Integrated Modeling Framework Research Articles

Health co-benefits and mitigation costs as per the Paris Agreement under different technological pathways for energy supply

This study assesses the reductions in air pollution emissions and subsequent beneficial health effects from different global mitigation pathways consistent with the 2 °C stabilization objective of the Paris Agreement. We use an integrated modelling framework, demonstrating the need for models with an appropriate level of technology detail for an accurate co-benefit assessment. The framework combines an integrated assessment model (GCAM) with an air quality model (TM5-FASST) to obtain estimates of premature mortality and then assesses their economic cost. The results show that significant co-benefits can be found for a range of technological options, such as introducing a limitation on bioenergy, carbon capture and storage (CCS) or nuclear power. Cumulative premature mortality may be reduced by 17–23% by 2020–2050 compared to the baseline, depending on the scenarios. However, the ratio of health co-benefits to mitigation costs varies substantially, ranging from 1.45 when a bioenergy limitation is set to 2.19 when all technologies are available. As for regional disaggregation, some regions, such as India and China, obtain far greater co-benefits than others.

Rainwater harvesting for urban flood management – An integrated modelling framework

It is well known that rainwater harvesting (RWH) can augment water supply and reduce stormwater pollutant discharges. Due to the lack of continuous 2D modelling of urban flood coverage and its associated damage, the ability of RWH to reduce urban flood risks has not been fully evaluated. Literature suggests that small distributed storage spaces using RWH tanks will reduce flood damage only during small to medium flooding events and therefore cumulative assessment of their benefits is needed. In this study we developed a new integrated modelling framework that implements a semi-continuous simulation approach to investigate flood prevention and water supply benefits of RWH tanks. The framework includes a continuous mass balance simulation model that considers antecedent rainfall conditions and water demand/usage of tanks and predicts the available storage prior to each storm event. To do so, this model couples a rainfall-runoff tank storage model with a detailed stochastic end-use water demand model. The available storage capacity of tanks is then used as a boundary condition for the novel rapid flood simulation model. This flood model was developed by coupling the U.S. EPA Storm Water Management Model (SWMM) to the Cellular-Automata Fast Flood Evaluation (CA-ffé) model to predict the inundation depth caused by surcharges over the capacity of the drainage network. The stage-depth damage curves method was used to calculate time series of flood damage, which are then directly used for flood risk and cost-benefit analysis. The model was tested through a case study in Melbourne, using a recorded rainfall time series of 85 years (after validating the flood model against 1D-2D MIKE-FLOOD). Results showed that extensive implementation of RWH tanks in the study area is economically feasible and can reduce expected annual damage in the catchment by up to approximately 30 percent. Availability of storage space and temporal distribution of rainfall within an event were important factors affecting tank performance for flood reduction.

Mechanism-based modeling of thermal and irradiation creep behavior: An application to ferritic/martensitic HT9 steel

In this work, the creep behavior of HT9 steel in both thermal and irradiation environments is predicted using an integrated modeling framework. Multiple physical mechanisms such as diffusional creep and dislocation climb are incorporated into crystal plasticity calculations using the Visco-Plastic Self-Consistent (VPSC) approach. Climb velocities are informed by mean field rate theory laws in place of empirical power law formulations. More interestingly, the climb velocities explicitly consider the contribution of irradiation-induced point defects, i.e., stress induced preferential absorption (SIPA) effect. The developed expressions are shown to apply under conventional thermal creep and to the more complex irradiation conditions as well. This physically-informed, mechanism-based model is used to simulate the creep strain evolution of HT9 pressurized tubes under various loading conditions. It is demonstrated that the experimental behavior of this material reported in the literature is well described by this theoretical framework. The role of each relevant mechanism is discussed.

