Influence Of Climate Variability Research Articles

Homogeneity and Trend Analysis of Climatic Variables in Cap-Bon Region of Tunisia

As a semi-arid Mediterranean country, Tunisia is affected by the impacts of climate change, particularly the coastal regions like the Cap-Bon. Irregular rainfall, rising temperatures and the recurrence of extreme events are all indicators that affect ecosystems and populations and make them more vulnerable to the influence of climatic variables. Therefore, an analysis of the trends of climate variables can contribute to facilitating the development of effective adaptation strategies. In this matter, this study was conducted to assess the homogeneity and trends of minimum and maximum air temperature (Tmin and Tmax) and precipitation (P) in the Cap-Bon region. Daily data were collected from the meteorological station of Nabeul for the period of 1982–2020. Pettitt and SNHT tests for homogeneity were applied to identify the breakpoints in multi-time scales of Tmax, Tmin and P data series. The Mann–Kendall (MK) test was used to detect the change in the time-series trend. A modified Mann–Kendall (mMK) test was used to remove the autocorrelation effect from the data series. Both the MK and mMK tests were used at the 5% significant level. The magnitude of the climatic trend was estimated using the non-parametric Sen’s slope estimator. Contrary to Tmin and P, the results of the homogeneity tests revealed the existence of significant breakpoints in the annual, seasonal and monthly Tmax time series. For most cases, the breakpoint occurred around the year 2000. For Tmin, significant breakpoints were recorded in March and April, while a significant shift in the P time series was detected in December. The Mann–Kendall results show a significant warming trend in annual Tmax, with magnitudes equal to 0.065 and 0.045 °C/year before and after the breakpoint, respectively. Nevertheless, non-significant tendencies were observed in the annual Tmin and P time series. On the monthly time scale, Tmax exhibited a significant upward trend in June and August, before the observed breakpoints, with Sen’s slope values equal to 0.065 and 0.045 °C/year, respectively. Regarding the Tmin data, a significant positive trend was observed in July at a rate of 0.033 °C/year.

Influence of air pollution and climate variability on dengue in Singapore – A time-series analysis

Influence of air pollution and climate variability on dengue in Singapore – A time-series analysis

Preparing municipal water system planning for a changing climate: Integrating climate‐sensitive demand estimates

AbstractSeasonality and a changing climate exert strong influences on supply and demand in the western United States, challenging municipal water system (MWS) management. Although supply and demand exhibit characteristics of nonstationarity, the commonly used econometric‐based models to estimate demands discount the influences of climate variability and trends in seasonal MWS vulnerability assessments. Given the projected impacts of climate change on water resources, we use the documented performance of a real‐world MWS with a calibrated systems model to investigate how demands modeled with and without the influences of climate impact system vulnerability indicators—determined by the exceedance of historical daily mean imported water—for MWS planning guidance. Neglecting climatic influences on MWS demands, the model overestimates the volume of imported water by up to 50% and misclassifies vulnerabilities during supply‐limiting conditions. The climate‐sensitive demand estimates reduced model error (i.e., <3% error) and correctly categorized vulnerabilities. Moreover, the MWS exhibited an average threefold greater sensitivity to percent changes in demand relative to percent changes in supply. The sensitivity to variances in demand emphasizes the need to account for factors influencing supply and demand when investigating the impacts of a changing climate, suggesting future research to examine the coupled influences of modeled supply and demand accuracy on MWS performance.

Wind influence and bathymetric effects in wave overtopping based on a long-term field campaign in the Outer Port of Punta Langosteira (Spain)

The operability of harbour facilities and the safety of those working within them can be compromised by overtopping. The aim of the present study is to analyse this phenomenon through a long-term field campaign, of 5 years’ duration, in the Outer Port of Punta Langosteira (Spain). Image monitoring techniques were used to identify the events, which allowed to study the influence of climatic variables and the distribution of overtopping. Results show that the place with the highest density of events was located in the central area of the third alignment. This turned out to be the area of sea wave concentration generated by the bathymetry, as shown by the propagation with a numerical model. Furthermore, wind with a magnitude greater than 30 km/h perpendicular to the breakwater increased the number of events per sea state, that is, the probability that the phenomenon will occur. In addition, the volume of 29 overtopping events and the mean discharge of 13 sea states were estimated using measurements from two pressure sensors on the crest of the breakwater. The results of this study allow to design a breakwater access warning system integrated with open access into the Port Authority’s Environmental Control Panel (http://cma.puertocoruna.com).

