Today, inhabitants residing in floodplains face a serious and perpetual threat of flooding. Flood... more Today, inhabitants residing in floodplains face a serious and perpetual threat of flooding. Flooding causes fatalities and considerable property damage in metropolitan areas. Therefore, robust structural measures need to be adopted to eliminate flood catastrophe. Structural measures in the floodplain are the most promising solutions. However, there are cost-associated factors for proposing a flood retention plan. Navsari city (98.36 km2, area extent) of Gujarat was used as a case study to investigate the impact of mesh grid structures (100 m, 90 m, and 50 m) along with structural measures for the preparation of a flood retention plan. The HEC-RAS 2D hydrodynamic model was performed for the Purna River. The output of the model was characterized by four different scenarios: (i) Without weir and levees (WOWL), (ii) With weir (WW), (iii) With levees (WL), and (iv) With weir and levees (WWL). The statistical parameters (R2, RMSE, NSE, inundation time, and inundation area) were determined...
Flood risk mapping using multi-criteria analysis (TOPSIS) model through geospatial techniques- A case study of the Navsari city, Gujarat, India
<p>Flood is one of the most devastating natural disasters that cause enormous socio... more <p>Flood is one of the most devastating natural disasters that cause enormous socioeconomic and environmental destruction. The severity of flood losses has evoked emphasis on more comprehensive and vigorous flood modeling techniques for alleviating flood damages. Flood vulnerability in Navsari is intensifying due to urbanization, industrialization, and population growth. Although there has been a significant increase in research on flood assessment at a local scale in Navsari, there remains a lack of tools developed which utilize the risk map of the city. In response to this prerequisite, in this study we have employed a GIS-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria analysis model to develop a flood risk map for Navsari city in Gujarat, India, to determine the vulnerable areas that are more susceptible to flooding. To estimate the extent of flood hazard, vulnerability, and risk intensities in terms of area covered, the city was divided into ten zones (i.e. NC1 to NC10) and classified into five classes: very high, high, moderate, low, and very low. A total of seven hazard forming spatial layers (i.e. slope, elevation, soil, rainfall, flow accumulation, distance to a river, and drainage density) and seven vulnerability forming spatial layers (i.e. female population, population density, land use, household, distance to hospital, road network density, and literacy rate) were appraised for evaluating the risk of flooding. The generated flood risk map has been compared with the extent of flood calculated based on field data collected from thirty-six random places. The outcome of the model unveiled the capability of the TOPSIS model since it capitulate low RMSE value varied between 0.95 to 0.43 and high R square value ranged from 0.78 to 0.95. The zones indicated under ‘high’ and ‘very high’ categories (i.e. NC8, NC6, NC4, NC1, NC7, and NC10) demand abrupt flood control action to alleviate the severity of flood risk and subsequent damages. The approach implemented in the study can be applied to any flood-sensitive region around the globe to accurately evaluate the risk of flood. Lastly, flood risk mapping using TOPSIS based geospatial techniques divulge the novel and efficacious approach, especially for data-sparse regions.</p>
Delhi has witnessed a recent blow up in urbanization along river Yamuna passing through Wazirabad... more Delhi has witnessed a recent blow up in urbanization along river Yamuna passing through Wazirabad to Okhla section leading to the shrinkage in the flood plain that has considerably reduced the water levels within the river section. The present study quantifies the changes that have taken place over a period of ten years within the flood plains of river Yamuna by using two IRS LISS III images of year 2001 and 2011. Land Use Land Cover maps of the study area were prepared and areas covered in each land cover class in the two images were evaluated and compared in terms of percent increase or decrease. Results from the analysis revealed that agricultural area lying within the flood plain has been increased to 234.52 hectares in the year 2011 as compared to 164.5 hectares in 2001, thereby indicating an overall increase of 42.6%. A significant reduction of 61.6% in areas covered under dense trees has also been observed during the study period. Further, a notable increase of 59.5% in the b...
Land use Mapping of Yamuna river Flood Plain in Delhi using K-Mean and spectral angle image classification algorithms
Water and Energy International, 2019
This study intends to analyze the land use mapping within the Yamuna river flood plain in Delhi b... more This study intends to analyze the land use mapping within the Yamuna river flood plain in Delhi by USGS-LULC level II category classification system using K-Mean and Spectral Angle algorithm. ERDAS imagine 9.2 were used for Image processing and land use assessment. The Landsat 8 (2018) and TM (2000) images were acquired for assessing the classification algorithms. LULC classification was achieved with overall accuracies of 86.00%, 86.00%, 94.00% and 96.00% for the year of assessment 2000 and 2018 by K-Mean and Spectral Angle algorithm respectively. The kappa coefficient was achieved as 0.76, 0.69, 0.88 and 0.9 for the year of assessment 2000 and 2018 by K-Mean and Spectral Angle algorithm respectively. For the year of assessment 2000, the maximum and minimum land use was 40% and 4% for Agriculture and barren land respectively where as for the year of assessment 2018, the maximum and minimum land use was 30% and 6% for Forest and barren land respectively. During the assessment period...
