Spatial-temporal Variations Research Articles

Variability in surface CO2 flux: Implication for monitoring surface emission from geothermal fields

In the last decade the international push for the development of various renewable energy and the increase of the carbon tax for emitters, has put high enthalpy geothermal on a hot seat. Anthropic geothermal emissions in volcanic areas are not negligible due to the inherent nature of their volcanic setting but are counted regardless, similarly to a gas or coal power plant, despite their non-fossil carbon origin. Natural volcanic emissions are however poorly constrained due to the lack of field scale soil CO2 flux assessments. In this study, we analyse the temporal and spatial variations of soil CO2 flux and soil temperature in the Taupō region, Taupō Volcanic Zone, New Zealand, in the light of seasonal variation, field utilisation, and seismicity. Fortnightly monitoring between 2019 and 2023 at 8 sites across the Tauhara and Wairakei geothermal fields provides insight into changes of seasonal variations and geothermal activities. To understand the broader distribution of natural degassing and to compare the CO2 flux over decades, we repeated the CO2 flux survey between 2019 and 2023 and compared to previous results at Karapiti, Wairakei geothermal field (2004, 2018), Ring of Fire, Tauhara geothermal field (2006), and Rotokawa geothermal field (2003, 2011). Similar emissions but a change in the spatial distribution at Tauhara geothermal field suggests that human surface development has affected permeability in the shallow subsurface. In contrast, a similar spatial distribution of flux, but higher emissions, at Karapiti, Wairakei indicates the recovery or modification of reservoir pressure. Finally, a decrease of total emission flux of the natural geothermal features at Rotokawa coincides with the decrease of CO2eq emissions at the power stations. This study showcases the complexity and uncertainties of natural CO2 emission calculations and provides recommendations for future monitoring studies.

Ecological Environment Assessment and Driving Mechanism Analysis of Nagqu and Amdo Sections of Qinghai-Xizang Highway Based on Improved Remote Sensing Ecological Index

The ecological environment along the Qinghai-Xizang highway is an important part of the construction of the ecological civilization in the Xizang region, and current research generally suffers from difficulties in data acquisition, low timeliness, and failure to consider the unique "alpine saline" environmental conditions in the study area due to the unique geographical environment of the Qinghai-Xizang plateau. Based on the GEE platform and the unique geographical environment of the study area, the remote sensing ecological index (RSEI) was improved, and a new saline remote sensing ecological index (SRSEI) applicable to the alpine saline region was constructed by using principal component analysis as an ecological environment quality evaluation index. The spatial distribution pattern and temporal variation trend of ecological environment quality along the Qinghai-Xizang Highway Nagqu-Amdo section were analyzed at multiple spatial and temporal scales using the ArcGIS 10.3 platform and geographic probes, and the driving mechanisms of eight control factors, including natural and human-made, on the spatial and temporal changes in SRSEI were investigated. The results showed that:① compared with RSEI, SRSEI was more sensitive to vegetation and had a stronger discriminatory ability in areas with sparse vegetation and severe salinization, which is suitable for ecological quality evaluation in alpine saline areas. ② The spatial scale of ecological environment quality in the study area had obvious geographical differentiation, and the areas with poor ecological quality were mainly concentrated in the northern Amdo County, whereas the areas with excellent and good quality grades were mainly distributed in the central-western and southeastern Nagqu areas. On the temporal scale, the ecological environment of the study area as a whole showed an improvement trend over 32 years, and the vegetation cover in the central-western and southeastern areas increased significantly, which had a strong improvement effect on the ecological environment. The improvement area was 1 425.98 km2, accounting for 99.82%. The mean value of SRSEI was 0.49, with an overall fluctuating upward trend and an average increase of 0.015 7 a-1. ③ The land use pattern was the most driving influence factor in the change of ecological environment quality in the study area, with an average q value of 0.157 6 over multiple years, and the influence of environmental factors was low. The multi-factor interaction results showed that the ecological environment in the study area was the result of multiple factors acting together, all factors had synergistic enhancement under the interaction, the influence of human factors was gradually increasing, and the interaction of the net primary productivity (NPP) of vegetation and land use pattern was the main interactive control factor of ecological environment quality in the study area. This study can provide a theoretical basis for ecological environmental protection and sustainable development along the Nagqu to Amdo section.

