Balance Estimates Research Articles

Estimating Risk Relativity of Driving Records using Generalized Additive Models: A Statistical Approach for Auto Insurance Rate Regulation

Abstract Studying driving records (DR) and assessing their risk relativity is crucial for auto insurance rate regulation. Typically, the evaluation of DR involves estimating risk using empirical loss cost or modeling approaches such as Generalized Linear Models (GLM). This article presents a novel methodology employing Generalized Additive Models (GAM) to estimate the risk relativity of DR. By treating the integer level of DR as a continuous variable, the proposed method offers enhanced flexibility and practicality in evaluating the associated risk. Extending the linear model to GAM is a critical advancement that harnesses advanced statistical methods in actuarial practice, providing a more statistically robust application of the proposed approach. Moreover, the integration of functional patterns with Class or Territory enables the investigation of statistical evidence supporting the existence of associations between risk factors. This approach helps address the issue of potential double penalties in insurance pricing and calls for a statistical solution to overcome this challenge. Our study demonstrates that utilizing the GAM approach yields a more balanced estimation of DR relativity, thereby reducing discrimination among different DR levels. This finding highlights the potential of this statistical method to improve fairness and accuracy in auto insurance rate making and regulation.

Deer survey from drone thermal imagery using enhanced faster R-CNN based on ResNets and FPN

Deer surveys play an important role in the estimation of local ecological balance. In the Chitwan National Park of Nepal, the dense tree canopies and tall vegetation often obscure the presence of wild deer, which has a negative effect on the accurate population surveys of wild deer. UAVs equipped with infrared sensors have been increasingly used to monitor wild deer by capturing a lot of images. How to automatically recognize and obtain the number of deer objects from thermal images is becoming an important research topic. Due to the difference between thermal images and true-color images, as well as the variations in deer object sizes in these two types of images, current ready-to-use object detection models, designed for true-color imagery, are ill-suited for the task of detecting small deer objects within thermal imagery. In this paper, an enhanced Faster R-CNN was constructed to detect small deer objects from thermal images, in which a Feature Pyramid Network (FPN) based on a residual network is used to improve feature extraction for small deer objects and multi-scale feature map constrution for the subsequent region proposals searching, bounding box regression, and regions of interest (RoIs) classification. In addition, small-scaled anchor boxes and a multi-scale feature map selection criterion are devised to improve the detection accuracy of small objects. Finally, based on Faster R-CNN, FPN, and different residual networks including ResNet18, ResNet34, ResNet50, ResNet101, and ResNet152, we constructed five object detection models, and evaluated their detection performance by using COCO evaluation matrix. Under the condition of IoU≥0.5, the integration of Faster R-CNN, FPN, and ResNet18 demonstrated to perform better than others. Specifically, The COCO evaluation results revealed an Average Precision (AP) score of 91.6% for all deer objects. Small deer objects (area ≤ 200 pixels) achieved an AP score of 73.6%, medium deer objects (200 < area ≤ 400 pixels) demonstrated an AP score of 93.4%, and large deer objects (area > 400 pixels) achieved the highest AP score of 94.3%. Our research is helpful for effective wild deer monitoring and conservation and can be a valuable reference for the exploration of small object detection from low-resolution thermal images.

Combined GNSS reflectometry–refractometry for automated and continuous in situ surface mass balance estimation on an Antarctic ice shelf