A watershed scale assessment of phosphorus remediation strategies for achieving water quality restoration targets in the western Everglades

Watershed scale models have become important tools to assess the effectiveness of regional and farm level remediation strategies for ecological restoration. The Everglades is an ecologically unique and complex system posing numerous challenges to water managers in South Florida. The Feeder Canal Basin (FCB) in Hendry County, Florida, drains 277 km2 of land into the central Everglades. During 2008–2017, the average annual total phosphorus (TP) concentration at the FCB outflow was approximately 89 μg/L, almost an order of magnitude higher than the restoration target for the Everglades marshes. This study aimed at evaluating remediation strategies - Best Management Practices (BMPs) and Stormwater Treatment Areas (STAs) to achieve TP targets for ecosystem restoration using an integrated modeling framework with a top-down approach. The baseline regime was modeled using the Watershed Assessment Model with multi-gage calibration (2000−2003) and validation (2004–2010). With the model performing satisfactory to very good for all gage locations, results indicated that row crops, groves & orchards, and improved pastures were largely responsible for TP concentrations and/or loads. BMP scenario results showed that TP loads could be reduced by 8% to 24% at the FCB outlet under minimal or very aggressive BMPs, respectively, indicating the need for additional water quality improvement projects to meet restoration targets. A preliminary design of two STAs, using the Dynamic Model for Stormwater Treatment Areas, estimated that a total of 52 km2 and 11.3 km2 of STAs will be required to achieve the TP concentration targets. The analysis framework employed in this study can be replicated in other watersheds to provide a holistic picture of remediation measures required to achieve water quality targets.

Integrated modelling of hot forging of low-alloyed steels for an ICME workflow

One of the key aspects of integrated computational materials engineering approach is the integrated modelling of process chains that capture the essential microstructure physics and predict the final properties. In the current work, such an integrated modelling approach is attempted for analyzing the hot forging process for low-alloyed steels. Traditionally, hot forging process is designed with primary focus on the deformation step, with less attention paid to the incorporation of microstructure information flow between its sub-steps of heating, deformation and cooling. Such a siloed approach restricts its integration with other manufacturing processes, and also with design and material selection stages. To address the issue, in this work, a FEM based thermo-mechanical modelling framework, integrating composition dependent microstructure evolution models for heating, deformation and cooling sub-steps, is implemented for hot forging of low-alloyed steels. The evolution of key microstructural features at each sub-step is tracked and fed to the following step. The integrated modelling framework is then used to study the effect of process parameters and macrosegregation in the billet on the distribution of final microstructure and properties obtained for a sample steel upsetting process. Key observations made in the studies are discussed. Ways of representation of the distribution of microstructure and properties across the forged part, that can enable better decision making in the larger perspective of downstream processing and final use, are highlighted. Consequently, the utility of the integrated modelling approach to aid the development of improved process and product design capabilities for hot forged products is established.

Understanding Business Disruption and Economic Losses Due to Electricity Failures and Flooding

Failure of critical national infrastructures can cause disruptions with widespread economic impacts. To analyze these economic impacts, we present an integrated modeling framework that combines: (1) geospatial information on infrastructure assets/networks and the natural hazards to which they are exposed; (2) geospatial modeling of the reliance of businesses upon infrastructure services, in order to quantify disruption to businesses locations and economic activities in the event of infrastructure failures; and (3) multiregional supply-use economic modeling to analyze wider economic impacts of disruptions to businesses. The methodology is exemplified through a case study for the United Kingdom. The study uses geospatial information on the location of electricity infrastructure assets and local industrial areas, and employs a multiregional supply-use model of the UK economy that traces the impacts of floods of different return intervals across 37 subnational regions of the UK. The results show up to a 300% increase in total economic losses when power outages are included in the risk assessment, compared to analysis that just includes the economic impacts of business interruption due to flooded business premises. This increase indicates that risk studies that do not include failure of critical infrastructures may be underestimating the total losses.

A knowledge-based method for the automatic determination of hydrological model structures

Abstract To determine a suitable hydrological model structure for a specific application context using integrated modelling frameworks, modellers usually need to manually select the required hydrological processes, identify the appropriate algorithm for each process, and couple the algorithms' software components. However, these modelling steps are difficult and require corresponding knowledge. It is not easy for modellers to master all of the required knowledge. To alleviate this problem, a knowledge-based method is proposed to automatically determine hydrological model structures. First, modelling knowledge for process selection, algorithm identification, and component coupling is formalized in the formats of the Rule Markup Language (RuleML) and Resource Description Framework (RDF). Second, the formalized knowledge is applied to an inference engine to determine model structures. The method is applied to three hypothetical experiments and a real experiment. These experiments show how the knowledge-based method could support modellers in determining suitable model structures. The proposed method has the potential to reduce the knowledge burden on modellers and would be conducive to the promotion of integrated modelling frameworks.

