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Over the last three decades, the Government of India (GOI) has used watershed management as a solution to solve issues concerning sustainable agricultural output in rainfed areas. Additionally, since 2003, the GOI has made watershed management a national policy. A lot of thought is given to all of the significant crops that have disappeared from farming systems in the watershed development programs (WDPs) of India's current development plans, which are primarily focused on increasing and sustaining productivity levels. In the Sarguja division of Chhattisgarh, the present study attempted to document the on-site and off-site effects of these watershed development programs, as it observed an increase in the ground water level, a rise in the surface water and stream flow levels, a reduction in runoff as well as in soil erosion, increased agricultural and dairy production, improved livelihood and employment generation, and changes in the land use and farming patterns. These findings showed that the percentage of cropland increased in both Kharif and Rabi, because they started planting crops in Zaid, particularly cucumber, melon, and vegetables, that had been kept fallow. The patterns of land usage in the WDP regions have improved over time; due to farmers utilizing more wasteland for productive reasons, there has been a rise in the net sown area of these locations. Additionally, it has been claimed that many crops that were previously abandoned due to water shortages and other requirements are now being cultivated. Responses from the region's population have been in favor of the introduction of innovative techniques like Agroforestry systems. [ABSTRACT FROM AUTHOR]

Amid global concerns regarding climate change and urbanization, understanding the interplay between land use/land cover (LULC) changes, the urban heat island (UHI) effect, and land surface temperatures (LST) is paramount. This study provides an in-depth exploration of these relationships in the context of the Kamrup Metropolitan District, Northeast India, over a period of 22 years (2000–2022) and forecasts the potential implications up to 2032. Employing a high-accuracy supervised machine learning algorithm for LULC analysis, significant transformations are revealed, including the considerable growth in urban built-up areas and the corresponding decline in cultivated land. Concurrently, a progressive rise in LST is observed, underlining the escalating UHI effect. This association is further substantiated through correlation studies involving the normalized difference built-up index (NDBI) and the normalized difference vegetation index (NDVI). The study further leverages the cellular automata–artificial neural network (CA-ANN) model to project the potential scenario in 2032, indicating a predicted intensification in LST, especially in regions undergoing rapid urban expansion. The findings underscore the environmental implications of unchecked urban growth, such as rising temperatures and the intensification of UHI effects. Consequently, this research stresses the critical need for sustainable land management and urban planning strategies, as well as proactive measures to mitigate adverse environmental changes. The results serve as a vital resource for policymakers, urban planners, and environmental scientists working towards harmonizing urban growth with environmental sustainability in the face of escalating global climate change. [ABSTRACT FROM AUTHOR]

The main aim of this study is to comprehensively analyze the dynamics of land use and land cover (LULC) changes in the Bathinda region of Punjab, India, encompassing historical, current, and future trends. To forecast future LULC, the Cellular Automaton–Markov Chain (CA) based on artificial neural network (ANN) concepts was used using cartographic variables such as environmental, economic, and cultural. For segmenting LULC, the study used a combination of ML models, such as support vector machine (SVM) and Maximum Likelihood Classifier (MLC). The study is empirical in nature, and it employs quantitative analyses to shed light on LULC variations through time. The result indicates that the barren land is expected to shrink from 55.2 km2 in 1990 to 5.6 km2 in 2050, signifying better land management or increasing human activity. Vegetative expanses, on the other hand, are expected to rise from 81.3 km2 in 1990 to 205.6 km2 in 2050, reflecting a balance between urbanization and ecological conservation. Agricultural fields are expected to increase from 2597.4 km2 in 1990 to 2859.6 km2 in 2020 before stabilizing at 2898.4 km2 in 2050. Water landscapes are expected to shrink from 13.4 km2 in 1990 to 5.6 km2 in 2050, providing possible issues for water resources. Wetland regions are expected to decrease, thus complicating irrigation and groundwater reservoir sustainability. These findings are confirmed by strong statistical indices, with this study's high kappa coefficients of Kno (0.97), Kstandard (0.95), and Klocation (0.97) indicating a reasonable level of accuracy in CA prediction. From the result of the F1 score, a significant issue was found in MLC for segmenting vegetation, and the issue was resolved in SVM classification. The findings of this study can be used to inform land use policy and plans for sustainable development in the region and beyond. [ABSTRACT FROM AUTHOR]