Abstract. Reliable in situ surface mass balance (SMB) estimates in polar regions are scarce due to limited spatial and temporal data availability. This study aims at deriving automated and continuous specific SMB time series for fast-moving parts of ice sheets and shelves (flow velocity &gt; 10 m a−1) by developing a combined global navigation satellite system (GNSS) reflectometry and refractometry (GNSS-RR) method. In situ snow density, snow water equivalent (SWE), and snow deposition or erosion are estimated simultaneously as an average over an area of several square meters and independently on weather conditions. The combined GNSS-RR method is validated and investigated regarding its applicability to a moving, high-latitude ice shelf. A combined GNSS-RR system was therefore installed in November 2021 on the Ekström ice shelf (flow velocity ≈ 150 m a−1) in Dronning Maud Land, Antarctica. The reflected and refracted GNSS observations from the site are post-processed to obtain snow accumulation (deposition and erosion), SWE, and snow density estimates with a 15 min temporal resolution. The results of the first 16 months of data show a high level of agreement with manual and automated reference observations from the same site. Snow accumulation, SWE, and density are derived with uncertainties of around 9 cm, 40 kg m−2 a−1, and 72 kg m−3, respectively. This pilot study forms the basis for extending observational networks with GNSS-RR capabilities, particularly in polar regions. Regional climate models, local snow modeling, and extensive remote sensing data products will profit from calibration and validation based on such in situ time series, especially if many such sensors will be deployed over larger regional scales.

Assessing human internal exposure to chemicals at different physical activity levels: A physiologically based kinetic (PBK) model incorporating metabolic equivalent of task (MET)

Physical activity levels have the potential to impact human internal exposure to environmental chemicals. However, the current lack of simple modeling approaches hinders the high-throughput screening of chemical exposure at different physical activity levels. To address this gap, this study proposes a straightforward model for assessing human internal exposure to chemicals. Our approach is based on the physiologically based kinetic (PBK) model and utilizes the metabolic equivalent of task (MET) to characterize internal exposure to chemicals at varying activity levels. To facilitate the application of this model, we have developed an Excel-based operation tool, allowing users to easily modify the MET value and generate simulation results for different physical activity levels. The simulation results demonstrate that as physical activity levels increase, the biotransfer factors (BTFs) of chemicals decrease, suggesting that higher physical activity levels reduce the bioaccumulation potential of chemicals. The intensified physical activity enhances the overall elimination kinetics of chemicals from the human body. However, the simulated concentrations of chemicals in the human body increase with higher physical activity levels, due to the significantly increased external exposure to chemicals, such as through inhalation. Our proposed modeling approach, along with the operational tool, enables high-throughput simulation of human chronic internal exposure to chemicals at different physical activity levels, where the findings can assist in screening chemicals for further health risk assessment. To accomplish this, the model incorporates certain assumptions and utilizes generic model input values. However, due to the intricate nature of the interaction between external and internal exposures at different physical activity levels, validating the simulation through experimental studies becomes challenging and is not performed in this study. For future studies, we recommend incorporating more MET-related physiological input variables, improving energy balance estimates, comprehending external exposure estimates, and conducting cohort studies to enhance and validate the proposed modeling approach.

Variance analysis of multiple importance sampling schemes

Multiple importance sampling (MIS) is an increasingly used methodology where several proposal densities are used to approximate integrals, generally involving target probability density functions. The use of several proposals allows for a large variety of sampling and weighting schemes. Then, the practitioner must choose a given scheme, i.e., sampling mechanism and weighting function. A variance analysis has been proposed in Elvira et al (2019, Statistical Science 34: 129-155), showing the superiority of the balanced heuristic estimator with respect to other competing schemes in some scenarios. However, some of their results are valid only for two proposals. In this paper, we extend and generalize these results, providing novel proofs that allow to determine the variance relations among MIS schemes.

A Widely Applicable Modeling and Efficient Simulation Method for Power Electronics Grids Based on Unit Switching Circuits

As an essential part of modern power systems, power electronics have improved system performance. They also brought new dynamic and transient problems and posed significant challenges to precise and efficient simulation. Traditional modeling and solving methods fail to balance between the simulation accuracy and efficiency, and they are not flexible enough to adapt to converters with various new topologies. This article proposed a widely applicable modeling and simulation method based on the unit switching circuit that greatly promote the simulation efficiency and modeling simplicity by converting switching circuits into constant sub-grid equations with injection functions. Critical issues for engineering applications, such as the blocking state and the triggering deadband of converters, were also discussed and addressed by boundary balance and conduction path estimation. The error and stability of the solving method were qualitatively analyzed, with further discussions on the validity and numerical features. Several cases, including common and general cases and a real project of power electronic microgrid, tested and verified the accuracy, generalization ability, and efficiency of the proposed method.

