Climatic shifts and vegetation response in Western India: a four-decade retrospective through GIS and multi-variable analysis

Abstract

Climate change is having a profound impact on Western India, manifesting in altered weather patterns and ecological shifts. This research paper delves into an extensive analysis of meteorological data spanning the years 1981 to 2018, covering nearly four decades of climatic variations. Utilizing data from 40 meteorological stations across the region, examined changes in key climate variables including precipitation, humidity, wind speed, pressure, and temperature. We used Geographic Information Systems (GIS) to analyze spatial patterns of climate and forest cover changes. This approach visualized and quantified the climate changes over the studied period effectively. The results showed an average temperature increase of 0.66°C and a decrease in precipitation by 25.36 mm, indicating a trend towards warmer and drier conditions. The spatial analysis provided a clearer understanding of how these changes are distributed across Western India, linking them directly to shifts in forest ecosystems as evidenced by changes in the Normalized Difference Vegetation Index (NDVI) for the corresponding months and years. The findings from this research are critical for policymakers, as they offer valuable insights that can inform strategies for environmental conservation and restoration, ensuring sustainable management of the region's natural resources in the face of ongoing global warming.

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Introduction

The intricate dance between human activities and natural ecosystems underlies the profound changes we observe in the world today [1–3]. As human influence extends its reach, the landscapes, water bodies, and atmospheres of regions like Western India are significantly transformed [4–8]. This paper focuses on Western India, examining how land use and vegetation dynamics, driven by human interventions, have altered climate variability over the last four decades. Similar to other regions globally that are experiencing shifts in climate patterns, Western India faces significant challenges, including increasing temperatures and altered precipitation cycles, which mirror trends observed in parts of Africa, Southeast Asia, and South America.

Human activities such as mining, deforestation, urban development, and agriculture have reshaped the physical and biological systems of the earth, leading to noticeable changes in the biosphere, hydrosphere, lithosphere, and atmosphere [9–14]. These modifications have not only altered landforms but have also impacted the ecological dynamics and climate of various regions. The introduction of non-native species, the removal of natural vegetation, and the extensive use of agricultural machinery are prime examples of human interventions that have disrupted natural processes [15–18].

Vegetation plays a critical role in regulating environmental processes, including erosion control and climate modulation [19–21]. Plants protect the soil by absorbing rainfall and reducing surface runoff, thereby maintaining soil structure and fertility [22, 23]. However, the reduction or removal of vegetation cover due to human activities such as overgrazing and deforestation increases soil erosion, alters albedo, and impacts local and regional climates. Changes in albedo, for instance, influence the earth’s temperature and, subsequently, the patterns of weather and climate [24, 25]. Forests are pivotal in maintaining ecological balance, providing ecosystem services such as carbon sequestration, habitat provision, water regulation, and soil conservation. The disruption of these services due to climate change poses significant threats to biodiversity and human livelihoods [26, 27]. In Western India, changes in forest cover and land use have direct implications for the regional climate, influencing monsoon patterns and the overall hydrological cycle [28, 29].

The primary objectives of this study are: (i) to quantify the changes in key climate variables—precipitation, humidity, wind speed, pressure, and temperature—over the period from 1981 to 2018 in Western India, and (ii) to assess the impact of these climatic shifts on vegetation dynamics, using the Normalized Difference Vegetation Index (NDVI) as a measure of vegetation health. This study employs a novel integration of long-term meteorological data with Geographic Information Systems (GIS) to provide a comprehensive spatial and temporal analysis, offering critical insights into the region’s evolving climate and ecological patterns. This unique combination allows for an unprecedented visualization and understanding of how changes in land use and vegetation cover directly impact regional climate patterns. By correlating these changes with precise climatic shifts, the study provides actionable insights that can significantly improve local environmental management and policy-making strategies. This approach enhances the granularity and relevance of climate impact assessments, enabling more targeted and effective interventions for sustainability and conservation efforts in the region.

This research leverages Geographic Information Systems (GIS) to analyze spatio-temporal changes in land use and vegetation over a period stretching from 1981 to 2020. By examining meteorological data across this timeframe, including parameters like precipitation, humidity, wind speed, pressure, and temperature, we gain insights into the climatic shifts that have occurred in response to alterations in land use and vegetation cover. The analysis reveals that the last four decades have seen significant climate variability in Western India. This period has been marked by increasing temperatures and changing precipitation patterns, which have influenced the phenology and distribution of plant species. These climatic changes are not isolated phenomena but are part of a global trend of rising temperatures and shifting climatic zones, which have been particularly pronounced since the mid-20th century.

