Balanced Framework Research Articles

The EU regulatory data protection in the agrochemical industry: Towards a data sharing model in favour of sustainable market play and a sustainable environment

AbstractRegulatory data protection is mandated in the Agreement on the Trade Related Aspects of Intellectual Property Rights (TRIPS Agreement) for two kinds of goods: medicinal products and plant protection products (PPP). In the European Union (EU), the level of their protection has been set far beyond the minimum TRIPS standards and the adopted model of protection has been, for the most part, based on temporary exclusivity. Innovative plant protection products benefit from data exclusivity combined with a compulsory data sharing regime. Data exclusivity refers to products being authorised for the first time for the market of the EU on the grounds of a complete authorisation procedure, based on submission of a full data dossier. Within the period of exclusivity, these data may not be referred to in the authorisation procedure of a generic product—an equivalent to the reference one. In this way, data exclusivity creates a period of factual monopoly for the innovative products and constitutes a sui generis intellectual property right. This paper presents the regime of regulatory data protection in the European Union law as an instrument of legal protection for innovative products in the agrochemical industry. It first analyzes the purpose and functions of regulatory data protection in EU law and in the TRIPS Agreement. Then, the rules of protection by means of data exclusivity and compulsory data sharing are examined. This allows for further considerations on the role of regulatory data protection and compulsory sharing of data in the overall legal protection for innovative products in the agrochemical industry. In view of the above, this chapter discusses both the instruments of protection for PPP regulatory data and poses several questions concerning their rules, practical meaning and possible future modifications. In particular, it is considered whether data exclusivity is the optimal regime of protection for registration data and recommend that a data sharing approach could be used instead of the data exclusivity rule, as is the case with compulsory vertebrate data sharing, to the benefit of the industry and public interest. This chapter allows for evaluation and assessment of the economic and social value of data exclusivity in said areas for fostering primary and secondary innovation, while acknowledging other vital interests such as protection of public interest and safeguarding competition in the relevant markets. Finally, this chapter maps challenges of the current model of protection and indicates areas for further consideration in both creating a coherent and balanced framework of PPP data protection and the possible extrapolation of the data sharing rules to systems of data protection for other life science products.

Partitioning of respired CO2 in newly sprouted Moso bamboo culms.

Stem respiration (R s) plays a vital role in ecosystem carbon cycling. However, the measured efflux on the stem surface (E s) is not always in situ R s but only part of it. A previously proposed mass balance framework (MBF) attempted to explore the multiple partitioning pathways of R s, including sap-flow-transported and internal storage of R s, in addition to E s. This study proposed stem photosynthesis as an additional partitioning pathway to the MBF. Correspondingly, a double-chamber apparatus was designed and applied on newly sprouted Moso bamboo (Phyllostachys edulis) in leafless and leaved stages. R s of newly sprouted bamboo were twice as high in the leafless stage (7.41 ± 2.66 μmol m-2 s-1) than in the leaved stage (3.47 ± 2.43 μmol m-2 s-1). E s accounted for ~80% of R s, while sap flow may take away ~2% of R s in both leafless and leaved stages. Culm photosynthesis accounted for ~9% and 13% of R s, respectively. Carbon sequestration from culm photosynthesis accounted for approximately 2% of the aboveground bamboo biomass in the leafless stage. High culm photosynthesis but low sap flow during the leafless stage and vice versa during the leaved stage make bamboo an outstanding choice for exploring the MBF.

The Varying Earth’s Radiative Feedback Connected to the Ocean Energy Uptake: A Theoretical Perspective from Conceptual Frameworks

