NPP 时空 MGWR 丹江口

Vegetation photosynthesis is a key Earth system process that can fix carbon dioxide in the atmosphere. Mountainous areas usually have high productivity and extensive vegetation cover, but their study requires a higher spatiotemporal resolution due to the complex climate and vegetation variations with altitude. In this study, we analyzed the variations and climatic responses of vegetation gross primary productivity (GPP) in northwestern Hubei, China, at a 30 m spatial resolution from 2001 to 2020, based on the fusion of multi-source remote sensing data. A GPP estimation framework based on the CASA model was applied, and spatiotemporal fusion of Landsat and MODIS data was achieved using the STNLFFM algorithm. The results indicate that GPP exhibits higher values in the mountainous regions of west Shennongjia, compared to the eastern plain regions, with a generally increasing trend with increasing elevation. GPP has shown an overall increasing trend over the past 20 years, with almost 90% of the high-elevation regions showing an increasing trend, and the low-elevation regions showing an opposite trend. The relationship between GPP and climate factors is greatly impacted by the temporal scale, with the most pronounced correlation at a seasonal scale. The impact of temperature has been generally stable over the past 20 years across different altitudes, while the relationship with precipitation has exhibited an overall decreasing trend with the increase of altitude. Precipitation and temperature correlations show opposing variations in different months and elevations, which can be mainly attributed to the varied climatic conditions in the different elevations.

Reservoir ecosystems are under increasing pressure from ecological degradation and land-use conflict. This study proposes an integrated framework combining ecosystem service (ES) evaluation, trade-off analysis, and service bundling to support ecological functional zoning in the Danjiangkou Reservoir Area, a key water source in China. Six ESs were assessed from 2010 to 2023, revealing spatial heterogeneity and rising trends in water- and climate-related services. Over time, ES interactions shifted from trade-off dominance to synergy, indicating improved ecological coordination. Cluster analysis identified two ES bundles in 2010 and four stable bundles after 2015. Based on bundle composition and inter-service dynamics, four functional zones were delineated: regulation protection, restoration priority, agricultural production core, and water yield–conservation core. These zones reflect dominant ES structures and offer a practical basis for differentiated, adaptive ecosystem management in reservoir regions. The proposed method provides a transferable tool for ecological zoning in data-rich reservoir watersheds, offering new insights for adaptive ecosystem governance.

The long‐term dynamics of ecosystem services (ESs) under the intervention of large‐scale water diversion and ecological restoration projects remain poorly understood, especially the dynamic evolution laws under their interaction, which is a major challenge for basin management. To address this research gap, this study explores the complex trade‐offs and synergies between ecosystem services (ESs) and their drivers in the Hanjiang River Basin, influenced by water diversion and ecological restoration projects. A novel framework combining Bayesian network modeling and node sensitivity analysis was applied to link four key ESs—water yield (WY), carbon storage (CS), habitat quality (HQ), and sediment delivery ratio (SDR). Multiple‐scenario‐based ecosystem optimization and recommendations for ecological restoration in the Hanjiang River Basin are also provided. The results show that due to altered precipitation patterns and water diversion from the South‐to‐North Project, WY has shown significant spatial reorganization. CS, HQ, and SDR have remained relatively stable due to ecological restoration. ESs respond to land‐use changes with a time lag. At the regional level, trade‐offs are more common in southern sub‐basins, while synergies are predominant in western and northern areas. SDR shows synergies with WY, HQ, and CS, whereas WY exhibits trade‐offs with CS and HQ. When trade‐offs and synergies among ecosystem services are at a low level, their relationships tend to alternate over time. Population, land‐use changes, and climatic factors more significantly impact trade‐off relationships. In contrast, land use and slope have a more substantial effect on synergy relationships. Upstream inter‐basin water transfer areas and central erosion‐prone regions are identified as key zones for future ES optimization. This study outlines the state and spatial patterns of environmental drivers across various trade‐offs and synergies, offering insights for sustainable spatial planning and management.