Spatial-temporal variation of economic resilience and its influencing factors under COVID-19: Evidence from Henan province, China

In order to explore the impact of COVID-19 on regional economy, the resilience characteristics of regional economy and influencing factors, this paper takes Henan province as an example and innovatively employ PSR and SBM model to measure the economic resilience of 18 areas in Henan province under the epidemic. The results show that (1) after the outbreak of COVID-19, the economic resilience of Henan province reduced with a tiny interannual variation, the distribution of resilience shifted from concentration to dispersion.(2) The economic resilience was higher in the central, west and south, and lower in the north and east. (3)Generally speaking, the economic resilience in Henan province did not significantly show certain spatial correlation, but formed an obvious "circle structure". The surrounding areas of Zhengzhou belonged to the "first circle", where the economic resilience was in the low-high cluster area and had a negative relationship. Areas outside the "first circle" gathered in the outer edge and formed the "second circle", where the economic resilience was in the low-low agglomeration area, with significant positive spatial spillover effect. (4) The level of health services had the strongest influence and GDP per capita played a fundamental role in improving economic resilience. This study is helpful for the policymakers to formulate relevant policies to improve economic resilience under public health emergencies in the future.

The Impact of Urbanization on Spatial–Temporal Variation in Vegetation Phenology: A Case Study of the Yangtze River Delta, China

The response of vegetation phenology to urbanization has become a growing concern. As impervious surfaces change as urbanization advances, the variation in vegetation phenology at the dynamic urbanization level was analyzed to significantly quantify the impact of urbanization processes on vegetation phenology. Based on the MOD13Q1 vegetation index product from 2001 to 2020, vegetation phenology parameters, including the start of the growing season (SOS), the end of the growing season (EOS), and the length of the growing season (GSL), were extracted, and the spatial–temporal variation in vegetation phenology, as well as its response to urbanization, was comprehensively analyzed. The results reveal that (1) from 2001 to 2020, the average rates of change for the SOS, EOS, and GSL were 0.41, 0.16, and 0.57 days, respectively. (2) The vegetation phenology changes showed significant spatial–temporal differences at the urbanization level. With each 10% increase in the urbanization level, the SOS and EOS were advanced and delayed by 0.38 and 0.34 days, respectively. (3) The urban thermal environment was a major factor in the impact of urbanization on the SOS and EOS. Overall, this study elucidated the dynamic reflection of urbanization in phenology and revealed the complex effects of urbanization on vegetation phenology, thus helping policymakers to develop effective strategies to improve urban ecological management.

Global characteristics of cloud macro-physical properties from active satellite remote sensing

Based on the products of joint CloudSat and CALIPSO observations from 2006 to 2017, this study investigates the global cloud macro-physical characteristics, including the spatial differences in cloud height, cloud thickness, cloud type, and cloud phase, along with the spatial-temporal variations and the land-sea discrepancy of the cloud vertical structure variables according to the study areas. The results show that the cloud frequency is higher over oceans than over land globally, but the opposite is true for cloud systems with more than two layers. Seasonal variability of global-average total cloud fraction is small, but large among different latitudinal bands. The global spatial distributions of cloud top height (CTH) and cloud base height (CBH) are similar, showing larger cloud heights over the land than over the ocean. The low clouds are mostly located in the central subtropical region, with CTH among 2.5–7.5 km, While the high clouds are mainly distributed in the equatorial region with CTH about 10–15 km. Meanwhile, the regional and seasonal variability of cloud geometric thickness (CGT) in all study areas are small, and the average thickness of higher clouds is slightly larger than that of lower clouds. By categorizing the clouds into eight types, it was found that the frequency of cirrus (Ci) and stratocumulus (Sc) is higher, followed by altocumulus (Ac), altostratus (As), nimbostratus (Ns) and cumulus (Cu), and the frequency of stratus (St) and deep convective clouds (DC) is the lowest. In addition, the occurrence frequency of clouds in phases was ranked from high to low as ice clouds, liquid clouds and mixed-phase clouds. Ice clouds are concentrated in the tropics and mid-latitudes, and located almost symmetrically around the equator during Mar-Apr-May (MAM) and Sep-Oct-Nov (SON). Liquid clouds are mainly distributed around 30°S and 30°N with large seasonal variability, and their frequency is higher over the ocean than over the land. Mixed-phase clouds are concentrated in the middle and high latitudes, with much less occurring in the equatorial regions.