Soil Potassium Balance in the Hilly Region of Central Sichuan, China, Based on Crop Distribution

The problem of soil fertility imbalance in hilly agriculture is prominent, and accurate estimation of soil potassium balance is key to achieving precision fertilization at the regional level. Crop distribution has a significant impact on potassium balance, but studies on potassium balance with a focus on crop cultivation types are scarce, especially with regard to hilly areas. In this study, the spatial distribution characteristics of soil potassium balance under different cropping conditions and its influencing factors were analyzed for a hilly region. The results showed that (1) the soil rapidly available potassium (RAK) and slowly available potassium (SAK) content in the 0–20 cm soil layer ranged from 29.37 to 122.07 mg kg−1 and from 472.31 to 772.77 mg kg−1, respectively. (2) The soil potassium equilibrium status varied considerably among different cropping systems and the soil potassium deficit was greatest under the rapeseed–maize rotation, reaching −129.50 kg K ha−1 yr−1. The difference in soil potassium deficits between the rice–rapeseed and wheat–maize rotations was not significant, at −46.79 kg K ha−1 yr−1 and −44.07 kg K ha−1 yr−1, respectively, and only the rice–wheat rotation showed a potassium surplus. Due to the low potassium absorption of crops, the equilibrium value of soil potassium is higher than that of crop rotation, and rice and wheat can achieve different degrees of potassium surplus. Rapeseed planting was generally under-applied with potassium, and the potassium deficit could reach −70 kg K ha−1 yr−1. (3) Climate, topography, anthropogenic activity, and soil available potassium explained 20.8% of the variance in soil potassium balance. Anthropogenic activity such as roads and population density had the greatest influence, with 0.797. Topography and average annual precipitation had the weakest influences. These findings emphasize the importance of anthropogenic activity for soil potassium balance, and also provide regional evidence for formulating efficient measures for regional potassium resources management.

A material balance approach for modelling banks’ production process with non-performing loans

The aim of this to study is to examine how non-performing loans on the balance sheets of Japanese banks affect their performance by adopting a material balance principle. The paper outlines how the material balance conditions can be applied when modelling banks’ production process in the presence of non-performing loans. The paper utilizes the generalized weak G-disposability principle which accounts for the heterogeneity among banks’ input quality. We test how an input-oriented model (non-performing loans are treated as an input), the weak disposability assumption and the adopted material balance approach, affect banks’ performance levels. We apply our test on a sample of Japanese banks over the period 2013 to 2019. Our findings indicate that the input-oriented model and the material balance estimator even if they present similar distributions, they account differently the effect of non-performing loans’ fluctuations over the examined period. In addition, the results under the weak disposability assumption are found to be different compared to the material balance measures and less sensitive to banks’ non-performing loans variation levels. We also provide evidence that the generalized weak G-disposability assumption captures better banks’ performance fluctuations that has been caused by the restructuring of the Japanese banking industry.

Energy balance determination of crop evapotranspiration using a wireless sensor network

