River discharge simulation using variable parameter McCarthy–Muskingum and wavelet-support vector machine methods

In this study, an extended version of variable parameter McCarthy–Muskingum (VPMM) method originally proposed by Perumal and Price (J Hydrol 502:89–102, 2013) was compared with the widely used data-based model, namely support vector machine (SVM) and hybrid wavelet-support vector machine (WASVM) to simulate the hourly discharge in Neckar River wherein significant lateral flow contribution by intermediate catchment rainfall prevails during flood wave movement. The discharge data from the year 1999 to 2002 have been used in this study. The extended VPMM method has been used to simulate 9 flood events of the year 2002, and later the results were compared with SVM and WASVM models. The analysis of statistical and graphical results suggests that the extended VPMM method was able to predict the flood wave movement better than the SVM and WASVM models. A model complexity analysis was also conducted which suggests that the two parameter-based extended VPMM method has less complexity than the three parameter-based SVM and WASVM model. Further, the model selection criteria also give the highest values for VPMM in 7 out of 9 flood events. The simulation of flood events suggested that both the approaches were able to capture the underlying physics and reproduced the target value close to the observed hydrograph. However, the VPMM models are slightly more efficient and accurate, than the SVM and WASVM model which are based only on the antecedent discharge data. The study captures the current trend in the flood forecasting studies and showed the importance of both the approaches (physical and data-based modeling). The analysis of the study suggested that these approaches complement each other and can be used in accurate yet less computational intensive flood forecasting

Assessment of LNAPL in subsurface under fluctuating groundwater table using 2D sand tank experiments

The focus of this study was to investigate the fate and transport of toluene, a light nonaqueous-phase liquids (LNAPLs) in the subsurface region under dynamic groundwater table conditions. A series of experiments were conducted using two-dimensional (2D) sand tank setup having dimensions 125×90×10  cm 125×90×10  cm (L×H×W L×H×W ) and integrated with an auxiliary column of inner diameter 14 cm and height 120 cm. Initially, a steady-state flow and LNAPL transport experiment was conducted under stable groundwater table condition. Thereafter, three groundwater table fluctuation experiments were conducted on a rising and falling groundwater table in 2, 4, and 8 h to maintain rapid, general, and slow fluctuation conditions, respectively. The pure phase of toluene was injected at a rate of 1  mL/min 1  mL/min for a total duration of 5 min. Soil-water and soil-vapor samples were periodically collected and analyzed for toluene concentrations. Later, the representation of the 2D sand tank setup was numerically simulated to obtain the response of flow and the LNAPL transport under varying groundwater table conditions. Analysis of the results shows that a large LNAPL pool area (250  cm 2 250  cm2 ) develops under rapidly fluctuating groundwater conditions, which significantly enhances the dissolution rate and contributes to a high concentration of dissolved LNAPLs at the receiving receptors. Estimated values of Sherwood and Peclet numbers show that the dissolution rates were highly affected by groundwater table dynamics, which may cause loss of pure-phase pollutant mass around the pollutant source. The concentration isolines of toluene show that the transport of dissolved LNAPL plumes was also comparatively fast in the case of rapidly fluctuating groundwater. A high biodegradation rate was observed in plume regions having concentration ranges of 140–160 ppm, while it decreases in plume regions having very high (>160  ppm >160  ppm ) and low concentrations (<140  ppm <140  ppm ) of dissolved LNAPL. In the sand tank, microbial growth was found to increase as the plume moved away from the LNAPL pool toward a low gradient, which intensifies the detrimental impact of toluene on the survival of indigenous microorganisms near the LNAPL pool. The results of this study may help in implementing effective remediation techniques to decontaminate LNAPL polluted sites under fluctuating groundwater table conditions, especially in (semi)-arid coastal aquifers

Electrocatalytic properties of La1-xCuxCoO3 (0 ≤ x ≤ 0.8) film electrodes for oxygen evolution in alkaline medium: Part II. A comparative study

1295-1301The present study is concerned with the preparation of perovskite-type oxide film electrodes of La, Cu and Co having composition La1-xCuxCoO3 (0 ≤ X ≤ 0.8) on Ni conducting support and study of their electrocatalytic properties towards oxygen evolution reaction (OER) in alkaline medium. Materials have been synthesized by using malic acid sol-gel route at pH 4.00. X-ray diffraction study of the material indicated the formation of almost pure perovskite phase with hexagonal crystal geometry. The electrocatalytic activity of the material has been determined in three electrode single compartment glass cell. Techniques used in the electrochemical studies are cyclic voltammetry (CV), oxide roughness factor and anodic polarization (Tafel plot). Each cyclic voltammogram exhibits an anodic and a corresponding cathodic peak prior to the oxygen evolution reaction. The observed anodic and cathodic peak potential values are 553±31 and 312±27 mV, respectively. The study of anodic polarization curve indicates that the oxide with 0.6 mol Cu-substitution (ja = 182.4 mA cm-2 at 750 mV) shows highest electrocatalytic activity with lowest Tafel slope value (b = 65 mV decade-1) towards OER. Thermodynamic properties of the material have also been investigated by recording the anodic polarization curve at different temperatures. The value of electrochemical activation energy has been found to be lowest with most active 0.6 mol Cu-substituted oxide material. Electrocatalytic activities of the oxide electrodes, so obtained, have been compared with the similar oxide prepared at 3.75 pH