Temporal and Spatial Variations of Sea Temperature in the Suez Gulf, Egypt

Temporal and Spatial Variations of Sea Temperature in the Suez Gulf, Egypt

Urban Complexity and the Dynamic Evolution of Urban Land Functions in Yiwu City: A Micro-Analysis with Multi-Source Big Data

The diversification of business forms leads to functional and spatial complexity in cities. The efficient determination of the complexity of an urban system is the basis for the scientific monitoring of the multi-functional aggregation within cities. Previous studies on the urban spatial structure were limited by the difficulty of collecting micro-data and the high time cost, and they focused on the macro-spatial structure, lacking fine-grained investigations of the micro-spatial structure. Additionally, high-resolution remote sensing images, which mainly rely on the textural characteristics of the spectrum of ground objects, cannot detect the social and economic functions of ground objects. Thus, it is difficult to meet the actual needs of urban planning and management. The purpose of this paper is to automatically identify the spatial heterogeneity and temporal variation of urban land use functions in the context of complex urban systems. The TF-IDF (term frequency–inverse document frequency) algorithm, a machine learning classification algorithm, and other methods are applied to identify the urban functions and distribution characteristics of the main urban area based on the POI (point of interest) data and urban form data. The results show the following: (1) From 2012 to 2022, all types of land use in Yiwu city grew at different rates, with logistics and warehousing space growing the fastest, which is in line with Yiwu’s goal of building a national logistics center for trade and services. (2) The residential area has a spatial structure with a dense central circle and a scattered periphery extending from northeast to southwest and from east to west. (3) The commercial service sector shows clear spatial differentiation between the core and the periphery. The commercial functional areas of Niansanli, Houzhai, and Chengxi, where the number of commercial POIs is relatively small, are located at the intersection of the administrative subdistricts near the city center, indicating that the commercial economic activities of the downtown subdistrict have a certain spillover effect on adjacent subdistricts. (4) The public facilities of each subdistrict are generally located in the core of each subdistrict, which ensures better convenience and accessibility. (5) Industrial land with a large total area that is scattered and mixed with urban residential land gradually tends to be centralized, forming an industrial belt around the city. This study comprehensively considers the aggregation relationship between urban buildings and land use and improves the accuracy of land identification and functional zoning.

Evaluating dynamics in human‐bear interactions within social‐ecological system

Abstract Over the past few decades, social‐ecological transformations have contributed to the restoration of numerous carnivores, presenting new challenges for human‐wildlife coexistence. Evaluating and understanding human‐wildlife interaction dynamics, particularly for conflict‐prone species, is crucial for conservation and management strategies. Our study focuses on Asiatic Black Bear (Ursus thibetanus) in Western Yunnan, China, a region with favourable bear conditions and significant environmental changes due to conservation policies. This study employed a multifaceted approach to gather data on bear occurrences and human‐bear conflicts. Utilising species distribution models, we predicted the potential bear habitat in 2000 and 2020. We proposed a methodology integrating bear habitat with human footprint to delineate the human‐bear interface. Additionally, we evaluated the spatial–temporal variations in bear habitat and human‐bear interface between 2000 and 2020. Semi‐structured interviews were conducted to capture the perceptions of local communities regarding the bear population, human‐bear interactions and conservation policies. Our findings indicated that the potential habitats of bears were strongly influenced by forest cover. We noticed improvements in bear habitat from 2000 to 2020, notwithstanding localised losses in specific areas. Most respondents attributed the increasing bear population to forest restoration and reduced human impact during this period. Notably, a significant proportion of respondents supported the conservation policies, previously participating in their formulation and implementation. Our analysis further revealed increases in the human‐bear interface and human‐bear interactions from 2000 to 2020. Remarkably, these changes did not significantly diminish local communities' endorsement of conservation policies. This resilience can be attributed to the net positive impacts of conservation policies on the livelihoods of these communities. Our study highlights the complexity and dynamic nature of human‐wildlife interactions within the social‐ecological system and provides new insights to facilitate sustainable conservation and management measures. Read the free Plain Language Summary for this article on the Journal blog.