Determining crop evapotranspiration (ET) is essential for managing water at various scales, from regional water accounting to farm irrigation. Quantification of ET may be carried out by several procedures, being eddy covariance and energy balance the most established methods among the research community. One major limitation is the high cost of the sensors included in the eddy covariance or energy balance systems. We report here the development of a simpler device (CORDOVA-ET: COnductance Recording Device for Observation and VAlidation of ET) to determine crop ET based on industrial-grade, commercial off-the-shelf (COTS) sensors costing far less than research-grade sensors. The CORDOVA-ET contains a sensor package that integrates the basic micrometeorological instrumentation and the infrared temperature sensors required for estimating ET over crops using the energy balance approach. One novel feature is the presence of four different nodes that allow the determination of ET in four different locations within a field or in four different fields of the same crop, thus allowing an assessment of ET spatial variability. The system was conceived as an open-source and hardware alternative to commercial devices, using a collaborative approach for the development of a regional ET network in countries of North Africa and the Near East. Comparisons of radiation, temperature, humidity, and wind against those of research-grade sensors yielded excellent results, with coefficients of correlation (R2) above 0.96. The estimated reference ET calculated from these measurements showed R2 = 0.99 and a root mean square error (RMSE) of 0.22 mm/day. The infrared temperature measurements at the four different nodes showed an RMSE below 0.56°C. The energy balance components and estimates of ET from the CORDOVA-ET were validated against an eddy-covariance system over a wheat crop. The high (R2) for net radiation (0.98), sensible heat (0.88), and latent heat (0.86) showed good agreement between the modeled energy fluxes and the field measurements. The hardware components, acquisition, and data processing software are available as open-source repositories to facilitate adoption for different applications, from water use efficiency research to irrigation management.

Land Surface Modeling in the Himalayas: On the Importance of Evaporative Fluxes for the Water Balance of a High‐Elevation Catchment

AbstractHigh Mountain Asia (HMA) is among the most vulnerable water towers globally and yet future projections of water availability in and from its high‐mountain catchments remain uncertain, as their hydrologic response to ongoing environmental changes is complex. Mechanistic modeling approaches incorporating cryospheric, hydrological, and vegetation processes in high spatial, temporal, and physical detail have never been applied for high‐elevation catchments of HMA. We use a land surface model at high spatial and temporal resolution (100 m and hourly) to simulate the coupled dynamics of energy, water, and vegetation for the 350 km2 Langtang catchment (Nepal). We compare our model outputs for one hydrological year against a large set of observations to gain insight into the partitioning of the water balance at the subseasonal scale and across elevation bands. During the simulated hydrological year, we find that evapotranspiration is a key component of the total water balance, as it causes about the equivalent of 20% of all the available precipitation or 154% of the water production from glacier melt in the basin to return directly to the atmosphere. The depletion of the cryospheric water budget is dominated by snow melt, but at high elevations is primarily dictated by snow and ice sublimation. Snow sublimation is the dominant vapor flux (49%) at the catchment scale, accounting for the equivalent of 11% of snowfall, 17% of snowmelt, and 75% of ice melt, respectively. We conclude that simulations should consider sublimation and other evaporative fluxes explicitly, as otherwise water balance estimates can be ill‐quantified.

Monitoring Spatiotemporal Variation of Individual Tree Biomass Using Multitemporal LiDAR Data

Assessing the spatiotemporal changes in forest aboveground biomass (AGB) provides crucial insights for effective forest carbon stock management, an accurate estimation of forest carbon uptake and release balance, and a deeper understanding of forest dynamics and climate responses. However, existing research in this field often lacks a comprehensive methodology for capturing tree-level AGB dynamics using multitemporal remote sensing techniques. In this study, we quantitatively characterized spatiotemporal variations of tree-level AGB in boreal natural secondary forests in the Greater Khingan Mountains region using multitemporal light detection and ranging (LiDAR) data acquired in 2012, 2016, and 2022. Our methodology emphasized improving the accuracy of individual tree segmentation algorithms by taking advantage of canopy structure heterogeneity. We introduced a novel three-dimensional metric, similar to crown width, integrated with tree height to calculate tree-level AGB. Moreover, we address the challenge of underestimating tree-level metrics resulting from low pulse density, ensuring accurate monitoring of AGB changes for every two acquisitions. The results showed that the LiDAR-based ΔAGB explained 62% to 70% of the variance of field-measured ΔAGB at the tree level. Furthermore, when aggregating the tree-level AGB estimates to the plot level, the results also exhibited robust and reasonable accuracy. We identified the average annual change in tree-level AGB and tree height across the study region, quantifying them at 2.23 kg and 0.25 m, respectively. Furthermore, we highlighted the importance of the Gini coefficient, which represents canopy structure heterogeneity, as a key environmental factor that explains relative AGB change rates at the plot level. Our contribution lies in proposing a comprehensive framework for analyzing tree-level AGB dynamics using multitemporal LiDAR data, paving the way for a nuanced understanding of fine-scale forest dynamics. We argue that LiDAR technology is becoming increasingly valuable in monitoring tree dynamics, enabling the application of high-resolution ecosystem dynamics products to elucidate ecological issues and address environmental challenges.