Leakage of CO2 from geological storage and its impacts on fresh soil–water systems: a review

Leakage of CO2 from the geological storage is a serious issue for the sustainability of the receiving fresh soil–water systems. Subsurface water quality issues are no longer related to one type of pollution in many regions around the globe. Thus, an effort has been made to review studies performed to investigate supercritical CO2 (scCO2) and CO2 enrich brine migration and it's leakage from geological storage formations. Further, the study also reviewed it's impacts on fresh soil–water systems, soil microbes, and vegetation. The first part of the study discussed scCO2/CO2 enrich brine migration and its leakage from storage formations along with it's impact on pore dynamics of hydrological regimes. Later, a state-of-the-art literature survey has been performed to understand the role of CO2–brine leakage on groundwater dynamics and its quality along with soil microbes and plants. It is observed in the literature survey that most of the studies on CO2–brine migration in storage formations reported significant CO2–brine leakage due to over-pressurization through wells (injections and abandoned), fracture, and faults during CO2 injection. Thus, changes in the groundwater flow and water table dynamics can be the first impact of the CO2–brine leakage. Subsequently, three major alterations may also occur—(i) drop in pH of subsurface water, (ii) enhancement of organic compounds, and (iii) mobilization of metals and metalloids. Geochemical alteration depends on the amount of CO2 leaked and interactions with host rocks. Therefore, such alteration may significantly affect soil microbial dynamics and vegetation in and around CO2 leakage sites. In-depth analysis of the available literature fortifies that a proper subsurface characterization along with the bio-geochemical analysis is extremely important and should be mandatory to predict the more accurate risk of CO2 capture and storage activities on soil–water systems

Evaluation of best management practices for sediment and nutrient loss control using SWAT model

The intensive study of an individual watershed is required to develop effective and efficient watershed management plans. Identification of critical erosion-prone areas of the watershed and implementation of best management practices (BMPs) is necessary to control the watershed degradation by reducing the sediment and nutrient losses. The present study evaluates and recommends the BMPs in an agriculture-based Marol watershed (5092 km2) of India, using a hydrologic model, Soil and Water Assessment Tool (SWAT). After successful calibration and validation, the model simulated daily/monthly discharge and sediment were found satisfactory throughout the simulation period. The model was then applied with a calibrated set of parameters for evaluating the effectiveness of various management practices for sediment and nutrient loss control. Keeping in mind the existing agricultural practices, socio-economic aspects and geography of the study area, the management practices were focused on four crops (Maize, Rice, Soybeans and Ground nut), three fertilization levels (high, medium and low), four tillage treatments (Field cultivator, Conservation tillage, Zero tillage and Mould board plough), and two conservation operations (Contour farming and Filter strips). The simulated annual average sediment yield from the watershed was found to be 12.2 t.ha−1yr−1. The water balance analysis revealed that, the evapo-transpiration is predominant over the watershed (approximately 46.3% of the annual average rainfall). Reduction in sediment yield and nutrient loss was observed with alternate cropping treatments of Groundnut and Soybean, as compared to Paddy and Maize cultivation. Overall, based on simulated results, the field cultivator tillage practice and conservation practices viz., contour farming and filter strips, could be adopted to reduce sediment yield and nutrient losses in the critical sub-watersheds of the study area and in other watersheds with similar hydro-climatic conditions

Ensemble modelling framework for groundwater level prediction in urban areas of India

India is facing the worst water crisis in its history and major Indian cities which accommodate about 50% of its population will be among highly groundwater stressed cities by 2020. In past few decades, the urban groundwater resources declined significantly due to over exploitation, urbanization, population growth and climate change. To understand the role of these variables on groundwater level fluctuation, we developed a machine learning based modelling approach considering singular spectrum analysis (SSA), mutual information theory (MI), genetic algorithm (GA), artificial neural network (ANN) and support vector machine (SVM). The developed approach was used to predict the groundwater levels in Bengaluru, a densely populated city with declining groundwater water resources. The input data which consist of groundwater levels, rainfall, temperature, NOI, SOI, NIÑO3 and monthly population growth rate were pre-processed using mutual information theory, genetic algorithm and lag analysis. Later, the optimized input sets were used in ANN and SVM to predict monthly groundwater level fluctuations. The results suggest that the machine learning based approach with data pre-processing predict groundwater levels accurately (R > 85%). It is also evident from the results that the pre-processing techniques enhance the prediction accuracy and results were improved for 66% of the monitored wells. Analysis of various input parameters suggest, inclusion of population growth rate is positively correlated with decrease in groundwater levels. The developed approach in this study for urban groundwater prediction can be useful particularly in cities where lack of pipeline/sewage/drainage lines leakage data hinders physical based modelling