The information regarding spatial and temporal variation of soil moisture in a catchment is of ut... more The information regarding spatial and temporal variation of soil moisture in a catchment is of utmost importance in hydrological, as well as many other studies. Point measurements from gravimetric and other methods for soil moisture determination are insufficient to understand the spatial behaviour of soil moisture in a region. Microwave remote sensing data from active sensors on board various satellites are increasingly being used to map spatial distribution of soil moisture within the 0–10 cm top surface. The northern part of India has a network of large rivers and canals and, therefore, spatial and temporal distribution of soil moisture in this region has a significant bearing on the hydrology of the region. In this paper, results on estimation of soil moisture from an ERS-2 SAR image in the catchment of the Solani River (a tributary to the River Ganga) in and around the town of Roorkee, India, have been presented. The radar backscatter coefficient for each pixel of the image has...
The present study evaluates the water quality status of 6-km-long Kali River stretch that passes ... more The present study evaluates the water quality status of 6-km-long Kali River stretch that passes through the Aligarh district in Uttar Pradesh, India, by utilizing high-resolution IRS P6 LISS IV imagery. In situ river water samples collected at 40 random locations were analyzed for seven physicochemical and four heavy metal concentrations, and the water quality index (WQI) was computed for each sampling location. A set of 11 spectral reflectance band combinations were formulated to identify the most significant band combination that is related to the observed WQI at each sampling location. Three approaches, namely multiple linear regression (MLR), backpropagation neural network (BPNN) and gene expression programming (GEP), were employed to relate WQI as a function of most significant band combination. Comparative assessment among the three utilized approaches was performed via quantitative indicators such as R 2 , RMSE and MAE. Results revealed that WQI estimates ranged between 203.7 and 262.33 and rated as "very poor" status. Results further indicated that GEP performed better than BPNN and MLR approaches and predicted WQI estimates with high R 2 values (i.e., 0.94 for calibration and 0.91 for validation data), low RMSE and MAE values (i.e., 2.49 and 2.16 for calibration and 4.45 and 3.53 for validation data). Moreover, both GEP and BPNN depicted superiority over MLR approach that yielded WQI with R 2 ~ 0.81 and 0.67 for calibration and validation data, respectively. WQI maps generated from the three approaches corroborate the existing pollution levels along the river stretch. In order to examine the significant differences among WQI estimates from the three approaches, one-way ANOVA test was performed, and the results in terms of F-statistic (F = 0.01) and p-value (p = 0.994 > 0.05) revealed WQI estimates as "not significant," reasoned to the small water sample size (i.e., N = 40). The study therefore recommends GEP as more rational and a better alternative for precise water quality monitoring of surface water bodies by producing simplified mathematical expressions.
Spatial forecasting of solar radiation using ARIMA model
Remote Sensing Applications: Society and Environment, 2020
Abstract This paper is an attempt to forecast monthly solar radiation using remote sensing data o... more Abstract This paper is an attempt to forecast monthly solar radiation using remote sensing data on a region. Seasonal ARIMA (SARIMA) models are used for simulating and forecasting time series of insolation data from NASA's POWER (Prediction of Worldwide Energy Resources) data archive. Remotely sensed modelled insolation data for 34 years (i.e. January 1984 to December 2017) has been retrieved and analysed for forecasting. Monthly average insolation forecasts of the region around India's capital Delhi have been generated for next four years (i.e. January 2018 to December 2021) and presented in the form of contours obtained using marching square algorithm. The overall accuracy of forecasts in terms of R2 (0.9293), Root Mean Square Error (0.3529), Mean Absolute Error (0.2659) and Mean Absolute Percentage Error (6.556) was obtained. The ARIMA model forecasted the maximum insolation values in the months of May (6.52–6.76 KwH/m2/day in year 2018, 6.56–6.8 KwH/m2/day in 2019, 6.6–6.8 KwH/m2/day in 2020 and 6.6–6.84 KwH/m2/day in 2021) and Minimum in the months of January and December (3.2–3.7 KwH/m2/day in January 2018, 3.28–3.52 KwH/m2/day in December 2018). Insolation contours were analysed for identification of potential regions receiving maximum insolation as well as high average annual values of insolation for implementing efficient solar power generation projects. Parts of Haryana and Rajasthan region in study area were found most suitable for such projects.
