Reservoir water quality: a case from Jordan

Jordan relies heavily on reservoirs building and development to cope with water supply challenges, where monitoring and assessment of reservoir water quality are critically important for the sustainable use of these water supplies. Mujib Dam is an important water supply source in central western Jordan. Evaluation of water quality parameters and their spatial distributions (vertical and horizontal) showed near-neutral pH values with nearly similar values from surface to bottom. The vertical profile of DO and TDS in the dammed reservoir showed slight decreasing trends with increasing depth. Although Ca, Mg, Na, and K concentrations varied slightly with depths, their variations showed no trends. Similarly, the vertical and horizontal distribution patterns of Cl, SO₄, HCO₃, NO₃, and PO₄ in Mujib reservoir water showed insignificant variations in surface water layer and relatively unchanged values or decreasing trends through the water column. Higher values of TN have been observed, especially in the western part, suggesting that agricultural activities and livestock farming in the upstream catchment are impacting water quality. Results revealed that weathering and dissolution of rocks are the major source of water chemistry. The majority of trace metal levels (Cd, Cr, Cu, Fe, Mn, Pb, Zn, Co, Ni, Sr, and B) in water showed relatively similar surface and bottom values. The concentrations of COD and BOD₅ in surface water were relatively low with higher concentrations observed in the northwestern corner, coincided with higher levels of chlorophyll a. The average ratio of TN to TP in surface water suggests that phosphorus is the limiting factor for the algal blooms, whereas the average chlorophyll a level in surface water indicates oligo-mesotrophic water.     

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.     

FIA-coupled spectrophotometric method for determination of Cr (VI) traces in natural waters: application of in-line dissolution of 1,5-diphenylcarbazide after heat treatment and activated alumina as adsorbent for preconcentration

This work proposes the quantification of Cr (VI) ions in natural waters in trace level, using activated alumina (Al₂O₃) as preconcentration support, controlled in-line dissolution of the solidified chromophore diphenylcarbazide after heat treatment and spectrophotometric detection. The manifold ensures high sensitivity of analytical response, good repeatability, and stability. In this work, optimization of experimental conditions of a flow injection system was chosen as the parameters for greater sensitivity and better selectivity. The selected optimized conditions were 0.30 mol L^?1 for H₂SO₄ concentration, system flow rate as 0.40 mL min^?1, sample injection volume of 192.50 μL, 2 min for preconcentration time, and 0.10 mol L^?1 for eluent concentration. The analytical curves obtained for real sample analysis show linear range from 0.192 to 0.961 μM, linear correlation coefficient R?=?0.9997 and LOD?=?0.024 μM. The preconcentration factor of about four times was obtained through the passage of 800 μL of a standard solution containing 0.961 μM of Cr (VI) through mini-column of preconcentration followed by elution at 192.5 μL of NH₄OH 0.1 mol L^?1 solution. The solid chromogenic reagent presented high durability (weeks in daily use with mass of 0.0993 g) and good reproducibility in analytical signal. The reactivation of the mini-column of alumina should be executed after ten injections of eluent, using 800 μL of HCl 0.02 mol L^?1 solution in flow through the same. Each cycle of injection and elution of the sample takes about 5 min on the proposed terms. Despite the length of each cycle still be high, low concentrations can be detected using a technique of relatively low cost. This is due in part, the association dissolution of the chromogenic reagent directly in the line and the preconcentration step. Another important factor is the economy of reagent chromogenic, low generation of reject contributing to better quality of the environment, and the high potential for applications to work in field.     

