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The morphometric characteristic of the Satluj Lower basin, which contains eight sub-watersheds, was the subject of the research study. Using a Geographic Information System (GIS), the watershed and sub-watershed boundaries, as well as stream network, were retrieved from the Digital Elevation Model (DEM). The study area includes the eight Sub-watersheds. Morphometric aspects have been categorised according to their properties, which include Linear, Areal and Relief aspects. Using Published standard equation, these parameters are assessed. Linear parameter consists of (Stream order, Stream length and bifurcation ratio etc.), Areal parameter consists of (Drainage density, texture ratio, stream frequency and length of the overland flow etc.) and Relief parameter consists of (Relief, Relief ratio, Ruggedness number etc.). There is also other watershed parameter like relative perimeter (Prel), Mean basin width (Wmb), Fitness ratio (Rf), Lemniscate ratio (K), Hypsometric integral (HI), Rho Coefficient, Drainage Intensity (Di), Infiltration number (In) and Melton ruggedness number (MRn) were used to assessment of the soil erosion in the watershed. The drainage density, stream frequency, drainage texture and length of overland flow has major impact on the groundwater recharge potential. The lower values of drainage densities show the permeable subsoil material and have scope for groundwater recharge. The results show that the Lower Satluj basin cover total area about 5969.18 km2 and having total five-stream order. The prioritization of each sub-basin was carried out based on linear, aerial and relief parameters based on their influence on groundwater and surface water runoff. Compound factor value was used to determine each watershed's priority rank. The result of this analysis illustrated that the SW-3 has lowest compound parameter value, so it is subjected to more runoff, hence priority is given to this watershed for the development and management. The decision-making authorities can utilise the findings to plan and carry out watershed management actions towards the better practices to establish new recharge structures to enhance the groundwater recharge potential in this region. [ABSTRACT FROM AUTHOR]

The present study focuses primarily on the rapid mapping of flood-inundated areas using high-resolution Synthetic Aperture Radar (SAR) data and its impact assessment in the Ghaggar basin during the 2019 floods. Further, a comprehensive analysis has been carried out by Global Precipitation Mission (GPM) data to investigate the intensity and frequency of precipitation over the basin. Multi-temporal, dual-polarised (VH & VV) Sentinel-1 (SAR) data have been used for mapping the flood inundated area. SAR data is very useful and most preferred for detecting flood-inundated areas in all weather and day/night time. In this study, binarisation technique was applied to separate satellite image pixel values into flooded and non-flooded groups. Thresholds for backscattering coefficient (σ0) between –22 to –30 and –10 to –20 dB have been applied for both the polarised band (VH & VV) to extract the maximum flood pixels. It was also observed that flood extent was at its peak during July 20–23, 2019, and on July 26–27, 2019, and impacted a large part of agricultural and urban patches during this time. The zonal statistics are calculated to find the inundated area over the study region. The results have been validated against Radarsat-1 images provided by NRSC-ISRO during the flood period and found an accuracy of 82% in both polarisations. VH polarisation has been found to have higher accuracy than VV polarisation. The finding reveals that ~9600 hectares and ~2700 hectares of land have been affected in Patiala and Sangrur districts. The results revealed that paddies were mostly inundated by flooding with low elevations and low slopes. From the proposed approach, it is evident that the SAR images, along with GIS data, can be used efficiently for mapping flood-inundated areas. [ABSTRACT FROM AUTHOR]