An update on the influence of natural climate variability and anthropogenic climate change on tropical cyclones

A substantial number of studies have been published since the Ninth International Workshop on Tropical Cyclones (IWTC-9) in 2018, improving our understanding of the effect of climate change on tropical cyclones (TCs) and associated hazards and risks. These studies have reinforced the robustness of increases in TC intensity and associated TC hazards and risks due to anthropogenic climate change. New modeling and observational studies suggested the potential influence of anthropogenic climate forcings, including greenhouse gases and aerosols, on global and regional TC activity at the decadal and century time scales. However, there are still substantial uncertainties owing to model uncertainty in simulating historical TC decadal variability in the Atlantic, and the limitations of observed TC records. The projected future change in the global number of TCs has become more uncertain since IWTC-9 due to projected increases in TC frequency by a few climate models. A new paradigm, TC seeds, has been proposed, and there is currently a debate on whether seeds can help explain the physical mechanism behind the projected changes in global TC frequency. New studies also highlighted the importance of large-scale environmental fields on TC activity, such as snow cover and air-sea interactions. Future projections on TC translation speed and medicanes are new additional focus topics in our report. Recommendations and future research are proposed relevant to the remaining scientific questions and assisting policymakers.

Evaluation The Leachate Characteristics and its Impacts on Groundwater Contamination Around Al-Diwaniyah Open Dumpsite

Groundwater contamination presents an increasing concern for environmental sustainability and human health, especially organic contamination. The effect of leachate percolation on groundwater contamination was investigated at Al-Diwaniyah open dumpsite to assess the groundwater quality of hand-dug observation wells surrounding the dumpsite. Samples of raw leachate and groundwater were collected for laboratory analysis, where they were analyzed using standard methods in order to evaluate any potential seasonal and variations for rainy, and dry seasons. Analytical results of leachate samples indicate that all physiochemical parameters were high revealing that they were highly contaminated with both organic and inorganic materials. High pH value and low BOD5/COD ratio for leachate indicated that dumpsite is old and in the methanogenic stage of anaerobic decomposition. In groundwater, average values of pH, EC, TDS, and major ion concentrations were higher in the dry season as compared to that in the rainy season. In contrast, the variation in TSS, BOD5, and COD showed more in rainy season than in dry season. GW1 and GW2 samples were more impacted by leachate percolation than GW3. The findings further revealed that except for pH, and nitrate all other examined parameters were above the permitted limitations of World Health Organization and Iraqi Quality standards. Relying on pH, EC, and major ions respectively, groundwater adjacent to dumpsite can be described as slightly alkaline, water with health hazards, and Chloride is the dominating ion. Inferred from the preceding, the noticeable influence of climate variation and distance from dumpsite on the extent of groundwater contamination. Continuously monitoring the groundwater resources in the area and constructing engineering landfills subject to the environmental limitations to control leachate infiltration into groundwater is recommended.

Impact of Climate Variables on Paddy Production in Tamil Nadu, India

The significant reduction in agricultural production in Sri Lanka, compounded by the rising prices of fuel and basin food items followed by agricultural food shortages in Afghanistan and increase in food consumption worldwide carry our global concern towards food security and sustainability mere self-sufficient in production. Agriculture is extremely vulnerable to climate change. Extreme climate happens like heavy rainfall, high temperature and drought making heavy losses in agriculture regionally and significantly damaging the harnessing of better crop yields. As a major staple food crop, Paddy is selected for examining the impact of climate variability on paddy crop yield and variance thereof in Indian state of Tamil Nadu. Season and Crop Reports published by the Department of Agriculture, Government of Tamil Nadu and NASA Power Data are the secondary data sources were used for the study. Just-Pope yield function was used to determine the influence of climate variables on mean crop yield and variance. The results indicate that yield of paddy increases from the increase in temperature, however, are negatively associated with precipitation intensity. The variability in the yield of paddy also increases with increase in rainfall. The study has suggested weather-based crop insurance policy and climate-resilient farming techniques to reduce the losses to the farmers.