Observation and modeling of irradiance near water surface of a photovoltaic pond

Accurate evaluation of near ground solar radiation in photovoltaic (PV) covered areas is essential for controlling adverse environmental effects and comprehensively utilizing the earth’s surface resources. The irradiance near the water surface of a photovoltaic fishpond was measured with eighteen distributed pyranometers. A simplified penetration model is proposed to reveal the shielding effect of PV panels on direct and diffuse irradiance. The model can well capture the spatial–temporal variation of the global irradiance due to the shielding effect of PV arrays. Numerical results show that proper modeling of the shading effect on diffuse irradiance is essential for the calculation accuracy of the cumulative global irradiance loss for various weather types and sky-view restriction levels. The spatial variation range of global radiation penetration ratio under the PV panels is 10%–90%. The spatially-averaged monthly shielding effects show that the maximum (87%) and minimum (46%) relative irradiance loss ratios in the studied PV area occur in December and June, respectively.

Role of time variant and invariant terms on soil moisture spatio‐temporal variability in a subhumid coastal wetland

AbstractThe knowledge of soil moisture spatio‐temporal variability is highly relevant for water resources management. This paper reports an analysis of the spatial–temporal variability of soil moisture data for a small to medium‐scale soil‐sensors network in a coastal wetland of southwestern Spain. Measurements were taken from five sites located in the Doñana National Park over the time‐period of one hydrological year from September 2017 to September 2018. The total area of the soil‐sensors network shows an extension about 25 × 3 km. Soil moisture data was separated into time invariant (the temporal mean of the whole period at each site) and time‐variant terms (the deviations of soil moisture from the mean, or anomalies). The time‐invariant component was generally the main contributor to the total spatial variance of soil moisture and it was mostly controlled by the groundwater levels in the area. Nevertheless, the time variant terms have a huge effect on soil moisture variability in very dry states. Characteristic convex time‐dependent patterns for this field site were found between spatially averaged soil moisture and its variability. This information could be used for the up and downscaling of soil moisture from satellite data. Those patterns of relation between spatial mean and variability of soil moisture were only affected by heavy rainfalls giving rise to hysteretic behaviour. This study shows that even though groundwater level is a time‐variant variable, it significantly affects soil moisture's time‐variant but also time‐invariant terms due to the different average groundwater level depths at the different sites.

Spatial-temporal variations of Paleolithic human activities in Northeast China

Northeast China played an irreplaceable role in population migrations and cultural exchanges in East Asia during the Paleolithic. This paper collected 182 archaeological sites to analyse the characteristics of spatial-temporal variations of Paleolithic human activities in Northeast China, and explored the driving mechanisms behind these variations in combination with the paleoenvironmental and archaeological studies. During the Lower Paleolithic, constrained by the relatively cold-dry climate and blocked by the Songnen paleo-lake basin, the population was sparse and distributed only near 40° N at the southern end of Northeast China. Upon entering the Middle Paleolithic, as humans developed greater tolerance to cold climates and adopted more sophisticated survival strategies with the application of small lithic tools, their numbers increased and geographical distribution expanded northward to 45° N at the central region of Northeast China. The Upper Paleolithic saw a considerable increase in population and expansion across almost all of Northeast China except for the eastern Inner Mongolia Plateau. We speculated that 50 ka and 30 ka BP were two key points, both of which may be associated with a significant increase in the frequency of migrations and communications among humans, and the widespread popularity of highly mobile microblade technology, respectively. In addition, the environmental analysis of archaeological sites revealed a continuous spread of Paleolithic humans to areas with higher elevations, steeper slopes, and lower temperatures. Meanwhile, they were becoming less reliant on water resources and were more widely conducting activities in open-air areas, showing that the environmental adaptability had been continuously improving over time. This study can provide a reference for the reconstruction of the migration history of early humans in East Asia, and is also of great significance for a comprehensive understanding of the evolutionary process of early human-environment interactions.

