A historical and future impact assessment of mining activities on surface biophysical characteristics change : A remote sensing-based approach

Mining activities and associated actions cause land-use/land-cover (LULC) changes across the world. The objective of this study were to evaluate the historical impacts of mining activities on surface biophysical characteristics, and for the first time, to predict the future changes in pattern of vegetation cover and land surface temperature (LST). In terms of the utilized data, satellite images of Landsat, and meteorological data of Sungun mine in Iran, Athabasca oil sands in Canada, Singrauli coalfield in India and Hambach mine in Germany, were used over the period of 1989-2019. In the first step, the spectral bands of Landsat images were employed to extract historical LULC changes in the study areas based on the homogeneity distance classification algorithm (HDCA). Thereafter, a CA-Markov model was used to predict the future of LULC changes based on the historical changes. In addition, LST and vegetation cover maps were calculated using the single channel algorithm, and the normalized difference vegetation index (NDVI), respectively. In the second step, the trends of LST and NDVI variations in different LULC change types and over different time periods were investigated. Finally, a CA-Markov model was used to predict the LST and NDVI maps and the trend of their variations in future. The results indicated that the forest and green space cover was reduced from 9.95 in 1989 to 5.9 Km(2) in 2019 for Sungun mine, from 42.14 in 1999 to 33.09 Km(2) in 2019 for Athabasca oil sands, from 231.46 in 1996 to 263.95 Km(2) in 2016 for Singrauli coalfield, and from 180.38 in 1989 to 133.99 Km(2) in 2017 for Hambach mine, as a result of expansion and development of of mineral activities. Our findings about Sungun revealed that the areal coverage of forest and green space will decrease to 15% of the total study area by 2039, resulting in reduction of the mean NDVI by almost 0.06 and increase of mean standardized LST from 0.52 in 2019 to 0.61 in 2039. our results further indicate that for Athabasca oil sands (Singrauli coalfield, Hambach mine), the mean values of standardized LST and NDVI will change from 0.5 (0.44 and 0.4) and 0.38 (0.38, 0.35) in 2019 (2016, 2017) to 0.57 (0.5, 0.47) and 0.33 (0.32, 0.28), in 2039 (2036, 2035), respectively. This can be mainly attributed to the increasing mining activities in the past as well as future years. The discussion and conclusions presented in this study can be of interest to local planners, policy makers, and environmentalists in order to observe the damages brought to the environment and the society in a larger picture.Peer reviewe

Bacteria transport and retention in intact calcareous soil columns under saturated flow conditions

Study of bacterial transport and retention in soil is important for various environmental applications such as groundwater contamination and bioremediation of soil and water. The main objective of this research was to quantitatively assess bacterial transport and deposition under saturated conditions in calcareous soil. A series of leaching experiments was conducted on two undisturbed soil columns. Breakthrough curves of Pseudomonas fluorescens and Cl were measured. After the leaching experiment, spatial distribution of bacteria retention in the soil columns was determined. The HYDRUS-1D one- and two-site kinetic models were used to predict the transport and deposition of bacteria in soil. The results indicated that the two-site model fits the observed data better than one-site kinetic model. Bacteria interaction with the soil of kinetic site 1 revealed relatively fast attachment and slow detachment, whereas attachment to and detachment of bacteria from kinetic site 2 was fast. Fast attachment and slow detachment of site 1 can be attributed to soil calcium carbonate that has favorable attachment sites for bacteria. The detachment rate was less than 0.02 of the attachment rate, indicating irreversible attachment of bacteria. High reduction rate of bacteria was also attributed to soil calcium carbonate

CSM-CERES-Wheat Sensitivity to Evapotranspiration Modeling Frameworks under a Range of Wind Speeds

