ABSTRACT Global warming increases the potential risks of hydrological extremes, such as extreme precipitation and flood. Limited attention has been given to the integrated effects of climate change, land‐use change, and socioeconomic advancement on flood risk under global warming of 1.5°C and 2.0°C threshold outlined in the Paris Agreement. Here, utilizing the latest coupled model Intercomparison Project 6 (CMIP6), the new shared socioeconomic pathway scenarios (SSPs), hydrological model and future land use simulation (FLUS) model, we perform a comprehensive assessment of the flood risk in the Huai River Basin (HRB) under the global warming of 1.5°C and 2.0°C scenarios. The results reveal that (1) more intense extreme precipitation events will occur in the HRB under two global warming scenarios. The increases in extreme precipitation are approximately twice as high under 2.0°C than under 1.5°C global warming scenario; (2) under global warming of 1.5°C and 2.0°C scenarios, future 100‐year floods will increase by 18.4% and 19.2%, respectively, in the HRB; and (3) high flood‐risk areas are expected to primarily locate in regions with unfavorable flood regimes, with increases of 4.3% and 17.8%, and very high flood‐risk areas are projected to expand by 2% and 4.3%, respectively. Considering the holistic effects of future environmental changes on the flood risk, it is imperative to incorporate flood control management and prevention measures into regional adaptation strategies.

Land use configuration optimization based on ecosystem service enhancement in Xi'an City

As a core city in central China and a key node of the Changsha–Zhuzhou–Xiangtan (CZT) Metropolitan Area, Changsha has experienced profound territorial space restructuring amid rapid urbanization and high-quality development. This study focuses on the spatiotemporal evolution characteristics, driving mechanisms, and future optimization paths of production–living–ecological space (PLES) in Changsha, using three key time nodes: 2010, 2020, and 2025. Based on updated land use data (30 m spatial resolution), socioeconomic statistics, and the latest territorial spatial planning policies, we integrated multiple research methods including the land use transfer matrix, dynamic degree model, Logistic regression, and FLUS (Future Land Use Simulation) model. The results reveal the evolutionary law of PLES space from “rapid expansion” (2010–2020) to “quality improvement” (2020–2025) in Changsha and simulate the 2035 PLES layout under three scenarios (natural development, cultivated land protection, and ecological protection) incorporating rigid policy constraints such as urban development boundaries and ecological conservation red lines. This research provides updated scientific support for the coordinated and sustainable development of territorial space in new first-tier cities and metropolitan area cores.

Reduction planning has been implemented to mitigate urban sprawl in Chinese megacities. However, few studies have focused on the spatial implementation of urban land consolidation, and tools to estimate and simulate urban land consolidation are still lacking. To address the critical gap in urban land consolidation modeling, this study develops a bidirectional cellular automata model as a novel geospatial tool for quantifying consolidation potential and simulating future construction land dynamics under reduction planning. Our framework uniquely integrates high-resolution (30 m) simulation of simultaneous construction land expansion and reduction, overcoming limitations of conventional unidirectional models like the Future Land Use Simulation (FLUS) system, with validation confirming better accuracy. Using Beijing as a case study, the model identifies hotspots for land consolidation and, based on neighborhood-scale land transformation probabilities, delineates the spatial distribution of expansion and reduction zones, highlighting priority areas for consolidation. This provides the first operational tool for evidence-based urban reduction planning and land consolidation, offering a transferable methodology for optimizing land use efficiency and curbing disorderly expansion in megacities globally.

Regional carbon emissions are closely related to land use composition and its pattern. Optimizing the spatial distribution of land use is pivotal for reducing carbon emissions and enhancing carbon sequestration, thereby contributing to the achievement of the "carbon neutrality" goal in 2060. This study established a future land use simulation （FLUS） model of Guangzhou based on the land use change in 2015-2020 and optimally allocated the land uses in Guangzhou using the carbon emission coefficient method and the linear programming model, which was triggered by the goal of carbon neutrality. The integrated valuation of ecosystem services and trade-offs （InVEST） model was employed to assess the carbon emission and carbon storage of land uses in 2015-2020 and the optimized land use pattern for 2060 in Guangzhou. Adaptive strategies and suggestions were proposed to achieve carbon neutrality in Guangzhou. The findings are as follows： ① During the period of 2015-2020, land use changes in Guangzhou were characterized by the outward and infill expansion of urban land, occupying the surrounding farmland and ecological land. This resulted in a reduction of 2.4×106 t carbon emissions and 1.26×105 t carbon stock, with 89.02% of the land achieving carbon balance. ② Land use optimization under the 2060 carbon neutrality goal could greatly restrict land use conversion. The built-up land could increase by 17 038 hm2, predominantly through extension, while ecological land would increase by 6 521.68 hm2, mainly through the integration of small patches. Farmland would decrease by 23 446 hm2. ③ With the carbon neutrality target, the 2060 land use could reduce net carbon emission, accounting for 5.5% of that in 2015, and bolster carbon stock by an additional 1.12×105 t. The spatial effects of carbon emissions could be weakened, and 96.89% of the land would achieve carbon balance. This study contributes a robust scientific foundation, using Guangzhou as a reference towards a low-carbon urbanization, thereby promoting the attainment of carbon neutrality.