Ископаемые угли-это сложная композиционная система, состоящая из органических микрокомпонентов в ... more Ископаемые угли-это сложная композиционная система, состоящая из органических микрокомпонентов в виде мацералов и минеральных включений. Актуальность работы определяется тем, что для прогноза технологических свойств и выбора основных направлений промышленного использования углей большое значение имеют данные о вещественно-петрографическом их составе, так как мацеральный состав углей является одним из параметров классификаций и кодификаций углей. В качестве объектов исследования использовались бурые угли следующих месторождений: Итатского, Мунайского, Архаро-Богучанского, Кангаласского, Багануур (Монголия). Исследованные образцы охарактеризованы техническим и элементным методами анализа. Установлено, что зольность бурых углей составляет величину менее 10%, выход летучих веществ изменяется в пределах от 41% до 48%. Методом петрографического анализа для исследованных углей определен показатель отражения витринита (Ro,r). Установлено, что наименьшим показателем отражения витринита обладает образец бурого угля Итатского месторождения (Ro,r = 0.388%), максимальной величиной характеризуется бурый уголь Кангаласского месторождения (Ro,r = 0.490%). Увеличение генетической зрелости исследованных образцов связано с изменением технологических свойств их органической массы. Показано, что с ростом Ro,r увеличивается содержание углерода (С daf), снижается выход летучих веществ, а также атомное отношение Н/С и О/С. Визуальный анализ аншлифов позволил определить мацеральный состав исследуемых углей. В образце бурого угля Багануурского месторождения (Монголия) выявлено наибольшее содержание инертинита (более 60%), в образце Кангаласского месторождения содержится наибольшее количество мацералов группы витринита (86%).
Vegetation effects on soil moisture estimation from ERS-2 SAR images
Hydrological Sciences Journal, 2012
The aim of this study was to map soil moisture from ERS-2 SAR images by minimizing the effect of ... more The aim of this study was to map soil moisture from ERS-2 SAR images by minimizing the effect of vegetation on the backscatter coefficient. Detailed analysis was carried out to identify the prominent crop descriptor (i.e. crop height, h; leaf area index, LAI; and plant water content, PWC), and to minimize its effect on soil moisture estimation. A semi-empirical water
The information regarding spatial and temporal variation of soil moisture in a catchment is of ut... more The information regarding spatial and temporal variation of soil moisture in a catchment is of utmost importance in hydrological, as well as many other studies. Point measurements from gravimetric and other methods for soil moisture determination are insufficient to understand the spatial behaviour of soil moisture in a region. Microwave remote sensing data from active sensors on board various satellites are increasingly being used to map spatial distribution of soil moisture within the 0-10 cm top surface. The northern part of India has a network of large rivers and canals and, therefore, spatial and temporal distribution of soil moisture in this region has a significant bearing on the hydrology of the region. In this paper, results on estimation of soil moisture from an ERS-2 SAR image in the catchment of the Solani River (a tributary to the River Ganga) in and around the town of Roorkee, India, have been presented. The radar backscatter coefficient for each pixel of the image has been modelled from the digital numbers of the SAR image. Gravimetric measurements have been made simultaneously during the satellite pass to determine the concurrent value of volumetric soil moisture at a large number of sample points within the satellite sweep area. The backscatter coefficient is found to vary from-30 dB to-42 dB for a variation in soil moisture from 30 to 75%. Regression analyses between volumetric soil moisture and both the digital numbers and backscatter coefficients were performed. Strong correlations between volumetric soil moisture and digital number were observed with R 2 values of 0.84, 0.75 and 0.83 for bare soil, vegetative and combined surfaces, respectively. A similar trend was observed with the relationship between backscatter and volumetric soil moisture with R 2 values of 0.60, 0.89 and 0.67 for bare soil, vegetative and combined surfaces, respectively. These results demonstrate the utilization of SAR data for estimation of spatial distribution of soil moisture in the region of the present study.
Journal of Water and Land Development, Dec 1, 2018
Morphometric analysis of any watershed and its prioritization is one of the important aspects of ... more Morphometric analysis of any watershed and its prioritization is one of the important aspects of planning for implementation of management programmes. Present study evaluates the quantitative morphometric characteristics of Nagmati River watershed in Kutch District of Gujarat by utilizing Cartosat-1 data (CartoDEM). In all 19 aerial and 6 linear morphometric parameters of the watershed have been evaluated. Drainage map of the study area reveals a dendritic drainage pattern with sixth order stream network comprising 492 numbers of streams and confining an area of 129.41 km 2. Mean bifurcation ratio (R b) and stream length ratio (R L) of the watershed evaluated are 3.44 and 0.54 respectively which corroborates the fact that drainage pattern is not influenced by the geological evolutions and disturbances in the recent past. The drainage density of 2.68 kmꞏkm-2 indicates impermeable subsoil material with sparse vegetation and moderate to low relief. Elongation ratio of 0.956 infers the basin to be closer to a circular shape. The geologic stage of development and erosion proneness of the watershed is quantified by hypsometric integral (HI) bearing value as 0.5, indicating the landscape to be uniform and in early mature stage. The study prioritizes eight sub-watersheds as high, medium and low for taking up soil and water conservation activities. Hence, remote sensing applications proved to be highly useful in extracting the precise data for the evaluation and analysis of watershed characteristics.