Clarifying the relationship between annual maximum daily precipitation and climate variables by wavelet analysis

Analyzing the temporal hydrological response of regional precipitation to climate variables is critical for improving precipitation prediction and understanding the underlying mechanism. We study the potential relationship between the annual maximum daily precipitation (RX1day) in Guangdong Province and 21 climate variables, including the length of the day of the earth's rotation (LOD), Niño 3.4, and Pacific Decadal Oscillation (PDO). Wavelet coherence (WTC), partial wavelet coherence (PWC), and multiple wavelet coherence (MWC) are used to identify possible individual, independent, and coupled relationships between the RX1day and climate variables. The analysis results show that Tropical Southern Atlantic Index (TSA), Niño 3.4, Southern Oscillation Index (SOI), Western Pacific Index (WP), Tripole Index for the Interdecadal Pacific Oscillation (TPI), North Pacific pattern (NP), Atlantic Multidecadal Oscillation (AMO), and Tropical Northern Atlantic Sea Surface Temperatures Index (TNA) are important driving forces influencing RX1day in Guangdong. After excluding the influence of Niño 3.4 and PDO, PWC accurately explains the influence of a single climate variable on RX1day. A single climate variable is insufficient to describe the influence on RX1day, but MWC accurately reflects the combined influence of different climate variables on RX1day. Our work emphasizes the use of PWC and MWC to reveal the independent and combined influences of climate variables on RX1day on different time scales. This study provides new insights into selecting the optimum predictive factors of RX1day.

Influence of Climatic Variables on Corporal Attributes of Adult Female Caiman and Their Relationship with Reproductive Success

Influence of Climatic Variables on Corporal Attributes of Adult Female Caiman and Their Relationship with Reproductive Success

Interactive response and spatial heterogeneity of alpine grassland biodiversity to soil, topography, climate, and human factors on the Qinghai‐Tibet Plateau

AbstractThe alpine grassland ecosystem is a critical part of the Qinghai‐Tibet Plateau (QTP), mainly including alpine meadows and alpine steppes. However, the influence factors of alpine grassland biodiversity are not clear for different alpine grassland types. In this study, pathway analysis was applied to explore the influences of soil, topography, climate, and human factors on alpine grassland biodiversity. Then, by using the geographically weighted regression (GWR) model, the spatial sensitivity response of alpine grassland biodiversity to soil, topography, climate, and human activities was revealed in different grassland types. The results were as follows: (1) The data and pathway analysis passed the validity and reliability analysis, indicating that the model fit of alpine grassland biodiversity was good for different grassland types. (2) For alpine meadows, the total effect coefficients of altitude, slope, and topographic wetness index (TWI) on normalized difference vegetation index (NDVI) (net primary productivity [NPP]) were 0.50, 0.21, and −0.48 (0.59, 0.17, and −0.41), respectively, suggesting that altitude had the strongest and positive effect on alpine meadow diversity. In addition, among human activity and climate variables, human activity intensity and precipitation exhibited significant effects on NDVI (NPP), with total effect coefficients of −0.17 and 0.61 (−0.19 and 0.63). The influence of soil, topography, climate, and human variables on alpine steppe diversity showed similarities with alpine meadow diversity. (3) Alpine grassland biodiversity was directly and indirectly influenced by multiple driving factors for different grassland types. The total coefficients of soil, topography, climate, and human factors on NDVI (NPP) were 0.41, 0.38, −0.21, and 0.71 (0.32, 0.50, −0.21, and 0.91), respectively, which indicated that alpine meadow diversity was mainly regulated by climate on the QTP, consistent with alpine steppe diversity. (4) For different grassland types, the spatial effects of various driving factors on alpine grassland biodiversity all showed significant spatial heterogeneity at the grid scale. Based on the knowledge about the driving mechanism and spatial response of alpine grassland biodiversity to its driving factors in different grassland types of the QTP, we aim to provide guidance for alpine grassland biodiversity conservation and rational ecosystem management.