Adsorption-desorption and leaching potential of glyphosate and aminomethylphosphonic acid in acidic Malaysian soil amended with cow dung and rice husk ash

This study investigates adsorption-desorption and the leaching potential of glyphosate and aminomethylphosphonic acid (AMPA) in control and amended—addition of cow dung or rice husk ash—acidic Malaysian soil with high oxide mineral content. The addition of cow dung or rice husk ash increased the adsorptive removal of AMPA. The isotherm data of glyphosate and AMPA best fitted the Freundlich model. The constant K_f for glyphosate was high in the control soil (544.873 mg g^?1) followed by soil with cow dung (482.451 mg g^?1) then soil with rice husk ash (418.539 mg g^?1). However, for AMPA, soil with cow dung was high (166.636 mg g^?1) followed by soil with rice husk ash (137.570 mg g^?1) then the control soil (48.446 mg g^?1). The 1/n values for both glyphosate and AMPA adsorptions were <?1 indicating their strong affinity for adsorbents. Desorption of both glyphosate and AMPA occurred only in the control soil. The compounds were not detected in soils with added cow dung or rice husk ash. The addition of cow dung or rice husk ash increased glyphosate mobility. However, ground water ubiquity scores for both control and amended soils were <?2.8. This indicated glyphosate is a transitional herbicide; therefore, its leaching potential in the soil is low, despite the addition of cow dung or rice husk ash. Addition of these wastes decreased the mobility and leaching potential of AMPA. The addition of cow dung or rice husk ash could be beneficial in increasing adsorption and enhancing degradation of these compounds.     

The probabilistic tsunami hazard assessment along Karnataka Coast from Makran Subduction Zone,west coast of India

Coastal tsunami amplitudes were calculated to identify areas susceptible to tsunami hazard at selected locations of the coast of Karnataka, west of India, due to earthquakes in the Makran Subduction Zone. This is the first time that the probabilistic tsunami hazard assessment along this study area has been attempted. A series of earthquake source scenarios with magnitudes of Mw 8.0, Mw 8.5, and a mega thrust of Mw 9.1 were modeled by using the Community Model Interface for Tsunami interface with the MOST model of Titov and Synolakis (J. Waterway, Port, Coastal and Ocean Engineering, 121(6), 308–316, 1995). As per the previous occurrences, the two least magnitudes are probable, while Mw 9.1 is a worst-case scenario as described by Heidarzadeh et al. (Ocean Engineering, 36(5), 368–376, 2009) and the same is reported by Burbidge et al. (Geoscience Australia Professional Opinion No. 2009/11) as high magnitude. These are not at all historical earthquakes or specifically from historical catalogues. The results of modeling show that all the seven coastal locations are inundated barely in our worst-case scenario with maximum water levels in the range of 100–200 cm. The first tsunami wave strikes the coast within 4–5 h of earthquake occurrence.     

Monitoring of meteorological and hydrological droughts in the Vistula basin (Poland)

The article presents the course of meteorological droughts in Vistula subcatchments in years 1981–2010 and their influence on the occurrence of hydrological droughts. Using the Standardized Precipitation Index (SPI) as an indicator of meteorological drought on the one hand and the Standardized Water-level Index (SWI) and Standardized Runoff Index (SRI) as indicators of hydrological drought on the other, the mutual relationships between precipitation conditions and hydrological conditions were evaluated, as well as the relationships between the two drought types. Studies were conducted for three cumulative periods of these indices, of 12, 24, and 48 months. It was determined that meteorological droughts occurred earliest in the north-western and central part of the basin, and latest in areas lying above 300 m a.s.l. and in the south of Poland. Total duration, depending on the cumulative period, for SPI comprised from 38 to 41% of the analyzed period and for SWI (35–47%) and SRI (24–51%). The strongest relationships were identified in the central part of the Vistula (0.8?<?r?<?0.85), while the weakest relationships were recorded in the foothill region (r?<?0.5). There were also indicated non-climate-related factors influencing those relationships (underground reservoirs, diverse Vistula water resource usage for municipal and industrial intake).     