River Yamuna is the largest tributary of river Ganges and has been acclaimed as a heavenly waterw... more River Yamuna is the largest tributary of river Ganges and has been acclaimed as a heavenly waterway in Indian mythology. However, 22-km segment of river Yamuna passing through Delhi from downstream of Wazirabad barrage up to Okhla barrage is considered as the filthiest stretch having been rendered into a sewer drain. The present study employs high-resolution GeoEye-2 imagery for mapping and monitoring pollution levels within the river segment by testing correlation between water quality parameters (WQPs) and the corresponding spectral reflectance values of the image. A total of 100 water samples collected from random sampling locations along the river segment were analyzed for 12 WQPs in the laboratory and grouped into two classes, namely (WQP) organic and (WQP) inorganic. Several spectral band combinations as well as single bands were tested for any significant correlation with the two formulated WQP classes by performing multiple linear regression analysis. Results reveal that spectral band combination, i.e., � (RGB) × √ B∕R � , and the two formulated WQP classes exhibit strong positive correlation with R = 0.92 and 0.91 (R 2 ~ 0.85 and 0.82; RMSE ~ 1.03 and 1.12) for calibration data and 0.85 and 0.84 (i.e., R 2 ~ 0.74 and 0.72; RMSE ~ 1.45 and 1.64) for validation data, respectively. The spatial distribution maps depicting pollution levels of two WQP classes were generated in GIS framework, substantiating to the actual in situ pollution concentration levels in the river segment. The methodology adopted in the present study and results obtained validate the potential of high-resolution GeoEye-2 imagery for monitoring and mapping pollution levels in the water bodies.
Box–Jenkins multiplicative ARIMA modeling for prediction of solar radiation: a case study
International Journal of Energy and Water Resources
This study deals with stochastic modeling of solar radiation in all sky conditions and presents a... more This study deals with stochastic modeling of solar radiation in all sky conditions and presents an effort to predict and analyze the future trends of monthly insolation based on time series analysis. Multiplicative seasonal autoregressive integrated moving average (ARIMA) model, using Box–Jenkins approach, has been utilized for simulating monthly average insolation data retrieved from NASA POWER (Prediction of Worldwide Energy Resource) data over the study area. The satellite dataset for a period of 34 years has been analyzed for modeling monthly average insolation. The insolation data time series examined by differencing and autocorrelation functions clearly indicates the existence of seasonality. Various multiplicative seasonal ARIMA models developed were validated by assessing various estimation parameters and their performance was evaluated by utilizing different selection measure criterion. The ARIMA (1, 0, 1) × (0, 1, 1)12, possessing minimum value of these criteria, was identified as the most adequate model. Forecasting of insolation was performed through selected models at 95% confidence interval. Results also reveal that ARIMA (1, 0, 1) × (0, 1, 2)12 produces minimum mean percentage error (MPE) in the forecast. As the difference in MPE for ARIMA (1, 0, 1) × (0, 1, 1)12 and ARIMA (1, 0, 1) × (0, 1, 2)12 is marginal (i.e., 0.004), the two models present minimal differences in estimated values and are therefore, reckoned as adequate for forecasting solar radiation.
Most of the industrial sewage effluents used for irrigation contains heavy metals which cause tox... more Most of the industrial sewage effluents used for irrigation contains heavy metals which cause toxicity to crop plants as the soils are able to accumulate heavy metal for many years. The vegetables grown for the present study were irrigated with treated wastewater brought from a nearby full-scale sewage treatment plant at different compositions along with tap water as a control. The concentration levels of the Cd, Co, Cu, Mn and Zn in the soil were found to below the toxic limits as prescribed in literature. Daily Intake Metals (DIM) values suggest that the consumption of plants grown in treated wastewater and tap water is nearly free of risks, as the dietary intake limits of Cu, Fe, Zn and Mn. The Enrichment Factor for the treated wastewater irrigated soil was found in order Zn> Ni> Pb> Cr> Cu> Co> Mn> Cd. Thus, treated wastewater can be effectively used for irrigation. This will have twofold significant environmental advantages: (1) helpful to reduce the ground...
Image fusion involves integration of the geometric details of a high-resolution panchromatic (PAN... more Image fusion involves integration of the geometric details of a high-resolution panchromatic (PAN) image and the spectral information of a low resolution multispectral (XS) image which is useful for regional planning and large scale urban mapping. Present study compares the effectiveness of three image fusion techniques namely, Principal Component Analysis (PCA), Wavelet Transform (WT) and Intensity Hue Saturation (IHS) to merge the XS information and PAN data of QuickBird satellite imagery. Comparison between the fused images obtained from the three fusion techniques is carried out on the basis of qualitative and quantitative evaluations implying, visual interpretation, inter-band correlation, correlation coefficient, standard deviation and mean. Results indicate that all three fusion techniques improves spatial resolution as well as spectral details, however, IHS technique provides the best spectral fidelity by preserving the XS integrity between all the bands under consideration.
