open sun drying. It was found that the average drying air temperature of 60°C with average air velocity of 0.6m/sec was sufficient for the drying of ginger in the hybrid drier. Ginger quality after drying is better and drying time is less in the hybrid drier in comparison to open-sun drying. The hybrid drier is a simple device, which can be manufactured with locally available materials and can be used for drying of other spices, vegetables and fruits etc.