The economic value of stochastic climate information for agricultural adaptation in a semi-arid region in Austria

Identifying efficient adaptation measures in land and water use requires integrated approaches and a spatially and temporally explicit representation of water demand and supply. Stochastic climate information may further improve adaptation assessments to reduce the risk of misinterpretation of climate signals. We aim at developing an integrated modeling framework (IMF) that meets these requirements for assessing impacts of three stochastic climate scenarios (DRY, SIMILAR, WET), and regional irrigation water restrictions on land and water use. Furthermore, impacts on regional net benefits and the economic value of stochastic climate information (VOI) are assessed. The VOI is defined as the difference between regional net benefits with and without efficient adaptation of land and water use to a specific climate scenario. The IMF has been applied to the semi-arid Seewinkel region in Austria. Considering efficient adaptation, regional net benefits amount to 8 M€ and irrigation water use to 8.4 Mm³ in a DRY climate scenario. In a WET climate scenario and a scenario with SIMILAR conditions compared to the past, regional net benefits amount to 38 and 20 M€ and irrigation water use to 41 and 21 Mm³, respectively. High regional net benefits are obtained through an expansion of vineyards, irrigation, and fertilization. On average, the VOI is highest if land and water use is efficiently adapted to DRY but a WET scenario is realized (506 €/ha/a) and lowest with efficient adaptation to WET but the realization of a SIMILAR scenario (58 €/ha/a).

Cross‐Scale Interactions Dictate Regional Lake Carbon Flux and Productivity Response to Future Climate

AbstractLakes support globally important food webs through algal productivity and contribute significantly to the global carbon cycle. However, predictions of how broad‐scale lake carbon flux and productivity may respond to future climate are extremely limited. Here, we used an integrated modeling framework to project changes in lake‐specific and regional primary productivity and carbon fluxes under 21st century climate for thousands of lakes. We observed high uncertainty in whether lakes collectively were to increase or decrease lake CO2 emissions and carbon burial in our modeled region owing to divergence in projected regional water balance among climate models. Variation in projected air temperature influenced projected changes in lake primary productivity (but not CO2 emissions or carbon burial) as warmer air temperatures decreased productivity through reduced lake water volume. Cross‐scale interactions between regional drivers and local characteristics dictated the magnitude and direction of lake‐specific carbon flux and productivity responses to future climate.

Integrating Life Cycle Assessment and Agent-Based Modeling: A Dynamic Modeling Framework for Sustainable Agricultural Systems

Abstract As food demand increases, it is critical to develop effective strategies and evaluate their potential in reducing Greenhouse Gas (GHG) emissions and other environmental footprints of large-scale agricultural systems. This study addresses the challenge by developing a dynamic system modeling framework integrating Life Cycle Assessment (LCA), Agent-Based Modeling (ABM), and Techno-Economic Analysis (TEA). LCA and TEA were coupled with dynamic simulation models of crop yields, costs, and prices, allowing for the estimation of life-cycle environmental impacts and profitability of crop planting activities under changing climate and economic conditions. The framework was demonstrated by a case study for an agricultural system, including 1,000 farms in the United States over a 30-year time frame. The results indicated that information exchange among farmers, farmers' environmental awareness, access to environmental information, and farm size are key factors driving the system's environmental impacts. The results can provide a broad range of stakeholders (e.g., policymakers, nonprofits, agriculture companies) with insightful information to tailor their strategies for effectively managing the environmental footprints of large-scale agricultural systems. The integrated modeling framework has the potential to address sustainability challenges in other systems that are dynamic, involve human behaviors, and have complex interactions among human and nature systems.