Today, inhabitants residing in floodplains face a serious and perpetual threat of flooding. Flood... more Today, inhabitants residing in floodplains face a serious and perpetual threat of flooding. Flooding causes fatalities and considerable property damage in metropolitan areas. Therefore, robust structural measures need to be adopted to eliminate flood catastrophe. Structural measures in the floodplain are the most promising solutions. However, there are cost-associated factors for proposing a flood retention plan. Navsari city (98.36 km2, area extent) of Gujarat was used as a case study to investigate the impact of mesh grid structures (100 m, 90 m, and 50 m) along with structural measures for the preparation of a flood retention plan. The HEC-RAS 2D hydrodynamic model was performed for the Purna River. The output of the model was characterized by four different scenarios: (i) Without weir and levees (WOWL), (ii) With weir (WW), (iii) With levees (WL), and (iv) With weir and levees (WWL). The statistical parameters (R2, RMSE, NSE, inundation time, and inundation area) were determined...
Flood risk mapping using multi-criteria analysis (TOPSIS) model through geospatial techniques- A case study of the Navsari city, Gujarat, India
<p>Flood is one of the most devastating natural disasters that cause enormous socio... more <p>Flood is one of the most devastating natural disasters that cause enormous socioeconomic and environmental destruction. The severity of flood losses has evoked emphasis on more comprehensive and vigorous flood modeling techniques for alleviating flood damages. Flood vulnerability in Navsari is intensifying due to urbanization, industrialization, and population growth. Although there has been a significant increase in research on flood assessment at a local scale in Navsari, there remains a lack of tools developed which utilize the risk map of the city. In response to this prerequisite, in this study we have employed a GIS-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria analysis model to develop a flood risk map for Navsari city in Gujarat, India, to determine the vulnerable areas that are more susceptible to flooding. To estimate the extent of flood hazard, vulnerability, and risk intensities in terms of area covered, the city was divided into ten zones (i.e. NC1 to NC10) and classified into five classes: very high, high, moderate, low, and very low. A total of seven hazard forming spatial layers (i.e. slope, elevation, soil, rainfall, flow accumulation, distance to a river, and drainage density) and seven vulnerability forming spatial layers (i.e. female population, population density, land use, household, distance to hospital, road network density, and literacy rate) were appraised for evaluating the risk of flooding. The generated flood risk map has been compared with the extent of flood calculated based on field data collected from thirty-six random places. The outcome of the model unveiled the capability of the TOPSIS model since it capitulate low RMSE value varied between 0.95 to 0.43 and high R square value ranged from 0.78 to 0.95. The zones indicated under ‘high’ and ‘very high’ categories (i.e. NC8, NC6, NC4, NC1, NC7, and NC10) demand abrupt flood control action to alleviate the severity of flood risk and subsequent damages. The approach implemented in the study can be applied to any flood-sensitive region around the globe to accurately evaluate the risk of flood. Lastly, flood risk mapping using TOPSIS based geospatial techniques divulge the novel and efficacious approach, especially for data-sparse regions.</p>
Delhi has witnessed a recent blow up in urbanization along river Yamuna passing through Wazirabad... more Delhi has witnessed a recent blow up in urbanization along river Yamuna passing through Wazirabad to Okhla section leading to the shrinkage in the flood plain that has considerably reduced the water levels within the river section. The present study quantifies the changes that have taken place over a period of ten years within the flood plains of river Yamuna by using two IRS LISS III images of year 2001 and 2011. Land Use Land Cover maps of the study area were prepared and areas covered in each land cover class in the two images were evaluated and compared in terms of percent increase or decrease. Results from the analysis revealed that agricultural area lying within the flood plain has been increased to 234.52 hectares in the year 2011 as compared to 164.5 hectares in 2001, thereby indicating an overall increase of 42.6%. A significant reduction of 61.6% in areas covered under dense trees has also been observed during the study period. Further, a notable increase of 59.5% in the b...
Land use Mapping of Yamuna river Flood Plain in Delhi using K-Mean and spectral angle image classification algorithms
Water and Energy International, 2019
This study intends to analyze the land use mapping within the Yamuna river flood plain in Delhi b... more This study intends to analyze the land use mapping within the Yamuna river flood plain in Delhi by USGS-LULC level II category classification system using K-Mean and Spectral Angle algorithm. ERDAS imagine 9.2 were used for Image processing and land use assessment. The Landsat 8 (2018) and TM (2000) images were acquired for assessing the classification algorithms. LULC classification was achieved with overall accuracies of 86.00%, 86.00%, 94.00% and 96.00% for the year of assessment 2000 and 2018 by K-Mean and Spectral Angle algorithm respectively. The kappa coefficient was achieved as 0.76, 0.69, 0.88 and 0.9 for the year of assessment 2000 and 2018 by K-Mean and Spectral Angle algorithm respectively. For the year of assessment 2000, the maximum and minimum land use was 40% and 4% for Agriculture and barren land respectively where as for the year of assessment 2018, the maximum and minimum land use was 30% and 6% for Forest and barren land respectively. During the assessment period...