Abstract When quadrupling the atmospheric CO2 concentration in relation to preindustrial levels, most global climate models show an initially strong net radiative feedback that significantly reduces the energy imbalance during the first two decades after the quadrupling. Afterward, the net radiative feedback weakens, needing more surface warming than before to reduce the remaining energy imbalance. Such weakening radiative feedback has its origin in the tropical oceanic stratiform cloud cover, linked to an evolving spatial warming pattern. In the classic linearized energy balance framework, such variation is represented by an additional term in the planetary budget equation. This additional term is usually interpreted as an ad hoc emulation of the cloud feedback change, leaving unexplained the relationship between this term and the spatial warming pattern. I use a simple nonlinearized energy balance framework to justify that there is a physical interpretation of this term: the evolution of the spatial pattern of warming is explained by changes in the ocean’s circulation and energy uptake. Therefore, the global effective thermal capacity of the system also changes, leading to the additional term. In reality, the clouds respond to what occurs in the ocean, changing their radiative effect. In the equation, the term is now a concrete representation of the ocean’s role. Additionally, I derive for the first time an explicit mathematical expression of the net radiative feedback and its temporal evolution in the linearized energy balance framework. This mathematical expression supports the new proposed interpretation. As a corollary, it justifies the 20-yr time scale used to study the variation of the net radiative feedback. Significance Statement Linearized energy balance models have helped the study of Earth’s radiative response. However, the present linear models are at the edge of usefulness to get more insights. In this work, I justify that part of the nonlinearity in the radiative response can be explained without peculiar atmospheric radiative feedback mechanisms or a nonlinearity in the radiative response. Instead, the concept of an evolving thermal capacity recovers the ocean’s role in redistributing the energy, changing the spatial warming pattern, and, finally, altering the atmospheric feedback mechanisms. This work also justifies the time scales used in the field for studying the variation of the net radiative feedback.

Integrating temperature gradient-based 3T and resistance-based models for simulating evapotranspiration and its components

The accurate estimation of evapotranspiration (ET) and its major components [e.g., transpiration (Tr) and soil evaporation (Ev)] requires an understanding of complex soil–plant-atmosphere interactions. The temperature gradient-based three temperature (3T) model for simulating the dynamics of Ev and Tr has no requirement for resistance terms and its use of simple input variables (i.e., temperature and radiation) allows its application to both field studies and remote sensing. However, reference temperature is a key requirement for the 3T model and approaches for obtaining accurate reference temperature and the implications of different reference temperature choices on ET estimates remain poorly understood. This study improved a resistance-based model applicable to a wide range of climatic/ecosystem conditions and integrated it with the 3T model to predict ET and Tr. A novel numerical approach was used to estimate the reference temperature under dry land surface scenarios. The two models provided similar predictions of Ev, Tr, and ET at the four sites provided that the available energy for the canopy (e.g., net radiation) and ground soil (e.g., net radiation and ground heat flux) was constrained within the framework of the energy balance. Alternatively, the accuracy of simulations of Ev and ET by the 3T model significantly declined due to systematic mismatching of input drivers (temperature and radiation) under dry and wet scenarios. We emphasize that 3T is working better when input temperature and radiation under dry and wet land conditions were systematically matched within the framework of energy balance. The results of this study provide a promising novel temperature-gradient method for detecting canopy water stress.

Balanced Mixture Design Framework for Asphalt Mixtures Based on Index- and Performance-Volumetrics Relationships

Asphalt mixture design methods range from approaches that rely on the volumetric properties of the mix to those that are based on the pavement performance. More advanced mixture analysis procedures allow a comprehensive evaluation that attempts to predict pavement distress based on factors such as traffic, climate, and mixture properties. Among them, balanced mix design (BMD) has been a frequently used approach; its purpose is to achieve an optimum balance between stability and durability. The objective of this work is to bridge the gap between the volumetric properties and performance of asphalt mixtures with respect to pavement fatigue cracking and rutting. In the study, an asphalt mixture was initially designed and then variations in voids in mineral aggregate (VMA) and voids filled with asphalt (VFA) were evaluated based on specified volumetric limits to create a broad volumetric space. Then, dynamic modulus, cyclic fatigue, and stress sweep rutting (SSR) tests were performed at each volumetric condition. Index-volumetrics and performance-volumetrics relationships were calibrated and the optimum mixture design was identified. In addition, a BMD framework was developed, which allows the mixture performance evaluation at multiple volumetric conditions and the selection of an optimized mixture based on the predicted pavement performance and on indexes for all possible combinations of the given set of component materials.

Crimea in Ukraine: Smoothing the Edges as Diversity Institutionalization

From the early 1990s, Ukrainian Crimea seemed to face the Russian majority’s separatist inclinations and far-reaching political claims of the formerly deported Crimean Tatars. Nevertheless, the peninsula’s autonomous status secured ethnopolitical stability for about 19 years, and the article considers how the established regime of diversity governance contributed to the autonomy’s endurance. The author concludes that this regime did not fit into an explanatory framework of inter-group balance, such as power-sharing. Among the factors securing durablity were the ambiguity of official narratives, loosely formalized participatory mechanisms encouraging opportunisic behavior and the maintenace of the elites’ and population segments’ expectations.

