Feasibility study of rainwater harvesting system in Sylhet City

In rural areas in Bangladesh, groundwater is the principal source of water supply. This underground water is available in considerable amount in shallow aquifers. It is free from pathogenic microorganisms and hence water-borne diseases. In plain lands, other than hilly areas, water supply to 97% rural population comes from tube-wells, which is regarded to be a phenomenal achievement in preserving public health. Besides, a dependable water supply system all throughout the country is offset by two factors: (a) high salinity in surface plus groundwater in coastal areas; (b) want of suitable groundwater aquifers in hilly areas and the high cost of setting up tube-wells due to deep underground water table and stony layers. However, presence of arsenic in underground water now poses a serious threat to the success once made in water supply by setting up of manually operated tube-wells in the village areas—the achievement is now on the brink of total collapse. In about 61 districts out of 64, presence of arsenic exceeds a quantity of 0.05 mg/1, a permissible limit as per Bangladeshi water quality standard. Harvesting rainwater can be a pragmatic solution to this problem, which is common in many places in Sylhet especially in the hilly areas on the north eastern part of the city. This can be an alternative source of drinking water because of availability of rainwater from March to October. Heavy rain occurs from end of May till mid September, which is commonly known as the rainy season. This paper focuses on the possibility of harvesting rainwater in rural communities and thickly populated urban areas of Sylhet. It also demonstrates the scopes of harvesting rainwater using simple and low-cost technology. With setting up of a carefully planned rainwater storage tank, a family can have all of its drinking water from rain. Planned use of rainwater through rainwater harvesting in the roof catchments may fulfill the entire annual domestic water demand of a family in the rural areas of Bangladesh.     

Mixed response in bacterial and biochemical variables to simulated sand mining in placer-rich beach sediments,Ratnagiri, West coast of India

We investigated the influence on bacterial community and biochemical variables through mechanical disturbance of sediment-akin to small-scale mining in Kalbadevi beach, Ratnagiri, a placer-rich beach ecosystem which is a potential mining site. Changes were investigated by comparing three periods, namely phase I before disturbance, phase II just after disturbance, and phase III 24 h after disturbance as the bacterial generation time is ≤7 h. Cores from dune, berm, high-, mid-, and low-tide were examined for changes in distribution of total bacterial abundance, total direct viability (counts under aerobic and anaerobic conditions), culturability and biochemical parameters up to 40 cm depth. Results showed that bacterial abundance decreased by an order from 10⁶ cells g^− 1 sediment, while, viability reduced marginally. Culturability on different-strength nutrient broth increased by 155% during phase II. Changes in sedimentary proteins, carbohydrates, and lipids were marked at berm and dune and masked at other levels by tidal influence. Sedimentary ATP reduced drastically. During phase III, Pearson’s correlation between these variables evolved from non-significant to significant level. Thus, simulated disturbance had a mixed effect on bacterial and biochemical variables of the sediments. It had a negative impact on bacterial abundance, viability and ATP but positive impact on culturability. Viability, culturability, and ATP could act as important indicators reflecting the disturbance in the system at short time intervals. Culturability, which improved by an order, could perhaps be a fraction that contributes to restoration of the system at bacterial level. This baseline information about the potential mining site could help in developing rational approach towards sustainable harnessing of resources with minimum damage to the ecosystem.     