The information regarding spatial and temporal variation of soil moisture in a catchment is of ut... more The information regarding spatial and temporal variation of soil moisture in a catchment is of utmost importance in hydrological, as well as many other studies. Point measurements from gravimetric and other methods for soil moisture determination are insufficient to understand the spatial behaviour of soil moisture in a region. Microwave remote sensing data from active sensors on board various satellites are increasingly being used to map spatial distribution of soil moisture within the 0–10 cm top surface. The northern part of India has a network of large rivers and canals and, therefore, spatial and temporal distribution of soil moisture in this region has a significant bearing on the hydrology of the region. In this paper, results on estimation of soil moisture from an ERS-2 SAR image in the catchment of the Solani River (a tributary to the River Ganga) in and around the town of Roorkee, India, have been presented. The radar backscatter coefficient for each pixel of the image has...
The present study evaluates the water quality status of 6-km-long Kali River stretch that passes ... more The present study evaluates the water quality status of 6-km-long Kali River stretch that passes through the Aligarh district in Uttar Pradesh, India, by utilizing high-resolution IRS P6 LISS IV imagery. In situ river water samples collected at 40 random locations were analyzed for seven physicochemical and four heavy metal concentrations, and the water quality index (WQI) was computed for each sampling location. A set of 11 spectral reflectance band combinations were formulated to identify the most significant band combination that is related to the observed WQI at each sampling location. Three approaches, namely multiple linear regression (MLR), backpropagation neural network (BPNN) and gene expression programming (GEP), were employed to relate WQI as a function of most significant band combination. Comparative assessment among the three utilized approaches was performed via quantitative indicators such as R 2 , RMSE and MAE. Results revealed that WQI estimates ranged between 203.7 and 262.33 and rated as "very poor" status. Results further indicated that GEP performed better than BPNN and MLR approaches and predicted WQI estimates with high R 2 values (i.e., 0.94 for calibration and 0.91 for validation data), low RMSE and MAE values (i.e., 2.49 and 2.16 for calibration and 4.45 and 3.53 for validation data). Moreover, both GEP and BPNN depicted superiority over MLR approach that yielded WQI with R 2 ~ 0.81 and 0.67 for calibration and validation data, respectively. WQI maps generated from the three approaches corroborate the existing pollution levels along the river stretch. In order to examine the significant differences among WQI estimates from the three approaches, one-way ANOVA test was performed, and the results in terms of F-statistic (F = 0.01) and p-value (p = 0.994 > 0.05) revealed WQI estimates as "not significant," reasoned to the small water sample size (i.e., N = 40). The study therefore recommends GEP as more rational and a better alternative for precise water quality monitoring of surface water bodies by producing simplified mathematical expressions.
Spatial forecasting of solar radiation using ARIMA model
Remote Sensing Applications: Society and Environment, 2020
Abstract This paper is an attempt to forecast monthly solar radiation using remote sensing data o... more Abstract This paper is an attempt to forecast monthly solar radiation using remote sensing data on a region. Seasonal ARIMA (SARIMA) models are used for simulating and forecasting time series of insolation data from NASA's POWER (Prediction of Worldwide Energy Resources) data archive. Remotely sensed modelled insolation data for 34 years (i.e. January 1984 to December 2017) has been retrieved and analysed for forecasting. Monthly average insolation forecasts of the region around India's capital Delhi have been generated for next four years (i.e. January 2018 to December 2021) and presented in the form of contours obtained using marching square algorithm. The overall accuracy of forecasts in terms of R2 (0.9293), Root Mean Square Error (0.3529), Mean Absolute Error (0.2659) and Mean Absolute Percentage Error (6.556) was obtained. The ARIMA model forecasted the maximum insolation values in the months of May (6.52–6.76 KwH/m2/day in year 2018, 6.56–6.8 KwH/m2/day in 2019, 6.6–6.8 KwH/m2/day in 2020 and 6.6–6.84 KwH/m2/day in 2021) and Minimum in the months of January and December (3.2–3.7 KwH/m2/day in January 2018, 3.28–3.52 KwH/m2/day in December 2018). Insolation contours were analysed for identification of potential regions receiving maximum insolation as well as high average annual values of insolation for implementing efficient solar power generation projects. Parts of Haryana and Rajasthan region in study area were found most suitable for such projects.