Influence of climate and non-climatic attributes on declining glacier mass budget and surging in Alaknanda Basin and its surroundings

Globally glaciers are rapidly shrinking, endangering the sustainability of melt water and altering the regional hydrology. Understanding long-term glacier response to climate change and the influence of non-climatic attributes like morpho-topographic factors on ice loss is of high relevance. Here we estimate the multi-temporal mass balance of 445 glaciers in the upper Alaknanda basin and neighboring transboundary glaciers using optical stereo imageries from 1973 to 2021. Our measurements indicate a mean annual area change rate of −1.14 ± 0.07 km2 a−1 and a geodetic glacier mass balance of −0.34 ± 0.08 m w.e. a−1 from 1973 to 2020, leading to an overall mass loss of 12.9 ± 1.7 Gt, that accounts for up to 0.036 ± 0.006 mm of sea level rise. Before 2000 (1973–2000), the mean regional glacier mass loss rate was −0.30 ± 0.07 m w.e. a−1, which increased to −0.43 ± 0.06 m w.e. a−1 during 2000–2020. ERA5 Land reanalysis data showed a summer and annual temperature rise of ∼0.6 °C and ∼ 0.5 °C respectively in recent time period (2015–2020) and consequent strong mass loss (−0.68 ± 0.09 m w.e. a−1). In addition to climatic influence, glacier morphometry, topographic features and uneven debris cover distribution further impacted the regional and glacier specific mass balance. Our multi-temporal observation from space also emphasized that though the glaciers in this region experienced an increasing mass loss but a strong heterogeneous glacier specific response, like surging and dynamic separation of glacier, are also evident that was not captured by the available long-term global elevation change grids. Among all the climatic and non-climatic attributes, we identified summer temperature having most significant influence over glacier mass budget in this region, with a mass balance sensitivity of −0.6 m w. e. a−1 °C−1. Hence, knowing the mean summer temperature will help to predict the mass balance for any intermediate year for this region. If such climatic trend continues, smaller glaciers are likely to disapear in coming decades. Similar studies in other parts of the world and on specific glaciers can reveal links with climate factors, reconstruct mass balance, and enhance comprehension of glacier response to climate change. Our geodetic mass balance estimates will improve the estimation of meltwater run-off component of the hydrological cycle in this part of the Himalaya, which could be used to calibrate/validate glacier mass balance models.

Illuminating the complexity of hydrogeological regimes in fault-influenced, anticlinal karst aquifers: Insights into the recharge patterns in tectonically complex karst catchments

For many countries, karst aquifers are a significant source of potable water; thus, understanding their hydrogeological behavior is of great importance. However, in tectonically complex karst areas, knowledge of their hydrogeological behaviors has remained largely limited due to the high heterogeneity, often necessitating the use of costly and time-consuming techniques. In this study, spring discharge hydrographs, water balance estimates, hydrochemical and stable isotopic analyses, geomorphological surveys, and a consideration of the geological and structural setting of the study area were used to investigate the hydrogeological function of karst aquifers drained by two large permanent springs: the Bibitalkhone (Bt) and Sabzab (Sa) springs, located in a highly faulted catchment in the Zagros Mountains (southwest Iran). The results obtained from these different approaches suggested that fault-controlled, external waters from neighboring karst aquifers are responsible for more than two-thirds of the total discharge recorded at both springs. In this study, this predominantly conduit-type recharge is referred to as “regional (or external) autogenic recharge”. A smaller portion of the springs’ discharge (∼25% and ∼5% of the Bt and Sa springs’ discharge, respectively) originates from internal waters associated with the springs’ host aquifer, which is supplied by rainfall and infiltrates into the subsurface via joints and fractures. This type of recharge is largely diffuse and is referred to here as “local (or internal) autogenic recharge”. A relatively large portion of the Sa Spring’s discharge (∼35%) originates from a nearby dam reservoir, which can leak into the host spring aquifer through joints and fractures. This type of recharge is described as “local (or internal) allogenic recharge” and is primarily diffuse. The results of this study demonstrate that the karst aquifers in the downstream catchments can supply a stable and continuous source of potable groundwater that can meet the region’s annual consumption, agricultural, and industrial demands. This study will provide insights into the hydrogeological regimes of fault-influenced aquifers, contributing to the sustainable development and proper management of water resources in tectonically complex karst catchments.

