Contribution Of Human Activities Research Articles

Significant influence of urban human activities and marine input on rainwater chemistry in a coastal large city, China

The coastal urban region is generally considered an atmospheric receptor for terrestrial and marine input materials, and rainfall chemistry can trace the wet scavenging process of these materials. Fast urbanization in China's east coastal areas has greatly altered the rainwater chemistry. However, the chemical variations, determinants, and sources of rainfall are unclear. Therefore, the typical coastal city of Fuzhou was selected for 1-year rainwater sampling and inorganic ions were detected to explore above problems. The findings depicted that rainwater ions in Fuzhou were slightly different from those in other coastal cities. Although NO3−, SO42−, Ca2+ and NH4+ dominated the rainwater ions, the marine input Cl− (22 %) and Na+ (11 %) also contributed a considerable percentage to the rainwater ions. Large differences in ion concentrations (2∼28 times) were found in monthly scale due to the rainfall amount. Both natural and anthropogenic determinants influenced the rainwater ions in coastal cities, such as SO2 emission, air SO2 and PM10 content on rainwater SO42−, NO3−, and Ca2+, and soot & dust emission on rainwater SO42−, NO3−, indicating the vital contribution of human activities. Stoichiometry and positive matrix factorization-based sources identification indicated that atmospheric dust/particles were the primary contributor of Ca2+ (83.3 %) and F− (83.7 %), and considerable contributor of SO42− (39.5 %), NO3− (38.3 %) and K+ (41.5 %). Anthropogenic origins, such as urban waste volatilization and fuel combustion emission, contributed 95 % of NH4+, 54.5 % of NO3− and 41.9 % of SO42−, and the traffic sources contribution was relatively higher than fixed emission sources. The marine input represented the vital source of Cl− (77.7 %), Na+ (84.9 %), and Mg2+ (55.3 %). This work highlights the significant influence of urban human activities and marine input on rainwater chemicals and provides new insight into the material cycle between the atmosphere and earth-surface in coastal city.

Anthropogenic activities dominated the spatial and temporal changes of normalized difference vegetation index (NDVI) in the Hehuang valley in the northeastern Qinghai Province between 2000 and 2020

The Hehuang Valley (HV) is a key development area in the Qinghai Province; understanding changes in the vegetation within this area is of great significance if we are to maintain the ecological quality of this regional environment. Based on the 30 m spatial resolution Normalized difference vegetation index (NDVI) time series dataset, this paper analyzes the spatial and temporal characteristics and evolutionary trends of NDVI in the HV from 2001 to 2020 under the influences of climate change and human activities, by applying Mann-Kendall trend analysis, the Hurst index, and residual analysis. Analysis showed that firstly, high NDVI values (>0.5) were distributed in the low elevation areas of the HV except for towns and cropland, while the low NDVI values (<0.5) were mainly distributed in the high elevation regions; the NDVI exhibited an increasing trend over the study period. Second, human activities promoted NDVI growth in the HV by changing land-use types, although there is a risk of vegetation degradation in the future. Third, the proportion of NDVI changes affected by climate change and human activities was determined to be 87.24% of the HV; furthermore, the contribution of human activities was three-fold higher than that of climate change. Fourth, managers should scientifically manage grasslands and forests and implement specific anthropogenic interventions based on the characteristics of regional NDVI degradation, to improve ecosystem resilience. These results can be used to quantitatively analyze the relative contributions of natural and anthropogenic factors to the ecological changes in the HV, and provide reference guidelines for the management of ecological environments.

Megacities are causal pacemakers of extreme heatwaves

Global climate change has been shown to cause longer, more intense, and frequent heatwaves, of which anthropogenic stressors concentrated in urban areas are a critical contributor. In this study, we investigate the causal interactions during heatwaves across 520 urban sites in the U.S. combining complex network and causal analysis. The presence of regional mediators is manifest in the constructed causal networks, together with long-range teleconnections. More importantly, megacities, such as New York City and Chicago, are causally connected with most of other cities and mediate the structure of urban networks during heatwaves. We also identified a significantly positive correlation between the causality strength and the total populations in megacities. These findings corroborate the contribution of human activities e.g., anthropogenic emissions of greenhouse gases or waste heat, to urban heatwaves. The emergence of teleconnections and supernodes are informative for the prediction and adaptation to heatwaves under global climate change.