… to NPP; precipitation patterns exert an influence on water supply and hydrological adjusting; soil conservation is tied to precipitation. As a result, we can utilize NPP, … and Danjiangkou …

Maintaining an optimal eco-environment is important for sustainable regional development. However, existing methods are inadequate for examining both spatial and temporal dimensions. Here, we propose a systematic procedure for spatiotemporal examination of the eco-environment using the space-time cube (STC) model and describe a preliminary investigation of the coupling relationships between basin ecological quality and water eutrophication in upstream of the Han River basin between 2000 and 2020. The STC model considers the temporal dimension as the third dimension in calculations. We first categorized the basin into three sub-watershed types: forest, cultivated land, and artificial surface. Subsequently, the ecological quality and driving factors were assessed and identified using the remote sensing ecological index (RSEI) and Geodetector method, respectively. The findings indicated that the forest basin and artificial surface basin had the highest and lowest ecological quality, respectively. The spatiotemporal cold spots of ecological quality during the past 20 years were mostly located in the vicinity of reservoirs, rivers, and artificial surface areas. Human activity, precipitation, and the percentage of cultivated land were other important driving factors in the artificial surface, forest, and cultivated land sub-watersheds, respectively, in addition to the dominant factors of elevation and temperature. The results also indicated that when the ecological quality degraded to a certain extent, water eutrophication was significantly coupled with the ecological quality of the catchments. The findings of this study are useful for ecological restoration and sustainable river basin development.

… The results showed that (1) apart from NPP, which increased … high synergistic relationships, NPP showed mostly trade-off … More importantly, the Danjiangkou Reservoir, located in the …

… situ NPP and MODIS-NPP (figure A1). The deviation analysis between the MODIS … spatial-temporal change and trade-off/synergy relationships of ecosystem services in the …

Inter-basin water transfer projects (IBWT) are a key strategy for alleviating regional water shortages. However, studies on the long-term effects of such projects on ecosystem services (ESs) in water source areas, as well as their spatiotemporal evolution, remain insufficient. In particular, the specific impacts of the entire project lifecycle (project initiation, dam heightening, project operation, and ecological restoration) on ESs need further exploration. This study focuses on the Middle Route of the South-to-North Water Diversion Project in China, utilizing multi-source datasets (land use and land cover, meteorological data, soil texture, digital elevation models, normalized difference vegetation index, and net primary productivity), applying the biophysical model method to examine the spatiotemporal variations in ESs across the Hanjiang River Basin over the past three decades, and investigates the impact of IBWT on the ESs of water source areas. The findings reveal: (1) During the project initiation phase (2000–2010), vegetation restoration strategies enhanced soil retention by over 60%, demonstrating that simultaneous project-ecological implementation can mitigate habitat degradation risks. (2) The dam heightening phase (2005–2010) drove spatial reconfiguration of water-energy fluxes, leading to declines in water conservation and carbon sequestration in the midstream region, while enhancing flood mitigation and climate regulation in the reservoir area, unveiling the reshaping mechanisms of dam heightening on ESs supply patterns. (3) The operation phase exhibited significant temporal heterogeneity: initial operation (2010–2015) saw a sharp decline in water conservation (>40%) and soil retention (>60%) due to hydrological disturbances, whereas sustained operation (2015–2020) restored water conservation by nearly 70% and soil retention by over 40% through ecological restoration, alongside a net increase of 14.14% in carbon sequestration, confirming the time-lag compensation effects of restoration measures and the dynamic interplay between ecological restoration and project interventions. This research presents empirical evidence supporting the sustainable management and ecological restoration of IBWT, emphasizing the need to balance spatial water allocation with ecological conservation.

The Danjiangkou Reservoir (DR) serves as the primary water source for the Middle Route of China’s South-to-North Water Diversion Project (SNWDP), and its ecological security (ES) is critical to water supply safety in North China and to broader regional sustainability. However, systematic assessments of ES in the DR region remain limited. In this study, a health–risk–service framework was developed to evaluate the evolution of the ecological security in DR across three benchmark years (2003, 2013, and 2023). Furthermore, the XGBoost–SHAP model was employed to uncover the dominant natural, anthropogenic, and landscape influential factors behind ES variation. The results indicate that: (1) The proposed framework effectively captures the ES status of DR, with a strong correlation between ecological security index (ESI) and remote sensing ecological index (RSEI) (R² > 0.8, P < 0.001); (2) ESI exhibited a fluctuating upward trend over time, with over 95% of the area classified as Medium or above in terms of ecological security. The ESI hotspots were primarily distributed in the northern and southern regions, which are dominated by forest cover, whereas the cold spots were mainly concentrated in the central region, characterized by cropland and built-up land; (3) Results from the XGBoost–SHAP model revealed that ESI is influenced by multiple factors in a nonlinear fashion. NDVI and LPI were the primary positive contributors, whereas HDI and urbanization had negative impacts, with all these relationships exhibiting nonlinear threshold effects. Notably, threshold effects were identified within specific ranges of these variables. This framework provides a practical approach for evaluating ESI in reservoir regions and offers a scientific foundation for ecological protection and source-area ecological security management in cross-basin water diversion projects such as the DR.