An efficient multiple harmonic balance method for computing quasi-periodic responses of nonlinear systems

Quasi-periodic responses composed of multiple base frequencies widely exist in science and engineering problems. The multiple harmonic balance (MHB) method is one of the most commonly used approaches for such problems. However, it is limited by low-order estimations due to complex symbolic operations in practical uses. Many variants have been developed to improve the MHB method, among which the time domain MHB-like methods are regarded as crucial improvements because of their high efficiency and simple derivation. But there is still one main drawback remaining to be addressed. The time domain MHB-like methods negatively suffer from non-physical solutions, which have been shown to be caused by aliasing (mixtures of the high-order into the low-order harmonics). Inspired by the collocation-based harmonic balancing framework recently established by our group, we herein propose a reconstruction multiple harmonic balance (RMHB) method to reconstruct the conventional MHB method using discrete time domain collocations. Our study shows that the relation between the MHB and time domain MHB-like methods is determined by an aliasing matrix, which is non-zero when aliasing occurs. On this basis, a conditional equivalence is established to form the RMHB method. Three numerical examples demonstrate that this new method is more robust and efficient than the state-of-the-art methods.

A re‐examination of the plant variety act 2021 from the perspective of pre‐exisiting obligation to protect plant varieties

AbstractThe paper examines the newly enacted Plant Variety Act in Nigeria in relation to the obligations of Nigeria to protect plant varieties. The paper views these obligations from different perspectives in the protection of diverse interest related to plant varieties. The paper finds that the Act offers an unbalanced protection of right which strongly protects the intellectual property rights of breeders without recourse to the other interest obligated to be protected by several international agreement which Nigeria is a signatory to especially farmers', communities and biodiversity interests. The paper advocates for an amendment of the Act to ensure a balanced and compliant legal framework for the protection of plant varieties in Nigeria.

Gradual behaviour change towards meat reduction: Development and validation of a novel decisional balance scale

Meat reduction is gaining attention among consumers, marketers, policymakers and scientists. Yet little is known about decision-making processes and behaviour change towards meat reduction. This paper explores the applicability of the decisional balance (DB) framework to the field of meat reduction. A novel DB scale to measure the perceived importance of beliefs about meat reduction at different stages of behaviour change was developed and validated in two studies with German meat eaters. In Study 1 (N = 309), the item inventory was tested using an exploratory factor analysis and then validated in Study 2 (N = 809). The results yielded two higher-order DB factors (pros and cons), which were subdivided into five lower-order factors (perceived benefits of a plant-based diet, downsides of factory farming, health barriers, legitimation barriers and feasibility barriers). The pros and cons were summarised in a DB index. All DB factors and the DB index were tested for internal consistency (Cronbach's alpha ≥.70) and aspects of validity. The typical DB pattern of the pros and cons of behaviour change was confirmed: the cons outweighed the pros for consumers who did not intend to reduce meat consumption, while the pros outweighed the cons for consumers who intended to reduce meat consumption. The new DB scale for meat reduction has proven to be a suitable measure to gain insights into consumers' decision making and could be used to develop targeted meat reduction interventions.

Technical note: A stochastic framework for identification and evaluation of flash drought

Abstract. The rapid development of droughts, referred to as flash droughts, can pose serious impacts on agriculture, the ecosystem, human health, and society. However, its definition, using pentad-averaged soil moisture, could result in low accuracy in assessing the drought occurrence, making it difficult to analyze various factors controlling the formation of flash droughts. Here we used a stochastic water balance framework to quantify the whole probability structure of the timing for soil moisture dropping from a higher level to a lower one. Based on this framework, we can theoretically examine the nonlinear relationship between the rapid decline rate of soil moisture and various hydrometeorological factors and identify possible flash drought risks caused by less rainfall (e.g., long dry spells), higher evapotranspiration (e.g., extreme heat waves), lower soil water storage capacity (e.g., deforestation), or a combination thereof. Applying this framework to the global datasets, we obtained global maps of the average time for drought development and the risks of flash drought. We found that possible flash drought development in humid regions, such as southern China and the northeastern United States, calls particular attention to the need for flash drought monitoring and mitigation.