Providing Enhanced Insights into Groundwater Exchange Patterns through Downscaled GRACE Data

The measurement of groundwater exchange between neighboring regions is a critical topic in water resource management and can usually be achieved through a combination of field investigations and the use of groundwater flow models. In this study, we employed the water balance and Darcy’s law methods, utilizing downscaled Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) data to assess groundwater exchange patterns in the Beijing-Tianjin-Hebei (BTH) region of China. Additionally, we determined the contributions of human activities and climate factors to the observed variations via residual analysis. The results revealed a consistent decrease in groundwater storage in the study area since 2008, especially in the spring and summer months. The groundwater exchange rates calculated by 1° and 0.05° groundwater storage anomalies (GWSAs) were basically consistent, and the downscaled GWSAs could better reflect the small-scale groundwater exchange characteristics. The groundwater exchange rate showed a decreasing trend from the Piedmont plain to the coastal areas. A notable trend of declining groundwater exchange between the Taihang Mountains and Piedmont plains was observed, and the downward trend gradually intensified from north to south between 2003 and 2007. After 2008, there was an increasing trend, and coastal areas exhibited the smallest amount of groundwater exchange. Human activities emerged as the predominant factor accounting for more than 90.9% of the overall reduction in groundwater storage, while climate change imposed a minimal influence on groundwater storage variations. The insights obtained in this study hold significant implications for groundwater resource planning and management in the region.

Vegetation Greening and Its Response to a Warmer and Wetter Climate in the Yellow River Basin from 2000 to 2020

Vegetation greening is time-dependent and region-specific. The uncertainty of vegetation greening under global warming has been highlighted. Thus, it is crucial to investigate vegetation greening and its response to climate change at the regional scale. The Yellow River Basin (YRB) is a vital ecological barrier in China with high ecological vulnerability and climatic sensitivity. The relationship between vegetation greening and climate change in the YRB and the relative contribution of climate change remain to be explored. Using the Enhanced Vegetation Index (EVI) and meteorological observation data, the spatiotemporal patterns of vegetation greening across the YRB in response to climate change at the basin and vegetation sub-regional scales from 2000 to 2020 were analyzed. The impact of human activities on regional greening was further quantified. Results showed that approximately 92% of the basin had experienced greening, at average annual and growing season rates of 0.0024 and 0.0034 year–1, respectively. Greening was particularly prominent in the central and eastern YRB. Browning was more prevalent in urban areas with a high intensity of human activities, occupying less than 6.3% of the total basin, but this proportion increased significantly at seasonal scales, especially in spring. Regional greening was positively correlated with the overall warmer and wetter climate, and the partial correlation coefficients between EVI and precipitation were higher than those between EVI and temperature. However, this response varied among different seasonal scales and vegetation sub-regions. The combined effects of climate change and human activities were conducive to vegetation greening in 84.5% of the YRB during the growing season, while human activities had a stronger impact than climate change. The relative contributions of human activities to greening and browning were 65.15% and 70.30%, respectively, mainly due to the promotion of ecological rehabilitation programs and the inhibition of urbanization and construction projects.

Climate change and geo-environmental factors influencing desertification: a critical review.

The problem of desertification (DSF) is one of the most severe environmental disasters which influence the overall condition of the environment. In Rio de Janeiro Earth Summit on Environment and Development (1922), DSF is defined as arid, semi-arid, and dry sub-humid induced LD and that is adopted at the UNEP's Nairobi ad hoc meeting in 1977. It has been seen that there is no variability in the trend of long-term rainfall, but the change has been found in the variability of temperature (avg. temp. 0-5°C). There is no proof that the air pollution brought on by CO2 and other warming gases is the cause of this rise, which seems to be partially caused by urbanization. The two types of driving factors in DSF-CC (climate change) along with anthropogenic influences-must be compared in order to work and take action to stop DSF from spreading. The proportional contributions of human activity and CC to DSF have been extensively evaluated in this work from "qualitative, semi-quantitative, and quantitative" perspectives. In this study, we have tried to connect the drives of desertification to desertification-induced migration due to loss of biodiversity and agriculture failure. The authors discovered that several of the issues from the earlier studies persisted. The policy-makers should follow the proper SLM (soil and land management) through using the land. The afforestation with social forestry and consciousness among the people can reduce the spreading of the desertification (Badapalli et al. 2023). The green wall is also playing an important role to reduce the desertification. For instance, it was clear that assessments were subjective; they could not be readily replicated, and they always relied on administrative areas rather than being taken and displayed in a continuous space. This research is trying to fulfill the mentioned research gap with the help of the existing literatures related to this field.