Design of a Sensor-Technology-Augmented Gait and Balance Monitoring System for Community-Dwelling Older Adults in Hong Kong: A Pilot Feasibility Study.

Routine assessments of gait and balance have been recognized as an effective approach for preventing falls by issuing early warnings and implementing appropriate interventions. However, current limited public healthcare resources cannot meet the demand for continuous monitoring of deteriorations in gait and balance. The objective of this study was to develop and evaluate the feasibility of a prototype surrogate system driven by sensor technology and multi-sourced heterogeneous data analytics, for gait and balance assessment and monitoring. The system was designed to analyze users' multi-mode data streams collected via inertial sensors and a depth camera while performing a 3-m timed up and go test, a five-times-sit-to-stand test, and a Romberg test, for predicting scores on clinical measurements by physiotherapists. Generalized regression of sensor data was conducted to build prediction models for gait and balance estimations. Demographic correlations with user acceptance behaviors were analyzed using ordinal logistic regression. Forty-four older adults (38 females) were recruited in this pilot study (mean age = 78.5 years, standard deviation [SD] = 6.2 years). The participants perceived that using the system for their gait and balance monitoring was a good idea (mean = 5.45, SD = 0.76) and easy (mean = 4.95, SD = 1.09), and that the system is useful in improving their health (mean = 5.32, SD = 0.83), is trustworthy (mean = 5.04, SD = 0.88), and has a good fit between task and technology (mean = 4.97, SD = 0.84). In general, the participants showed a positive intention to use the proposed system in their gait and balance management (mean = 5.22, SD = 1.10). Demographic correlations with user acceptance are discussed. This study provides preliminary evidence supporting the feasibility of using a sensor-technology-augmented system to manage the gait and balance of community-dwelling older adults. The intervention is validated as being acceptable, viable, and valuable.

Combination of geometric and gravimetric data sets for the estimation of high-resolution mass balances of the Greenland ice sheet

SUMMARY In this study, we develop a model that allows to combine gravimetric and geometric data. By the combination, we improve the spatial resolution of the resulting mass balance estimate compared to a purely gravimetric one. The equivalent ice or firn density of the changing ice volume is estimated within a mathematical inversion model, which includes geometric information about the volumetric change of the ice sheet and the resulting gravity change. This gravity change is computed from monthly GRACE gravity fields. They have a limited spatial resolution of a few 100 km, but allow direct conclusions about the true mass changes over Greenland. The ice-volume changes are described by a product by the Climate Change Initiative of European Space Agency, which is based on altimetry data. They have a very fine spatial resolution (down to a few km), but are not directly sensitive to mass changes. By combining both data sets in a common mathematical model, the advantages of both data types (direct sensitivity to mass versus high spatial resolution) are made use of. In this way, we improve the spatial resolution of mass balance estimates over Greenland. This leads to a map of mass trends, which has the same spatial resolution as the input map of geometric changes, but which is consistent with the input gravity fields. It will enable improving the localization of mass change signals of ice sheets and glaciers, which are usually rather small-scale. We compare our estimates to the results of complementary studies regarding the total mass loss of the Greenland ice sheet and its surrounding land surface. Our study leads to a value of $-213\pm 37\, \text{Gt}\,\text{a}^{-1}$ in the time span from 2011 to 2015. We also discuss the problem of separating the mass contribution of the Greenland ice sheet itself and its surrounding region.

