Your search found 12 records
1 Prasood, S. P.; Mukesh, M. V.; Rani, V. R.; Sajinkumar, K. S.; Thrivikramji, K. P. 2021. Urbanization and its effects on water resources: scenario of a tropical river basin in South India. Remote Sensing Applications: Society and Environment, 23:100556. [doi: https://doi.org/10.1016/j.rsase.2021.100556]
Urbanization ; Water resources ; River basins ; Groundwater ; Surface water ; Water demand ; Water security ; Forecasting ; Land use ; Land cover ; Surface temperature ; Normalized difference vegetation index ; Infiltration / India / Kerala / Karamana River Basin / Thiruvananthapuram
(Location: IWMI HQ Call no: e-copy only Record No: H050468)
(9.90 MB)
Karamana River Basin (KRB), set in the tropical monsoon climate (i.e., Koppen's Am), hosts the drinking water supply to the capital city of Thiruvanathapuram, one of the highly urbanized cities in the southwestern seaboard of India. Primary focus of the study is a scrutiny of future water security status of KRB, amidst the rising population and subsequent urban sprawl. The study was done through a combination of analysis of remotely sensed data, and collation of data on population growth, surface water distribution and decadal-level groundwater monitoring. An uptrend of the decadal-level population and unscientific constructions across KRB led to the decline of per capita water entitlement and causing conflicts around water service delivery. So this study has an imperative focus on the effects of rapidly growing urban life and its impact on water resources in KRB. This was accomplished by studying the land use, land surface temperature (LST), annual precipitation, and groundwater trend for two decades, followed by land use modeling and quantifying total water deposit. The estimated LST values in KRB, robustly substantiate an upward shift in surface temperature between 2001 (47.55%) to 2020 (64.01%), a testimony of urban sprawl and it may be the major cause to reduce the rate of rainwater infiltration and increase in runoff. The Normalized Difference Vegetation Index (NDVI), used to generate land use map, and LST of the basin have been assessed for the years 2001, 2011, and 2020 to model whether or not land use has been modulated by urbanization. Based on this, future trends of land use changes for 2030 and 2050 have been predicted using CA-Markov model - a model combining Cellular Automata and Markov chain. We also carried out a quantification of annual water deposit, potential evapo-transpiration, infiltration, surface runoff, and storage. Decadal trends of population change, degree of urbanization and consequent rise in domestic water demand and shrinkage of area of open space/soil cover have also been factored in assessing water security in KRB. The results show that, as of today, the city is facing an acute annual shortage of surface water by 321.51 MCM. Furthermore, we propose potential sources for future water security of the state's capital region.
2 Damm, A.; Cogliati, S.; Colombo, R.; Fritsche, L.; Genangeli, A.; Genesio, L.; Hanus, J.; Peressotti, A.; Rademske, P.; Rascher, U.; Schuettemeyer, D.; Siegmann, B.; Sturm, J.; Miglietta, F. 2022. Response times of remote sensing measured sun-induced chlorophyll fluorescence, surface temperature and vegetation indices to evolving soil water limitation in a crop canopy. Remote Sensing of Environment, 273:112957. (Online first) [doi: https://doi.org/10.1016/j.rse.2022.112957]
Plant water relations ; Leaf water potential ; Canopy ; Remote sensing ; Surface temperature ; Vegetation index ; Chlorophylls ; Fluorescence ; Soil water ; Maize / Italy / Tuscany
(Location: IWMI HQ Call no: e-copy only Record No: H050996)
https://www.sciencedirect.com/science/article/pii/S0034425722000712/pdfft?md5=f358a1acfb0c958d984037b09f412ce7&pid=1-s2.0-S0034425722000712-main.pdf
https://vlibrary.iwmi.org/pdf/H050996.pdf
https://vlibrary.iwmi.org/pdf/H050996.pdf
(10.80 MB) (10.8 MB)