Influence of watershed characteristics and human activities on the occurrence of organophosphate esters related to dissolved organic matter in estuarine surface water

Organophosphate esters (OPEs) are widespread in aquatic environments and pose potential threats to ecosystem and human health. Here, we profiled OPEs in surface water samples of heavily urbanized estuaries in eastern China and investigated the influence of watershed characteristics and human activities on the spatial distribution of OPEs related to dissolved organic matter (DOM). The total OPE concentration ranged from 22.3 to 1201 ng/L, with a mean of 162.6 ± 179.8 ng/L. Chlorinated OPEs were the predominant contaminant group, accounting for 27.4–99.6 % of the total OPE concentration. Tris(2-chloroisopropyl) phosphate, tris(1,3-dichloro-2-propyl) phosphate, and tributyl phosphate were the dominant compounds, with mean concentrations of 111.2 ± 176.0 ng/L, 22.6 ± 21.5 ng/L, and 14.8 ± 14.9 ng/L, respectively. Variable OPE levels were observed in various functional areas, with significantly higher concentrations in industrial areas than in other areas. Potential source analysis revealed that sewage treatment plant effluents and industrial activities were the primary OPE sources. The total OPE concentrations were negatively correlated to the mean slope, plan curvature, and elevation, indicating that watershed characteristics play a role in the occurrence of OPEs. Individual OPEs (triisobutyl phosphate, tris(2-butoxyethyl) phosphate, tris(2-chloroethyl) phosphate, and tricresyl phosphate) and Σalkyl-OPEs were positively correlated to the night light index or population density, suggesting a significant contribution of human activity to OPE pollution. The co-occurrence of OPEs and DOM was also observed, and the fluorescence indices of DOM were found to be possible indicators for tracing OPEs. These findings can elucidate the potential OPE dynamics in response to DOM in urbanized estuarine water environments with intensive human activities.

The Intersectionality of Climate Change and Post-Stroke Aphasia.

Persons with communication disabilities including persons with post-stroke aphasia (PWAs) possess a vulnerability to climate change as a result of their communication impairments. The disproportionate effects of climate change are likely to exacerbate preexisting inequities in social determinants of health. Communication disability intersecting with other characteristics subject to discrimination (e.g., race, age, sex, income) may lead to inequities in climate-related adaptive capacity. This article echoes earlier concerns related to climate change and further educates healthcare professionals about the impact of climate change on the global human population, with particular consideration of PWAs. The aims of this article are the following: (1) to broaden the understanding of aphasiologists and clinicians caring for PWAs about climate change and the contributions of human activity (anthropogenic) to this crisis; (2) to describe climate change and its impact on health; (3) to detail the intersectionality of climate and health; (4) to explore climate change and its potential effects on PWAs; and (5) to offer hope through emissions reduction, adaptation, resilience, and immediate change.

Assessing the contributions of human activities to runoff and sediment transport change: A method for break point identification in double mass curves based on model fitting

Study regionThe upper Yellow River basin, the Wuding River basin, and the Xinshui River basin in China. Study focusThe double mass curve (DMC) is a widely used tool for assessing the contributions of human activities to runoff and sediment transport change. Scientifically identifying break points in the DMC is crucial for the assessment of human activities contribution. This study proposes a DMC break point identification method using model fitting and applies it to three watersheds with different human disturbance intensities, while also highlighting issues that should be considered in the application of DMC. New hydrological insights for the regionCompared to the baseline period, the runoff transport at Toudaoguai, Baijiachuan, and Daning stations decreased by 36.25 %, 43.68 %, and 51.17 %, with human activities contributing 109.64 %, 102.45 %, and 107.85 %, respectively. Human activities contribution was underestimated by 7.21 %, 6.88 %, and 14.45 %, respectively when using break point identification methods only based on runoff. Additionally, the trends in runoff (sediment) transport may not perfectly align with when human activities occur. The effect of human activities and climate change on runoff and sediment transport is not quantified in absolute terms, the human contributions calculated by DMC methods are only relative. The findings of this study can provide a scientific reference for the application of DMC to calculate the contribution of human activities to runoff and sediment transport change.