This research is particularly relevant for policymakers and environmental managers as it provides a comprehensive analysis of how land use changes influence climate variability. Understanding these dynamics is crucial for developing strategies to manage land sustainably and mitigate the adverse effects of climate change. By integrating land use data with climatic variables, this study not only highlights the impacts of human activity on climate variability but also underscores the need for integrated approaches to land and environmental management in the face of global climate challenges.

The interaction between human activities and natural systems is complex and consequential, necessitating detailed study and thoughtful intervention. Our findings underscore the importance of maintaining healthy forest ecosystems and managing land use effectively to mitigate the impacts of climate change. This study contributes to a growing body of knowledge that can inform sustainable development strategies and help ensure the resilience of ecosystems and human communities alike in Western India and beyond.

Study area

Western India is a region of remarkable geographical and cultural diversity, encompassing three large states—Maharashtra, Gujarat, Rajasthan—one smaller state, Goa, and two union territories, Dadra and Nagar Haveli and Daman and Diu [30–32]. This area is bordered by Pakistan's ancient Indus Valley plains to the west and India's expansive Gangetic plains to the east, with the Arabian Sea also lining its western edge (Fig. 1). The states of Maharashtra and Gujarat stand out as two of India's most industrialized regions, while Rajasthan and Goa attract tourists from around the world due to their rich history and stunning landscapes. Maharashtra is notable for its major urban centers, Mumbai and Pune, which are economic powerhouses and cultural hubs. Gujarat, a vital trading center, is renowned for its traditional textiles and vibrant markets. Rajasthan, known as the land of warriors and colorful dresses, is dotted with historic forts and Rajput temples that narrate tales of its storied past [33]. This region is critical for examining climate variability and vegetation response due to its diverse climatic zones, significant economic activities, and unique ecological characteristics, which make it highly sensitive to climatic shifts and a valuable case for understanding broader patterns of environmental change.

Geographically, the semi-arid zones of Saurashtra and Kutch constitute a significant part of Western India, transitioning into the humid southern regions south of Khambhat in Gujarat. Along the coast, the Western Ghats run through South Gujarat, Maharashtra, and Goa, creating a rich tapestry of rainforests that contrast sharply with the northern arid regions of Gujarat. The diverse ecology is supported by an extensive network of rivers including the Mahi, Narmada, Tapi, Godavari, Zuari, and Mandovi, along with their tributaries, which play a crucial role in the region's agriculture and biodiversity [34].

The climate of Western India varies considerably from tropical humid in the coastal areas to dry and semi-arid in the inland regions [35, 36]. Seasonal variations are somewhat moderated by the sea, with coastal temperatures ranging from 20°C to 38°C. The interior cities experience hot summers where temperatures can reach up to 40°C, and mild winters with temperatures occasionally dropping to around 7°C. Gujarat experiences similarly hot summers and cooler winters, reflecting the overall climatic pattern of the region. Overall, Western India is a vibrant and dynamic region characterized by its diverse ecosystems, cultural richness, and significant economic activities. It is a region where ancient traditions merge with modernity, and natural beauty coexists with urban development, making it a pivotal area in the socio-economic landscape of India.

Data and methods used

Data used

The data used in this study encompass various datasets essential for analyzing land use, vegetation cover, and climate variables over the designated periods (Table 1). Land Use and Land Cover (LULC) data for the years 1985 and 2020 were obtained from the ORNL DAAC for Biogeochemical Dynamics and Esri 2020 Land Cover Downloader [37], respectively, with spatial resolutions of 80 m for 1985 and 10 m for 2020. The LULC classification is summarized in Table 2. Additionally, NDVI maps were sourced from the USGS EROS Archive—AVHRR NDVI Composites, which provide essential information on vegetation density and health. The Digital Elevation Model (DEM) data, crucial for terrain mapping, was acquired from ASTER with a resolution of 30 m. Climate data, which include precipitation, temperature, humidity, pressure, and wind speed for the period from 1981 to 2018, were sourced from WorldClim for historical monthly weather data and Iowa State University's Iowa Environmental Mesonet. These datasets were used to create a comprehensive profile of the study area, categorizing the land into eight distinct classes: Water, Dense Forest, Grassland, Wetlands, Crops, Shrubland, Built-up Area, and Barren Land.