Microfluidic system for screening disease based on physical properties of blood

Introduction: A key feature of the 'One Health' concept pertains to the design of novel point of care systems for largescale screening of health of the population residing in resource-limited areas of low- and middle-income countries with a view to obtaining data at a community level as a rationale to achieve better public health outcomes. The physical properties of blood are different for different samples. Our study involved the development of an innovative system architecture based upon the physical properties of blood using automated classifiers to enable large-scale screening of the health of the population living in resource-limited settings. Methods: The proposed system consisted of a simple, robust and low-cost sensor with capabilities to sense and measure even the minute changes in the physical properties of blood samples. In this system, the viscosity of blood was derived from a power-law model coupled with the Rabinowitsch-Mooney correction for non-Newtonian shear rates developed in a steady laminar Poiseuille flow. Surface tension was measured by solving the Young-Laplace equation for pendant drop shape hanging on a vertical needle. An anticipated outcome of this study would be the development of a novel automated classifier based upon the rheological attributes of blood. This automated classifier would have potential application in evaluating the health status of a population at regional and global levels. Results: The proposed system was used to measure the physical properties of various samples like normal, tuberculous and anemic blood samples. The results showed that the physical properties of these samples were different as compared to normal blood samples. The major advantage of this system was low-cost, as well as its simplicity and portability. Conclusion: In this work, we proposed making a case for the validation of a low-cost version of a microfluidic system capable of scanning large populations for a variety of diseases as per the WHO mandate of "One Health"

Utilization of Agro-Industrial Wastes as Edible Coating and Films for Food Packaging Materials

Mostly, food packaging employs synthetic materials obtained from nonrenewable sources. These packaging materials are based on petrochemicals and cause substantial environmental problems by producing massive amounts of non-biodegradable solid wastes. Edible coatings and films are considered as the potential solution to these problems of non-biodegradable packaging solid wastes for maintaining food-environment interactions, retaining food quality, and extending shelf life. In addition, edible coatings and films offer prevention from microbial spoilage of packed foods by controlling moisture and gas barrier characteristics. Increasing environmental concerns and consumer demands for high-quality eco-friendly packaging have fueled the advancement of innovative packaging technologies, for instance, the development of biodegradable films from renewable agricultural and food processing industry wastes. Therefore, the current chapter presents the application of edible coatings and films as an alternative to conventional packaging, emphasizing the fundamental characterization that these biodegradable packaging should hold for specific applications such as food preservation and shelf life enhancement. The primary employed components (e.g., biopolymers, bioactive, and additives components), manufacturing processes (for edible films or coatings), and their application to specific foods have all been given special consideration in this chapter. Besides, a future vision for the use of edible films and coatings as quality indicators for perishable foods is presented

Scaling up indigenous rainwater harvesting: a preliminary assessment in Rajasthan, India

Rainwater harvesting (RWH) has the potential to enhance the sustainability of ground and surface water to meet increasing water demands and constrained supplies, even under a changing climate. Since arid and semi-arid regions frequently experience highly variable spatiotemporal rainfall patterns, rural communities have developed indigenous RWH techniques to capture and store rainwater for multiple uses. However, selecting appropriate sites for RWH, especially across large regions, remains challenging since the data required to evaluate suitability using critical criteria are often lacking. This study aimed to identify the essential criteria and develop a methodology to select potential RWH sites in Rajasthan (India). We combined GIS modeling (multicriteria decision analysis) with applied remote sensing techniques as it has the potential to assess land suitability for RWH. As assessment criteria, spatial datasets relating to land use/cover, rainfall, slope, soil texture, NDVI, and drainage density were considered. Later, weights were assigned to each criterion based on their relative importance to the RWH system, evidence from published literature, local expert advice, and field visits. GIS analyses were used to create RWH suitability maps (high, moderate, and unsuited maps). The sensitivity analysis was also carried out for identified weights to check the inadequacy and inconsistency among preferences. It was estimated that 3.6%, 8.2%, and 27.3% of the study area were highly, moderately, and unsuitable, respectively, for Chauka implementation. Further, sensitivity analysis results show that LULC is highly sensitive and NDVI is the least sensitive parameter in the selected study region, which suggests that changing the weight of these parameters is more likely to decide the outcome. Overall, this study shows the applicability of the GIS-based MCDA approach for up-scaling the traditional RWH systems and its suitability in other regions with similar field conditions, where RWH offers the potential to increase water resource availability and reliability to support rural communities and livelihoods

Estimation of groundwater recharge in semiarid regions under variable land use and rainfall conditions: a case study of Rajasthan, India

In the semiarid regions of India, the annual rainfall is very low (~650 mm) and erratic; hence groundwater recharge is vital to support crops, especially in the winter season. For groundwater budgeting it is essential to consider how groundwater recharge is affected by both land-use and rainfall distribution. This study used a soil water balance approach, considering hydrological, meteorological, hydrogeological and crop information to understand the recharge process in semiarid regions. The approach was used at a sub-watershed scale where farmers grow rainfed and irrigated crops. Delayed recharge response on the water table was considered to estimate actual recharge, which closely matches the observed water levels in the field. The recharge estimated in rainfed agricultural lands, rainfed-irrigated agricultural lands, and barren lands was 29%, 17%, and 31% of the total inflow.Natural Environment Research Council (NERC): NE/R003351/