The Hanjiang River Basin (HJRB) encompasses the Danjiangkou Reservoir, a critical water source for the South-to-North Water Transfer project, the world’s largest such endeavor. Recent studies have highlighted that increased vegetation growth in the HJRB has led to reduced water availability in the region. To investigate the seasonal dynamics and spatial patterns of vegetation and their association with the local climate, we employed Gross Primary Productivity (GPP), a pivotal component of terrestrial carbon-water cycling, derived from the MODIS MOD17A2HGF dataset at a 500 m resolution. We combined this dataset with station meteorological data and the Standardized Precipitation Evapotranspiration Index (SPEI) to explore the complex relationship between vegetation productivity, climate fluctuations, and hydrothermal changes in the HJRB from 2000 to 2020. Our findings reveal that the rising trend in vegetation productivity in the HJRB is primarily attributable to climate warming. Different types of vegetation in the upstream and downstream areas exhibit varying water requirements. While the region has not experienced prolonged widespread drought conditions thanks to its excellent water conservation capabilities, there remains a certain level of drought risk in the downstream area as the climate continues to warm. Moreover, variables such as wind speed and sunshine duration significantly impact the hydrothermal conditions within the river basin, consequently influencing vegetation productivity. This study elucidates the mechanisms through which climate change affects vegetation productivity in the HJRB. Despite afforestation efforts in the upstream region and climate warming leading to increased greening, there may be implications for the water retention function of the HJRB. This understanding is crucial for water resource management and ecosystem sustainability in the HJRB.

Investigating the interplay between vegetation, climate change, and anthropogenic activities is essential for advancing global environmental research. The Hanjiang River Basin exhibits heightened susceptibility to anthropogenic influences that markedly alter its ecological dynamics. This study utilized MODIS NDVI data (2002-2022) alongside precipitation and temperature data to evaluate the distinct impacts of climatic factors and anthropogenic activities on NDVI variability by applying Pearson correlation and residual analysis. Additionally, the partial derivatives method quantified the individual contributions of each factor to NDVI changes. The research revealed that NDVI exhibited a consistent upward trend, particularly in the western regions, while urbanization in the mid-to-lower reaches, especially around Wuhan city, led to vegetation degradation. Mean NDVI increased from 0.8067 to 0.8467 between 2002 and 2022, corresponding to an average rate of 0.002 NDVI units per year. Temperature emerged as the primary climatic driver of NDVI fluctuations, with precipitation impacts varying across the basin. However, human activities were found to exert a more significant influence on vegetation dynamics than climatic factors. Hurst index analysis predicted a positive future trend in 58.11 % of the basin, but 41.89 % may face further degradation. This study highlights the dual effects of anthropogenic activities on vegetation under climate change, providing theoretical insights for robust ecological management and sustainable development strategies within the study area.

Water-use efficiency (WUE) and carbon-use efficiency (CUE) are critical indicators of ecosystem function and hydrologic processes, reflecting the water-carbon flux exchange rate. Climatic variables, land use and land cover change (LUCC) and water diversion project (WDP) have altered water-carbon cycle; however, their roles in modulating WUE and CUE remain uncertain. To explore these effects, a framework is proposed and Han River basin (HRB) in China is selected as a case study including the data sets from both remote sensing and in situ observations during 2000-2020. The process-based Regional Hydro-Ecological Simulation System model and a supervised machine learning model are applied to simulate the impacts of climatic variables, LUCC and WDP on WUE and CUE, which are conducted by designing four experiments. We find that no significant WUE and CUE trends attributed to contrasting trends in the dry (October to March) and wet (April to September) seasons. Temperature variations greatly affect WUE and CUE, with WUE decreasing in the wet season and increasing in the dry season due to minimum temperature changes. LUCC has litter impacts on WUE and CUE changes. From 2014 to 2020, the middle route of the South-to-North WDP decreased WUE by 0.22 gCkg-1H2O in the middle-low HRB's wet season, slightly affecting CUE. Seasonal CUE was stable, with the largest decrease of 0.04 in the upper HRB during the wet season. The WDP also increased WUE sensitivities to minimum and maximum temperatures, while CUE sensitivities remained constant. Our case study has proven that the proposed framework is an effective way to understand the roles of climate change and WDP in modulating WUE and CUE.