Methods

The methodology used in this result is summarized in Fig. 2. Geographic Information Systems (GIS) played a crucial role in both the preparation of climate maps and the analysis of the vegetation-climate relationship. This versatile environment greatly facilitates the integration of data and analysis, providing a robust toolkit for exploring potential impacts under various climate change scenarios. The methods involved rectifying raster data to match the Area of Interest, rearranging and correcting meteorological data to suit the study's requirements. The use of Random Point Generation and interpolation methods was pivotal for mapping climate data [38–40]. Random Point Generation is a statistical method used to create a random sample of points within a specified area. This technique helps in spatial analysis by ensuring unbiased representation of data across the study region. The statistical analysis was further supported by the Raster Calculator and Random Point techniques in GIS, which helped in calculating regression coefficients using NDVI values as independent variables to predict climate variables. Additionally, Digital Elevation Model data was employed for detailed terrain mapping and watershed analysis using the hydrological tools available in ArcGIS software [41, 42]. Maps were also generated for other climate parameters including relative humidity, precipitation, average temperature, wind speed, and pressure, providing a multifaceted view of the climatic influences on the regional ecosystem.

Results and discussion

Land use and land cover change

The analysis of the Land Use and Land Cover (LULC) from 1985 to 2020, based on the classified maps (Fig. 3a and b), reveals substantial changes in the landscape of Western India. The visual comparison of these maps indicates a marked transformation in various land cover classes, most notably in the extent of green cover, bare lands, urban areas, and grasslands. From the data presented (Table 3), it is evident that water bodies have diminished by about 4.5%, a change that could be attributed to varying factors, including increased land use for agriculture and urban development. The dense forest cover shows a worrying decline of 61.37%, highlighting the vulnerability of forests to land conversion for agricultural or developmental purposes. Grasslands have suffered the most significant loss, with an 86.39% reduction, suggesting that these areas may have been repurposed for agricultural expansion or urbanization. The extent of barren land has also decreased by 93.76%, indicating a possible increase in land cultivation and infrastructure development.

Conversely, the areas classified as shrubland have increased by a striking 255.51% in 2020. This growth could be interpreted as a transition from other land cover types, possibly due to changes in agricultural practices or as a natural succession stage in previously disturbed areas. Crop cover has increased by 15.55%, which aligns with the global trend of intensifying agriculture to meet the food demands of a growing population.

The wetland areas have seen an astonishing increase of 1237.64%, and built-up areas have grown by 890.50%, as illustrated in Fig. 5a and b. These dramatic changes can be linked to the significant urban expansion and infrastructural development that Western India has experienced over the past 35 years [43, 44]. The increase in wetland areas could also be partly due to the conservation efforts and recognition of their ecological importance, leading to better preservation and possibly restoration activities.

The data portrayed in Fig. 4, representing the LULC area in square kilometers, further corroborates these findings, providing a quantifiable perspective on the land cover transitions. The pie charts in Fig. 5a and b reveal the proportional changes in land cover types, where the shrinkage of dense forest and grassland areas is starkly visible when comparing the two time points. The shift towards more shrublands and built-up areas signifies a landscape experiencing rapid changes, driven by human activity and possibly climate change.

These findings indicate that Western India's landscape has undergone significant anthropogenic transformation, with repercussions for biodiversity, water resources, and regional climate patterns. The increase in built-up areas not only represents urban expansion but also brings into focus the challenges related to sustainable development, including the need for green spaces and the management of water resources. This change in land cover, coupled with the decline in natural vegetation like dense forests and grasslands, can have profound impacts on the local climate, water cycles, and biodiversity, necessitating urgent attention from policymakers and conservationists to devise strategies that balance development with ecological preservation.

Normalized difference vegetation index (NDVI) analysis

The Normalized Difference Vegetation Index (NDVI) serves as a pivotal tool in the remote sensing analysis of vegetative health, with its values ranging from −1 to +1, encapsulating a spectrum of conditions from the absence of green vegetation to dense green canopies.

Pre-monsoon NDVI analysis

The analysis of pre-monsoon NDVI reveals a notable increase in the maximum values of vegetation health from 0.60 in 1981 to 0.79 in 2018, as indicated by the darker green shades on the map for 2018 (Fig. 6b). This enhancement suggests an improvement in the density and health of vegetation over the 37-year period. Conversely, the minimum NDVI values have seen a slight decrease from 0.12 in 1981 to 0.10 in 2018, represented by the darker pink shades, indicating areas with less or no vegetation cover (Fig. 6a). This reduction in minimum values could imply either a loss of vegetative cover in certain areas or a shift in vegetation types to those with lower NDVI readings. The statistical graph (Fig. 6a1 and b1) corroborates these observations, showing a broader range of NDVI values in 2018 than in 1981, which could reflect greater variability in vegetation health across the landscape.

