This study employed multivariate statistical techniques in one of the main river basins in Brazil, the Doce River basin, to select and evaluate the most representative parameters of the current water quality aspects, and to group the stations according to the similarity of the selected parameters, for both dry and rainy seasons. Data from 63 qualitative monitoring stations, belonging to the Minas Gerais Water Management Institute network were used, considering 38 parameters for the hydrological year 2017/2018. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to reduce the total number of variables and to group stations with similar characteristics, respectively. Using PCA, four principal components were selected as indicators of water quality, explaining the cumulative variance of 68% in the rainy season and 65% in the dry season. The HCA grouped the stations into four groups in the rainy season and three groups in the dry season, showing the influence of seasonality on the grouping of stations. Moreover, the HCA made it possible to differentiate water quality stations located in the headwaters of the basin, in the main river channel, and near urban centers. The results obtained through multivariate statistics proved to be important in understanding the current water quality situation in the basin and can be used to improve the management of water resources because the collection and analysis of all parameters in all monitoring stations require greater availability of financial resources.The paper presents the effects of the dam reservoir in Komorów on the water quality in the Utrata river. The implementation of the adopted objective involved a comparison of water quality at two points, above and below the reservoir. The Utrata River is polluted with biogenic compounds throughout the whole section studied. COD content also indicates significant contamination exceeding permissible limits. A positive effect of the reservoir on water quality in the river was also observed in terms of the content of dissolved oxygen, with concentration increasing below the reservoir. The reservoir had a positive effect on reducing the concentration of total phosphorus in the water. Water in the Utrata below the reservoir showed higher values of chemical oxygen demand (CODMn) than above the reservoir. There were no differences in the concentration of NH4+ and NO3- ions in the water before and after the reservoir.Land use/cover change is the main driving force of urban expansion which influences human-environment interactions. Generally, the formation of urban heat islands (UHIs) can be referred to as a negative "by-product" of urbanization. In the context of rapid urbanization, the present paper aims to capture the landscape changes and three patterns of urban expansion (i.e., infill, extension, and leapfrog), and provide a better understanding of the formation of the surface urban heat island (SUHI) in Dongguan, China, during the past 20+ years. Urban land increased from 28.87 × 103 ha in 1994 to 78.89 × 103 ha in 2005 and 101.05 × 103 ha in 2015, with a compound annual urban growth rate of 9.57% (1994-2005) and 2.51% (2005-2015), respectively.  https://www.selleckchem.com/products/vt103.html  Based on the mean land surface temperature difference (Δ mean LST) between urban land (UL) and green space (GS), the SUHI intensity (SUHII) increased from 1.46 °C in 1994 to 2.32 °C in 2005 and 3.83 °C in 2015 in Dongguan. Overall, the Δ mean LST of urban areas increased from 2.61 °C (1994-2005) to 4.78 °C (2005-2015). The Δ mean LST between the city center and its surrounding areas decreased from 1994 to 2015, and the Δ mean LST between the city center and the suburbs gradually increased, primarily in 2015. In particular, both dense urban and the infill pattern of urban expansion had high mean LSTs in Dongguan, thus having negative impacts on sustainable urban development. The limited green space and open land should be strictly controlled or prohibited for transformation in urban areas. Particularly in dense regions, green roofs, green areas, and urban renewal actions could be considered for mitigating the urban heat island effect.Temporal/spatial variations of surface water quality were examined for the Nile River in the Damietta region where it serves as the major source of water for the inhabitants of Damietta Governorate. A total of 32 water quality parameters were monitored at six sampling sites for 12 months from February 2016 to January 2017. Higher values of chemical oxygen demand (COD), biological oxygen demand (BOD), heavy metals, and nutrients were observed upstream. About ~ 70% of the total variance in observations was explained by five main influences using factor analysis. The first factor (24.6% of the variance) was indicative of the mixed sources of natural and anthropogenic inputs. The second (nutritional) and the third (organic) factors were mainly controlled by the discharges from agricultural and domestic sources, respectively. Human activities and natural processes controlled the fourth and fifth factors. Only 11 parameters (K, temperature, COD, HPC, total hardness, DO, NO2, Na, TDS, Cl, and EC) were necessary for distinguishing temporal variations according to Discriminant analysis (DA). Seven parameters (BOD, PO4, SiO3, Al, Turbidity, Fe, and Chlorophyll-a) were the most important variables responsible for spatial variations. Using the results we developed a water quality index (WQI) using only those parameters identified as important. All water quality parameters were below the permissible limits except for turbidity according to the World Health Organization standards, BOD and COD according to the Egyptian regulations. The calculated WQI values ranged between 12.73 and 33.73. According to these values, the Nile River Damietta branch represents a good to an excellent source of drinking water for entering secondary treatment.Deciphering land use and land cover (LULC) change patterns, identifying the variables that act as the major driving forces of change, and predicting possible changes are necessary tools of decision support for policymakers. Estuarine landscapes world over are under extreme pressure of developmental activities because of their resources. The developmental activities lead to unforeseen changes in the traditional land use practices, making it necessary for investigation of the possible outcomes. The present study aims to study the changing pattern of LULC in the East Godavari River Estuarine Ecosystem (EGREE) landscape during 1977-2015 using temporal satellite data and to predict the possible LULC changes by 2029. Cellular Automata-Markov model (CAMM) with and without the multi-criteria evaluator (MCE) and the multi-layer perceptron (MLP) models were used for future LULC prediction. Between 1977 and 2015, mangroves were converted to aquaculture (5.81 km2) on the landward side and were also lost to submergence at the seaward side (15 km2).