… The boundary between these 360 regions is defined by the Danjiangkou Reservoir, with the Huangjiagang 361 hydrological station monitoring discharges from this reservoir (D. Liu et …

The impacts of different driving factors on ecosystem health involve complex nonlinear response mechanism. Here, we focus on northwest Hubei Province in China, an ecologically …

… 国内外对 NEP 的研究主要借助 CASA 和 TEC 模 型,且集中在对其时间动态,影响因素及不确定 性… ecosystems in China using an improved CASA model and soil respiration model[J]. IEEE …

The Hanjiang River Basin (HJRB) is an important water conservation and ecological barrier area for the South–North Water Transfer Central Project. The quantitative analysis of regional differences in vegetation changes and their main drivers is important for the monitoring of the ecological environment of the basin and formulation of ecological protection measures. Based on MODIS13Q1 data from 2000 to 2020, spatiotemporal variation characteristics of vegetation in the HJRB were analyzed using Theil–Sen + Mann–Kendall, the Hurst index, and correlation analysis. Then, we detected the drivers using an optimal parameter geographic detector. The results showed that from 2000 to 2020, the average NDVI value increased from 0.651 to 0.737, with a spatial distribution pattern of “high in the northwest and low in the southeast”, and 88.68% of the study area showed an increase in vegetation cover, while 5.80% showed a significant degradation. The positive persistence of future vegetation changes is stronger than the negative. It may show a slowdown or degradation trend, among which the vegetation restoration along the Han River and urbanized areas need to be strengthened. The factor detector indicated that the main factors influencing vegetation change were topography and climate, for which the most influential variables, respectively, were elevation (0.1979), landform (0.1720), slope (0.1647), and soil type (0.1094), with weaker influence from human activity factors. The interaction test results showed that the interaction of various geographic factors enhanced the explanatory power of vegetation changes and showed mainly nonlinear and two-factor enhancements. The dominant factor varies between sub-basins; for example, the interaction between wind speed and land use conversion was the dominant factor in the middle reaches of the HJRB; the dominant factor in the lower reaches of the HJRB was expressed as the interaction between land use conversion and temperature. Finally, the effects of the range or category of different drivers on vegetation growth were systematically analyzed. The results of the study contribute to the understanding of the dynamic changes of vegetation based on a comprehensive consideration of the interaction of topography, climate, and human activities, taking into account the totality and variability of the geographical environment, and provide a reference for the ecological restoration and rational use of vegetation resources in the HJRB.

ABSTRACT The Daning River Basin is a typical representative of the ‘mountain forest’ in the Three Gorges Reservoir (TGR) area of the Yangtze River. In recent years, with the completion of the Three Gorges Project, the local vegetation has degraded, soil erosion has become severe, and there is an urgent need to assess the environmental quality. Data were fused using the MODIS Normalized Difference Vegetation Index (NDVI) (250 m) and Landsat NDVI (30 m) through an Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) to obtain ESTARFM NDVI (30 m). This data was then entered into the Carnegie Ames Stanford Approach (CASA) model, along with meteorological and land use data, to calculate vegetation net primary productivity (NPP) and trends in the Daning River Basin. The detection of drivers with a high impact on vegetation NPP was done using a Geodetector. The results show that: (1) In terms of spatial and temporal changes, the annual average NPP of the watershed during the 13 years from 2008 to 2020 generally showed an upward trend, with the average yearly vegetation NPP being 512.33gC·m−2·a−1, exhibiting a low southwest to surrounding increasing trend along the river. (2) The spatial and temporal variation of vegetation NPP is influenced by several factors synergistically, with elevation, temperature, and distance from settlements being the dominant factors. The interaction of these two factors can enhance the explanatory power of vegetation NPP. Through the estimation of vegetation NPP and the analysis of influencing factors in the Daning River Basin, this study can provide a reference for the ecological restoration and management of vegetation NPP in small watersheds under similar environments.