Integrating distance sampling with minimum counts to improve monitoring

ABSTRACTMinimum counts are commonly used to estimate population size and trend for wildlife conservation and management; however, the scope of inference based on such data is limited by untestable assumptions regarding the detection process. Alternative approaches, such as distance sampling, occupancy surveys, and repeated counts, can be employed to produce detection‐corrected estimates of population parameters. Unfortunately, these approaches can be more complicated and costly to implement, potentially limiting their use. We explored a conceptual framework linking datasets collected at different spatial scales under different survey designs, with the goal of improving inference. Specifically, we link landscape‐scale distance sampling surveys with local‐scale minimum counts in an integrated modeling framework to estimate mountain goat (Oreamnos americanus) abundance at both the local and regional scale in south‐central Alaska, USA, and provide an estimate of detection probability (i.e., sightability) for the minimum counts. Estimated sightability for the minimum count surveys was 0.67 (95% credible interval [CrI] = 0.52–0.83) and abundance for the entire area was 5,600 goats (CV = 9%), both in broad agreement with estimates from previous studies. Abundance estimates at the local scale (i.e., individual min. count unit) were reasonably precise ( = 18%), suggesting the integrated approach can increase the amount of information produced at both spatial scales by linking minimum count approaches with more rigorous survey designs. We propose that our integrated approach may be implemented in the context of a modified split‐panel monitoring design by altering survey protocols to include frequent minimum counts within local count units and intermittent but more rigorous survey designs with inference to the entire study area or population of interest. Doing so would provide estimates of abundance with appropriate measures of uncertainty at multiple spatial scales, thereby improving inference for population monitoring and management. © 2019 The Wildlife Society.

Water benefits sharing under transboundary cooperation in the Lancang-Mekong River Basin

Rapid economic development and population growth in the Lancang-Mekong River Basin makes it imperative for water resources to be used fairly and efficiently among all stakeholders. This paper proposes an integrated model framework to assess the water benefits sharing schemes among the five stakeholders in the basin, namely, China, Thailand, Laos, Cambodia, and Vietnam. Three objectives are considered for this assessment—hydropower (HP), eco-index (EI), and agricultural water use (AW). The hydrologic model, optimization model, and cooperative game theory methods are jointly used to analyze the water benefits of stakeholders under different scenarios. According to the model, cooperation can bring more incremental benefits in dry years when water resources are scarce. Three cooperative game theoretical methods, namely, the Shapley value, the Gately point, and the Nash–Harsanyi solution, are employed to find the possible benefit sharing solutions. The results show that China and Laos need to operate their reservoirs for downstream countries’ beneficial uses under cooperation, and thus, compensation by reallocating the incremental benefit from cooperation is necessary no matter which method is used. It is found that all of the future damming plans would enhance the basin-level cooperation in most cases. In particular, according to the analysis, damming in the basins of the Sesan, Srepok, and Sekong rivers would have more effect than damming in the upper Lancang-Mekong River Basin after 2030. Based on some verified assumptions, the results of this paper can offer real-world preferences, but the uncertainties need to be further explored.

Assessing the potential impacts of climate and land use change on water fluxes and sediment transport in a loosely coupled system

Climate and land use change are the two primary factors that affect different components of hydrological cycle as well as sediment transport in the watershed. Quantifying potential impact of these two stressors enables decision makers to formulate better water resource management strategies to adapt to the changing environment. To that end, we have developed an integrated modeling framework employing an Agent-based approach to simulate land use conversion that then serves as input to the Soil and Water Assessment tool (SWAT) in a loosely coupled fashion. The modeling framework was tested on the Neshanic River Watershed (NRW), 142 km2 area in central New Jersey that contains mix of urban, agricultural and forested lands. An ensemble of 10 different global climate models (GCMs) for two different greenhouse gas emission scenarios including representative concentration pathways-4.5 and 8.5 (RCP-4.5 and 8.5) were employed to model future climate from 2020 to 2045. Land use conversion for 2040 was developed based on six driving factors including distance to residential lands, agricultural lands, roads, streams, train stations, and forest using three land use transition potential models and further, the best transition potential model accompanied with some local land use restrictions.The study evaluated various components of hydrological cycle and sediment transport for the three different scenarios one-at-a-time including climate change alone, land use change alone, and combined climate and land use change. Results indicate that the changing climate will have a larger effect on the hydrologic cycle than intensifying urban land uses in the study watershed. The climate change scenarios, either alone or in composite with land use change, predict higher streamflow (32% and 36% increase over baseline, respectively), overriding the effect of land use change which predicts a decline of 5% in streamflow. The increase in streamflow results in an increase in sediment loading, presumably due to an increase stream downcutting. Conversely, the effect of land use change (in this case the conversion of agricultural land to low density residential uses), is predicted to decrease sediment load. When modelled in composite, the effect of changing land use (in this case the conversion of erodible agricultural fields to suburban development) appears to override the adverse effect of climate change, enhancing watershed resiliency by reducing sediment load and thereby improving health of the downstream aquatic ecosystems.