Crop modeling uncertainty is expected to be high under weather data limitations; thus, jeopardizing decision-making on food-water security. Missing near-surface wind speed (u2) data required to accurately estimate reference evapotranspiration (ETo) seemed to significantly affect both the potential evapotranspiration (ETP) and yield simulations for data-scarce windy regions. In this study, the uncertainty in crop modeling based on different ETP approaches was assessed. In this regard, wheat yield and evapotranspiration were simulated with the CSM-CERES-Wheat model using either the Priestley-Taylor/Ritchie (PT) or the Penman-Monteith DSSAT (PM) methods under “rain-fed, low-nitrogen stress”, “rain-fed, high nitrogen stress”, “full irrigation, low nitrogen stress”, and “full irrigation, high nitrogen stress” scenarios for a u2 range from 0.8 to 3.5 m s−1. The daily weather data required to run the model were retrieved from 18 semi-arid areas located in western Iran. The statistically significant differences in mean yield and cumulative distribution were determined by the non-parametric Wilcoxon signed-rank and the Kolmogorov-Smirnov tests, respectively. The deviation in evaporation and transpiration simulated by applying PT and PM was lower under rain-fed condition. Under “rain-fed, low-nitrogen stress”, the PT-simulated yield deviated significantly (p < 0.05) from PM-simulated yield by more than 26% for the sites with u2 above 3 m s−1. The deviation in ETP estimates did not, however, lead to statistically significant difference in yield distribution curves for almost all sites and scenarios. Nitrogen deficiency resulted in a smaller difference in yield for rain-fed condition. The yield results showed a deviation below 6% under full irrigation condition. Under windy rain-fed condition, high deviation in leaf area index (LAI) and ETP estimates caused a large difference in the actual transpiration to potential transpiration ratio (Ta/TP), and yield. However, the deviation between PT- and PM-simulated LAI and Ta/TP for the full irrigation scenarios was less than 6%. Overall, the results from this study indicate that when soil moisture is depleted, resembling rain-fed condition, simulation of yield appears to be highly sensitive to the estimation of ETP for windy areas

Comparison of empirical models to estimate soil erosion and sediment yield in micro catchments

Assessment of sediment yield in soil conservation and watershed Project and implementation plan for water and soil resources management is so important. Regarding to somewhere that doesn’t have enough information and statistical data such as upper river branches, Empirical models should be used to estimate erosion and sediment yield. However the efficiency and usage of these models before calibration isn’t clear. In this research, the measurement of erosion and sediment yield of 10 basins upstream of reservoirshas been estimated by RUSLE and MPSIAC empirical models.In order to compare means between measured and estimated datat-test method was applied.Theresults indicated no significant differences between means of measured and estimated sediment yield in MPSAIC model in 5% level. In contrast, T-test showed contrary results in RUSLE model. Then the applicability and priority of two models were examined by statistical methodssuch as MAE and MBE methods. By regarding to accuracy and precision, MPSIAC model placed in first priorityto estimate soil erosion and sediment yield and has minimum value of MAE=0.79 and MBE = -0.59

A novel strategy for optimal placement of locally controlled voltage regulators in traditional distribution systems

In this paper, an approach for placement of voltage regulators (VRs) in traditional distribution systems by considering a local controller model is presented. The main aims of this paper are controlling the voltage level in its permitted range and decreasing the costs imposed to the distribution system companies, such as costs that stem from power losses, VRsâ\u80\u99 investment and maintenance. Genetic algorithm (GA) has been used as a tool to determine the number, location and rated power of VRs. Since in traditional distribution systems, tap position determination of VRs is achieved by local controllers, local controller model is established to determine tap operations. A 70-bus distribution system is considered to prove the value of the presented approach. Effectiveness of the proposed approach and ineffectiveness and infeasibility of conventional approaches are presented in numerical studies. The presented approach allowed to eliminate voltage violation in all load conditions and a reduction of power losses of about 6% for the maximum load level

CSM-CERES-Wheat Sensitivity to Evapotranspiration Modeling Frameworks under a Range of Wind Speeds

Crop modeling uncertainty is expected to be high under weather data limitations; thus, jeopardizing decision-making on food-water security. Missing near-surface wind speed (u2) data required to accurately estimate reference evapotranspiration (ETo) seemed to significantly affect both the potential evapotranspiration (ETP) and yield simulations for data-scarce windy regions. In this study, the uncertainty in crop modeling based on different ETP approaches was assessed. In this regard, wheat yield and evapotranspiration were simulated with the CSM-CERES-Wheat model using either the Priestley-Taylor/Ritchie (PT) or the Penman-Monteith DSSAT (PM) methods under “rain-fed, low-nitrogen stress”, “rain-fed, high nitrogen stress”, “full irrigation, low nitrogen stress”, and “full irrigation, high nitrogen stress” scenarios for a u2 range from 0.8 to 3.5 m s−1. The daily weather data required to run the model were retrieved from 18 semi-arid areas located in western Iran. The statistically significant differences in mean yield and cumulative distribution were determined by the non-parametric Wilcoxon signed-rank and the Kolmogorov-Smirnov tests, respectively. The deviation in evaporation and transpiration simulated by applying PT and PM was lower under rain-fed condition. Under “rain-fed, low-nitrogen stress”, the PT-simulated yield deviated significantly (p 2 above 3 m s−1. The deviation in ETP estimates did not, however, lead to statistically significant difference in yield distribution curves for almost all sites and scenarios. Nitrogen deficiency resulted in a smaller difference in yield for rain-fed condition. The yield results showed a deviation below 6% under full irrigation condition. Under windy rain-fed condition, high deviation in leaf area index (LAI) and ETP estimates caused a large difference in the actual transpiration to potential transpiration ratio (Ta/TP), and yield. However, the deviation between PT- and PM-simulated LAI and Ta/TP for the full irrigation scenarios was less than 6%. Overall, the results from this study indicate that when soil moisture is depleted, resembling rain-fed condition, simulation of yield appears to be highly sensitive to the estimation of ETP for windy areas