Understanding global groundwater-climate interactions

Global warming is emerging as an important predictor of water availability and future water supplies across the world through inducing the frequency and severity in hydrological extremes. These extremes (e.g., drought) have potential impacts on groundwater, environmental flows, as well as increase social inequalities (limited access to water by the poor), among a range of other issues. Understanding the influence of global climate on groundwater systems is thus critical to help reshape global water markets through policies underpinned by the knowledge of climatic processes driving the water cycle and freshwater supply. The main aim of this study is to improve understanding of the influence of climate variability on global groundwater using statistical methods (e.g., multi-linear regression and wavelet analyses). The response of groundwater to climate variability are assessed and the feasibility of identifying climatic hotspots of groundwater-climate interactions are explored (2003−2017). Generally, climate variability plays a major role in the distribution of groundwater recharge, evidenced in the groundwater-rainfall relationship (r ranging from 0.6 to 0.8 with lags of 1–5 months) in several regions (Amazon and Congo basins, West Africa, and south Asia). Some of the areas where no relationship exists coincide with major regional aquifer systems (e.g., Nubian sand stone in north Africa) in arid domains with fossil groundwater. Our results also show that groundwater fluxes across the world are driven by global climate teleconnections. Notable among these climate teleconnections are PDO, ENSO, CAR, and Nino 4 with PDO showing the strongest relationship (r= 0.80) with groundwater in some hotspots (e.g. in South America). The explicit role of the Pacific ocean in regulating groundwater fluxes provides an opportunity to improve the prediction of climate change impact on global freshwater systems. As opposed to remarkably large productive hydrological systems (Amazon and Congo basins), in typically arid domains, groundwater could be restricted during prolonged drought, constraining the persistence of surface water in the maintenance of a healthy surface-groundwater interactions.

Water or mirage? Nightmare over dams and hydropower across Iran

ABSTRACT This study examines the influence of human activities and climate variability on 86 dams and hydropower across Iran. The term ‘mirage water’ is introduced to estimate the impact of these factors on inflow. Data analysis shows that out of 1729 m3s−1 of mirage water, 705 m3s−1 are contributed by anthropogenic activities and 1024 m3s−1 by precipitation deficits. This indicates that some parts of Iran’s strategic investments in water resources management over the past 60 years have failed. The study underscores the necessity for enhanced management practices and infrastructure investments to ensure sustainable water resources in arid and semi-arid regions.

Assessment of Climate Variability on Poultry Production in Nigeria: 1990-2020

This study examined the influence of climate variability on poultry production in Nigeria from 1990-2020. State the broad objective only. This study adopted the quasi-experimental research design. Secondary data were used in the study. The method employed for analyzing the time series data was the Auto Regressive Distributed Lag (ARDL) model. Pre-estimation diagnostics tests were employed to check for stationarity of the data. From the results of the Error Correction Models (ECM’s), average rainfall and Carbon dioxide emission have significant influence on poultry (egg and meat) production in Nigeria. A unit increase in average rainfall brought about -0.4% reduction in egg production, while a unit increase in carbon dioxide emission brought about a -0.27% reduction in egg production. Average rainfall had positive influence on broiler production a unit increase in rainfall increased broiler production by 0.41% and 0.52% at the current and two period lag, while carbon dioxide emission reduced broiler production by -0.16%. The study concluded that climate change do affect poultry production both negatively and positively and recommended that climate smart agricultural practices such as proper ventilation and vaccination should be applied in poultry production to mitigate the negative effects of climate change

What is the probability that a drought will break in Australia?

Large scale modes of climate variability influence rainfall and soil moisture in southeastern Australia, and extended dry conditions have been associated with a lack of climate mode phases conducive to wetter conditions. However, the role of large-scale climate variability in breaking ongoing soil moisture droughts has not been well quantified, and the utility of large-scale signals in drought recovery assessments have not been explored. Here, we study the influence of El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on the probability of soil moisture drought breaking in eastern and southeastern Australia, using logistic regression modelling. A long-term historical dataset from the Australian Water Resources Assessment Landscape (AWRA-L) model is used for the assessment. The probability estimates from the logistic regression modelling validate well against observed probability of a drought ending. We then use model estimates to understand the probability contributions from different climate modes. We show that there is a seasonal pattern in soil moisture drought breaking probabilities with higher probabilities in austral summer in eastern Australia and summer/autumn in southeastern Australia. ENSO has the largest influence on probabilities in winter with extreme opposite phases of the mode resulting in regional average probability differences of 15–26%. The IOD exhibits the largest influences during spring and winter and opposite phases result in differences of about 18%. The method can be used to estimate soil moisture drought breaking probabilities in near real-time during drought events, and may assist decision making by managers engaged in drought risk and water resources planning.