A Voronoi-Based Semantically Balanced Dummy Generation Framework for Location Privacy

Location-based services (LBS) require users to provide their current location for service delivery and customization. Location privacy protection addresses concerns associated with the potential mishandling of location information submitted to the LBS provider. Location accuracy has a direct impact on the quality of service (QoS), where higher location accuracy results in better QoS. In general, the main goal of any location privacy technique is to achieve maximum QoS while providing minimum or no location information if possible, and using dummy locations is one such location privacy technique. In this paper, we introduced a temporal constraint attack whereby an adversary can exploit the temporal constraints associated with the semantic category of locations to eliminate dummy locations and identify the true location. We demonstrated how an adversary can devise a temporal constraint attack to breach the location privacy of a residential location. We addressed this major limitation of the current dummy approaches with a novel Voronoi-based semantically balanced framework (VSBDG) capable of generating dummy locations that can withstand a temporal constraint attack. Built based on real-world geospatial datasets, the VSBDG framework leverages spatial relationships and operations. Our results show a high physical dispersion cosine similarity of 0.988 between the semantic categories even with larger location set sizes. This indicates a strong and scalable semantic balance for each semantic category within the VSBDG’s output location set. The VSBDG algorithm is capable of producing location sets with high average minimum dispersion distance values of 5861.894 m for residential locations and 6258.046 m for POI locations. The findings demonstrate that the locations within each semantic category are scattered farther apart, entailing optimized location privacy.

Does Nepal Have the Agriculture to Feed Its Population with a Sustainable Diet? Evidence from the Perspective of Human–Land Relationship

Nepal is one of the least developed countries in the world, with more than 80% of the population engaged in agricultural production and more than two-fifths of the population still living below the poverty line. Ensuring food security has always been a key national policy in Nepal. Using a nutrient conversion model and an improved resource carrying capacity model as well as statistical data and household questionnaires, an analysis framework for food supply balance is developed in this study, which quantitatively analyzes the balance of food supply and demand in Nepal from the perspectives of food and calories during the period 2000-2020. Nepal's agricultural production and consumption have increased significantly, and the diet has been relatively stable over the past two decades. The diet structure is stable and homogeneous, with plant products occupying the absolute position in overall dietary consumption. The supply of food and calories varies widely from region to region. Although the increasing supply level at the national scale can meet the needs of the current population, the food self-sufficiency level cannot meet the needs of the local population development at the county level due to the influence of population, geographical location, and land resources. We found that the agricultural environment in Nepal is fragile. The government can improve agricultural production capacity by adjusting the agricultural structure, improving the efficiency of agricultural resources, improving the cross-regional flow of agricultural products, and improving international food trade channels. The food supply and demand balance framework provided a reference for achieving balance between the supply and demand of food and calories in a resource-carrying land and provides a scientific basis for Nepal to achieve zero hunger under the framework of the Sustainable Development Goals. Furthermore, development of policies in order to increase agricultural productivity will be critical for improving food security in agricultural countries such as Nepal.

Financing decision, ownership type and financial performance of listed non-financial companies in Ghana

The study aims to investigate the nexus between financing decision, ownership type and financial performance of listed non-financial companies in Ghana. Data were selected from 22 listed non-financial companies on the Ghana Stock Exchange from the years 2010 to 2021. A non-parametric estimation technique-robust OLS (Driscoll-Kraay) was employed to test the variables of interest. Findings indicate that long-term debt funding directly affects ROA, ROE and TQ negatively. Again, total debt funding posits a positive link with ROE and TQ. Moreover, the direct relationship between ownership type, financing decision and accounting-based performance measure (ROE) was insignificant but significant with market-based performance measure (TQ). Subsequently, the interaction role propelled ownership (foreign and state) to be significant on the relation between financing decision and financial performance. Largely, foreign-owned companies play a strong positive role on the link between financing decision and financial performance. Further, state ownership negatively affects the association between financing decision and financial performance. The study contributes to knowledge by considering the multiplier effect of ownership type on the relationship between financing decision and financial performance in Ghana. For policy implication, regulators specifically of state interest entities should formulate balanced frameworks for welfare seeking in public service delivery and performance for sustainability.