Vegetation responds at varying temporal scales to changing soil water availability. These process dynamics complicate assessments of plant-water relations but also offer various access points to advance understanding of vegetation responses to environmental change. Remote sensing (RS) provides large capacity to quantify sensitive and robust information of vegetation responses and underlying abiotic change driver across observational scales. Retrieved RS based vegetation parameters are often sensitive to various environmental and plant specific factors in addition to the targeted plant response. Further, individual plant responses to water limitation act at different temporal and spatial scales, while RS sampling schemes are often not optimized to assess these dynamics. The combination of these aspects complicates the interpretation of RS parameter when assessing plant-water relations. We consequently aim to advance insight on the sensitivity of physiological, biochemical and structural RS parameter for plant adaptation in response to emerging soil water limitation. We made a field experiment in maize in Tuscany (Central Italy), while irrigation was stopped in some areas of the drip-irrigated field. Within a period of two weeks, we measured the hydraulic and physiological state of maize plants in situ and complemented these detailed measurements with extensive airborne observations (e.g. sun-induced chlorophyll fluorescence (SIF), vegetation indices sensitive for photosynthesis, pigment and water content, land surface temperature). We observe a double response of far-red SIF with a short-term increase after manifestation of soil water limitation and a decrease afterwards. We identify different response times of RS parameter representing different plant adaptation mechanisms ranging from short term responses (e.g. stomatal conductance, photosynthesis) to medium term changes (e.g. pigment decomposition, changing leaf water content). Our study demonstrates complementarity of common and new RS parameter to mechanistically assess the complex cascade of functional, biochemical and structural plant responses to evolving soil water limitation.
3 Wei, J.; Cui, Y.; Zhou, S.; Luo, Y. 2022. Regional water-saving potential calculation method for paddy rice based on remote sensing. Agricultural Water Management, 267:107610. (Online first) [doi: https://doi.org/10.1016/j.agwat.2022.107610]
Water conservation ; Rice ; Remote sensing ; Irrigation water ; Flood irrigation ; Water balance ; Energy balance ; Evapotranspiration ; Surface temperature ; Mapping ; Drainage ; Datasets ; Models / China / Hubei / Zhanghe Irrigation District
(Location: IWMI HQ Call no: e-copy only Record No: H051065)
(6.00 MB)
To improve the calculation applicability and operability of regional water-saving potential (RWSP) for paddy rice, a calculation method based on remote sensing (RWSP-RS) was proposed. RWSP-RS consists of three sections: (a) paddy rice mapping by the decision tree algorithm, (b) rice evapotranspiration (ET) inversion under different irrigation modes by the surface energy balance algorithm for land (SEBAL), and (c) WSP based on ET (WSPE) and irrigation (WSPI) calculation by coupling water balance models for paddy fields. The RWSP-RS was applied in the Zhanghe Irrigation District in southern China in 2018 and 2019. The results showed that the three sections of RWSP-RS had high precision: paddy rice mapping errors ranged from 2% to 16%; WSPE of paddy rice errors were 26 mm and 5 mm for 2018 and 2019, respectively; and WSPI errors were 5 mm and 23 mm for 2018 and 2019, respectively. The WSPI of paddy rice in the whole region was 44.52 million m3 and 99.12 million m3 for 2018 and 2019, respectively. RWSP-RS has the characteristics of solid operability, good regional applicability, and time and labor savings, making it a recommended method for calculating the RWSP of paddy rice and contributing to regional water resource management.
4 Qian, Y.; Chakraborty, T. C.; Li, J.; Li, D.; He, C.; Sarangi, C.; Chen, F.; Yang, X.; Leung, L. R. 2022. Urbanization impact on regional climate and extreme weather: current understanding, uncertainties, and future research directions. Advances in Atmospheric Sciences, 39(6):819-860. [doi: https://doi.org/10.1007/s00376-021-1371-9]
Climate change ; Extreme weather events ; Urbanization ; Uncertainty ; Precipitation ; Air temperature ; Air pollution ; Air quality ; Towns ; Satellite observation ; Meteorological stations ; Heat stress ; Surface temperature ; Vegetation ; Land cover ; Land use ; Boundary layers ; Turbulence ; Models / China
(Location: IWMI HQ Call no: e-copy only Record No: H051076)
https://link.springer.com/content/pdf/10.1007/s00376-021-1371-9.pdf
https://vlibrary.iwmi.org/pdf/H051076.pdf
https://vlibrary.iwmi.org/pdf/H051076.pdf
(3.73 MB) (3.73 MB)
Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms. In this review article, we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies. We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.