Trace metals biogeochemistry of Kumaun Himalayan Lakes,Uttarakhand, India

The increasing urbanization, along with tourism, has posed a major threat to the Kumaun Himalayan Lakes, Uttarakhand, India. The total metal concentration in the water, interstitial water, and sediments along with the metal fractionation studies were carried out to understand the remobilization of the trace metals from the sediments of the lakes. The high concentration of the metals in the water column of the lakes generally decreases with depth and the metals release from the sediment is mainly due to the prevalence of anoxic condition at the sediment–water interface and sediment column. The sediment shows that metals Fe and Cr are derived from detrital source, whereas Co, Ni, and Zn are derived mainly from the organic matter dissolution. The sparse correlation of the trace metals with Ti shows most of the metals have chiefly re-precipitated from the water column. The metals speciation studies also supports that metals experience a high rate of anoxic dissolution and their precipitation onto the sediments are determined by the sediment composition and organic matter content. The high concentration of manganese in the interstitial water in the lakes indicates dissolution of organic matter. The released manganese is adsorbed/precipitated as carbonate phase (Nainital Lake) and oxide pahse (in other lakes). The study shows that the trace metals are regenerated from the sediments due to oxyhydroxide dissolution and organic matter decomposition.     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

Anticipating Climate Threshold Damages

Several integrated assessment studies have concluded that future learning about the uncertainties involved in climate change has a considerable effect on welfare but only a small effect on optimal short-term emissions. In other words, learning is important but anticipation of learning is not. We confirm this result in the integrated assessment model “model of investment and technological development” for learning about climate sensitivity and climate damages. If learning about an irreversible threshold is included, though, we show that anticipation can become crucial both in terms of necessary adjustments of pre-learning emissions and resulting welfare gains. We specify conditions on the time of learning and the threshold characteristic, for which this is the case. They can be summarized as a narrow “anticipation window.”     

Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

Vegetation in the upper catchment of Yellow River is critical for the ecological stability of the whole watershed. The dominant vegetation cover types in this region are grassland and forest, which can strongly influence the eco-environmental status of the whole watershed. The normalized difference vegetation index (NDVI) for grassland and forest has been calculated and its daily correlation models were deduced by Moderate Resolution Imaging Spectroradiometer products on 12 dates in 2000, 2003, and 2006. The responses of the NDVI values with the inter-annual grassland and forest to three climatic indices (i.e., yearly precipitation and highest and lowest temperature) were analyzed showing that, except for the lowest temperature, the yearly precipitation and highest temperature had close correlations with the NDVI values of the two vegetation communities. The value of correlation coefficients ranged from 0.815 to 0.951 (p?<?0.01). Furthermore, the interactions of NDVI values of vegetation with the climatic indicators at monthly interval were analyzed. The NDVI of vegetation and three climatic indices had strong positive correlations (larger than 0.733, p?<?0.01). The monthly correlations also provided the threshold values for the three climatic indictors, to be used for simulating vegetation growth grassland under different climate features, which is essential for the assessment of the vegetation growth and for regional environmental management.     

Workplace aerosol mass concentration measurement using optical particle counters

Direct-reading aerosol measurement usually uses the optical properties of airborne particles to detect and measure particle concentration. In the case of occupational hygiene, mass concentration measurement is often required. Two aerosol monitoring methods are based on the principle of light scattering: optical particle counting (OPC) and photometry. The former analyses the light scattered by a single particle, the latter by a cloud of particles. Both methods need calibration to transform the quantity of scattered light detected into particle concentration. Photometers are simpler to use and can be directly calibrated to measure mass concentration. However, their response varies not only with aerosol concentration but also with particle size distribution, which frequently contributes to biased measurement. Optical particle counters directly measure the particle number concentration and particle size that allows assessment of the particle mass provided the particles are spherical and of known density. An integrating algorithm is used to calculate the mass concentration of any conventional health-related aerosol fraction. The concentrations calculated thus have been compared with simultaneous measurements by conventional gravimetric sampling to check the possibility of field OPC calibration with real workplace aerosols with a view to further monitoring particle mass concentration. Aerosol concentrations were measured in the food industry using the OPC GRIMM? 1.108 and the CIP 10-Inhalable and CIP 10-Respirable (ARELCO?) aerosol samplers while meat sausages were being brushed and coated with calcium carbonate. Previously, the original OPC inlet had been adapted to sample inhalable aerosol. A mixed aerosol of calcium carbonate and fungi spores was present in the workplace. The OPC particle-size distribution and an estimated average particle density of both aerosol components were used to calculate the mass concentration. The inhalable and respirable aerosol fractions calculated from the OPC data are closely correlated with the results of the particle size-selective sampling using the CIP 10. Furthermore, the OPC data allow calculation of the thoracic fraction of workplace aerosol (not measured by sampling), which is interesting in the presence of allergenic particles like fungi spores. The results also show that the modified COP inlet adequately samples inhalable aerosol in the range of workplace particle-size distribution.     