Toward Principled Background Principles in Takings Law

Oversights by lawyers, judges, and legal scholars have caused the Supreme Court’s opinion in Cedar Point Nursery v. Hassid to be deeply misunderstood. In Cedar Point, the Court rewrote much of takings law by treating temporary and part-time entries by the government or third parties onto private property as per se takings. Prior to Cedar Point, these sorts of government-authorized physical entries would have been evaluated under a balancing framework that almost invariably enabled the government to prevail. As it happens, there was a well-established rule of black letter law that California’s lawyers and amici failed to invoke in defending the Cedar Point union organizer’s access regulation: A physical takings claim accrues when a regulation authorizing third parties to enter private property is promulgated, not when the third party actually enters the land. A second timing rule was plausibly applicable too: Only the party that owned the land at the time the physical taking cause of action accrued can prevail, and Cedar Point Nursery acquired the land at issue decades later. As a result, Cedar Point Nursery’s lawsuit was filed decades too late. Quite possibly by the wrong plaintiff. California’s mistakes were probably outcome determinative.
 Moving beyond Monday-morning quarterbacking, we argue that the statute of limitations arguments available to governments in future cases help provide the essential limiting principles that went unmentioned in Cedar Point. In the aftermath of Cedar Point, prominent scholars denounced the opinion as a vehicle for gutting antidiscrimination law, labor law, environmental law, rent control, and other parts of the regulatory state. Our analysis reveals that these concerns are likely exaggerated because defenders of those longstanding limits on the right to exclude can invoke the statute of limitations arguments that California’s lawyers failed to raise. On the other hand, new restrictions on owners’ rights to exclude are vulnerable to legal challenge. Properly understood, contemporary takings law grandfathers in many longstanding limits on the right to exclude while constraining governments that wish to tackle collective action problems by restricting property rights in new ways. Moreover, statutes of limitations and related doctrines can provide courts with something that has been elusive since the Supreme Court’s 1992 takings decision in Lucas v. South Carolina Coastal Council: a principled and coherent account of what restrictions on owners’ rights are impervious to takings claims because they qualify as background principles of state property law.

A primer on stream temperature processes

AbstractStream temperature is one of the most critical factors controlling aquatic ecosystem health. Practitioners and researchers from a range of fields, including biology, ecology, hydrology, engineering, and watershed management, are concerned with how climate and environmental changes are impacting stream thermal regimes. This primer provides an introduction to the various energy and water exchange processes that underpin stream temperature patterns from small headwater streams to large river systems. An overview of the various energy exchanges is provided, including (1) advection associated with hydrologic processes, and energy exchanges at (2) the stream–atmosphere interface and (3) stream–bed interface. The interaction and spatiotemporal variability of these energy exchange processes are discussed using a water and energy balance framework. A sound physical understanding and appreciation of the complex controls governing stream thermal regimes will help inform effective management strategies to sustain healthy aquatic ecosystems in a changing world.This article is categorized under: Science of Water > Science of Water Science of Water > Hydrological Processes Science of Water > Water Quality Water and Life > Nature of Freshwater Ecosystems

CLAIRE: contrastive learning-based batch correction framework for better balance between batch mixing and preservation of cellular heterogeneity.

Integration of growing single-cell RNA sequencing datasets helps better understand cellular identity and function. The major challenge for integration is removing batch effects while preserving biological heterogeneities. Advances in contrastive learning have inspired several contrastive learning-based batch correction methods. However, existing contrastive-learning-based methods exhibit noticeable ad hoc trade-off between batch mixing and preservation of cellular heterogeneities (mix-heterogeneity trade-off). Therefore, a deliberate mix-heterogeneity trade-off is expected to yield considerable improvements in scRNA-seq dataset integration. We develop a novel contrastive learning-based batch correction framework, CIAIRE, which achieves superior mix-heterogeneity trade-off. The key contributions of CLAIRE are proposal of two complementary strategies: construction strategy and refinement strategy, to improve the appropriateness of positive pairs. Construction strategy dynamically generates positive pairs by augmenting inter-batch mutual nearest neighbors (MNN) with intra-batch k-nearest neighbors (KNN), which improves the coverage of positive pairs for the whole distribution of shared cell types between batches. Refinement strategy aims to automatically reduce the potential false positive pairs from the construction strategy, which resorts to the memory effect of deep neural networks. We demonstrate that CLAIRE possesses superior mix-heterogeneity trade-off over existing contrastive learning-based methods. Benchmark results on six real datasets also show that CLAIRE achieves the best integration performance against eight state-of-the-art methods. Finally, comprehensive experiments are conducted to validate the effectiveness of CLAIRE. The source code and data used in this study can be found in https://github.com/CSUBioGroup/CLAIRE-release. Supplementary data are available at Bioinformatics online.