Asymmetries in climate change and livestock productivity: non-linear evidence from autoregressive distribution lag mode

IntroductionThe livestock sector is extremely important to Socioeconomic growth in Pakistan, yet it is also quite vulnerable to weather changes. Climate change reduces livestock production by changing ecosystem services such as water availability, feed quality and quantity, disease outbreaks, animal heat stress, and a decline in livestock variety and breeds. Climate change has a direct impact on ecological and animal health. As a consequence of climate change, animal diseases, and infections are becoming more widespread. With the non-linearities of climate change in the livestock industry in mind, the present study investigated the asymmetric influence of climatic and non-climatic variables on livestock productivity across Pakistan. The empirical analysis was conducted utilizing secondary time series data from 1980 to 2021.MethodThe non-linear autoregressive distributive lag (NARDL) model is used to examine the asymmetric behavior of climatic variability in the livestock sector. We included CO2 emissions, mean temperature (MT), and precipitation (PERC) as climatic variables in the current study, along with additional control factors.Results and discussionOur research discovered that CO2, MT, and PREC had asymmetries in their impacts on livestock. Variations in CO2, MT, and PREC have contradictory effects on livestock productivity in the long and short term. A percent increase in LCO2 leads to a fall in livestock production insignificantly by 1.0062% for Model I and significantly by 5.7613% and 5.3929% for Models II and III, respectively. A percent decrease in LCO2 significantly lowers livestock production by 4.1739% for Model I and improves livestock production by 8.5928% and 6.7901%, respectively, for Model II and Model III. A unit increase in MT significantly improves livestock productivity by 1.5520% and 0.8149% for Models II and III, respectively, while a unit decrease in MT insignificantly improves livestock production by 0.1316% and 0.2122% for Models II and III, respectively. A unit increase and decrease in PREC significantly lowers and insignificantly improve livestock productivity respectively by 0.002% in both cases for Model III. To protect the livestock industry from the negative effects of climate change, this study suggests that livestock producers use new environmentally friendly technologies and ecological agricultural systems.

Complicating Cultural Reproduction Theory: A Critical Multilevel Analysis of Systematic Inequality in U.S. Schools

The purpose of the current study is to examine malleable school practices and norms that contribute to inequitable school learning environments based on student background. Using multilevel structural equation modeling (SEM) with the U.S. sample of PISA 2015, this study examines the extent to which student-level access to inquiry-based science learning opportunities and academic press mediates the relationship between intersectional student background and scientific literacy outcomes, as well as the influence of school-level context, tracking, and academic climate variables on student learning opportunities, perceptions of academic press, and science outcomes. After accounting for variance explained at the school level, OTL was not a significant mediator of the relationship between student intersectional background or gender and scientific literacy outcomes. However, academic press was a significant mediator at the student level, and was a significant negative predictor of science achievement. At the school level, while tracking was not a significant predictor of mean school science achievement, tracking was a predictor of mean school academic press and OTL inquiry-based science. There were significant differences in school academic climate based on school context, and school-level perceptions of academic climate were significant predictors of science achievement, findings that can inform education policy and practice.

Influences of Ecological Restoration Programs on Ecosystem Services in Sandy Areas, Northern China

Ecosystem services (ESs) are important for supporting human development. However, a changing climate and anthropogenic impacts are resulting in the degradation of dryland ecosystems to varying degrees. While there has been the global implementation of Ecological Restoration Programs (ERPs) to restore degraded ecosystems, there remains limited comprehensive assessment of their impacts on ESs of drylands. In this study, the sandy areas of northern China were used as the study area. The RUSLE, RWEQ, CASA, and InVEST models were used to simulate four major ESs: soil conservation (SC), sand fixation (SF), carbon sequestration (CS), and water yield (WY). The study aimed to evaluate the influences of various ERPs on major ESs. The dominant factors affecting the overall benefits provided by ESs were also identified. Since ERPs were implemented, forest areas have increased by 2.8 × 104 km2, whereas the areas of cropland, shrubland, and grassland have decreased. There were generally increasing trends in SF, SC, and CS, whereas there was a decreasing trend in WY. We then used a scenario-based simulation approach to eliminate the influence of climate variability on ESs. The results showed increasing trends in SF, SC, and CS, whereas there were minimal changes in WY. The results suggested that although ERPs can significantly increase regional ESs, unregulated expansion in vegetation can result in a water crisis and affect regional water security.