Exploring future land use changes in river basins and assessing habitat quality are crucial for ensuring the sustainable development of basin ecosystems. Based on land use data from 2000 to 2020 in the Hutuo River Basin, this study applied the future land use simulation （FLUS）-integrated valuation of ecosystem services and tradeoffs （InVEST） model to simulate and analyze the spatial-temporal evolution characteristics of land use and habitat quality in the basin from 2030 to 2070 under typical shared socioeconomic pathway （SSPs）-representative concentration pathway （RCPs） scenarios （SSP1-2.6, SSP2-4.5, and SSP5-8.5）. The results indicate that： The primary land use types in the Hutuo River Basin were cropland, grassland, and forest land, with cropland and grassland continuously converting into construction land in densely populated areas over the 20-year period. Under the SSP1-2.6 and SSP2-4.5 scenarios, cropland and grassland decreased, while forest land and construction land increased, with SSP1-2.6 exhibiting the greatest reduction in cropland and the highest increase in forest land. Under the SSP5-8.5 scenario, construction land expanded continuously and intensively. The overall habitat quality in the Hutuo River Basin demonstrated a spatial distribution pattern of "high in the central region and low in the periphery." Habitat quality declined continuously over the 20-year period, with more severe degradation from 2000 to 2010 and a slight mitigation in the degradation rate from 2010 to 2020. Under the SSP1-2.6 scenario, overall habitat quality in the basin improved, whereas it declined under the SSP2-4.5 and SSP5-8.5 scenarios, with the most pronounced decline observed under the SSP5-8.5 scenario. The SSP1-2.6 and SSP5-8.5 scenarios primarily showed an increase in hotspots and coldspots, respectively. These findings provide valuable insights for enhancing habitat quality in the basin and promoting the synergistic development of ecological and economic systems in the future.

ABSTRACT Land use and cover change (LUCC) is the predominant factor contributing to changes in ecosystem carbon storage (ECS). Studying the relationship between LUCC and ECS is crucial for optimizing regional land use patterns and making informed ecological decisions. However, despite the growing body of research on LUCC and its impact on ECS, there is still a significant gap in understanding the continuous, large‐scale dynamics of ECS over extended periods and the detailed interactions between human activities and climate change in influencing ECS. This study aims to address these gaps by focusing on the comprehensive analysis of ECS dynamics in western China from 1990 to 2020 and predicting LUCC under various future scenarios. This study explored the changes in ECS and its response to LUCC in western China from 1990 to 2020 and predicted LUCC under various projected scenarios: Natural development scenario (NDS), cropland protection scenario (CPS), and ecological priority scenario (EPS) in 2030 using the future land use simulation (FLUS) model. LUCC has a profound landscape reshaping, marked by a retreat of cultivated land and grassland, and the inexorable expansion of built‐up areas. The spatial distribution of ECS exhibited clear clustering, with overall characteristics of “high in the west and south, and low in the east and north,” closely linked to LUCC patterns and topography. In contrast, low ECS areas are often at higher elevations. ECS in Shanxi Province declined from 226.57 Gt in 1990 to 225.59 Gt in 2020, reflecting a loss of 0.98 Gt, largely driven by rapid urban expansion that converted cropland, forest, and grassland. FLUS‐based simulations in 2030 are 224.88 Gt under NDS, 225.41 Gt under CPS, and 227.12 Gt under EPS, indicating that an ecological priority land use pathway best supports carbon storage recovery. Additionally, the analysis of net primary productivity (NPP) reveals significant influences from both human activities and climate change, with the adverse effects of human activities on NPP being more widespread and pronounced than those of climate factors. These findings offer valuable insights for future urban planning and ecological security strategies in the main urban energy areas.