5 Elfarkh, J.; Simonneaux, V.; Jarlan, L.; Ezzahar, J.; Boulet, G.; Chakir, A.; Er-Raki, S. 2022. Evapotranspiration estimates in a traditional irrigated area in semi-arid Mediterranean. Comparison of four remote sensing-based models. Agricultural Water Management, 270:107728. [doi: https://doi.org/10.1016/j.agwat.2022.107728]
Evapotranspiration ; Estimation ; Irrigated farming ; Semiarid zones ; Remote sensing ; Models ; Calibration ; Energy balance ; Surface temperature ; Soil moisture ; Vegetation / Mediterranean Region / Morocco / Marrakech
(Location: IWMI HQ Call no: e-copy only Record No: H051292)
(8.69 MB)
Quantification of actual crop evapotranspiration (ETa) over large areas is a critical issue to manage water resources, particularly in semi-arid regions. In this study, four models driven by high resolution remote sensing data were intercompared and evaluated over an heterogeneous and complex traditional irrigated area located in the piedmont of the High Atlas mountain, Morocco, during the 2017 and 2018 seasons: (1) SAtellite Monitoring of IRrigation (SAMIR) which is a software-based on the FAO-56 dual crop coefficient water balance model fed with Sentinel-2 high-resolution Normalized Difference Vegetation Index (NDVI) to derive the basal crop coefficient (); (2) Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) which is a surface energy balance model fed with land surface temperature (LST) derived from thermal data provided from Landsat 7 and 8; (3) a modified version of the Shuttleworth–Wallace (SW) model which uses the LST to compute surface resistances and (4) METRIC-GEE which is a version of METRIC model (“Mapping Evapotranspiration at high Resolution with Internalized Calibration”) that operates on the Google Earth Engine platform, also driven by LST. Actual evapotranspiration (ETa) measurements from two Eddy-Covariance (EC) systems and a Large Aperture Scintillometer (LAS) were used to evaluate the four models. One EC was used to calibrate SAMIR and SPARSE (EC1) which were validated using the second one (EC2), providing a Root Mean Square Error (RMSE) and a determination coefficient (R) of 0.53 mm/day (R=0.82) and 0.66 mm/day (R=0.74), respectively. SW and METRIC-GEE simulations were obtained respectively from a previous study and Google Earth Engine (GEE), therefore no calibration was performed in this study. The four models predict well the seasonal course of ETa during two successive growing seasons (2017 and 2018). However, their performances were contrasted and varied depending on the seasons, the water stress conditions and the vegetation development. By comparing the statistical results between the simulation and the measurements of ETa it has been shown that SAMIR and METRIC-GEE are the less scattered and the better in agreement with the LAS measurements (RMSE equal to 0.73 and 0.68 mm/day and R equal to 0.74 and 0.82, respectively). On the other hand, SPARSE is less scattered (RMSE = 0.90 mm/day, R = 0.54) than SW which is slightly better correlated (RMSE = 0.98 mm/day, R = 0.60) with the observations. This study contributes to explore the complementarities between these approaches in order to improve the evapotranspiration mapping monitored with high-resolution remote sensing data.