Spatial-temporal characteristics of temperature in Indonesian Sea based on a high-resolution reanalysis data

Influenced by both the Pacific and Indian Oceans, the temperature field in the Indonesian Sea are complicated. In order to reveal the spatial-temporal variability, the surface, thermocline and intermediate layers of the temperature field are studied based on the global ocean reanalysis data of Copernicus Marine Environment Monitoring Service (CMEMS) from 1993 to 2019 and the Empirical Orthogonal Function (EOF) analysis method. The results show that there is a warming trend of 1.36×10−2 °C /year in the surface layer. The first two modes both show reverse changes close to the Pacific and Indian Oceans. The correlation coefficients between the first and second modal time coefficients and the Niño 3.4 index are 0.62 and 0.48, respectively. And the correlation coefficient between the second modal time coefficient and the ITF inflow is -0.45. In the thermocline, there is a warmer trend, which is 4.78×10−2 °C /year. The correlation index of the first and second modal time coefficient with the Niño 3.4 and DMI indices are 0.87 and 0.43, respectively. The correlation index between the first and second modal time coefficient and the ITF inflow are -0.60 and 0.38, respectively. In the intermediate layer, the warming trend is 2.18×10−2 °C /year. From 1993 to 1999, from 2000 to 2016 and from 2017 to 2019, the Sulu Sea and northern Halmahera Sea experienced three periods of warming, cooling and warming, respectively. The study is helpful for further understanding the variation of the temperature field in the Indonesian Sea.

Temporal-Spatial Variations Analysis of Surface Temperature in Kalimantan Region for The Period of 2010 - 2020

Surface temperature information is important to study because it affects other climate parameters and has an impact on various sectors. This study aims to analyze the temporal and spatial variations of maximum surface temperature on Kalimantan Region during the period 2010 to 2020. The data used is Surface Maximum Temperature (SMT) in the form of a 0.5o x 0.5o grid from the Climate Prediction Center (CPC) NOAA PCL. The results of the temporal analysis showed that the highest monthly SMT values occurred in May (32.00o C) and September (31.75o C). While the lowest monthly SMT values were found in January (30.88o C) and July (31.40o C). The results of the annual SMT trend analysis show that the surface temperature in the Kalimantan Region has increased at an average rate of 0.03°C per year. This value is higher than the increase in global surface temperature (~0.02°C per year). Based on the results of spatial analysis, it was known that the distribution of SMT on Kalimantan Region tends to be stable in the range of 25o C to 35o C throughout the year. Spatial analysis of SMT in 2011 showed that low values (25o - 31o C) dominated South Kalimantan Province , while high values (33°C - 35°C) dominated West Kalimantan Province. The results of the 2019 SMT spatial analysis revealed a similar pattern to 2011. However, there was a significant increase in temperature compared to 2011, especially in the high SMT values observed in West Kalimantan and East Kalimantan Provinces.

City-level livestock methane emissions in China from 2010 to 2020

Livestock constitute the world’s largest anthropogenic source of methane (CH4), providing high-protein food to humans but also causing notable climate risks. With rapid urbanization and increasing income levels in China, the livestock sector will face even higher emission pressures, which could jeopardize China’s carbon neutrality target. To formulate targeted methane reduction measures, it is crucial to estimate historical and current emissions on fine geographical scales, considering the high spatial heterogeneity and temporal variability of livestock emissions. However, there is currently a lack of time-series data on city-level livestock methane emissions in China, despite the flourishing livestock industry and large amount of meat consumed. In this study, we constructed a city-level livestock methane emission inventory with dynamic spatial-temporal emission factors considering biological, management, and environmental factors from 2010 to 2020 in China. This inventory could serve as a basic database for related research and future methane mitigation policy formulation, given the population boom and dietary changes.

Monitoring Spatial–Temporal Variations in River Width in the Aral Sea Basin with Sentinel-2 Imagery