Spectral trend of vegetation with rainfall in events of El Niño-Southern Oscillation for Atlantic Forest biome,Brazil

This study aimed to analyze the spectral trend of vegetation with rainfall in El Niño-Southern Oscillation events (ENSO) in the Atlantic Forest, Brazil. Monthly rainfall data were collected from 85 conventional meteorological stations (EMC), data from the Enhanced Vegetation Index 2 (EVI2) and ENSO events (El Niño, La Niña, and Neutral) in the period from 2001 to 2013. Afterwards, state cluster analysis was performed using the results of non-parametric tests. The Mann-Kendall (MK) non-parametric test did not identify a trend pattern in rainfall distribution in the Atlantic Forest. The results for EVI2 by state and region showed that the trend is decreasing in the Northeast Region, except for the states of Alagoas and Pernambuco. Southeast region showed an increasing trend of EVI2 (except for Rio de Janeiro and São Paulo), while the South region showed a decreasing trend. In the Midwest, the trend was significantly decreasing. In the prognosis elaborated for the future, the regions with significant declines of the vegetation were the Northeast and Midwest. This study shows that the Atlantic Forest in some regions of Brazil has been suffering from the growing urbanization process and there is a trend of soil degradation.     

Influence of different textile fibers on characterization of dyeing wastewater and final effluent

Textile industry needs to recover and reuse its wastewater as to fulfil the demand of increasingly strict regulations. The characterization of dyeing wastewater samples according to textile fiber and final textile effluent enables the application of different treatment methods. This study aims to characterize dyeing wastewater in black color of polyamide, polyester, and viscose fibers and final textile effluent. Samples were collected and characterized completely for major pollution indicator parameters. Dyeing wastewater of polyester showed higher values for some parameters, e.g., 4994.44% (49,944,400 mg L^?1 and 917 NTU) of turbidity and 4100.00% of phenol when compared to dyeing wastewater of other fibers. Other parameters such as pH, alkalinity, color, phosphorus, nitrogen, sulfides, chlorides, oil and grease, dissolved solids, and chemical and biochemical oxygen demand were also assessed. In addition to individual characterization, this study also presents a correlation of the contribution of each parameter to the final textile effluent. Although dyeing wastewater of polyamide contributes the most in terms of quantity for the final effluent, this study revealed that dyeing wastewater of polyester influenced the most on the final composition of the textile wastewater when evaluating color, turbidity, total iron, biochemical oxygen demand, chemical oxygen demand, phenol, mercury, oil and grease, and total phosphorus. The present study is focused on bringing new insights to provide future research with other strategies to improve the treatment of dyeing wastewater. In addition, some suggestions are also given for wastewater treatments according to type of textile fiber.     

Water quality index for agricultural systems in Northwest Uruguay

Agricultural systems have experienced rapid expansion and intensification in the last several decades. In Uruguay, since the beginning of 2000, the most common cropping systems have included soybeans. Currently, this crop is expanding towards lowlands traditionally occupied by rice in rotation with pastures. However, the environmental effects of agricultural intensification and diversification are not well known. Thus, some indices have been proposed to quantify the changes in agricultural production systems and assess water quality. The main goal of this study was to develop a water quality index (WQI) to assess the impacts of the diversification of rice production systems in northwest Uruguay. The study was carried out in an agricultural basin where other summer crops have been incorporated in the rice-pasture sequence. Agriculture intensification and crop diversification indices were calculated using information provided by farmers. Water samples were collected downstream of the production area before crop sowing and after crop harvest (2008–2009 to 2010–2011 and 2016–2017 to 2017–2018). Biochemical oxygen demand, nitrates, total phosphorus, fecal coliforms, and total suspended solids were the variables that mainly explained the effects of the agricultural activities on water quality. The proposed water quality index included these unweighted variables, which allowed for the pre-sowing and post-harvest to be differentiated, as well as the degree of diversification. Therefore, the proposed WQI constitutes a tool that can be used to evaluate the water quality in an agricultural basin. Likewise, it can be used to select agricultural sequences that generate the least possible impacts on the associated water resources.