Land Use/Land Cover (LULC) changes have a significant impact on Land Surface Temperature (LST). The LST is an important parameter in various environmental and climatological studies, as it plays a crucial role in understanding the Earth's surface–atmosphere interactions. The LULC changes can modify the surface energy balance and alter the radiation budget, leading to changes in LST. Urbanization, deforestation, and agricultural land use changes are some of the primary drivers of LULC change that have a significant impact on LST. Deforestation and agricultural land use changes result in a reduction in evapotranspiration, leading to an increase in LST. The main objective of the study is to analyze the spatio-temporal change in Land Use/Land Cover (LULC) and its effect on Land Surface Temperature (LST), as well as to establish a correlation of LST with the Normalized Difference Vegetation Index (NDVI) and Normalize Difference Snow Index (NDSI). Understanding the impact of LULC on LST is essential for developing effective land use policies that can mitigate the adverse effects of LULC change on the environment and human health. [ABSTRACT FROM AUTHOR]

Soil carbon sequestration is vital to reduce the atmospheric carbon concentration, which is expected to increase within future climatic scenarios. The present study aims to investigate the effects of land use changes to different plantation systems on SOC stocks, and simulate these changes using the RothC model in Mizoram, India. With this aim, four land uses, viz., secondary forest, oil palm, orange, and arecanut plantations, established on degraded shifting cultivation lands, and a control natural forest were selected for this study. The soils were sampled 0–30 cm in the secondary forest, plantations, and the natural forest, at an interval of five years. Measured SOC stocks were the highest in the secondary forest (67.0 Mg C ha−1) and the lowest under the oil palm plantation (37.4 Mg C ha−1), 10 years after land use conversion. The climate change projections for 2021–2035 and 2036–2050 indicated that temperature and rainfall changes, projected to increase by 0.8 and 2.0 °C, and 5.9 and 5.4%, respectively, will affect SOC stocks in the future differently, depending on the land use and carbon input from vegetation. Baseline climate simulations under land use change showed the highest increase in the SOC stock under the secondary forest (116%), and the lowest in the oil palm plantation (27%). Overall, the model predicted that SOC stocks would increase, but the rate of change (0.23–1.86 Mg C ha−1 yr−1) varied with different land uses, plant species, and land management practices. The model results indicated that restoring secondary forest following the abandonment of a shifting cultivation and orange plantations are the best options to improve SOC stocks within future climate change scenarios. Conversely, arecanut and oil palm need to be reduced because the SOC storage is lower. [ABSTRACT FROM AUTHOR]

Understanding the likely impacts of climate change (CC) and Land Use Land Cover (LULC) on water resources (WR) is critical for a water basin's mitigation. The present study intends to quantify the impact of (CC) and (LULC) on the streamflow (SF) of the Parvara Mula Basin (PMB) using SWAT. The SWAT model was calibrated and validated using the SWAT Calibration Uncertainty Program (SWAT-CUP) for the two time periods (2003–2007 and 2013–2016) and (2008–2010 and 2017–2018), respectively. To evaluate the model's performance, statistical matrices such as R2, NSE, PBIAS, and RSR were computed for both the calibrated and validated periods. For both these periods, the calibrated and validated results of the model were found to be very good. In this study, three bias-corrected CMIP6 GCMs (ACCESS-CM2, BCC-CSM2-MR, and CanESM5) under three scenarios (ssp245, ssp370, and ssp585) have been adopted by assuming no change in the existing LULC (2018). The results obtained from the SWAT simulation at the end of the century show that there will be an increase in streamflow (SF) by 44.75% to 53.72%, 45.80% to 77.31%, and 48.51% to 83.12% according to ACCESS-CM2, BCC-CSM2-MR, and CanESM5, respectively. A mean ensemble model was created to determine the net change in streamflow under different scenarios for different future time projections. The results obtained from the mean ensembled model also reveal an increase in the SF for the near future (2020–2040), mid future (2041–2070), and far future (2071–2100) to be 64.19%, 47.33%, and 70.59%, respectively. Finally, based on the obtained results, it was concluded that the CanESM5 model produces better results than the ACCESS-CM2 and BCC-CSM2-MR models. As a result, the streamflow evaluated with this model can be used for the PMB's future water management strategies. Thus, this study's findings may be helpful in developing water management strategies and preventing the pessimistic effect of CC in the PMB. [ABSTRACT FROM AUTHOR]