Rivers in arid regions serve as crucial freshwater resources for local communities and play an essential role in global hydrological and biogeochemical cycles. The Aral Sea Basin (ASB) in Central Asia is characterized by an arid climate and river dynamics that are sensitive to climate change and human activities. Monitoring the spatiotemporal variations in river water extent in the ASB is essential to maintain an ecological balance and ensure water security. In this study, we extracted data regarding monthly river water bodies in the ASB from 2017 to 2022 by synthesizing monthly Sentinel-2 images. The water extents on the Sentinel images were automatically mapped using the Otsu method, and the river widths for all river channels were calculated using the RivWidth algorithm. We investigated the relationships between the river dynamics and the geomorphology, climatic change, human activities, and the annual and interannual variations in the river width in different reaches of the basin. The results show a seasonal variability in the river width, with most rivers reaching the largest width in the warm season and a few rivers in the middle and lower areas reaching the valley value in the warm season. Compared to their tributaries, the mainstem in the middle/lower regions showed less seasonal variability. According to interannual analysis, most of the rivers in the ASB significantly narrowed between 2017 and 2022, a phenomenon which is generally impacted by temperature and evapotranspiration variations. Comparisons show that our results provide improved information about the narrow river reaches and denser river networks compared to the previous global dataset, demonstrating the advantageous properties of high spatial resolution in Sentinel-2 imagery.

Long-Term Monitoring of Surface Water Dynamics and Analysis of Its Driving Mechanism: A Case Study of the Yangtze River Basin

In-depth insights into the profound impacts of climate change and human activities on water resources are garnered through the dynamic changes in surface water, a crucial aspect of effective water resource management and the preservation of aquatic ecosystems. This paper introduces an innovative approach employing the random forest algorithm for the systematic extraction and monitoring of surface water at large regional or national scales. This method integrates spectral bands, spectral indices, and digital elevation model data, offering a novel perspective on this critical task. A data-filling model is proposed to mitigate the impact of missing data due to cloud cover. Leveraging the capabilities of the Google Earth Engine (GEE), detailed information on surface water dynamics during the rainy and dry seasons in the Yangtze River Basin (YRB) from 1991 to 2021 is extracted using Landsat time series imagery. The analysis encompasses spatial-temporal variation characteristics and trends, with a specific focus on the intricate interplay between the areal extent of surface water and hydro-meteorological factors in each sub-basin of the YRB. Importantly, this includes considerations of potential groundwater contributions to surface water. Key findings from our research include: (1) Achieving a remarkable overall classification accuracy of 0.96 ± 0.03 in obtaining reliable surface water datasets with the support of GEE. (2) Identifying significant trends, such as a noteworthy increase in rainy season surface water bodies (+248.0 km2·yr−1) and a concerning decrease in surface ice/snow cover during both rainy and dry seasons, with change rates of −39.7 km2·yr−1 and −651.3 km2·yr−1, respectively. (3) Uncovering the driving mechanisms behind these changes, revealing positive correlations between the areal extent of rainy season surface water bodies and precipitation, as well as negative correlations between surface ice/snow cover area and average surface skin temperature. It is crucial to note that these driving factors exhibit variation among secondary river systems, underscoring the complexity of surface water dynamics. Furthermore, comparative analyses with existing surface water products are conducted, contributing to a deeper understanding of the advantages and uncertainties inherent in our proposed extraction method. The proposed method for large-scale surface water extraction not only enhances the monitoring of spatio-temporal surface water dynamics in the YRB but also provides valuable insights for the sustainable utilization and protection of water resources, considering the potential role of groundwater in supplementing surface water.

Assessment of microwave drying for rapid and convenient analysis of medicinal plants for quality assurance.

The safety and quality of many medicinally important herbs are compromised since farmers and small organizations are involved in the cultivation, aggregation, and primary processing of these herbs. Such organizations often lack adequate quality control facilities. To improve the safety and quality of herbal products, simple, rapid, and affordable quality control systems are required. The aim of this study was to assess the suitability of microwave oven-drying for moisture content (MC) determination and sample preparation of herbs in small organizations. Microwave oven-drying (720 W) and convective oven-drying at 105°C for MC determination were compared. The effects of three different drying methods (microwave oven-drying, low-temperature convective drying, and freeze-drying) on in vitro antioxidant and polyphenol oxidase (PPO) activity were determined, similarity analysis was conducted using HPLC signature spectra, and validation was performed with LC-MS focusing on one herb. Microwave oven-drying at 720 W significantly reduced the drying time (from hours to minutes), whereas the spatial variationof temperature in convective ovens set at 105°C can cause about 10% underestimation of MC. Microwave oven-dryingshowed similar macro-properties like freeze-drying and higher extractability (10%-20%) and in vitro antioxidant capacity (33%-66%) and lower PPO activity compared to low-temperature convective drying. HPLC signature spectra revealed strongsimilarity ofsoluble components between freeze-dried and microwave oven-dried herbs. LC-MS analysis demonstrated more common compounds between freeze-driedand microwave oven-driedCentella asiatica extracts, whereas convective tray-dried samples had fewer compounds common with samples obtained by freeze-drying or microwave oven-drying. Microwave oven-drying is rapid (tens of min) and shows small batch-to-batch variation compared to oven-drying at 105°C. The in vitro antioxidant assays and signature spectra can be used for assessing the source and purity or quality of a specific herb variety.