Ископаемые угли-это сложная композиционная система, состоящая из органических микрокомпонентов в ... more Ископаемые угли-это сложная композиционная система, состоящая из органических микрокомпонентов в виде мацералов и минеральных включений. Актуальность работы определяется тем, что для прогноза технологических свойств и выбора основных направлений промышленного использования углей большое значение имеют данные о вещественно-петрографическом их составе, так как мацеральный состав углей является одним из параметров классификаций и кодификаций углей. В качестве объектов исследования использовались бурые угли следующих месторождений: Итатского, Мунайского, Архаро-Богучанского, Кангаласского, Багануур (Монголия). Исследованные образцы охарактеризованы техническим и элементным методами анализа. Установлено, что зольность бурых углей составляет величину менее 10%, выход летучих веществ изменяется в пределах от 41% до 48%. Методом петрографического анализа для исследованных углей определен показатель отражения витринита (Ro,r). Установлено, что наименьшим показателем отражения витринита обладает образец бурого угля Итатского месторождения (Ro,r = 0.388%), максимальной величиной характеризуется бурый уголь Кангаласского месторождения (Ro,r = 0.490%). Увеличение генетической зрелости исследованных образцов связано с изменением технологических свойств их органической массы. Показано, что с ростом Ro,r увеличивается содержание углерода (С daf), снижается выход летучих веществ, а также атомное отношение Н/С и О/С. Визуальный анализ аншлифов позволил определить мацеральный состав исследуемых углей. В образце бурого угля Багануурского месторождения (Монголия) выявлено наибольшее содержание инертинита (более 60%), в образце Кангаласского месторождения содержится наибольшее количество мацералов группы витринита (86%).
Vegetation effects on soil moisture estimation from ERS-2 SAR images
Hydrological Sciences Journal, 2012
The aim of this study was to map soil moisture from ERS-2 SAR images by minimizing the effect of ... more The aim of this study was to map soil moisture from ERS-2 SAR images by minimizing the effect of vegetation on the backscatter coefficient. Detailed analysis was carried out to identify the prominent crop descriptor (i.e. crop height, h; leaf area index, LAI; and plant water content, PWC), and to minimize its effect on soil moisture estimation. A semi-empirical water
The information regarding spatial and temporal variation of soil moisture in a catchment is of ut... more The information regarding spatial and temporal variation of soil moisture in a catchment is of utmost importance in hydrological, as well as many other studies. Point measurements from gravimetric and other methods for soil moisture determination are insufficient to understand the spatial behaviour of soil moisture in a region. Microwave remote sensing data from active sensors on board various satellites are increasingly being used to map spatial distribution of soil moisture within the 0-10 cm top surface. The northern part of India has a network of large rivers and canals and, therefore, spatial and temporal distribution of soil moisture in this region has a significant bearing on the hydrology of the region. In this paper, results on estimation of soil moisture from an ERS-2 SAR image in the catchment of the Solani River (a tributary to the River Ganga) in and around the town of Roorkee, India, have been presented. The radar backscatter coefficient for each pixel of the image has been modelled from the digital numbers of the SAR image. Gravimetric measurements have been made simultaneously during the satellite pass to determine the concurrent value of volumetric soil moisture at a large number of sample points within the satellite sweep area. The backscatter coefficient is found to vary from-30 dB to-42 dB for a variation in soil moisture from 30 to 75%. Regression analyses between volumetric soil moisture and both the digital numbers and backscatter coefficients were performed. Strong correlations between volumetric soil moisture and digital number were observed with R 2 values of 0.84, 0.75 and 0.83 for bare soil, vegetative and combined surfaces, respectively. A similar trend was observed with the relationship between backscatter and volumetric soil moisture with R 2 values of 0.60, 0.89 and 0.67 for bare soil, vegetative and combined surfaces, respectively. These results demonstrate the utilization of SAR data for estimation of spatial distribution of soil moisture in the region of the present study.
Journal of Water and Land Development, Dec 1, 2018
Morphometric analysis of any watershed and its prioritization is one of the important aspects of ... more Morphometric analysis of any watershed and its prioritization is one of the important aspects of planning for implementation of management programmes. Present study evaluates the quantitative morphometric characteristics of Nagmati River watershed in Kutch District of Gujarat by utilizing Cartosat-1 data (CartoDEM). In all 19 aerial and 6 linear morphometric parameters of the watershed have been evaluated. Drainage map of the study area reveals a dendritic drainage pattern with sixth order stream network comprising 492 numbers of streams and confining an area of 129.41 km 2. Mean bifurcation ratio (R b) and stream length ratio (R L) of the watershed evaluated are 3.44 and 0.54 respectively which corroborates the fact that drainage pattern is not influenced by the geological evolutions and disturbances in the recent past. The drainage density of 2.68 kmꞏkm-2 indicates impermeable subsoil material with sparse vegetation and moderate to low relief. Elongation ratio of 0.956 infers the basin to be closer to a circular shape. The geologic stage of development and erosion proneness of the watershed is quantified by hypsometric integral (HI) bearing value as 0.5, indicating the landscape to be uniform and in early mature stage. The study prioritizes eight sub-watersheds as high, medium and low for taking up soil and water conservation activities. Hence, remote sensing applications proved to be highly useful in extracting the precise data for the evaluation and analysis of watershed characteristics.