The alteration of land use and land cover caused by human activities on a global scale has had a notable impact on ecosystem services at regional and global levels, which are crucial for the survival and welfare of human beings. Merbil, a small freshwater wetland located in the Brahmaputra basin in Assam, India, is not exempt from this phenomenon. In the present study, we have estimated and shown a spatio-temporal variation of ecosystem service values in response to land use and land cover alteration for the years 1990, 2000, 2010, and 2021, and predicted the same for 2030 and 2040. Supervised classification and the CA-Markov model were used in this study for land-use and land-cover classification and future projection, respectively. The result showed a significant increase in built-up areas, agricultural land, and aquatic plants and a decrease in open water and vegetation during 1990–2040. The study area experienced a substantial rise in ecosystem service values during the observed period (1990–2021) due to the rapid expansion of built-up areas and agricultural and aquatic land. Although the rise of built-up and agricultural land is economically profitable and has increased the study site's overall ecosystem service values, decreasing the area under open water and vegetation cover may have led to an ecological imbalance in the study site. Hence, we suggest that protecting the natural ecosystem should be a priority in future land-use planning. The study will aid in developing natural resource sustainability management plans and provide useful guidelines for preserving the local ecological balance in small wetlands over the short to medium term. [ABSTRACT FROM AUTHOR]

Ravine and gully formations are both spectacular and also the worst forms of water-induced soil erosion and have in situ and ex situ impact on geomorphology, hydrology, productivity and environmental security, and they are the root causes of degradation of marginal and adjacent land along with reduced production potential. A long-term (2011–2019) study was conducted on marginal land of the Chambal ravine to assess the impact of six land uses, i.e., Agriculture (T1—Rainfed Soybean), Agri-horticulture (T2—Soybean + Manilkara achras), Horti-Pastoral (T3—Emblica officinalis + Cenchurus ciliaris), Pasture (T4—C. ciliaris), Silviculture (T5—Acacia nilotica) and Silvi-pasture (T6—A. nilotica + C. Ciliaris) on soil properties, runoff interception, sediment trapping and soil loss reduction. The lowest average annual soil loss (4.83 ton ha−1 year−1) and runoff (109.52 mm) were recorded under T4, while the highest sediment loss (8.09 ton ha−1 year−1) and runoff (136.07 mm), respectively, were under T5. The runoff coefficient of land uses was in the order of T3 (20.30%) < T4 (20.56%) < T1 (21.95%) < T2 (22.26%) < T6 (22.83%) < T5 (25.54%). The C. ciliaris improved bulk density and recorded lowest in horti-pasture (1.63 ± 0.04 g cm−3) followed by pasture (1.66 ± 0.03 g cm−3) land use system. The active SOC content in pasture, horti-pasture and silvi-pasture was 0.95, 0.87 and 0.64 times higher, respectively, than agriculture land use. Under pure C. ciliaris cover, resistance to penetration varied from 0.68 to 1.97 MPa, while in silviculture land use, it ranges from 1.19 to 2.90 Mpa. Grass cover had substantial impact on soil loss and runoff reduction, SOC content, soil aggregation and resistance to penetration. In degraded ecosystems, Cenchrus ciliaris can be used alone and in combination with plants for protection of natural resources from water-induced soil erosion, runoff conservation, soil quality improvement and maximization of precipitation water use. [ABSTRACT FROM AUTHOR]