A low-cost and open-source approach for supraglacial debris thickness mapping using UAV-based infrared thermography

Abstract. Debris-covered glaciers exist in many mountain ranges and play an important role in the regional water cycle. However, modelling the surface mass balance, runoff contribution and future evolution of debris-covered glaciers is fraught with uncertainty as accurate observations on small-scale variations in debris thickness and sub-debris ice melt rates are only available for a few locations worldwide. Here we describe a customised low-cost unoccupied aerial vehicle (UAV) for high-resolution thermal imaging of mountain glaciers and present a complete open-source pipeline that facilitates the generation of accurate surface temperature and debris thickness maps from radiometric images. First, a radiometric orthophoto is computed from individual radiometric UAV images using structure-from-motion and multi-view-stereo techniques. User-specific calibration and correction procedures can then be applied to the radiometric orthophoto to account for atmospheric and environmental influences that affect the radiometric measurement. The thermal orthophoto reveals distinct spatial variations in surface temperature across the surveyed debris-covered area. Finally, a high-resolution debris thickness map is derived from the corrected thermal orthophoto using an empirical or inverse surface energy balance model that relates surface temperature to debris thickness and is calibrated against in situ measurements. Our results from a small-scale experiment on the Kanderfirn (also known as Kander Neve) in the Swiss Alps show that the surface temperature and thickness of a relatively thin debris layer (ca. 0–15 cm) can be mapped with high accuracy using an empirical or physical model. On snow and ice surfaces, the mean deviation of the mapped surface temperature from the melting point (∼ 0 ∘C) was 0.6 ± 2.0 ∘C. The root-mean-square error of the modelled debris thickness was 1.3 cm. Through the detailed mapping, typical small-scale debris features and debris thickness patterns become visible, which are not spatially resolved by the thermal infrared sensors of current-generation satellites. The presented approach paves the way for comprehensive high-resolution supraglacial debris thickness mapping and opens up new opportunities for more accurate monitoring and modelling of debris-covered glaciers.

Assessment of spatial–temporal variation of precipitation and meteorological drought in Shanxi province, China

Assessment of spatial–temporal variation of precipitation and meteorological drought in Shanxi province, China

Improving the accuracy of nitrogen estimates from nonpoint source in a river catchment with multi-isotope tracers

Climate change can affect precipitation patterns, temperature, and the hydrological cycle, consequently influencing the dynamics of nitrogen (N) within aquatic ecosystems. In this study, multiple stable isotopes (15N-NO3/18O-NO3 and 2H-H2O/18O-H2O) were used to investigate the N sources and flowpath within the Bogang stream in South Korea. Within the vicinity of the stream with complex land use where various N sources were present, four end-members (rainfall, soil, sewage, and livestock) were sampled and examined. Consequently, spatial-temporal variations of the N sources were observed dependent on the type of land use. During the dry season, sewage accounted for the dominant N source, ranging from 62.2 % to 80.2 %. In contrast, nonpoint sources increased significantly across most sites during the wet season (10.3–41.6 % for soil; 6.3–35.2 % for livestock) compared to the dry season (7.7–28.5 % for soil; 6–13.2 % for livestock). However, sewage (78.7 %) remains dominant, representing the largest ratio at the site downstream of the wastewater treatment plant during the wet season. This ratio showed a notable difference from the calculated N loading ratio of 52.2 %, especially for livestock. This suggests that a significant potential for N legacy effects, given that groundwater flow is likely to be the primary hydrological pathway delivering N to rivers. This study will help to develop water resource management strategies by understanding how the interaction between N sources and hydrological process responds to climate change within sub-basins.