6 Ly, R.; Matchaya, Greenwell; Fakudze, Bhekiwe; Dia, K. 2023. Predicting food crop production in times of crisis: the case of wheat in Mozambique. Kigali, Rwanda: AKADEMIYA2063. 10p. (AKADEMIYA2063 Ukraine Crisis Brief Series 17)
Food crops ; Crop production ; Forecasting ; Wheat ; Normalized difference vegetation index ; Surface temperature / Mozambique
(Location: IWMI HQ Call no: e-copy only Record No: H051763)
https://akademiya2063.org/publications/Ukraine%20Crisis%20and%20African%20Countries/Brief-17-AKADEMIYA2063%20Ukraine%20Crisis%20Brief%20Series.pdf
https://vlibrary.iwmi.org/pdf/H051763.pdf
https://vlibrary.iwmi.org/pdf/H051763.pdf
(0.51 MB) (517 KB)
7 Ly, R.; Matchaya, Greenwell; Pele, Winnie Kasoma; Dia, K. 2023. Predicting food crop production in times of crisis: the case of wheat in Zambia. Kigali, Rwanda: AKADEMIYA2063. 9p. (AKADEMIYA2063 Ukraine Crisis Brief Series 20)
Food crops ; Crop production ; Forecasting ; Wheat ; Rain ; Surface temperature ; Normalized difference vegetation index / Zambia
(Location: IWMI HQ Call no: e-copy only Record No: H051764)
https://akademiya2063.org/publications/Ukraine%20Crisis%20and%20African%20Countries/Brief-20-AKADEMIYA2063%20Ukraine%20Crisis%20Brief%20Series.pdf
https://vlibrary.iwmi.org/pdf/H051764.pdf
https://vlibrary.iwmi.org/pdf/H051764.pdf
(0.91 MB) (930 KB)
8 Springer, A.; Lopez, T.; Owor, M.; Frappart, F.; Stieglitz, T. 2023. The role of space-based observations for groundwater resource monitoring over Africa. Surveys in Geophysics, 44(1):123-172. [doi: https://doi.org/10.1007/s10712-022-09759-4]
Groundwater ; Monitoring ; Water resources ; Water storage ; Satellite observation ; Remote sensing ; Models ; Anthropogenic factors ; Climate change ; Sustainable development ; Surface water ; Aquifers ; Hydrological modelling ; Soil moisture ; Precipitation ; Decision making ; Surface temperature ; Water levels / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H051721)
https://link.springer.com/content/pdf/10.1007/s10712-022-09759-4.pdf?pdf=button
https://vlibrary.iwmi.org/pdf/H051721.pdf
https://vlibrary.iwmi.org/pdf/H051721.pdf
(4.98 MB) (4.98 MB)
Africa is particularly vulnerable to climate change impacts, which threatens food security, ecosystem protection and restoration initiatives, and fresh water resources availability and quality. Groundwater largely contributes to the mitigation of climate change effects by offering short- to long-term transient water storage. However, groundwater storage remains extremely difficult to monitor. In this paper, we review the strengths and weaknesses of satellite remote sensing techniques for addressing groundwater quantity issues with a focus on GRACE space gravimetry, as well as concepts to combine satellite observations with numerical models and ground observations. One particular focus is the quantification of changes in groundwater resources in the different climatic regions of Africa and the discussion of possible climatic and anthropogenic drivers. We include a thorough literature review on studies that use satellite observations for groundwater research in Africa. Finally, we identify gaps in research and possible future directions for employing satellite remote sensing to groundwater monitoring and management on the African continent.
9 Dube, T.; Seaton, D.; Shoko, C.; Mbow, C. 2023. Advancements in earth observation for water resources monitoring and management in Africa: a comprehensive review. Journal of Hydrology, 623:129738. [doi: https://doi.org/10.1016/j.jhydrol.2023.129738]
Earth observation satellites ; Water resources ; Monitoring ; Hydrology ; Climate change ; Sustainable development ; Precipitation ; Soil moisture ; Surface water ; Runoff ; Water quality ; Water security ; Land use ; Land cover ; Remote sensing ; Moderate resolution imaging spectroradiometer ; Machine learning ; Evapotranspiration ; Ecosystems ; Vegetation ; Surface temperature ; Landsat / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H052061)
https://www.sciencedirect.com/science/article/pii/S0022169423006807/pdfft?md5=3de3b4a2f3076b4ebe97c67e18a7be87&pid=1-s2.0-S0022169423006807-main.pdf
https://vlibrary.iwmi.org/pdf/H052061.pdf
https://vlibrary.iwmi.org/pdf/H052061.pdf
(8.62 MB) (8.62 MB)