Rivers are crucial components of human civilization, as they provide water for domestic, agricultural, and industrial use. Additionally, they transport domestic and industrial waste to the sea. The Ganga River is a major river in India, originating from Gangotri in the north, flowing through five provinces, and discharging into the Bay of Bengal. This study examined the impact of land use and land cover changes (LULC) on water quality along the River Hooghly in India. The research involved collecting water samples from different locations and analyzing them in the laboratory to estimate various parameters. The findings indicate that the expansion of built-up and agricultural lands is causing a reduction in tree cover and water bodies, leading to deteriorating water quality. The study highlights the need for sustainable land use practices and improved water management to preserve the river's ecosystem and maintain water quality. Specifically, the study identified localities in the vicinity of Dakshineshwar, Shibpur, and Garden Reach as particularly vulnerable to water quality deterioration due to LULC changes and population growth. The study's results provide valuable insights for policymakers and stakeholders in implementing strategies to address the challenges posed by land use changes and population growth. [ABSTRACT FROM AUTHOR]

One of the most valuable approaches in spatial analysis for a better understanding of the hydrological response of a region or a watershed is certainly the analysis of the well-known land use land cover (LULC) dynamicity. The present case study delves deeper into the analysis of LULC dynamicity by using digital Landsat TM and Landsat OLI data to classify the Kolkata Metropolitan Development Authority (KMDA) into seven classes with over 90% classification accuracy for decadal level assessments of 30 years (for the years 1989, 1999, 2009, and 2019). The change index, the Dematel method for analyzing the cause-effect relationship among the LULC classes, the Jaccard Similarity Index for measuring the nature of similarity among the LULC classes, and the Adherence Index for measuring the consistency of the LULC classes after the transition was used in this study to analyze the LULC transformation. In more detail, the present study considers how urban land use is altering at the expense of other land uses. Besides the shifting pattern of mean centers of the LULC classes through time, also gives a very significant insight into the LULC dynamics over 30 years of span. The current study of LULC dynamicity and transformation patterns over the 30 years of the KMDA area is expected to assist land and urban planners, engineers, and administrators in sustainable decisions and policies to ensure inclusive urbanization that accommodates population growth while minimizing the impact on potential natural resources within the whole study area. [ABSTRACT FROM AUTHOR]

It is widely known that land use/land cover (LULC) changes significantly alter watershed hydrology and sediment yields. The impact, especially on erosion and sedimentation, is likely to be exacerbated in regions dominated by high rainfall patterns such as monsoons. This study analyzed the hydrological responses of LULC changes in terms of streamflow (SF) and sediment yield (SY) in a monsoon-dominated tropical watershed, the Periyar River Watershed (PRW) in Kerala, India. This watershed drains an area of 4793 km2 characterized by an average monsoon rainfall of 2900 mm from June to November. The watershed hydrology and sediment dynamics were simulated using the Soil and Water Assessment Tool (SWAT) model for the impact assessment at the watershed outlet and the sub-watershed level. Historical LULC data were analyzed for 1988, 1992, 2002, and 2016 using the maximum likelihood method, and future LULC changes were projected for 2030, 2050, 2075, and 2100 using the Markov chain–cellular automata technique. Between 1988 and 2016, the urban area increased by 4.13 percent, while plantation and forest coverage decreased by 1.5 percent. At this rate, by 2100, the urban area is expected to grow by 16.45% while plantations and forest area will shrink by 13.7% compared to 1988. The effects of these changes on SF and SY were found to be minimal at the watershed outlet; however, at the spatial scale of sub-watersheds, the changes varied up to 70% for surface runoff and 200% for SY. These findings highlight the potential impacts of LULC changes in a monsoon-dominated watershed and may contribute to the development of successful LULC-based watershed management strategies for prevention of flooding and sediment loss. [ABSTRACT FROM AUTHOR]