How Do River Nitrate Concentrations Respond to Changes in Land-use? A Modelling Case Study of Headwaters in the River Derwent Catchment,North Yorkshire,UK

A combined semi-distributed hydrological model (CASCADE/QUESTOR) is used to evaluate the steady-state that may be achieved after changes in land-use or management and to explore what additional factors need to be considered in representing catchment processes. Two rural headwater catchments of the River Derwent (North Yorkshire, UK) were studied where significant change in land-use occurred in the 1990s and the early 2000s. Much larger increases in mean nitrate concentration (55%) were observed in the catchment with significant groundwater influence (Pickering Beck) compared with the surface water-dominated catchment (13% increase). The increases in Pickering Beck were considerably greater than could be explained by the model in terms of land-use change. Consequently, the study serves to focus attention on the long-term increases in nitrate concentration reported in major UK aquifers and the ongoing and chronic impact this trend is likely to be having on surface water concentrations. For river environments, where groundwater is a source, such trends will mask the impact of measures proposed to reduce the risk of nitrate leaching from agricultural land. Model estimates of within-channel losses account for 15–40% of nitrate entering rivers.     

Inexact Fuzzy-Stochastic Programming for Water Resources Management Under Multiple Uncertainties

In this study, an interval-parameter fuzzy-stochastic two-stage programming (IFSTP) approach is developed for irrigation planning within an agriculture system under multiple uncertainties. A concept of the distribution with fuzzy-interval probability (DFIP) is defined to address multiple uncertainties expressed as integration of intervals, fuzzy sets, and probability distributions. IFSTP integrates the interval programming, two-stage stochastic programming, and fuzzy-stochastic programming within a general optimization framework. IFSTP incorporates the pre-regulated water resources management policies directly into its optimization process to analyze various policy scenarios; each scenario has different economic penalty when the promised amounts are not delivered. IFSTP is applied to an irrigation planning in a water resources management system. Solutions from IFSTP provide desired water allocation patterns, which maximize both the system’s benefits and feasibility. The results indicate that reasonable solutions are generated for objective function values and decision variables; thus, a number of decision alternatives can be generated under different levels of stream flows.     

Water quality evaluation of two interconnected dam lakes with field-captured and laboratory-acclimated fish, <Emphasis Type="BoldItalic">Cyprinus carpio</Emphasis>

Karakaya and Sultansuyu Dam Lakes, located in the eastern part of Turkey, are important water sources, both for irrigation and fishery. The main goal of the study was to investigate water qualities of dam lakes using a set of biomarkers in the fish Cyprinus carpio. For this aim, field sample and laboratory-acclimated fish were compared to identify changes in selected biomarkers. The activities of ethoxyresorufin-O-deethylase, glutathione S-transferase, glutathione reductase, and carboxylesterase were determined in liver samples. Also, plasma and liver lactate dehydrogenase, aspartate aminotransferase, and alanine aminotransferase activities were assayed. Brain acetylcholinesterase and carboxylesterase activities were also determined. The hepatosomatic index and condition factors were calculated. Plasma vitellogenin assays were evaluated for the presence of xenoestrogen. Physicochemical values of water samples showed the existence of eutrophication risk, and also, some chemicals in both lakes were determined to be over tolerable limits. The comparisons of samples from both dam lake and laboratory-acclimated fish showed that the lakes may be at risk of pollution by some xenobiotics, namely xenoestrogens and acetylcholinesterase-inhibiting agents.