The yellow rust of wheat is a critical biotic stress causing the reduction in crop yield in different parts of the world. We hypothesized that identifying yellow rust from Sentinel-2 satellite imagery using a deep learning-based artificial neural network (ANN) classification model would be an efficient monitoring technique of the disease in the parts of Indian Punjab (Jalandhar/Kapurthala and Rupnagar). Six spectral indices (NDVI, NDWI, MCARI, Cl-Red Edge, NDMI, S2REP) were computed from the cloud-free Sentinel-2 data (9 February 2020 for Jalandhar/Kapurthala and 29 January 2020 for Rupnagar), and the random points were generated in disease and healthy wheat growing fields of the area. The pixel values of the spectral indices were extracted using the vector points, and this data was fed to a deep learning ANN classifier. The implementation of these models was performed in Python using Jupyter notebooks and standard python libraries like Keras, NumPy, and Pandas. The ANN model for classifications of yellow rust of wheat was different for both areas due to time differences of Sentinel-2, and the data of one area could not be classified using the trained model of the other area. The accuracy and F1 score were > 0.90 for both areas. These results suggest that Sentinel-2 data can be used to monitor the yellow rust of wheat. [ABSTRACT FROM AUTHOR]

River channel change is a dynamic process which involves erosion, accretion, lateral migration and changes in its width through the geomorphological process. Shifting of a river causes a direct impact on natural and manmade constructions which are located near the floodplain with consistent damage and devastation of the area. The objective of this study is to analyze the spatiotemporal variation along the Satluj river during the period 1990 to 2019 using Landsat TM, ETM+ and OLI satellite data. Spatiotemporal analysis of the river channel has been carried out to analyze the river channel change morphology, mid-line channel shifting and changes in surface water area of the Satluj river using twenty randomly distributed cross-sections (X1-X20). For surface water area change analysis, the satellite derived normalized difference water index (NDWI) has been used. The obtained results indicates that the river width increased by 0.033 km in overall cross-section (X1–X20) in the year 2019 as compared to the year 1990. Mid-line shifting of the river is mostly towards the left bank of the river. The maximum channel shifting of 1.364 km took place from Chak Bandala village in Jalandhar district to Madarpur village in Moga district between the years 1990 and 2019. However, the NDWI results indicate that the river surface area has been reduced by −90.33 km2 between the years 1990 and 2019. Additionally, the average shifting rate of the Satluj river during the period 1990 to 2019 is by 0.778 km. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Geospatial technology based morphometric analysis and watershed prioritization of lower Satluj basin in India for groundwater recharge potential" published in the journal Tropical Ecology. The correction states that there was an error in Figure 4 of the article, which has been rectified. Additionally, a sentence in the Relief aspects section has been deleted, and the corrected version of the article is now available. The authors of the article are Sashikanta Sahoo, Mayur Murlidhar Ramole, Pravin Dahiphale, Shubham Awasthi, and Brijendra Pateriya. [Extracted from the article]

Spatial patterns of land surface temperature (LST), surface urban heat island (SUHI), surface urban cold island (SUCI), and their seasonal variations during January (winter) and September (summer) were analyzed over the three cities of Indian Punjab (Balachaur, Ludhiana and Bathinda) using Landsat 5, 7 and 8 satellite data of the years 1991, 2001, 2011, and 2018. Urban hot spots and Urban Thermal Field Variance Index (UTFVI) were used to measure the ecological environment of these cities. Land surface temperature was retrieved from Landsat satellite data using Plank equation, mono-window algorithm (MWA), single-channel algorithm (SCA), and radiative transfer equation. The LST derived using these algorithms was validated with MODIS-LST product. The relationship between LST derived from Landsat 5, 7 and 8 using the four methods and MODIS-LST product was higher with the SCA algorithm (R2 > 0.75). Land surface temperature was significantly positively correlated with built-up but significantly negatively correlated with vegetation. The surface urban heat intensity was higher during September than January, and it was higher in Ludhiana followed by Bathinda and Balachaur, irrespective of the season. Besides built-up area and population density, soil moisture availability in surrounding rural areas has significant impact on increasing surface urban heat intensity during September than January. The SUCIs were formed in the center of Bathinda city during January 1991, but these were in Ludhiana and Balachaur cities during January 2011. The most critical areas for ecological environment based on UTFVI were identified and the critical UTFVI values (> 0.020) were highest in Bathinda city followed by Balachaur and Ludhiana cities. These results suggest that SUHIs and SUCIs are influenced by seasons and the mitigating plans to counteract the overheating of urban areas should be formulated taking into account soil moisture availability in surrounding rural areas, landscape pattern, seasonal variations, local climatic conditions, urban growth, and development plan etc. [ABSTRACT FROM AUTHOR]