Land use and land cover change (LULCC) is among the most apparent natural landscape processes impacted by anthropogenic activities, particularly in fast-growing regions. In India, at present, due to the impacts of anthropogenic climate change, supplemented by the fast pace of developmental activities, the areas providing the highest agricultural yields are facing the threat of either extinction or change in land use. This study assesses the LULCC in the fastest-changing landscape region of the Indian state of Bihar, District Muzaffarpur. This district is known for its litchi cultivation, which, over the last few years, has been observed to be increasing in acreage at the behest of a decrease in natural vegetation. In this study, we aim to assess the past, present and future changes in LULC of the Muzaffarpur district using support vector classification and CA-ANN (cellular automata-artificial neural network) algorithms. For assessing the present and past LULC of the study area, we used Landsat Satellite data for 1990, 2000, 2010, and 2020. It was observed that between 1990 and 2020, the area under vegetation, wetlands, water body, and fallow land decreased by 44.28%, 34.82%, 25.56%, and 5.63%, respectively. At the same time, the area under built-up, litchi plantation, and cropland increased by 1451.30%, 181.91%, and 5.66%, respectively. Extensive ground truthing was carried out to assess the accuracy of the LULC for 2020, whereas historical google earth images were used for 1990, 2000, and 2010, through the use of overall accuracy and kappa coefficient indices. The kappa coefficients for the final LULC for the years 1990, 2000, 2010, and 2020 were 0.79, 0.75, 0.87, and 0.85, respectively. For forecasting the future LULC, first, the LULC of 1990 and 2010 were used to predict the landscape for 2020 using the CA-ANN model. After calibrating and validating the CA-ANN outputs, LULC for 2030 and 2050 were generated. The generated future LULC scenarios were validated using kappa index statistics by comparing the forecast outcomes with the original LULC data for 2020. It was observed that in both 2030 and 2050, built-up and vegetation would be the major transitioning LULC. In 2030 and 2050, built-up will increase by 13.15% and 108.69%, respectively, compared to its area in 2020; whereas vegetation is expected to decrease by 14.30% in 2030 and 32.84% in 2050 compared to its area in 2020. Overall, this study depicted a decline in the natural landscape and a sudden increase in the built-up and cash-crop area. If such trends continue, the future scenario of LULC will also demonstrate the same pattern. This study will help formulate better land use management policy in the study area, and the overall state of Bihar, which is considered to be the poorest state of India and the most vulnerable to natural calamities. It also demonstrates the ability of the CA-ANN model to forecast future events and comprehend spatiotemporal LULC dynamics. [ABSTRACT FROM AUTHOR]

The emerging water crisis in India can be preempted by improving watershed management. The data scare regions need open access satellite observations to mitigate watershed problems. The water accounting plus (WA+) and open access earth observation datasets were applied to quantify the beneficial and non-beneficial water consumption in the Betwa River basin, Central India. The PERSIANN and CHIRPS precipitations were evaluated. Based on significant statistical relations with IMD rainfall, CHIRPS was found to be the best precipitation product. The seasonal water yield from PERSIANN depicts that the high water yield in the basin is associated with the July and August months of the monsoon season, with water yields of 240 mm/month and 120 mm/month, respectively, while CHIRPS showed higher water yields during the monsoon season, especially in July and August, with water yield amounts of 290 mm/month and 200 mm/month, respectively. The largest water consuming land use class is irrigated crops–cereals, which cover 62.06% of the total area of the basin. The amount of non-beneficial ET is almost twice the beneficial ET. The outcomes of this research will be helpful for sustainable water management, strategy development, and policy making. [ABSTRACT FROM AUTHOR]

Rivers are vital freshwater resources that cater to the needs of society. The burgeoning population and the consequent land-use changes have altered the hydrologic regime with biophysical and chemical integrity changes. This necessitates understanding the land-use dynamics, flow dynamics, hydrologic regime, and water quality of riverine ecosystems. An assessment of the land-use dynamics in the Aghanashini River basin reveals a decline in vegetation cover from 86.06% (1973) to 50.78% (2018). The computation of eco-hydrological indices (EHI) highlights that the sub-watersheds with native vegetation had higher infiltration (and storage) than water loss due to evapotranspiration and meeting the societal demand. The computation of water quality index helped to assess the overall water quality across seasons. The study provides insights into hydrology linkages with the catchment landscape dynamics to the hydrologists and land-use managers. These insights would aid in the prudent management of river basins to address water stress issues through watershed treatment involving afforestation with native species, appropriate cropping, and soil conservation measures. [ABSTRACT FROM AUTHOR]