Accurate prediction of land use and land cover (LULC) change is essential for sustainable development and climate change adaptation planning. This study projects LULC changes across 17 administrative regions of South Korea from 2020 to 2050 using the Future Land Use Simulation (FLUS) model under four integrated SSP-RCP scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The model was calibrated with land cover data for 2000–2010 and validated against observations for 2010–2020 using socioeconomic variables together with CMIP6 climate projections. In practical terms, FLUS produces scenario-based maps of future land patterns that inform land regulation, infrastructure planning, and climate adaptation. Across all scenarios, urban areas expanded by 488,000–585,000 ha, mainly through the conversion of agricultural land, which accounted for 10–24% of transitions in high-growth regions. Agricultural land decreased by 124,000–174,000 ha, and forests declined by 473,000–572,000 ha. Transformation intensity peaked around 2030 and then slowed in later decades. Urban expansion was greatest under SSP5-8.5, followed by SSP3-7.0, SSP1-2.6, and SSP2-4.5. Gyeonggi Province exhibited the most pronounced spatial change, whereas Seoul showed limited additional growth consistent with its already saturated urban structure. Validation results indicated an overall accuracy range of 57–83% with metropolitan areas generally outperforming provincial regions. These findings reveal spatial and temporal hotspots of land cover change and provide region-specific information that can guide urban development, land and ecosystem management, climate adaptation policy, and progress toward carbon neutrality.

Ecosystem services play a crucial role in sustaining human life, providing numerous benefits that are indispensable for our well-being. However, these vital functions are increasingly compromised by land use changes that have been instigated by human activities. This study aims to evaluate the spatiotemporal variability of ecosystem service value (ESV) within the urban agglomeration located on the northern slope of the Tianshan Mountains over a historical period stretching from 1990 to 2020, utilizing land use data to conduct a thorough analysis. Subsequently, the Future Land Use Simulation (FLUS) model was employed to forecast ESV in 2030 under three developmental pathways: Ecological Protection Scenario (EPS), Cultivated Land Protection Scenario (CLPS), and Natural Development Scenario (NDS). The evaluation incorporated six primary land classes: cultivated land, forest land, grassland, water bodies, construction land, and unused land. The FLUS model was validated with strong accuracy (overall accuracy = 0.97, Kappa = 0.94). ESV was estimated using the value coefficient method based on equivalent factors, adjusted with a local economic coefficient for crop production. All values are expressed in constant 2020 CNY without further price normalization. Our results show that between 1990 and 2020, cultivated land expanded by 27.18% (17,721 to 22,538 km2) and construction land increased by 75.91% (1926 to 3388 km2), while grassland decreased from 63,502 to 59,027 km2 and unused land declined from 106,292 to 104,690 km2. Minor changes occurred in forest land and water bodies. Total ESV decreased from 679.06 × 108 CNY in 1990 to 657.67 × 108 CNY in 2020, a decline of 3.15%. Regulating, supporting, and cultural services all decreased, while provisioning services increased. Spatially, vegetated areas functioned as ESV hot spots, whereas construction-degraded areas were identified as cold spots. Scenario projections for 2030 show that under the CLPS and NDS, ESV would further decline by 11.49 × 108 CNY (−1.75%) and 10.18 × 108 CNY (−1.55%), respectively. In contrast, the EPS is projected to increase ESV by 4.53 × 108 CNY (+0.69%), reaching 662.20 × 108 CNY.

A comprehensive understanding of the spatiotemporal dynamics of ecosystem service (ES) availability and use is essential for effective management and equitable urban development globally. This study used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to evaluate the supply-demand relationships of water conservation, soil conservation, carbon storage, and habitat quality in Guangzhou from 2000 to 2020. Spatial mismatches under three land-use scenarios-natural development (NDS), urban development (UDS), and ecological protection (EPS)-were also simulated using the Future Land Use Simulation (FLUS) model to predict landscape changes. The results showed a consistent increase in ES demand alongside a decline in supply with a significant supply-demand imbalance observed for all services except soil conservation. Additionally, spatial variations in ES supply and demand were evident across the three scenarios, with the EPS scenario providing the highest level of ES supply compared to NDS and UDS. These findings provide a scientific basis for urban planning and sustainable development in Guangzhou and comparable cities worldwide.