River Yamuna is the largest tributary of river Ganges and has been acclaimed as a heavenly waterw... more River Yamuna is the largest tributary of river Ganges and has been acclaimed as a heavenly waterway in Indian mythology. However, 22-km segment of river Yamuna passing through Delhi from downstream of Wazirabad barrage up to Okhla barrage is considered as the filthiest stretch having been rendered into a sewer drain. The present study employs high-resolution GeoEye-2 imagery for mapping and monitoring pollution levels within the river segment by testing correlation between water quality parameters (WQPs) and the corresponding spectral reflectance values of the image. A total of 100 water samples collected from random sampling locations along the river segment were analyzed for 12 WQPs in the laboratory and grouped into two classes, namely (WQP) organic and (WQP) inorganic. Several spectral band combinations as well as single bands were tested for any significant correlation with the two formulated WQP classes by performing multiple linear regression analysis. Results reveal that spectral band combination, i.e., � (RGB) × √ B∕R � , and the two formulated WQP classes exhibit strong positive correlation with R = 0.92 and 0.91 (R 2 ~ 0.85 and 0.82; RMSE ~ 1.03 and 1.12) for calibration data and 0.85 and 0.84 (i.e., R 2 ~ 0.74 and 0.72; RMSE ~ 1.45 and 1.64) for validation data, respectively. The spatial distribution maps depicting pollution levels of two WQP classes were generated in GIS framework, substantiating to the actual in situ pollution concentration levels in the river segment. The methodology adopted in the present study and results obtained validate the potential of high-resolution GeoEye-2 imagery for monitoring and mapping pollution levels in the water bodies.
Box–Jenkins multiplicative ARIMA modeling for prediction of solar radiation: a case study
International Journal of Energy and Water Resources
This study deals with stochastic modeling of solar radiation in all sky conditions and presents a... more This study deals with stochastic modeling of solar radiation in all sky conditions and presents an effort to predict and analyze the future trends of monthly insolation based on time series analysis. Multiplicative seasonal autoregressive integrated moving average (ARIMA) model, using Box–Jenkins approach, has been utilized for simulating monthly average insolation data retrieved from NASA POWER (Prediction of Worldwide Energy Resource) data over the study area. The satellite dataset for a period of 34 years has been analyzed for modeling monthly average insolation. The insolation data time series examined by differencing and autocorrelation functions clearly indicates the existence of seasonality. Various multiplicative seasonal ARIMA models developed were validated by assessing various estimation parameters and their performance was evaluated by utilizing different selection measure criterion. The ARIMA (1, 0, 1) × (0, 1, 1)12, possessing minimum value of these criteria, was identified as the most adequate model. Forecasting of insolation was performed through selected models at 95% confidence interval. Results also reveal that ARIMA (1, 0, 1) × (0, 1, 2)12 produces minimum mean percentage error (MPE) in the forecast. As the difference in MPE for ARIMA (1, 0, 1) × (0, 1, 1)12 and ARIMA (1, 0, 1) × (0, 1, 2)12 is marginal (i.e., 0.004), the two models present minimal differences in estimated values and are therefore, reckoned as adequate for forecasting solar radiation.
Most of the industrial sewage effluents used for irrigation contains heavy metals which cause tox... more Most of the industrial sewage effluents used for irrigation contains heavy metals which cause toxicity to crop plants as the soils are able to accumulate heavy metal for many years. The vegetables grown for the present study were irrigated with treated wastewater brought from a nearby full-scale sewage treatment plant at different compositions along with tap water as a control. The concentration levels of the Cd, Co, Cu, Mn and Zn in the soil were found to below the toxic limits as prescribed in literature. Daily Intake Metals (DIM) values suggest that the consumption of plants grown in treated wastewater and tap water is nearly free of risks, as the dietary intake limits of Cu, Fe, Zn and Mn. The Enrichment Factor for the treated wastewater irrigated soil was found in order Zn> Ni> Pb> Cr> Cu> Co> Mn> Cd. Thus, treated wastewater can be effectively used for irrigation. This will have twofold significant environmental advantages: (1) helpful to reduce the ground...
Image fusion involves integration of the geometric details of a high-resolution panchromatic (PAN... more Image fusion involves integration of the geometric details of a high-resolution panchromatic (PAN) image and the spectral information of a low resolution multispectral (XS) image which is useful for regional planning and large scale urban mapping. Present study compares the effectiveness of three image fusion techniques namely, Principal Component Analysis (PCA), Wavelet Transform (WT) and Intensity Hue Saturation (IHS) to merge the XS information and PAN data of QuickBird satellite imagery. Comparison between the fused images obtained from the three fusion techniques is carried out on the basis of qualitative and quantitative evaluations implying, visual interpretation, inter-band correlation, correlation coefficient, standard deviation and mean. Results indicate that all three fusion techniques improves spatial resolution as well as spectral details, however, IHS technique provides the best spectral fidelity by preserving the XS integrity between all the bands under consideration.
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