Quantitative Analysis of the Impact of Climate Change and Human Activities on Runoff Variation in Akwa Ibom State, Nigeria

The non-parametric Mann-Kendall (MK) trend test, including the Sen's slope test and Pettitt's test, was used to determine trends, magnitudes, and change points in hydro-meteorological variables from 1972 to 2021. The slope change ratio of accumulative quantity (SCRAQ) method was then used to calculate the relative contributions of climate change and human activities to runoff variation in the Uyo-Itu river basin. Annual rainfall, maximum temperature, minimum temperature, and runoff showed significant increasing trends, whereas annual relative humidity, solar radiation, and potential evapotranspiration showed significant decreasing trends. Between 1992 and 2010, there were abrupt changes in hydro-meteorological variables. However, the runoff shift occurred in 2003. The time period under consideration was divided into two parts: baseline period A and change (impacted) period B. Climate change dominates runoff variation in period B, accounting for 103.6 percent of the variation, while human activities have a negative impact (-3.6%). The results indicate that climate change is the primary driver of runoff variation and that its impact is becoming more severe. Furthermore, the Budyko hypothesis was used to validate the contributions of human activities and climatic changes based on the SCRAQ method. The results showed that the contributions of human activities and climatic changes computed using the SCRAQ method are comparable with those computed using the sensitivity-based method. From this study, it can be concluded that assessing the influence of climate changes and human activities on variations and identifying the major driving forces causing the variations are critical for more efficient water resources management for sustainable economic growth
  

Multi-Temporal Change of LULC and Its Impact on Carbon Storage in Jiangsu Coastal, China

Coastal is the coupling of socio-economic and fragile ecosystems area existing development and protection problems, with lots of reserve land resources (i.e., bottomland and tidal flats). Analyzing and predicting the carbon storage changes caused by land use/land cover (LULC) on the Jiangsu coast were critical for revealing the potential problems of land surface changes and sustainable development. Then, we utilized the single dynamic degree and transfer in/out contribution, exploring the characteristics of LULC change in the study area from 1980 to 2018. Using the InVEST model, PLUS-LEAS model, and PLUS-Markov chain module, we assessed the spatiotemporal of the study area at the county level to reveal the LULC change strategy and driving factor contribution, as well as the composition of LULC and carbon storage in 2036. The results show that the LULC structure in the study area significantly changed from 1980 to 2018, in which the tidal flat and high coverage grassland decreased by 552.84 km2 and 383.71 km2 while the reservoir ponds and urban residential land increased by 1210.69 km2 and 101.70 km2. The major driving factor of LULC change has shifted from a single-factor to multi-factor coupling, and the influence contribution of human activity increased by 6.73%, especially the population. The carbon storage of study areas showed a significant decrease trend during 1980–2010, followed by a slight increase during 2010–2018. High-density carbon storage was mainly distributed in Lianyungang and Nantong and presented a decreasing trend along the coastline extending inland. The dry land and reservoir ponds are the main composition of LULC types in 2036, and the carbon storage increased to 2.39 × 108 t. In addition, more than decades of LULC change will cover part or all of the land use change process and trends, especially high-covered grasslands, so we suggest a 10-year LULC change to analyze coastal areas with lots of tidal flats and bottomlands. Therefore, this study can provide reference and theoretical guidance for ecologically sustainable development and future LULC evolution in coastal cities.

Quantitative Analysis of Climate Variability and Human Activities on Vegetation Variations in the Qilian Mountain National Nature Reserve from 1986 to 2021

Rapid climate variability and intense human activities generate obvious impacts on the Qilian Mountains ecosystem. The time series of fractional vegetation coverage (FVC) from 1986 to 2021 were used to quantify the impact of climate variability and human activities on vegetation variations in the Qilian Mountain National Nature Reserve (QMNNR), using 3147 land satellite images based on the Google Earth Engine cloud platform. The contributions of climate variability and human activities to FVC were quantified using multiple regression residual analysis. Partial correlation and correlation methods were used to quantify the impact of temperature, precipitation, and human activity footprints on FVC. The results showed that from 1986 to 2021, the increase rate of FVC was 1.7 × 10−3 y−1, and the high vegetation coverage of the FVC was mainly distributed in the southeastern part of the reserve. In contrast, the low vegetation coverage was mainly distributed in the northwest part of the reserve. The Mann–Kendall mutation test found that the year of 2009 was the year of the mutation. The growth rate of FVC from 2010 to 2021 was greater than that from 1986 to 2009. In addition, climate variability and human activities exhibited a remarkable spatial heterogeneity in FVC changes. Climate variability and human activities contributed 49% and 51% to the increase in FVC in the reserve, respectively, and the contribution of human activities was greater than that of climate variability. The warming and humidification phenomena in the reserve were obvious. However, precipitation was the dominant factor affecting the dynamic changes in FVC. This study improves our understanding of the response of vegetation dynamics to the climate and human activities in the QMNNR.