Land use/land cover (LULC) and climate are two crucial environmental factors that impact watershed hydrology worldwide. The current study seeks to comprehend how the evolving climate and LULC patterns are impacting the hydrology of the Mahanadi Reservoir catchment. A semi-distributed Soil and Water Assessment Tool (SWAT) model was utilized to simulate various water balance elements. Twelve distinct scenarios were developed by combining three different climatic data periods (1985–1996, 1997–2008, and 2009–2020) with four sets of land use maps (1985, 1995, 2005, and 2014). The SWAT model demonstrated strong performance in simulating monthly stream flows throughout the calibration and validation phases. The study reveals that changes in LULC have a distinct effect on the environment. Specifically, the changes in LULC lead to heightened streamflow and reduced evapotranspiration (ET). These changes are mainly attributed to amplified urbanization and the diminished presence of water bodies, forest cover, and barren land within the Mahanadi Reservoir catchment. The combined impact of climate change and LULC shifts reveals complex interactions. Therefore, the present study offers an understanding of how changes in climate and land use over the past few decades have influenced the hydrological behavior of the Mahanadi Reservoir catchment in Chhattisgarh. The findings of this study have the potential to offer advantages to governmental bodies, policymakers, water resource engineers, and planners seeking effective strategies for water resource management. These strategies would be particularly relevant in the context of climate change and land use/land cover changes in ecological regions similar to those of the Mahanadi Reservoir catchment. In addition, a rational regulatory framework for land use patterns is essential for assisting stakeholders in managing water resources and appropriately developing the entire catchment. [ABSTRACT FROM AUTHOR]

This study performed a land use and land cover (LULC) change analysis over Southern India for the period 1981–2006 from the normalized difference vegetation index (NDVI) images of AVHRR data and applied the "observation minus reanalysis" (OMR) method to investigate the impact of the LULC change on the temperature of the region. The LULC change analysis indicated that the areas under agriculture/fallow land were significantly increased while the areas under shrubs/small vegetation were decreased during the period 1981–2006. The areas under forest cover and barren land were also decreased but relatively low compared to the other LULC types. The OMR results showed that the LULC changes over urban areas contributed to warming with a temperature of 0.02 °C during this period, while that over non-urban areas showed a cooling effect with a temperature reduction of 0.29 °C and that over the whole Southern India (looked at an average) indicated a cooling effect with a temperature reduction of 0.063 °C. The comparative analysis between the two (LULC change analysis and OMR) results showed that the cooling over Southern India was mostly due to the expansion of agriculture/fallow land and the decline of shrubs/small vegetation. The study suggests that the OMR method reasonably demonstrates the effect of LULC changes on the temperature over Southern India. [ABSTRACT FROM AUTHOR]

The mass accumulation of population in the larger cities of India has led to accelerated and unprecedented peripheral urban expansion over the last few decades. This rapid peripheral growth is characterized by an uncontrolled, low density, fragmented and haphazard patchwork of development popularly known as urban sprawl. The Kolkata Metropolitan Area (KMA) has been one of the fastest-growing metropolitan areas in India and is experiencing rampant suburbanization and peripheral expansion. Hence, understanding urban growth and its dynamics in these rapidly changing environments is critical for city planners and resource managers. Furthermore, understanding urban expansion and urban growth patterns are essential for achieving inclusive and sustainable urbanization as defined by the United Nations in the Sustainable Development Goals (e.g., SDGs, 11.3). The present research attempts to quantify and model the urban growth dynamics of large and diverse metropolitan areas with a distinct methodology considering the case of KMA. In the study, land use and land cover (LULC) maps of KMA were prepared for three different years (i.e., for 1996, 2006, and 2016) through the classification of Landsat imagery using a support vector machine (SVM) classification approach. Then, change detection analysis, landscape metrics, a concentric zone approach, and Shannon's entropy approach were applied for spatiotemporal assessment and quantification of urban growth in KMA. The achieved classification accuracies were found to be 89.75%, 92.00%, and 92.75%, with corresponding Kappa values of 0.879, 0.904, and 0.912 for 1996, 2006, and 2016, respectively. It is concluded that KMA has been experiencing typical urban sprawl. The peri-urban areas (i.e., KMA-rural) are growing rapidly, and are characterized by leapfrogging and fragmented built-up area development, compared to the central KMA (i.e., KMA-urban), which has become more compact in recent years. [ABSTRACT FROM AUTHOR]