Post-monsoon NDVI analysis

Post-monsoon data, on the other hand, indicate an overall improvement in vegetation health, with maximum NDVI values rising from 0.62 in 1981 to 0.80 in 2018 (Table 4 and Fig. 6c1 and d1). This increment highlights a positive shift towards more robust and healthier vegetation after the monsoon season. Additionally, the minimum NDVI values increased from 0.16 in 1981 to 0.25 in 2018, suggesting fewer areas with poor or non-existent vegetation and a general amelioration in vegetative cover (Fig. 6c and d). Interestingly, the standard deviation values for both pre- and post-monsoon periods have risen from 1981 to 2018 (Table 4), indicating an increase in heterogeneity of the vegetation. This could be due to factors like agricultural intensification, reforestation efforts, or natural regrowth in previously barren areas.

The NDVI statistics and accompanying maps provide a multifaceted view of vegetation dynamics, reflecting not only ecological transitions but also the impact of human land use. The overall trend towards higher NDVI values post-monsoon is encouraging and may be linked to efforts to enhance green cover, such as afforestation projects and better agricultural practices [45, 46]. However, the observed increase in variability and the decrease in minimum NDVI values pre-monsoon warrant further investigation into the causes, which could include urban expansion, land degradation, or shifts in regional climate patterns affecting vegetation growth cycles.

The NDVI analysis affirms that the vegetative landscape of Western India has undergone significant changes over the last four decades, showing both improvements in vegetation health and increased variability in vegetative cover. These findings suggest that while there are positive signs of recovery and growth in certain areas, there are also pockets of concern where vegetation is becoming sparse. The complexity revealed by this analysis underscores the need for targeted conservation efforts and sustainable land management practices to ensure the health and resilience of the region's ecosystems.

Terrain and hydrological features

Analysis of the digital elevation model

The Digital Elevation Model (DEM) of Western India provides a vivid depiction of the region's varied topography, which significantly influences its climate, vegetation, and cultural practices (Fig. 7a). The DEM reveals the stark contrast in elevation from the coastal plains to the rugged interior. The Konkan coast, known for its lush beauty and high monsoon rainfall, is characterized by low-lying topography, while the interior regions of Gujarat's Kutch area consist of salty soils and mudflats with minimal elevation, often resulting in standing water bodies due to the low gradient for runoff.

The model shows that except for the arid desert of Rajasthan, the terrain of Western India generally supports a hot and humid climate. However, Rajasthan breaks this pattern with its hot, dry climate for most of the year, punctuated by extremely cold conditions in winter. This diversity in elevation from coastal lowlands to inland deserts plays a critical role in the distribution of temperature and precipitation, which in turn affects the region's biodiversity and agricultural productivity.

Drainage systems and water bodies

The drainage pattern map (Fig. 7b) is crucial for understanding the hydrological systems and water resources in Western India. It reveals the intricate network of rivers, streams, and lakes that underpin the ecological and economic health of the region. The importance of these water bodies cannot be overstated—they are vital not just for human consumption, but also for the region's wildlife, agriculture, and industry. Water scarcity in forested areas is a growing concern, particularly during the summer months when many natural water bodies dry up, leading wildlife to venture into human settlements in search of water. The maintenance of watersheds and basins is essential; the physical layout of an area upstream from a specific outlet point dictates the water availability for the entire region. Without proper management, not only the water resources, but also the other natural resources that depend on them, risk depletion.

The drainage pattern map underscores the pressing need for conservation efforts and sustainable water management practices. The variation in water availability across different topographical features as depicted by the DEM and drainage patterns suggests a complex interplay between the physical landscape and water resources. These maps together provide valuable insights that can inform strategies for preserving the water systems that are the lifelines for communities, ecosystems, and economies in Western India. Thus, the analysis of terrain and water resources through the DEM and drainage pattern maps paints a picture of a region with varied elevations and a complex network of water bodies. The findings call attention to the delicate balance between natural resources and the need for their careful management in the face of climate variability, population growth, and economic development.

Climate variables

Humidity changes

The application of Inverse Distance Weighting (IDW) interpolation within a GIS framework has yielded detailed humidity maps for the pre- and post-monsoon seasons of 1981 and 2018, revealing significant climatic shifts in Western India. The data indicates an increase in pre-monsoon humidity levels from 22.24% to 24.35%, suggesting more atmospheric moisture which could result from heightened evaporation or changes in regional climate patterns influenced by phenomena like the Indian Ocean Dipole and El Niño Southern Oscillation (ENSO).