This paper provides an overview of the progress made in remote sensing of water resources in Africa, focusing on various applications such as precipitation estimation, land surface temperature analysis, soil moisture assessment, surface water extent measurement, surface runoff and streamflow analysis, water quality evaluation, land cover/land use mapping, and groundwater analysis. Specifically, the study sheds light on the remarkable progress made in remote sensing applications, showcasing scientific advancements and highlighting the challenges encountered. Moreover, it identifies crucial knowledge gaps that need to be addressed in order to further advance this field. The review's key findings indicate that the availability of sensors and observations, along with analytical models, has contributed to monitoring Africa's water resources at various scales. The availability and accessibility of hydrological data for monitoring and assessing water resources in Africa have been partially improved through the adoption of satellite data and processing technologies. Additionally, the emergence of various international remote sensing initiatives, North-South research collaborations, and projects has contributed to the research progress. Prominent satellite data series such as Landsat, MODIS, and GRACE have played significant roles in African hydrological research. However, the limited and malfunctioning in-situ hydrological monitoring networks in Africa have affected the accurate calibration and validation of remotely sensed hydrological models. Insufficient long-term rainfall and climate data pose challenges to long-term earth observation research on African water systems. The lack of high-resolution spatial and temporal data hampered accurate monitoring of hydrological processes at smaller scales. Despite the widespread use of rainfall satellite products, validation attempts over Africa, particularly in western and southern regions, have been limited. Furthermore, the reliability of hydrological satellite datasets is affected by factors such as the number and coverage of surface stations, retrieval algorithms, data integration techniques, and cloud cover. Overall, this work demonstrates the importance of earth observation in understanding Africa's hydrology, previously hindered by the lack of in-situ data. Nevertheless, efforts are therefore needed to enhance the adoption and application of remote sensing, particularly in groundwater and surface water estimation at smaller scales. Future research should focus on multi-source data integration, assimilation, and big data analytics using cloud computing and machine learning to address complex hydrological research questions at various scales.
10 Zeleke, T. T.; Giorgi, F.; Diro, G. T.; Zaitchik, B. F.; Giuliani, G.; Ayal, D.; Kassahun, T.; Sintayehu, W. D.; Demissie, T. 2023. Effect of urbanization on East African climate as simulated by coupled urban-climate model. Climate Services, 31:100398. (Online first) [doi: https://doi.org/10.1016/j.cliser.2023.100398]
Climate models ; Climate variability ; Climate change ; Urbanization ; Land cover change ; Land use ; Surface temperature ; Precipitation ; Evapotranspiration / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H052208)
https://www.sciencedirect.com/science/article/pii/S2405880723000596/pdfft?md5=05c8ce7dc28a558868d0846c9810d2b2&pid=1-s2.0-S2405880723000596-main.pdf
https://vlibrary.iwmi.org/pdf/H052208.pdf
https://vlibrary.iwmi.org/pdf/H052208.pdf
(17.10 MB) (17.1 MB)
This study examines the effect of urbanization on climate variability over East Africa. Seasonal trend of rainfall and temperature was analyzed using Mann-Kendall trend test and statistically significant rainfall trend is observed during spring (February-May) and summer (June-September) over northeast and spring/“bega”(October-January) seasons in southeastern regions of Ethiopia, thereby suggesting a seasonal shift of rainfall distribution. The temperature trend showed significant warming in the simulated field, except in central East Sudan, where there has been a significant decline. A numbers of idealized sensitivity experiments have been conducted with the Regional Climate Model (RegCM4.6) to investigate the contribution of urbanization to the East African region climate variability and trend. Model assessment against observed climate variables showed good performance in the simulation of spatial and temporal variability of regional climate variables. The results of the sensitivity experiment by prescribing different urban environments (tall building district (TBD), high density (HD), medium density (MD) and original land use) for the surface scheme (CLM4.5) reveal statistically significant impacts of urbanized surfaces on surface temperatures and precipitation due to variations in energy budget, local circulation and disturbance of hydro meteorological variables. It is noted that TBD urban environment has a higher impact on the local climate than other urban environments. Patterns of seasonal rainfall variability simulated using artificially urbanized land cover suggests involvement of complex interactions and is less similar to the observed rainfall trend, while surface temperature variability is significantly affected by local land-cover change and is very similar to the observed surface temperature trend.