Analysis of Net Primary Productivity Variation and Quantitative Assessment of Driving Forces-A Case Study of the Yangtze River Basin.

Net primary productivity (NPP) can indirectly reflect vegetation's capacity for CO2 fixation, but its spatiotemporal dynamics are subject to alterations to some extent due to the influences of climate change and human activities. In this study, NPP is used as an indicator to investigate vegetarian carbon ability changes in the vital ecosystems of the Yangtze River Basin (YRB) in China. We also explored the NPP responses to climate change and human activities. We conducted a comprehensive analysis of the temporal dynamics and spatial variations in NPP within the YRB ecosystems from 2003 to 2020. Furthermore, we employed residual analysis to quantitatively assess the contributions of climate factors and human activities to NPP changes. The research findings are as follows: (1) Over the 18-year period, the average NPP within the basin amounted to 543.95 gC/m2, displaying a noticeable fluctuating upward trend with a growth rate of approximately 3.1 gC/m2; (2) The areas exhibiting an increasing trend in NPP account for 82.55% of the total study area. Regions with relatively high stability in the basin covered 62.36% of the total area, while areas with low stability accounted for 2.22%, mainly situated in the Hengduan Mountains of the western Sichuan Plateau; (3) NPP improvement was jointly driven by human activities and climate change, with human activities contributing more significantly to NPP growth. Specifically, the contributions were 65.39% in total, with human activities contributing 59.28% and climate change contributing 40.01%. This study provides an objective assessment of the contributions of human activities and climate change to vegetation productivity, offering crucial insights for future ecosystem development and environmental planning.

Spatio-temporal dynamics of land use transitions associated with human activities over Eurasian Steppe: Evidence from improved residual analysis

We presented a framework to evaluate the land use transformations over the Eurasian Steppe (EUS) driven by human activities from 2000 to 2020. Framework involves three main components: (1) evaluate the spatial-temporal dynamics of land use transitions by utilizing the land change modeler (LCM) and remote sensing data; (2) quantifying the individual contributions of climate change and human activities using improved residual trend analysis (IRTA) and pixel-based partial correlation coefficient (PCC); and (3) quantifying the contributions of land use transitions to Leaf Area Index Intensity (LAII) by using the linear regression. Research findings indicate an increase in cropland (+1.17 % = 104,217 km2) over EUS, while a − 0.80 % reduction over Uzbekistan and − 0.16 % over Tajikistan. From 2000 to 2020 a slight increase in grassland was observed over the EUS region by 0.05 %. The detailed findings confirm an increase (0.24 % = 21,248.62 km2) of grassland over the 1st half (2000−2010) and a decrease (−0.19 % = −16,490.50 km2) in the 2nd period (2011−2020), with a notable decline over Kazakhstan (−0.54 % = 13,690 km2), Tajikistan (−0.18 % = 1483 km2), and Volgograd (−0.79 % = 4346 km2). Area of surface water bodies has declined with an alarming rate over Kazakhstan (−0.40 % = 10,261 km2) and Uzbekistan (−2.22 % = 8943 km2). Additionally, dominant contributions of human activities to induced LULC transitions were observed over the Chinese region, Mongolia, Uzbekistan, and Volgograd regions, with approximately 87 %, 83 %, 92 %, and 47 %, respectively, causing effective transitions to 12,997 km2 of cropland, 24,645 km2 of grassland, 16,763 km2 of sparse vegetation in China, and 12,731.2 km2 to grassland and 15,356.1 km2 to sparse vegetation in Mongolia. Kazakhstan had mixed climate-human impact with human-driven transitions of 48,568 km2 of bare land to sparse vegetation, 27,741 km2 to grassland, and 49,789 km2 to cropland on the eastern sides. Southern regions near Uzbekistan had climatic dominancy, and 8472 km2 of water bodies turned into bare soil. LAII shows an increasing trend rate of 0.63 year−1, particularly over human-dominant regions. This study can guide knowledge of oscillations and reduce adverse impacts on ecosystems and their supply services.