The GIS-generated humidity maps for Western India, corresponding to the pre-monsoon and post-monsoon seasons of April 1981 and 2018, present compelling evidence of the region's shifting climatic patterns over nearly four decades. These maps (Fig. 8a, b, d, and e) offer a visual narrative of how humidity levels have altered across different areas, with distinct spatial variations evident between the two time frames.

In the pre-monsoon month of April, the 1981 map (Fig. 8a) shows higher humidity levels predominantly along the coastal areas, which appear to decrease moving inland. By April 2018 (Fig. 8b), these levels show a modest increase, as illustrated by the shift in color gradient towards the higher end of the spectrum. The differential map (Fig. 8c) highlights these changes more starkly, with significant increases in humidity in some inland regions, contrasting with slight decreases along parts of the coast. This could be indicative of a shift in climatic influences, possibly associated with changing patterns in sea breezes or inland moisture retention due to evolving land use practices.

The post-monsoon maps of October for 1981 and 2018 (Fig. 8d and e) display a different trend. The 1981 map indicates higher humidity levels throughout the region, which seem to have diminished by 2018, especially in the coastal areas. The differential map (Fig. 8f) reinforces this observation, showing extensive areas of reduced humidity. Such a reduction in post-monsoon humidity could have critical implications for water resources, agriculture, and biodiversity, potentially exacerbating water scarcity and altering ecosystems dependent on seasonal moisture.

The significance of these results is multi-faceted. For agriculture, these changes could alter crop water requirements and potentially extend or shift agricultural seasons. For ecosystems, the observed variations in humidity levels may affect species distributions, plant phenology, and the health of natural habitats. For human populations, particularly in urban areas, the increased pre-monsoon humidity could lead to heightened thermal discomfort and have health implications.

The observed increase in humidity in certain inland areas during the pre-monsoon season and the general decrease post-monsoon suggest a complex interplay of regional climate dynamics that requires further investigation. For policymakers and stakeholders, understanding these trends is essential for effective water resource management, urban planning, and developing adaptive strategies to mitigate the impacts of climate change. These maps serve not only as a record of past changes but also as a tool for forecasting future climatic scenarios, guiding the implementation of sustainable practices to navigate the challenges posed by these shifts in humidity.

Precipitation variability

The GIS-derived precipitation maps for Western India, spanning April and October of the years 1981 and 2018, manifest a significant decline in rainfall, elucidating the region's changing hydrological patterns. During the pre-monsoon period of April, precipitation has markedly dropped from an average of 8.49 mm in 1981 to just 5.32 mm in 2018, as the maps (Fig. 9a and b) poignantly depict through their lightening color gradients. The differential map (Fig. 9c) highlights the magnitude of change, with considerable reduction concentrated in the northern coastal regions and parts of the interior.

In the post-monsoon observations of October, the maps (Fig. 9d and e) present an even more dramatic decline, with average precipitation levels plummeting from 34.11 mm in 1981 to a sparse 10.16 mm in 2018. The stark contrast between the two time points is visualized in the differential map (Fig. 9f), which underscores a significant decrease across the region, particularly in the southern coastal zones and interior Gujarat.

These findings paint a stark picture of the climatic challenges that Western India faces. Reduced rainfall during key agricultural periods can lead to inadequate soil moisture, affecting crop yields and necessitating shifts in farming practices. The decrease in post-monsoon rainfall is especially problematic as it traditionally replenishes water stocks and supports winter crops. This substantial reduction could have adverse effects on groundwater recharge, surface water bodies, and overall water security for the region.

The coastal reduction in rainfall from north to south, aligned with the decline in humidity, points to potential alterations in the Indian monsoon system or broader global climatic phenomena. Such changes could disrupt the intricate balance of the regional ecosystem, affecting not just agriculture but also the natural habitats that rely on seasonal rains.

Moreover, this decrease in precipitation must be considered within the broader context of climate change, where altered rainfall patterns can exacerbate existing stresses such as water scarcity, food security, and natural disasters. For policymakers and community stakeholders, these precipitation trends highlight the urgent need for water conservation strategies, the adoption of drought-resistant crop varieties, and the strengthening of regional water infrastructure. In light of these significant reductions in rainfall, there is a pressing need for integrated water resource management and climate adaptation planning. Addressing the decline in rainfall will require a multifaceted approach involving sustainable agriculture practices, water-efficient technologies, and community-led water management initiatives to ensure the long-term resilience of both human and ecological communities in Western India.

Atmospheric pressure

The atmospheric pressure maps of Western India for April and October across the years 1981 and 2018 (Fig. 10a, b, d, and e) reflect subtle yet telling shifts in atmospheric dynamics. These shifts, as quantified by the slight decline in average atmospheric pressure, illuminate the nuanced changes in the region's climatic profile over the span of four decades.