Water management dilemma in the agricultural sector of Iran: A review focusing on water governance

Around 90% of fresh renewable water is being used in Iran, indicating high water stress conditions across the country. Given that agricultural irrigation accounts for the majority of water use and consumption, any efforts to alleviate water stress must focus on enhancing agricultural water management. This paper aims to exhaustively compile the existing literature on the consequences and drivers of water insecurity, and to discuss the strategies balancing food and water security in the context of agricultural water management. Severe water scarcity can be largely attributed to governance gaps in Iran. In addition, inefficient water use, population growth, and warming/drying trends in the recent half a century are other major causes of the water scarcity. Groundwater over-depletion, quality deterioration of aquatic resources, decreased environmental flows and habitat destruction, and water conflicts are the significant consequences of improper water management in Iran. Several water productivity and conservation interventions, drawn from a rich literature, were suggested to improve agricultural water management in Iran. Furthermore, some water-food-energy nexus optimization methods, including changing cropping patterns, modifying energy tariffs, manipulating food diet, and reducing food waste, were discussed. Nexus-based strategies, which aim to achieve a balance between food production and water sustainability, are of high importance in reducing water consumption in the agricultural sector. While there has been a significant focus on improving water productivity and nexus-based measures, it is essential that policy-makers prioritize enhancing the water governance dimensions to effectively address water scarcity and its consequences in Iran. In other words, improving the water governance system is a prerequisite for adopting any strategy aimed at enhancing agricultural water management and coping with water security

Evaluating the Spectral Indices Efficiency to Quantify Daytime Surface Anthropogenic Heat Island Intensity

The surface anthropogenic heat island (SAHI) phenomenon is one of the most important environmental concerns in urban areas. SAHIs play a significant role in quality of urban life. Hence, the quantification of SAHI intensity (SAHII) is of great importance. The impervious surface cover (ISC) can well reflect the degree and extent of anthropogenic activities in an area. Various actual ISC (AISC) datasets are available for different regions of the world. However, the temporal and spatial coverage of available and accessible AISC datasets is limited. This study was aimed to evaluate the spectral indices efficiency to daytime SAHII (DSAHII) quantification. Consequently, 14 cities including Budapest, Bucharest, Ciechanow, Hamburg, Lyon, Madrid, Porto, and Rome in Europe and Dallas, Seattle, Minneapolis, Los Angeles, Chicago, and Phoenix in the USA, were selected. A set of 91 Landsat 8 images, the Landsat provisional surface temperature product, the High Resolution Imperviousness Layer (HRIL), and the National Land Cover Database (NLCD) imperviousness data were used as the AISC datasets for the selected cities. The spectral index-based ISC (SIISC) and land surface temperature (LST) were modelled from the Landsat 8 images. Then, a linear least square model (LLSM) obtained from the LST-AISC feature space was applied to quantify the actual SAHII of the selected cities. Finally, the SAHII of the selected cities was modelled based on the LST-SIISC feature space-derived LLSM. Finally, the values of the coefficient of determination (R2) and the root mean square error (RMSE) between the actual and modelled SAHII were calculated to evaluate and compare the performance of different spectral indices in SAHII quantification. The performance of the spectral indices used in the built LST-SIISC feature space for SAHII quantification differed. The index-based built-up index (IBI) (R2 = 0.98, RMSE = 0.34 °C) and albedo (0.76, 1.39 °C) performed the best and worst performance in SAHII quantification, respectively. Our results indicate that the LST-SIISC feature space is very useful and effective for SAHII quantification. The advantages of the spectral indices used in SAHII quantification include (1) synchronization with the recording of thermal data, (2) simplicity, (3) low cost, (4) accessibility under different spatial and temporal conditions, and (5) scalability.Peer Reviewe