How Did the Southwest China Mountains Turn Green from 2000 to 2020? A Case Study in Chongqing

Vegetation, as a comprehensive ecological indicator of environmental change, plays an essential role in terrestrial ecosystems. Dramatic climate change and increasing anthropogenic disturbances have led to a profound change in vegetation cover. This study employed Moderate Resolution Imaging Spectroradiometer (MODIS) and other relevant data in Southwest China mountains, using Chongqing as a case study, to explore the variation in Normalized Difference Vegetation Index (NDVI) and its spatial differentiation mechanisms, quantify the relative contributions of climate change and human activities to these variations, and assess the effects of ecological policies, including afforestation, mountain closure forestry and natural forest conservation, and agricultural improvement. Results showed that the spatial distribution of annual NDVI, on average, varied 0.109 to 0.929, with the rate varying from −0.033 to 0.017 yr−1. NDVI was improved in 83.4% areas of Chongqing, and human activities contributed 69.1% of revegetation, whereas climate contributed 30.9%. On the other hand, human activities and climate change contributed 76.3% and 23.7% to vegetation degradation in 17.6% areas, respectively. Moreover, the explanatory power of anthropogenic factors on spatial differentiation of NDVI were stronger than that of climatic factors, and land use type was the dominant factor. The cumulative afforestation area, effective irrigation rate, fertilizer application, and total agricultural machinery power of the whole city was extremely significantly correlated with NDVI (p < 0.01), and the vegetation cover fluctuation in the region affected by natural forest protection and mountain closure forestry project was much more stable than that in non-protected areas, which to a certain extent reflected the effective implementation of local ecological protection, agricultural improvement, and other related policies.

Quantitative analysis of spatiotemporal changes and driving forces of vegetation net primary productivity (NPP) in the Qimeng region of Inner Mongolia

Vegetation is an essential component of terrestrial ecosystems, and understanding the drivers of vegetation change is of great importance for ecological management. In recent years, vegetation growth has increased under the combined effect of global warming and human activities in Inner Mongolia. The net primary productivity (NPP) was used as an indicator to study the spatial and temporal changes in vegetation in the Qimeng Region (QR). The residual trend analysis method was used to analyze the relative contributions of climate variations (CV) and human activities (HA) to NPP changes across the QR, while their drivers were explored using a geographical detector approach to quantify the driving forces of NPP. The results show that (1) NPP exhibited a fluctuating growth trend from 2003 to 2020, with an overall growth rate of 2.91%/year. (2) Precipitation, GDP and population density were the dominant driving factors for the spatial distribution of NPP. The combined explanatory power of any two dominant factors exceeded the power of any dominant individual factor, and the interaction between climate and human factors had a significant effect on NPP. (3) The change in NPP was influenced by the combined effect of HA and CV, accounting for 37.69% of the total area, with the relative contribution of HA being 51.75%. Finally, the relative contribution of human activities was slightly higher than that of climate change, confirming the initial success of the Grain to Green Program as well as ecological conservation projects. This paper provides a scientific basis for the local government to carry out the conversion of cropland to forest.

Drought monitoring based on temperature vegetation dryness index and its relationship with anthropogenic pressure in a subtropical humid watershed in China

Drought has serious impacts on agricultural production and ecological environment in China. Study on the causes of drought and drought monitoring technology is crucial for drought mitigation. This study conducts drought monitoring based on temperature vegetation dryness index (TVDI) and investigates with the impact of anthropogenic pressure in the Poyang Lake basin (PYLB). In the study, the MODIS normalized vegetation index (NDVI) and land surface temperature (LST) products from 2000 to 2021 were selected to construct NDVI-LST feature space processed with elevation correction, from which the monthly TVDI data was calculated. The land use data and nighttime light data were used to construct the anthropogenic pressure index (API). The results indicate that the frequency of drought in the PYLB is higher in the south and lower in the north. According to drought influence scope (DIS), the occurrence frequency of basin-wide drought (DIS ≥ 50%) in the PYLB is the highest, followed by regional drought (33%≤DIS < 50%), partial local drought (25%≤DIS < 33%), and local drought (10%≤DIS < 25%). The basin as a whole showed an obvious wetting trend in spring and a drying trend in autumn. During the study period, API in the north of PYLB was obviously higher than that in the south, and showed a general increasing trend. The contribution of human activities to drought in the PYLB increased exponentially with the improvement of social development level. Meanwhile, the impact of human activities on drought shows spatial differentiation. Ecological protection and green development have been implemented in the northerly region of the PYLB, and anthropogenic pressure inhibited the degree of drought. Oppositely, extensive socioeconomic development in the central and southern parts of the PYLB has caused damage to the environment and indirectly aggravated regional drought. This study makes important contributions to exploring the response between remote sensing drought monitoring and anthropogenic pressure and promoting regional drought mitigation in humid areas.