In the pre-monsoon maps of April 1981 and 2018 (Fig. 10a and b), the pressure contours delineate a landscape where pressure has marginally decreased from an average of 96.89 to 96.88 kPa. This infinitesimal change, represented in the differential map (Fig. 10c), might be negligible at a casual glance. However, it hints at broader atmospheric stability that masks underlying regional variations. The nuances of this stability become crucial in a context where even minor fluctuations in atmospheric pressure can influence weather patterns and, consequently, the microclimates of diverse topographies present in Western India. Come October, in the post-monsoon period, a similar narrative unfolds with the average pressure descending marginally from 97.31 to 97.19 kPa (Fig. 10d and e). The differential map (Fig. 10f) displays these changes with areas showcasing slight depressions in pressure values. It's an intriguing observation as the post-monsoon season is critical for recharging aquifers and supporting the blooming of various ecosystems; thus, even small shifts in pressure could ripple into significant environmental consequences. The minimalistic change in pressure over four decades suggests a climatic consistency that belies the more dramatic changes observed in humidity and precipitation. The relative pressure stability may mask the transformative shifts occurring in the region's climate system, driven perhaps by global climatic trends or local atmospheric conditions not fully captured by pressure data alone.

This analysis of atmospheric pressure, while indicating overall stability, nonetheless plays a crucial role in the broader climate narrative of Western India. It calls for a deeper understanding of how these stable patterns intersect with the pronounced changes in other climatic variables and what this means for the region’s ecological balance. Given that pressure systems directly influence monsoonal winds, the data underscores the need for integrated climatic models to predict future weather scenarios, which are vital for agricultural planning, water resource management, and disaster mitigation strategies. In light of these findings, it becomes imperative for regional policymakers and scientists to consider these subtle atmospheric trends in conjunction with more volatile climatic variables. The data provides a foundation for proactive strategies to enhance resilience against climate variability, safeguarding the region's agriculture, water security, and natural ecosystems.

Mean temperature

The temperature maps generated for Western India across the pre- and post-monsoon seasons of April 1981 and 2018 (Fig. 11a, b, d, and e) reveal a discernible rise in temperatures, encapsulating the thermal narrative of global warming's local impact over the past four decades. The differential maps (Fig. 11c and f) further distill this warming trend, exhibiting the most significant changes in the coastal regions, as well as some interior areas.

In April's pre-monsoon period, the 1981 map (Fig. 11a) showcases cooler temperatures across the region when compared to the notably warmer temperatures of April 2018 (Fig. 11b). The differential map (Fig. 11c) underlines this warming, with the largest increases observed in the inland areas, suggesting an intensification of heat away from the moderating influence of the coast. These findings are particularly significant given the role of pre-monsoon temperatures in influencing the onset and intensity of the monsoon season, which is crucial for agriculture and water resources in the region. The post-monsoon period of October exhibits a similar pattern of rising temperatures from 1981 to 2018 (Fig. 11d and e), with the differential map (Fig. 11f) illustrating a region-wide trend of warming. This increase in temperature after the monsoon has important ecological ramifications, as it could lead to a prolonged growing season, potentially boosting agricultural productivity in the short term. However, it also raises concerns about the longer-term sustainability of such productivity in the face of exacerbated evapotranspiration and water stress.

The upward temperature trend along the coast, where water availability is generally higher, suggests that coastal ecosystems may be more resilient to the immediate impacts of temperature increases. Nevertheless, the mitigation provided by water availability is not infinite and may not be able to fully counteract the broader effects of warming, such as changes in species distributions and the health of coral reefs and mangroves. Overall, the rising temperature trend underscores the pressing challenge of climate change, with significant implications for biodiversity conservation, water management, agricultural practices, and human health.

The increase in mean temperature necessitates the development of heat-adaptation strategies, particularly in urban planning where heat island effects can intensify the impact on human populations. Moreover, these temperature trends point to the need for enhancing water storage and conservation methods to cope with the higher water demand resulting from increased temperatures. The study's findings call for an integrated approach to climate adaptation that takes into account the compounding effects of rising temperatures on water scarcity, ecosystem health, and agricultural timing. With the predictions of continuing temperature rises, Western India faces the challenge of adapting to a warmer future while mitigating the detrimental effects on its natural resources and human populations.