Toward multiscale consequential sustainable process design: Including the effects of economy and resource constraints with application to green urea production in a watershed

Decisions made by approaches that only consider the environmental domain could result in unexpected outcomes due to burdens shifting to economic and social domains. These consequences could occur through the entire supply chain at multiple spatial scales. In this work, the process-to-planet (P2P) multiscale modeling framework is integrated with the rectangular choice-of-technology (RCOT) consequential approach. The resulting RCOT-P2P multiscale technology choice modeling framework takes account of market effects, such as economic resource constraints, as a consequential approach for designing engineering systems and their supply chain networks. The integrated modeling framework can represent different stakeholders’ interests by considering engineering, environmental, and economic dimensions. The case study focuses on installation of a new green urea production system in a watershed where there are limited supplies of resources, such as water and land area. We identify how the adoption of new technologies could change and be limited by market constraints, as the urea demand increases. This multiscale consequential framework is useful for modeling substitution effects of emerging technologies while considering market effects.

Modelling the future impacts of urban spatial planning on the viability of alternative water supply

Greywater recycling and rainwater harvesting have the potential to increase the resilience of water management and reduce the need for investment in conventional water supply schemes. However, their water-savings would partly depend on the location and built-form of urban development and hence its household sizes and rainwater per dwelling. We have therefore tested how spatial planning options would affect the future viability of alternative water supply in the Greater South East of England. Our integrated modelling framework, for the first time, forecasts the future densities and variability of built-form to provide inputs to the modelling of alternative water supply. We show that using projections of the existing housing stock would have been unsound, and that using standard dwelling types and household sizes would have substantially overestimated the water-savings, by not fully representing how the variability in dwelling dimensions and household-sizes would affect the cost effectiveness of these systems. We compare the spatial planning trend over a 30 year period with either compaction at higher densities within existing urban boundaries, or market-led more dispersed development. We show how the viability of alternative water supply would differ between these three spatial planning options. The water-savings of rainwater harvesting would vary greatly at a regional scale depending on residential densities and rainfall. Greywater recycling would be less affected by spatial planning but would have a finer balance between system costs and water-savings and its feasibility would vary locally depending on household sizes and water efficiency. The sensitivity of the water savings to differences in rainfall and water prices would vary with residential density. The findings suggest that forecasts of residential densities, rainfall and the water price could be used in conjunction with more detailed local studies to indicate how spatial planning would affect the future water saving potential of alternative water supply.

Climate change will both exacerbate and attenuate urbanization impacts on streamflow regimes in southern Willamette Valley, Oregon