Understanding the drivers of water yield (WY) changes in ecologically sensitive, data-scarce watersheds is crucial for sustainable management, particularly in the context of accelerating forest expansion and urbanization. This study focuses on the upper Yellow River Basin (UYRB), a critical headwater region that supplies 60% of the Yellow River’s flow and is undergoing rapid land use transitions from 1990 to 2100. Using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and the Future Land-Use Simulation (FLUS) model, we quantify historical (1990–2020) and projected (2025–2100) WY dynamics under three SSP scenarios (SSP126, SSP370, and SSP585). InVEST, a spatially explicit ecohydrological model based on the Budyko framework, estimates WY by balancing precipitation and evapotranspiration. The FLUS model combines cellular automata (CA) with an artificial neural network (ANN)-based suitability evaluation and Markov chain-derived transition probabilities to simulate land-use change under multiple scenarios. Results show that WY increased significantly during the historical period (1990–2020), primarily driven by increased precipitation, with climate change accounting for 94% and land-use change for 6% of the total variation in WY. Under future scenarios (SSP126, SSP370, and SSP585), WY is projected to increase to 217 mm, 206 mm, and 201 mm, respectively. Meanwhile, the influence of land-use change is expected to diminish, with its contribution decreasing to 9.1%, 5.7%, and 3.1% under SSP126, SSP370, and SSP585, respectively. This decrease reflects the increasing strength of climate signals (especially extreme precipitation and evaporative demand), which masks the hydrological impacts of land-use transitions. These findings highlight the dominant role of climate change, the scenario-dependent effects of land-use change, and the urgent need for integrated climate–land management strategies in forest-urbanizing watersheds.

To explore the impact of land use change on carbon storage, taking Huainan City as an example, the future land use simulation （FLUS） model was used to simulate the spatial distribution of land use in 2030 under the inertia development scenario, farmland protection scenario, and ecological priority scenario. By combining this result with the integrated valuation of ecosystem services and trade-offs （InVEST） model, the carbon storage of the three scenarios in 1990, 2000, 2010, 2020, and 2030 was estimated. The study produced the following results： ① The main land type in Huainan City is cropland, which accounts for more than 75% of the total area. From 1990 to 2020, the area of cropland, grassland, and forest land in Huainan City continued to decrease, while the area of construction land continued to increase. The main land type transfer was the conversion of cropland to construction land. Compared with the other scenarios, the farmland protection scenario can better promote the increase of farmland area and effectively suppress the expansion of construction land. ② From 1990 to 2020, the carbon storage in Huainan City decreased by 8.29×105 t, with a continuous decreasing trend. Cropland was the main carbon reservoir in Huainan City, and the conversion of cropland to construction land was the main reason for the decrease in carbon storage in Huainan City. ③ The carbon stocks in Huainan City under the 2030 inertia development scenario, cropland protection scenario, and ecological priority scenario are 50 766×103, 50 822.21×103, and 50 597.95×103 t, respectively. The carbon storage decreases compared to the level in 2020 under the three scenarios, among which the cropland protection scenario has the most significant inhibitory effect on the reduction of carbon storage. In the future, prioritizing the protection of cropland should be considered.

Habitat quality (HQ) is recognized as a significant factor in biodiversity maintenance and ecological conservation advancement, and the land-use cover change (LUCC) can directly affect the spatial pattern and evolution of HQ. Land-use datasets spanning 2010, 2015, and 2020 were analyzed through the integrated application of the future land-use simulation (FLUS) model and the integrated valuation of ecosystem services and trade-offs (InVEST) model, supplemented by multiple analytical indicators, resulting in LUCC patterns and HQ variations being investigated within the urban agglomeration along the Yellow River in Ningxia, China. These findings demonstrate (Hall, Wiley on behalf of the Wildlife Society, 1997, 25(1), 173–82) a reduction in ecological land coverage during the previous period, which correlates with a decrease in the mean HQ. The value ratings in 2010, 2015, and 2020 were 0.4919, 0.4730, and 0.4654, respectively. Moreover, the evolution characteristics exhibited distinct divergence trends between the periods of 2010–2015 and 2015–2020. The spatial distribution showed a pronounced periphery–core gradient (Fahrig, Eution, and Systematics, 2017, 48(1), 1–23). The study area’s HQ was categorized within the moderate-to-good range, with mean values demonstrating a descending sequence: EPS (0.5348) > NDS (0.5165) > FSS (0.4967) > EDS (0.4681). Optimal ecosystem service performance was observed in the Helan Mountain Nature Reserve and Yellow River mainstream (Alaniz et al., Ecological Indicators, 2021, 126). Scenario modeling revealed that ecological conservation measures effectively enhanced biodiversity preservation and ecosystem service capacity. Scenario optimization was determined through the combined evaluation of ecological resource support limit and territorial development suitability. Multi-scenario methods and environmental simulation models were integrated in this study, enabling a more accurate assessment of the landscape spatiotemporal pattern. This approach provides decision-making insights and multiple perspectives for spatial planning under different developmental goal orientations.