The heavy metal contamination of river sediments by domestic, industrial, and agricultural waste is a major ecological and environmental problem. Therefore, heavy metal concentration and its associated risk were assessed in the sediments from the entry point of Sutlej River in Indian Punjab to its tail end when the river leaves India. The sediment samples (N = 47) were collected from the Sutlej River during April, 2018 and analyzed for heavy metals (As, Cd, Cr, Co, Cu, Fe, Mn, Ni, and Zn). Results showed that the metal concentration in sediments was higher along the transboundary of the river. The average concentration of metals in sediments was in the order: Fe > Mn > Cu > Zn > Cr > Co > Ni > Cd > As. The concentration of Cd in the sediments only exceeded the threshold values of metal concentration. Principle component analysis indicated that geogenic sources are primarily associated with metal concentration in sediments before river's entry point in Punjab. In contrast, agronomic and industrial sources are related to the origin of metals in the river flowing in Indian state of Punjab. The contamination factor and potential ecological risk index results showed that Cd is the primary contaminant in the sediments of the Sutlej River. Spatial distribution maps of risk indices showed the higher risk values along the transboundary of the river in Indian Punjab. These results suggest that strategic management practices and policies across municipal, industrial, and agricultural sectors are required to reduce the metal concentration in the Sutlej River. [ABSTRACT FROM AUTHOR]

The spatial and temporal variations in the hydrochemistry of the Sutlej river in the Indian Punjab were studied based on water quality parameters analysed during pre- and post-monsoon seasons of the years 2017 and 2018. The grab water samples were collected from the river using stratified random sampling and analysed for pH, electrical conductivity (EC), carbonate (CO3−2), bicarbonate (HCO3−), chloride (Cl−), nitrate (NO3−), total hardness, calcium (Ca+2), sodium (Na+) and potassium (K+) using standard methods. Spatio-temporal variations in the parameters used to evaluate the water quality for irrigation (electrical conductivity (EC), residual sodium carbonate (RSC) and sodium absorption ratio (SAR)) were also studied. In order to rate the composite influence of all the physicochemical parameters, water quality index (WQI) was computed. Spatial variations in WQI for drinking and irrigation purposes were studied using the inverse distance weighted method in GIS. Results showed that the river water was alkaline in nature, HCO3− and Cl− are the major anions, and Ca2+ and Na+ are the cations in the river water during both seasons. The regression analysis of EC with cations and anions showed that the regression coefficient was mainly significant with Ca2+ and HCO3−, irrespective of the season. The concentration of ions was not significantly affected by season, but it was higher along transboundary of the river. Total alkalinity of water was significantly (p < 0.05) higher during pre-monsoon than post-monsoon season. The EC, SAR and RSC values during different seasons showed that > 85% of the water samples were in good categories for irrigation purposes. According to grades of WQI for drinking purposes, the poor WQI was observed in 3.6%, 3.7% and 5.9% of the samples during pre-2017, pre-2018 and post-monsoon 2018, respectively. The poor water quality index for irrigation purposes was observed in 16.7% and 4.7% of the samples during pre-monsoon 2017 and 2018, respectively. The water quality index values for drinking and irrigation were higher (poor water quality) along transboundary of the river. The ratio of Ca2+/Mg2+, (Na+ + K+)/TZ+ and Ca2+ + Mg2+/(Na+ + K+) indicated both carbonate and silicate lithology contribute to hydrochemistry of the river besides anthropogenic factors. Non-metric multidimensional scaling showed that all the samples are of a similar origin across the river including transboundary, whereas cluster analysis resulted in the two main groups: pH and Cl in the one group, and EC along with the remaining cations and anions in the other group during pre-monsoon, but pH in the one group, and EC along with the remaining cations and anions in the other group during post-monsoon. The high concentration of Cl− is a signature of anthropogenic inputs in addition to the contribution of natural factors. These results suggest that the cultivation of crops on the soils along transboundary may cause the transfer of ions through the food chain to human beings affecting their health. Moreover, drinking of river water by inhabitants living along transboundary may affect their health. [ABSTRACT FROM AUTHOR]