Surface mass balance calculation with ground observation in the sub-basin of Larsemann Hills, East Antarctica

The study includes ground-based data of surface mass balance calculations to assess the input of climate change on the ice sheet health. The study covers an approximately 471 km2 area of the ice sheet that lies in between the Dålk and Polarårboken glaciers, Larsemann Hills, Prince Elizabeth, East Antarctica. Snow accumulation/ablation data is collected from 13 stake networks and 06 single stakes installed on the ice sheet. The monitored area is extrapolated on the basis of elevation and glaciological parameters using ArcGIS 10.8.1. The exposed height and precise locations of stakes have been recorded using DGPS and compared with the preceeding year's datasets. The annual measure accumulation/ablation data is processed in ArcGIS for the estimation of surface mass balance since 2018. The accumulation/ablation rate of the ice sheet is not uniform and influenced by the meteorological parameters i.e. temperature, precipitation and wind speed. The values of net surface mass balance are 0.027 Gt yr−1, 0.088 Gt yr−1, 0.044 Gt yr−1, and 0.026 Gt yr−1 since 2018 to 2021 respectively.

Historical and projected evolutions of glaciers in response to climate change in High Mountain Asia

Glacier changes are regarded as the conspicuous icon of climate change in High Mountain Asia (HMA) alpine environments. Multi-temporal glacier coverage is essential for mass balance estimations and understanding glacial changes in response to climate variability. However, consistent multi-temporal glacier area datasets across the HMA are limited due to challenges posed by seasonal snow and cloud cover in remote sensing satellite images. In this study, a new method is proposed to estimate glacier and nonseasonal snow (GNS) areas by combining the normalized difference snow index (NDSI) and bright temperature bands from Landsat remote sensing images in 1990s, 2000s, 2010s and 2020s. Meanwhile, the integrated ice dynamic Open Global Glacier Model (OGGM) is applied to simulate nine typical glaciers and project their changes using 15 general circulation models (GCMs) under four shared socioeconomic pathways (SSPs). The results showed that total GNS areas in HMA were estimated at 71.26 × 103 km2 in the 1990s, and decreased to 53.17 × 103 km2 in the 2020s. Massive proportions of GNS were mainly distributed in the southeast and northwest region. Tipping points of GNS indicating a transition from mass balance gain to loss during four periods were detected in the Upper Tarim basin, Inner Tibetan Plateau, Upper Yangtze river basin, Upper Brahmaputra river basin, and Upper Salween river basin. The reduction of total GNS area was attributed to significantly rising temperature and decreasing solid precipitation. The projections indicate that glacier shrinkages will be the dominant trend in the future, and most typical glaciers will experience a mass loss of 60% under SSP245 (SSP2-RCP4.5) and over 90% under SSP585 (SSP5-RCP8.5) by the end of the century. The response of glaciers to climate change is also found to be influenced by factors including local topography and elevation ranges. The findings of this study provides a better understanding of glacial dynamics in response to climate change and highlights the importance of making water resources management strategies to mitigate the influence of glacier retreat.

Bayesian parameter estimation in glacier mass-balance modelling using observations with distinct temporal resolutions and uncertainties

Abstract Empirical glacier mass-balance models are commonly used in assessments of glacier and runoff evolution. Recent satellite-borne geodetic mass-balance observations of global coverage facilitate large-scale model calibration that previously relied on sparse in situ observations of glacier mass change. Geodetic observations constitute temporally aggregated mass-balance signals with significant uncertainty, raising questions about the role of observations with different temporal resolutions and uncertainties in constraining model parameters. We employ a Bayesian approach and demonstrate the sensitivity of parameter values to commonly used mass-balance observations of seasonal, annual and decadal resolution with uncertainties characteristic to in situ and satellite-borne observations. For glaciers along a continentality gradient in Norway, the use of annual mass balances results in around 20% lower magnitude of modelled ablation and accumulation (1960–2020), compared to employing seasonal balances. Decadal mass balance also underestimates magnitudes of ablation and accumulation, but parameter values are strongly influenced by the prior distribution. The datasets yield similar estimates of annual mass balance with different margins of uncertainty. Decadal observations are afflicted with considerable uncertainty in mass-balance sensitivity due to high parameter uncertainty. Our results highlight the importance of seasonal observations when model applications require accurate magnitudes of ablation, e.g. to estimate meltwater runoff.