Ecosystem services (ESs) are a life-support system for human development that are also a strategic root for realizing global ecological security and sustainable development. In this study, the spatial distribution pattern of land-use and ESs under three scenarios (an ecological protection scenario (EPS), a natural development scenario (NDS), and a cropland protection scenario (CPS)) in the Tarim River Basin (TRB), Northwest China, is predicted for 2035 using the Future Land-Use Simulation (FLUS)–Integrated Valuation of ESs and Trade-Offs (InVEST) model. Land-use data from 2000 to 2023 are utilized as the basic data, and the spatial and temporal characteristics of land-use and multiple ESs under different scenarios are explored. The results show that (1) the land-use structure of the TRB is dominated by barren land (55.12%) and grassland (30.28%), and the dynamic evolution of the land-use pattern from 2000 to 2023 is characterized by the continuous shrinkage of the area of barren land and the expansion of impervious surfaces, cropland, water bodies, and other productive and living land and water. (2) According to the prediction results of the FLUS model, the different scenarios of land-use for 2020–2035 show various change trends. In the EPS, the proportion of ecological land jumps to 35.23%, while production land and living land show a systematic contraction. Under the NDS, water bodies, grassland, and impervious surfaces experience a decreasing trend, whereas cropland, forest land, and barren land increase in area. Under the CPS, the trend of shrinkage for ecological land accelerates, especially the fragmentation of forest patches (shrinking by 24 km2) and the expansion of cropland and barren land. (3) A comparison and an analysis of the ESs in several scenarios for 2035 show an increase in ESs under the EPS compared with those in 2020, along with a marked improvement in the TRB’s future ecological environment under this scenario. By adhering to the guidance of ecological priority through optimization of the national spatial pattern and the integration of ecological elements, the dynamic balance between ecological protection and economic development can be effectively coordinated, providing core support for the sustainable development of the region. (4) Ecosystem services are significantly impacted by changes in grassland in a variety of settings, particularly in the NDS. Contradictory trade-offs between ecological functions are revealed in the CPS, where cropland expansion promotes soil conservation but worsens the degradation of grassland. In the EPS, the synergistic expansion of grassland and water favorably regulates ecosystem services. A major way to increase the capacity of regional ecosystem services and accomplish sustainable development is to optimize the land-use for ecological preservation, with an emphasis on increasing the acreage of grassland, forest, and water while decreasing the area of cropland and barren.

Scenario forecasting of carbon neutrality by combining the LEAP model and future land-use simulation: An empirical study of Shenzhen, China

Urban flood susceptibility has emerged as a critical challenge for cities worldwide, exacerbated by rapid urbanization. This study evaluates urban flood susceptibility under different Shared Socioeconomic Pathways (SSPs) in the context of urbanization. A coupled modeling approach integrating the System Dynamics (SD) model and the Future Land Use Simulation (FLUS) model was employed to project future land use changes under sustainable development, moderate development, and conventional development scenarios. Additionally, an XGBoost model was developed to assess urban flood susceptibility. The results indicate that urban construction land will continue to increase over the next 30 years, with the extent of growth varying across different scenarios. Notably, under the conventional development scenario, rapid economic growth leads to a significant expansion of built-up land and a sharp decline in ecological land, which in turn exacerbates the urban flood susceptibility. Consequently, urban flood susceptibility is projected to increase across all three scenarios, albeit at varying rates. Specifically, under the sustainable development scenario, 27% of Guangzhou is projected to face high flood risk. In the moderate development scenario, the area classified as high-risk increased by 868.73 km2. Under the conventional development scenario, the high-risk area expanded from 1282.9 km2 in 2020 to 2761.33 km2, representing a 16% increase. These differences are primarily attributed to changes in land use, which alter surface runoff and subsequently enhance the city’s vulnerability to waterlogging. This study provides a comprehensive framework for assessing urban flood susceptibility in the context of urbanization, offering valuable insights for formulating targeted flood prevention and mitigation strategies.