Evaluating ecohydrological driving factors controlling the hydrology of the Wuijang River Basin, China

Abstract River hydrology is an important proxy for changes in river runoff and an important factor affecting the ecology of rivers. To quantitatively evaluate the hydrology of the Wuijang River basin, this paper uses various tests to analyze runoff. The IHA-RVA method combined with FDC ecohydrological indicators was used to evaluate the hydrology of the Wuijang River basin and to analyze and calculate the contribution of human activities and climate change to runoff. The results show that (1) the runoff in the Wujiang River basin has shown a decreasing trend over the years, with a sudden change in 2005 and mainly two inter-annual cycles; (2) the overall hydrological change in runoff is 48%, which is a moderate change; (3) The changes in FDC ecological indicators are significantly correlated with rainfall, and the correlation between FDC ecological indicators and IHA hydrological indicators is strong; (4) human activities are the main influencing factors of runoff changes in the Wujiang River. The results of this paper have some reference value for the management of the Wujiang River basin and the improvement and restoration of river ecology.

Eutrophication and salinization elevate the dissolved organic matter content in arid lakes

Dissolved organic matter (DOM) plays an essential role in the global lake carbon cycle. Understanding DOM composition and monitoring its spatiotemporal dynamics are of great significance for understanding the lake carbon cycle, controlling water pollution, and protecting water resources. However, previous studies have focused mainly on eutrophic freshwater lakes, with limited attention given to saline lakes. Based on in situ data collected in ten lakes in northwestern China, this study reported the changes in DOM components in different lake types. Parallel factor analysis (PARAFAC) was used to analyze the three-dimensional excitation emission matrix (EEMs) to obtain the DOM fluorescence components. The contributions of different environmental factors to the changes in DOM components were quantified by the generalized linear model (GLM). The results showed that the eutrophication index was significantly positively related to dissolved organic carbon (DOC) (R2 = 0.95, p < 0.01) and colored DOM (CDOM) (R2 = 0.96, p < 0.01) concentrations. Terrestrial humic-like and tryptophan-like components, which are highly correlated with human activities, explained 62% and 64% of the variations in DOC and CDOM, respectively. In sum, the contributions of human activities to the DOC and CDOM variations were 61% and 57%, respectively. Salinity also showed significant positive correlations with both DOC (R2 = 0.88, p < 0.01) and CDOM (R2 = 0.87, p < 0.01). Lake salinization led to increases in DOM concentration, and salinity contributed 20% and 16% to the DOC and CDOM variations, respectively. Therefore, human activities and salinity codetermined the DOM concentration and its composition in the western arid lakes.Based on these findings, this study proposed a feasible flowchart for remotely estimating DOM in saline lakes using satellite data. This study is significant for the long-term monitoring of the carbon cycle and the effective protection of lake water resources in saline lakes.

Quantifying climate and anthropogenic impacts on runoff using the SWAT model, a Budyko-based approach and empirical methods

ABSTRACT Understanding the impact of climate change and human activities on runoff is crucial for water resources management. However, an evaluation of available methods for analysing this impact is lacking. In this study, we comprehensively reviewed four commonly used quantitative methods: the Soil and Water Assessment Tool (SWAT) model, Budyko-based approach, and two empirical methods, i.e., Double mass curve (DMC) and Modified DMC (MDMC). Using the Wei River basin as a case study, we assessed the runoff reduction influenced by climate change and human activities from 1970 to 2017. The results show that human activities are the primary driver for runoff reduction. The highest contribution of human activities was estimated by the DMC (93.2%–99.9%), followed by MDMC and SWAT (65.6%–87.1%), while the Budyko-based had the smallest estimates (55.3%–61.2%). Each method has advantages and limitations, so the appropriate method should be selected based on research objectives and data availability/quality.