Detecting the long-term spatiotemporal crop phenology changes in a highly fragmented agricultural landscape

Trends in crop phenometrics reveal the influence of climate variability and change on crop growth and development. However, the trends are less clear in fragmented tropical smallholder landscapes, because there is high spatial and temporal variability in crop phenology. Frequent historical and high spatial resolution (≤30 m) Earth observations are needed to track changes in crop phenology in fragmented landscapes but are often unavailable. The spatial–temporal gap can be closed by integrating infrequent high spatial resolution Earth observations with low spatial/high temporal resolution observations through data fusion. We fused 30 m resolution Landsat and 250 m resolution MODIS imagery to investigate trends in crop phenology from 2000 to 2020 in a fragmented agricultural landscape of Ethiopia. We used the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) that had recently been modified for application in fragmented agricultural landscapes. We used the non-parametric Mann–Kendall test for crop phenology trend analysis. Crop phenology based on Landsat–MODIS fusion was compared to MODIS-based crop phenology without fusion. We found data fusion yielded a smaller magnitude of changes in the start of season (SOS: -0.2-day-y−1) and end of season (EOS: -0.50-day-y−1) compared to MODIS SOS (-0.5-day-y−1) and EOS (1.38-day-y−1) due to MODIS-related mixing with the surrounding natural vegetation in the fragmented agricultural landscape. EOS showed a faster rate of change compared to SOS over the 21-years. The Landsat and MODIS fusion captured spatial variation in the timing and magnitude of change specific to crops and their growing environment, which has implications for adaptation strategies. Our results highlight the importance of long-term data fusion to improve the spatial dimension of crop phenology time series analysis. Integrating time series land cover maps into the data fusion processing chain could further improve long-term data fusion for crop phenology trend analysis.

Rates of Stemwood Carbon Accumulation Are Linked to Hydroclimate Variability in Mexican Conifers

Evapotranspiration demand has increased rapidly as temperatures have risen, affecting forest productivity. Consequently, carbon (C) uptake by forests is being modified; therefore, a more refined knowledge of the relationships between C capture and hydroclimate variability is required, particularly in drought-prone regions. In this study, we analyzed the relationships between climate and C capture as stemwood through the dendroecological analyses of radial growth in 15 conifer species distributed along a broad bioclimatic gradient in Mexico. The C content was calculated using densitometry data; correlations and mixed models were then used to determine the influence of climatic variables (precipitation, mean maximum and minimum temperatures, SPEI drought index) on tree growth. Each species showed specific responses to the climate with Taxodium mucronatum being the most responsive species. Both precipitation and maximum temperature best explained changes in C capture, with minimum temperature and SPEI playing secondary roles. The winter before the growth period was the most important season for C capture, particularly through positive responses to wet-cool conditions. However, the climatic influences of the current fall and summer were also notable. Seasonal climatic influences have implications for C uptake and forest productivity in the face of the severe droughts that repeatedly affect the study region.

Quantifying climate variability and regional anthropogenic influence on vegetation dynamics in northwest India

To explore the spatio-temporal dynamics and mechanisms underlying vegetation cover in Haryana State, India, and implications thereof, we obtained MODIS EVI imagery together with CHIRPS rainfall and MODIS LST at annual, seasonal and monthly scales for the period spanning 2000 to 2022. Additionally, MODIS Potential Evapotranspiration (PET), Ground Water Storage (GWS), Soil Moisture (SM) and nighttime light datasets were compiled to explore their spatial relationships with vegetation and other selected environmental parameters. Non-parametric statistics were applied to estimate the magnitude of trends, along with correlation and residual trend analysis to quantify the relative influence of Climate Change (CC) and Human Activities (HA) on vegetation dynamics using Google Earth Engine algorithms. The study reveals regional contrasts in trends that are evidently related to elevation. An annual increasing trend in rainfall (21.3 mm/decade, p < 0.05), together with augmented vegetation cover and slightly cooler (−0.07 °C/decade) LST is revealed in the high-elevation areas. Meanwhile, LST in the plain regions exhibit a warming trend (0.02 °C/decade) and decreased in vegetation and rainfall, accompanied by substantial reductions in GWS and SM related to increased PET. Linear regression demonstrates a strongly significant relationship between rainfall and EVI (R2 = 0.92), although a negative relationship is apparent between LST and vegetation (R2 = −0.83). Additionally, increased LST in the low-elevation parts of the study area impacted PET (R2 = 0.87), which triggered EVI loss (R2 = 0.93). Moreover, increased HA resulted in losses of 25.5 mm GSW and 1.5 mm SM annually. The relative contributions of CC and HA are shown to vary with elevation. At higher elevations, CC and HA contribute respectively 85% and 15% to the increase in EVI. However, at lower elevations, reduced EVI is largely (79%) due to human activities. This needs to be considered in managing the future of vulnerable socio-ecological systems in the state of Haryana.