Land use conflicts represent an increasing challenge to sustainable development, particularly in regions undergoing rapid urbanization. This study investigated the spatiotemporal dynamics of land use conflicts and their ecological implications in Tianshui City from 1980 to 2020. The main objectives were to identify patterns of spatial heterogeneity, explore the driving factors behind these conflicts, and analyze their relationship with the ecological risks. The results indicate the following findings. In terms of spatiotemporal heterogeneity, early land use changes were primarily driven by structural factors, such as topography and climate, with a Nugget/Still ratio of <0.30 observed from 1980 to 2000. After 2000, however, stochastic factors, including an average annual urbanization rate increase of 5.2% and a GDP growth rate of 9.1%, emerged as the dominant drivers, as reflected in a Nugget/Still ratio > 0.36. Regarding conflict intensity, high-conflict areas expanded by approximately 1110 square kilometers between 1980 and 2020, predominantly concentrated in fertile agricultural regions such as the Weihe River Basin and urban core areas. Conversely, non-conflict zones decreased by 38.7%. In terms of ecological risk correlation, bivariate LISA cluster analysis revealed a significant spatial autocorrelation between severe land use conflicts and ecological risks (Moran’s I = 0.62, p < 0.01). High-risk clusters in areas transitioning from arable land to built-up land increased by 23% after 2000. Predictions based on the future land-use simulation (FLUS) model suggest that by 2030, high-intensity conflict areas will expand by an additional 16%, leading to intensified competition for land resources. Therefore, incorporating ecological safety thresholds into land spatial planning policies is essential for reconciling the conflicts between development and conservation, thereby promoting sustainable land use transitions.

Protective forests are vital to ecological security in arid desert regions, but their spatial distribution is often inefficient. This study aims to optimize the spatial distribution of protective forests in Alaer City using a combination of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and the Future Land Use Simulation (FLUS) model. The optimization focuses on three objectives: economic benefits, ecological benefits, and food security. A neural network model is applied to analyze forest distribution suitability based on spatial factors. The results show that the optimized distribution significantly enhances GDP, carbon sequestration, water yield, and food production, while reducing soil erosion. The forest area is mainly concentrated along rivers, agricultural fields, and desert edges, with increased coverage at the Taklamakan Desert’s periphery improving wind and sand resistance. The FLUS model is validated with high accuracy (90.73%). This study provides a theoretical foundation for the sustainable development of protective forests, balancing ecological and economic goals in Alaer City.

Future land use simulation modeling for sustainable urban development under the shared socioeconomic pathways in West African megacities: Insights from Greater Accra Region.

Land use changes profoundly affect hydrological processes and water quality at various scales, necessitating a comprehensive understanding of sustainable water resource management. This paper investigates the implications of land use alterations in the Gap-Cheon watershed, analyzing data from 2012 and 2022 and predicting changes up to 2052 using the Future Land Use Simulation (FLUS) model. The study employs the Hydrological Simulation Program-FORTRAN (HSPF) model to assess water quantity and quality dynamics. Seven land use classes were identified, and their evolution was examined, revealing significant shifts in urban, agricultural, grassland, wetland, and forested areas. The model performance across observed data was evaluated using coefficient of determination (R2), percent bias (PBAIS), and mean absolute error (MAE). Results show the dynamic nature of land use changes, highlighting shifts in urbanization, agriculture, and forested areas. Notably, the study explores the consequences of these changes on water quantity and quality, scrutinizing surface runoff, evapotranspiration, stream flow, and nutrient loads. Urban green spaces emerge as key mitigators, regulating runoff and enhancing water absorption. Forests (vegetation) also play a crucial role in maintaining water balance, while wetlands act as natural filters for flood mitigation and water quality improvement. The findings underscore the importance of informed land use planning, recognizing urban green spaces, forests, and wetlands as integral components for sustainable watershed management. As society navigates environmental challenges, this research contributes to a deeper understanding of the complex interactions between human activities and the natural environment emphasizing the need for nature-based solutions in land use planning for resilient and balanced ecosystems.