The water quality of Sutlej river in Indian Punjab is getting deteriorated due to expansion of agricultural, industrial and recreational activities in the region. Many studies have evaluated the water quality of Sutlej river around the stretches of contaminated drains confluence with the river, but there are very few studies in which hydrochemistry of surface water of the river has been studied from the entry point of Sutlej river in Indian Punjab to its tail end when it leaves the country. Surface water samples (n = 97) were collected from the river during May 2019 and analyzed for pH, electrical conductivity, carbonate, bicarbonate, chloride, calcium, magnesium, sodium, potassium, nitrate and sulfate in the laboratory using the standard protocols. Results showed that total alkalinity, total hardness, sodium, potassium, chloride and nitrate were higher along the transboundary of the river. Water samples of the river are mainly Ca–Mg–HCO3 and Ca–Mg–Cl–SO4 types. Spatial distribution of all the parameters showed higher concentration of cations and anions along transboundary of the river. Principal component analysis, Heat map analysis and non-metric multidimensional scaling showed that water quality along the transboundary of the river are having different signature from the other zones of the river due to variations in chloride, sodium, total alkalinity and total hardness in water. Health risk assessment due to nitrate in water also showed that possibility of hazard was higher in the areas along transboundary of the river and children are more prone to health risks followed by women and men. Water quality along transboundary of the river followed by the area from the confluence of contaminated drain with river to transboundary along with localized spots in the river are not suitable for irrigation and drinking purposes. These results suggest that management of anthropogenic pressure, implementation of wastewater management and other strategies are required to improve the water quality of river. [ABSTRACT FROM AUTHOR]

We collected water samples from contaminated Buddha Nullah drain in Ludhiana district of Punjab (India) during pre- and post-monsoon seasons of the year 2017 and 2018. The soil and plant (wheat and rice) samples were also taken from fields cultivated near the water sampling sites. The drain is mainly contaminated by discharge of industrial and urban effluents from the surrounding areas and its confluence with Sutlej River (a tributary of the Indus River). Water samples were analysed for nine metals (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn). Soil, rice and wheat grain samples were analysed for total metals. Besides this, soil samples were also analysed for and DTPA-extractable metals. The concentration of Cr, Pb and Fe in water exceeded the WHO guidelines during all the seasons. Total Zn, Pb, Mn, Ni and Co concentration in soils exceeded the permissible limits, whereas the average concentration of Fe, Pb, Co and Cd in rice and wheat grains exceeded the permissible limits. The bioaccumulation factor (BAF) for DTPA-extractable heavy metals was in the order: Fe > Cr > Co > Zn > Pb > Cd > Mn > Cu > Ni (BAF values > 1 for all the metals). Heavy metal toxicity load values (HMTL) in water samples were lower than the tolerable toxicity load of heavy metals. However, heavy metal pollution index (HPI) was higher than 100 in all the water samples. Based on the grading of geoaccumulation Index (Igeo), total Cd concentration showed extreme contamination around the soils of Buddha Nullah. The cancer risk associated with heavy metals due to intake of wheat and rice grains and ingestion of soils were in the order: Cd > Ni > Cr. Spatial distribution maps of HPI showed the maximum contamination and health risks were around the areas having higher industrial and urban activities These results suggest that heavy metals particularly Cd cause potential health risks to urban residents and environment. The HPI and HTML for water, Igeo for soils and BAF for plants are useful for assessing heavy metal contamination. The controlling measures must be taken to reduce the heavy metal contamination in the drain by checking of the urban and industrial effluents discharged in it and cleaning of the Buddha Nullah drain should be initiated to improve the water quality of Sutlej River. [ABSTRACT FROM AUTHOR]