Canopy Leaching Rather than Desorption of PM2.5 From Leaves Is the Dominant Source of Throughfall Dissolved Organic Carbon in Forest

AbstractDissolved organic carbon (DOC) in throughfall plays a vital role in providing carbon and energy to organisms in forests. We utilized carbon isotope analysis to allocate the sources of throughfall DOC, including leaching from plant tissues, PM2.5 deposition on plant foliage, and precipitation. Rainwater, PM2.5, and throughfall samples were collected from pine and oak forests between March and November 2021. The mean concentration of throughfall DOC was 7.9 mg L−1, approximately six times higher than that of rainfall. The mean Δ14C of throughfall DOC was −38.2‰, ∼200‰ higher than that of rainwater or PM2.5. Mass balance estimates revealed that canopy leaching contributed to ∼83% of throughfall DOC, while desorption of PM2.5 and rainwater accounted for only ∼3% and ∼14% of throughfall DOC, respectively. These results clearly highlight canopy leaching as the primary source of carbon input to the forest floor, with a relatively minor contribution from PM2.5 desorption on leaves.

Long-term estimation of glacier mass balance using geospatial techniques in Western Himalayas, Ladakh, India

All glaciers are subject to mass fluctuations in the current context of climate change. For daily requirements like food, drink, irrigation, and the generation of hydroelectric power, these glaciers provide water to important basins including the Indus, Ganga, and Brahmaputra. Changes in glacier patterns are a blatant sign of local climate variability. Monitoring of glaciers requires long-term studies on glacier dynamics. Himalayan glaciers, because of their disposition in a complex topographic setting and inaccessible terrain render difficulty in the glacier observations in a continuous mode. Glacier mass fluctuations can be associated with glacier area shrinkage or expansion and concomitant snout shift. In the current study, two adjoining glaciers of different sizes, Pensilungpa and Drang Drung glaciers in the Zanskar Valley, Ladakh, India are selected. The period of the study was taken between the years 2000–2022. Earlier studies used a single day per year Accumulation Area Ratio (AAR) method to compute mass balance, which had limitations due to snow cover variability. The present study calculated and averaged all the AAR values for cloud-free images per year during the peak ablation period (mid-July to early September). Digital Elevation Model (DEM) difference technique was also employed for computing the mass budget between 2000 and 2021 b y utilizing two-time period DEMs. It was revealed that in the case of the AAR method, the Pensilungpa glacier showed 7 years of positive and 16 years of negative mass balance. The years 2003–2005 and 2011 to 2016 were depicted with negative mass balance with the highest value up to −0.752-m water equivalent (m.w.e.) for the year 2015. It has negligible areal fluctuations ranging from 0.01 to 0.6 km2. Drang Drung Glacier has shown 12 years of positive and 11 years of negative mass balance. The years 2002–2004 and 2009 to 2012 were depicted with positive mass balance with the highest value up to 0.305 m. w.e. Except, for the year 2009–2012 (areal increment ∼ 2.65 km2), years 2013–2015 showed a negative mass balance with negligible areal fluctuations. Mass balance estimation using DEM differencing method revealed an average estimated mass balance of −0.03 m. w.e. For Pensilungpa glacier though, it is 0.08 m. w.e. For Drang Drung glacier which shows good matches with the mass balance estimated using AAR method in m. w.e. Such contrasting behavior of mass balance suggests higher sensitivity of smaller glaciers to climate change.