ExaLB: a mathematical framework for load balancing to support distributed exascale computing environments

ExaLB: a mathematical framework for load balancing to support distributed exascale computing environments

Optimal plant water use strategies explain soil moisture variability

Plant responses to water stress influence water and carbon cycles and can lead to feedbacks on climate yet characterizing these responses at ecosystem levels remains uncertain. Quantifying ecosystem-level water use strategies is complex due to challenges of upscaling plant traits and disentangling confounding environmental factors, ultimately limiting our ability to understand and anticipate global change in ecosystem dynamics and ecohydrological fluxes. We reduce the dimensionality of this problem and quantify plant water use strategies by combining plant traits with soil and climate variables into parameter groups that synthesize key eco-physiological tradeoffs. Using a parsimonious soil water balance framework, we explore variations in plant water uptake capacity, water stress responses, and water use performance via these non-dimensional parameter groups. The group characterizing the synchronization of plant water transport and atmospheric water demand emerges as the primary axis of variation in water use strategies and interacts with the group representing plant hydraulic risk tolerance, especially in arid conditions when plant water transport is limiting. Next, we show that specific plant water use strategies maximize plant water uptake (leading to carbon gain benefits) weighted by risks of water stress (leading to higher costs of water use). A model-data comparison demonstrates that these ecohydrologically optimal parameter groups capture observed soil moisture variability in 40 ecosystems and beyond aridity, rainfall frequency is an important environmental control for plant water use strategies. The emerging parsimonious link between ecohydrological performance and non-dimensional parameters provides a tractable representation of plant water use strategies, relevant to parameterize global models while accounting for ecological and evolutionary constraints on the water cycle.

Application of Population Balance Models in Particle-Stabilized Dispersions.

In this study, a first approach to model drop size distributions in agitated nanoparticle-stabilized liquid/liquid systems with population balance equations is presented. Established coalescence efficiency models fail to predict the effect of steric hindrance of nanoparticles at the liquid/liquid interface during the film drainage process. A novel modified coalescence efficiency is developed for the population balance framework based on the film drainage model. The elaborate submodel considers the desorption energy required to detach a particle from the interface, representing an energy barrier against coalescence. With an additional implemented function in the population balance framework, the interface coverage rate by particles is calculated for each time step. The transient change of the coverage degree of the phase interface by particles is thereby considered in the submodel. Validation of the modified submodel was performed with experimental data of agitated water-in-oil (w/o) dispersions, stabilized by well-defined spherical silica nanoparticles. The nanospheres with a size of 28 nm are positively charged and were hydrophobized by silanization with dimethyloctadecyl[3-(trimethoxysilyl)propyl]ammoniumchloride. This modeling approach is a first step toward predicting time-resolved dynamic drop size distributions of nanoparticle-stabilized liquid/liquid systems.

Response of glacier modelling parameters to time, space, and model complexity: Examples from eastern slopes of Canadian Rocky Mountains

Mountain glaciers are at risk of rapid retreat and require an accurate prediction of their melt and evolution. However, there is a great deal of hassle with mountain glacier melt modelling at a regional scale. Most advanced physical process-based models require an ample amount of high-resolution measurements, while widely-used empirical models suffer from parameter transferability. We developed a glacier melt, mass balance, and evolution modelling framework using three temperature index melt modelling approaches. We performed 24 model scenarios to examine the response of 19 empirical parameters to the effects of: (1) two time periods, for understanding how parameter response can vary with time period considered for the simulation; (2) two glaciers located at the eastern slopes of the Canadian Rocky Mountains, for understanding the effects of glaciers hydro-climate and geographic setting; and (3) two levels of complexity in the model structure including melt and mass balance models coupled with (complex) and without (simple) glacier evolution modules. The results showed that the best optimal melt parameter sets vary temporally and spatially for both simple and complex models, indicating that they are not transferable from one period to another and across glaciers. The variations of ice melt parameters are greater than the snowmelt parameters. The spatiotemporal variations of parameters are resulted from the geographical and local climatic settings and energy balance components, including albedo parameterization on the glacier surface, the altitudinal variations of the glaciers, and the slope and aspects to which glaciers are exposed. For all models, the most sensitive parameter is temperature Lapse rate (LR), but with increasing model complexity, the parameter responses vary depending on the melt model structure and input data. Our study provides important information for modelling glacier melt and evolution at a regional scale.