11 Khamidov, M.; Ishchanov, J.; Hamidov, A.; Shermatov, E.; Gafurov, Zafar. 2023. Impact of soil surface temperature on changes in the groundwater level. Water, 15(21):3865. (Special issue: Climate and Water: Impacts of Climate Change on Hydrological Processes and Water Resources) [doi: https://doi.org/10.3390/w15213865]
Soil temperature ; Surface temperature ; Groundwater level ; Energy ; Foods ; Environmental factors ; Nexus approaches ; Regression analysis ; Precipitation ; Solar radiation ; Monitoring / Uzbekistan / Bukhara Region
(Location: IWMI HQ Call no: e-copy only Record No: H052401)
https://www.mdpi.com/2073-4441/15/21/3865/pdf?version=1699350450
https://vlibrary.iwmi.org/pdf/H052401.pdf
https://vlibrary.iwmi.org/pdf/H052401.pdf
(3.61 MB) (3.61 MB)
The relationship between the soil surface temperature and groundwater level is complex and influenced by various factors. As the soil surface temperature increases, water evaporates quickly from the soil, which can lead to a decrease in the groundwater level. In this study, we analyzed the impact of soil surface temperature on changes in the groundwater level in the Bukhara region of Uzbekistan using data from 1991 to 2020. The Bukhara region experiences regular water shortages, increased soil salinization, and inefficient energy in lift-irrigated areas, which is a typical constellation of challenges to the water–energy–food–environment (WEFE) nexus. The soil surface temperature data were collected from the Hydrometeorological Service Agency, whereas groundwater level data were obtained from the database of the Amelioration Expedition under the Amu-Bukhara Basin Irrigation Systems Authority. We used linear regression analysis and Analysis of Variance (ANOVA) tests to establish the significance of the relationship between the soil surface temperature and groundwater level, as well as the impact of the location of the groundwater level measurements. The results indicate that the model was a good fit to the data, and both the intercept and the soil surface temperature were significant factors that affected groundwater level. The results further suggest that the strength of the relationship between solar radiation and soil surface temperature is very high, with a correlation coefficient of 0.840. This means that when solar radiation increases, soil surface temperature also tends to increase. The analysis also showed that 53.5% of the changes in groundwater level were observed by the regression model, indicating a moderately correlated relationship between the groundwater level and soil surface temperature. Finally, higher solar radiation leads to higher soil surface temperature and higher evapotranspiration rates, which can lead to a decrease in groundwater level. As a result, we observe that the soil surface temperature determines changes in the groundwater level in the study region.
12 Keria, H.; Bensaci, E.; Zoubiri, A.; Si Said, Z. B. 2024. Long-term dynamics of remote sensing indicators to monitor the dynamism of ecosystems in arid and semi-arid areas: contributions to sustainable resource management. Journal of Water and Climate Change, jwc2024409. (Online first) [doi: https://doi.org/10.2166/wcc.2024.409]
Resource management ; Semi-arid zones ; Ecosystems ; Monitoring ; Indicators ; Remote sensing ; Climate change ; Biodiversity ; Vegetation index ; Surface temperature ; Watersheds / Algeria
(Location: IWMI HQ Call no: e-copy only Record No: H052720)
https://iwaponline.com/jwcc/article-pdf/doi/10.2166/wcc.2024.409/1383130/jwc2024409.pdf
https://vlibrary.iwmi.org/pdf/H052720.pdf
https://vlibrary.iwmi.org/pdf/H052720.pdf
(1.18 MB) (1.18 MB)
Drought is expected to increase in water bodies due to climate change. Monitoring long-term changes in wetlands is crucial for identifying fluctuations and conserving biodiversity. In this study, we assessed the long-term variability of remote sensing indicators in 25 watershed areas in Algeria known for their significant biodiversity. We employed two statistical methods, namely linear regression and the Mann–Kendall (MK) test, to capture long-term fluctuations by integrating data from various sources, including Modis and Landsat satellite data. A time-series dataset spanning 22 years was developed, consisting of the following indicators: normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), normalized difference water index (NDWI), normalized difference moisture index (NDMI), and land surface temperature (LST). We evaluated the relationships between these variables. The results indicated that NDVI exhibited a stronger temporal response compared to EVI, NDWI, and NDMI. Additionally, negative associations between NDVI and LST confirmed the impact of drought and plant stress on vegetation in the study areas (R2 = 0.109–R2 = 0.5701). The NDMI results pointed to water stress in the water bodies, showing a significant decreasing trend. The results from the MK trend analysis underscored the importance of NDVI and highlighted its strong association with EVI, NDWI, and NDMI. Understanding the dynamics of vegetation and water stress has become crucial for ecosystem forecasts.
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