Wind speed

The wind speed data over Western India, observed through GIS mapping for the months of April and October in the years 1981 and 2018 (Fig. 12a, b, d, and e), reveal a notable decline in wind speeds across the region. This downtrend, as visualized in the differential maps (Fig. 12c and f), reflects broader climatic shifts that potentially impact ecological and atmospheric processes. In the pre-monsoon month of April, the map from 1981 (Fig. 12a) illustrates stronger winds, particularly in the coastal areas, which are crucial for moderating temperatures and contributing to the marine ecosystem's health. By April 2018 (Fig. 12b), these winds have weakened, as indicated by the smoother contours and lighter colors. The differential map for April (Fig. 12f) highlights areas with the most pronounced reduction, showing significant changes in the wind patterns that are instrumental in the regional climate's dynamics.

October's post-monsoon maps (Fig. 12d and e) further affirm this reduction, suggesting an alteration in the wind patterns that are vital for dispersing seeds, aiding in pollination, and regulating temperature and humidity through evapotranspiration. The decrease in wind speed depicted in the differential map for October (Fig. 12c) suggests a systemic change that could be attributed to various factors including landscape alterations, deforestation, urbanization, and possibly even large-scale climate phenomena such as global warming and shifts in ocean currents. The ramifications of this decline in wind speed are manifold. Ecologically, slower winds can lead to diminished seed dispersal for plants, affecting the regeneration of vegetation and altering the composition of ecosystems. For agriculture, changes in wind patterns could influence pollination success rates and thereby crop yields. Additionally, reduced wind speeds can contribute to air stagnation, potentially leading to an increase in air pollution and associated health risks.

Moreover, for coastal regions, the wind is a critical driver of ocean currents and upwelling, which are essential for nutrient cycling and marine biodiversity. The observed reduction along the coast from north to south and in western Gujarat raises concerns over marine productivity and the livelihoods of communities dependent on fishing and other marine resources. These changes in wind speed over the four-decade span warrant a comprehensive examination of their drivers and consequences. There is a pressing need for multidisciplinary research to unravel the complex interactions between wind patterns and climate change, and to assess the potential for these changes to amplify other climatic effects. Policymakers and environmental managers need to consider these findings in their strategies, particularly in the context of renewable energy planning, disaster risk reduction, and environmental conservation efforts, to adapt to and mitigate the impacts of these aerodynamic shifts on local and regional scales.

Comparative analysis of climate variables

The series of figures provided display the comparative analysis of climate variables for Western India during the pre-monsoon and post-monsoon periods of 1981 and 2018. The line graphs (Fig. 13a–d) represent the individual climate stations' recordings, while Table 5 and Fig. 14 synthesize average values for easier comparison. In the pre-monsoon of April 1981, there was a higher variability in precipitation, humidity, and wind speed among different stations as compared to April 2018. Over the years, the pre-monsoon season has experienced a decrease in precipitation and wind speed, with a slight increase in humidity and temperature. This trend reflects the alterations that might be due to changing atmospheric patterns, likely influenced by global warming and other climatic factors. The changes in wind speed are particularly significant, as they can directly affect evapotranspiration rates and, consequently, the hydrological cycle.

The post-monsoon data show an even more pronounced change. The humidity in October 2018 has notably decreased compared to 1981, which could indicate drier conditions following the monsoon season. This has critical implications for water storage and agricultural planning, as reduced humidity post-monsoon could lead to increased water stress and impact crop survival and yields. The decrease in precipitation is stark, indicating a significant shift that could lead to challenges in water resource management and the need for efficient rainwater harvesting techniques to compensate for reduced water availability.

Figure 14 aggregates these variables and displays them together, demonstrating the shifts in climate conditions. This integrated perspective emphasizes the interconnectivity of climate variables and their cumulative effect on regional climate systems. For instance, a decrease in wind speed may contribute to the observed temperature increase, due to reduced convective cooling. Likewise, changes in precipitation and humidity can directly influence agricultural productivity and water security.

The insights derived from these analyses are essential for guiding regional climate adaptation strategies. They highlight the critical need for understanding and predicting climatic trends to prepare for and mitigate the adverse impacts on agriculture, ecosystems, and water resources. The data underscore the urgency of developing and implementing robust, climate-resilient policies and practices to ensure sustainable development in the face of climatic changes.

NDVI comparison with climatic variables

The relationship between the Normalized Difference Vegetation Index (NDVI) as a marker of vegetation health and various climate variables was scrutinized using statistical regression for the years 1981 and 2018 (Fig. 15). A multi-linear regression model integrated Remote Sensing (RS) data to analyze the impact of climate factors—temperature, precipitation, humidity, pressure, and wind speed—on NDVI.

In 1981, during the post-monsoon period, NDVI showed a positive linear correlation with precipitation and humidity, indicating that vegetation vigor was closely linked to the water availability in the atmosphere and soil (Fig. 15). These variables are critical for photosynthesis and plant growth, thus their positive relationship with NDVI underscores the dependence of healthy vegetation on adequate water supply. Conversely, NDVI had a negative correlation with temperature, wind speed and pressure (Fig. 15), suggesting that higher temperatures and lower pressure, which are often associated with stressful conditions for plants, could impede vegetation growth. This negative association could reflect the stress imposed on plants due to heat and possibly the reduced water-holding capacity of the atmosphere.

By 2018, the correlation patterns indicate a continuing positive relationship between NDVI and humidity, as well as NDVI and rainfall in the post-monsoon season. This persistence highlights the ongoing importance of water-related variables for vegetation health despite climatic changes over the decades. The sustained negative correlation with temperature suggests that rising temperatures due to climate change could be increasingly detrimental to plant health, particularly if not offset by sufficient rainfall or humidity. These findings are pivotal for understanding how climate variables influence vegetation dynamics. They highlight the need for monitoring climate trends and implementing adaptive agricultural practices and conservation measures to safeguard vegetation health. The results from this analysis can inform policymakers and environmental planners in developing strategies that mitigate the negative impacts of climate change on ecosystems and enhance resilience against these changes.

Conclusions

This comprehensive study on Western India’s climate variability over nearly four decades reveals significant changes in key climatic variables and their consequent impact on the region’s vegetation dynamics, as indicated by the NDVI. A meticulous analysis using Geographic Information Systems (GIS), multi-linear regression models, and various climate-related datasets has provided a multi-dimensional view of the climatic shifts experienced from 1981 to 2018. The pre- and post-monsoon seasons have both exhibited a decline in precipitation and wind speed, with a slight increase in average temperature and a mix of rising and falling trends in humidity. These changes are not just isolated statistical figures; they represent a transformation in the region’s climate that holds far-reaching implications for its agriculture, water resources, ecosystems, and human populations. The rising temperatures, particularly in the post-monsoon period, suggest a lengthening of the growing season, which could be both an opportunity and a challenge for agriculture, depending on the availability of water resources. The reduction in wind speed could affect pollination processes, seed dispersal, and the natural purification of air, thus impacting biodiversity and the health of natural habitats. Crucially, the study’s findings underline the importance of sustained environmental monitoring and adaptive resource management. It becomes increasingly important to develop climate resilience strategies that account for the observed changes in climatic variables, especially as these changes could exacerbate existing environmental stresses. Furthermore, the evidence points to the need for integrated climate adaptation measures, embracing sustainable agricultural practices, water conservation and management, and the protection of biodiversity. Policymakers, informed by such studies, must navigate the complexities of balancing developmental aspirations with the imperative of environmental conservation. Thus, the study offers a scientific foundation for future research and policy-making, guiding actions to safeguard Western India against the adverse impacts of climate change. Future research should focus on the long-term monitoring of climate variables and LULC changes, with an emphasis on developing adaptive policies for sustainable environmental management in response to ongoing climate change. It calls for proactive and informed engagement with the environmental realities of today, emphasizing the need for regional cooperation, innovative technologies, and community-based approaches to ensure the sustainability of both human and natural systems in the face of shifting climatic conditions.

Acknowledgements

We extend our sincerest gratitude to the various data providers whose comprehensive datasets formed the backbone of this research. The ORNL DAAC, Esri, USGS EROS Archive, Digital Elevation Model data from ASTER, WorldClim and the Iowa State University’s Iowa Environmental Mesonet for their meticulous records. These contributions were not merely sources of information; they were the very tools that enabled a deep and meaningful inquiry into the climatic shifts and their ecological impacts on Western India.

Author contributions

Bhanwar Vishvendra Raj Singh (Conceptualization [equal], Data curation [equal], Formal analysis [equal], Investigation [equal], Methodology [equal], Software [equal], Validation [equal], Writing—original draft [equal], Writing—review & editing [equal]), Vivek Agarwal (Conceptualization [equal], Data curation [equal], Formal analysis [equal], Investigation [equal], Methodology [equal], Software [equal], Validation [equal], Visualization [equal], Writing—original draft [equal], Writing—review & editing [equal]) Varun Sanwal (Formal analysis [equal], Investigation [equal], Methodology [equal], Visualization [equal], Writing—review & editing [equal])

Conflict of interest: The authors declare no conflict of interest.

Funding

This study was conducted without any external funding.

References

Author notes