AbstractInteractions between climate change and urbanization may affect stream ecosystems in unexpected ways. With an integrated modelling framework, we assessed the combined hydrological impacts of climate change and urbanization under historical and future climate regimes across varied development scenarios in three watersheds in the Willamette Valley, Oregon. First, through an agent‐based land use change model Envision, we created four development scenarios that consisted of 2 × 2 combinations of regional growth (compact population growth in urban cores vs. dispersed growth into rural areas) and stormwater management scenarios (with vs. without integrated stormwater management, ISM). ISM was defined as the integration of strategic organization of land uses with site‐scale stormwater best management practices. Next, two future climate regimes were developed by statistically downscaling projections from two general circulation models (CanESM2 and CNRM‐CM5) that performed well in replicating historical climate. The hydrological assessment of these scenarios was then conducted with the Soil and Water Assessment Tool. Using 10 ecologically significant flow metrics, we evaluated each scenario based on the magnitude of change in each metric and the degree to which such changes could be mitigated. Climate change alone led to a drying trend in flow regimes under both future climates. Combined with urbanization, it magnified changes in six of 10 metrics but attenuated impacts for three other measures of flashiness in at least one basin. The combination of compact growth and ISM effectively mitigated alterations for seven (out of nine) metrics sensitive to the combined impacts in at least one basin, with ISM being more effective than compact growth. The modelling framework teased out both nuanced differences and generalizable trends in hydrological impacts of urbanization and climate change and offers key methodological innovations towards an integrated framework capable of linking landscape planning mechanisms with the goal of sustaining stream ecosystem health.

Integrating economic and engineering models for future electricity market evaluation: A Swiss case study

The addition of stochastic renewable resources within modern electricity markets creates a need for more flexible generation assets and for appropriate mechanisms to ensure capacity adequacy. To assess both of these issues, more cross-platform analysis is needed that can evaluate short-term reliability concerns, medium-term dispatch and price concerns, and long-term capacity expansion and market design concerns. We present an integrated modeling framework that combines a long-term investment model, a robust dispatch model of the energy market, a detailed AC network model, a novel quantification for reserves, and a rigorous evaluation of renewable energy resource potentials. We apply the framework to a business-as-usual reference case simulating the phase-out of nuclear capacity in Switzerland and a case with renewable generation targets for Switzerland. We find that the nuclear phase-out leads to a strong increase in Swiss imports. In contrast, additional renewable targets lead to a decrease of these imports. In both cases, the Swiss cross-border lines are found to be the most critical network bottlenecks and in both future cases the increased reliance on imports worsens the severity of these bottlenecks. However, the network and security assessments show no significant challenges associated with a faster and stronger renewable increase in Switzerland.

Prediction of nitrate accumulation and leaching beneath groundwater irrigated corn fields in the Upper Platte basin under a future climate scenario

Understanding the impacts of future climate change on soil hydrological processes and solute transport is crucial to develop appropriate strategies to minimize the adverse impacts of agricultural activities on groundwater quality. To evaluate the direct effects of climate change on the transport and accumulation of nitrate-N, we developed an integrated modeling framework combining climatic change, nitrate-N infiltration in the unsaturated zone, and groundwater level fluctuations. The study was based on a center-pivot irrigated corn field at the Nebraska Management Systems Evaluation Area (MSEA) site. Future groundwater recharge (GR) and actual evapotranspiration (ETa) rates were predicted via an inverse vadose zone modeling approach by using climatic data generated by the Weather Research and Forecasting (WRF) climate model under the RCP 8.5 scenario, which was downscaled from the global CCSM4 model to a resolution of 24 km by 24 km. A groundwater flow model was first calibrated on the basis of historical groundwater table measurements and then applied to predict the future groundwater table in 2057–2060. Finally, the predicted future GR rate, ETa rate, and groundwater level, together with future precipitation data from the WRF climate model, were used in a three-dimensional (3D) model to predict nitrate-N concentrations in the subsurface (saturated and unsaturated parts) from 2057 to 2060. The future GR was predicted to decrease in the study area, as compared with the average GR data from the literature. Correspondingly, the groundwater level was predicted to decrease (30 to 60 cm) over the 5 years of simulation in the future. The nitrate-N mass in the simulation domain was predicted to increase but at a slower rate than in the past. Sensitivity analysis indicated that the accumulation of nitrate-N is sensitive to groundwater table elevation changes and irrigation rates.

Integrated population models: Model assumptions and inference

Abstract Integrated population models (IPMs) have become increasingly popular for the modelling of populations, as investigators seek to combine survey and demographic data to understand processes governing population dynamics. These models are particularly useful for identifying and exploring knowledge gaps within life histories, because they allow investigators to estimate biologically meaningful parameters, such as immigration or reproduction, that were previously unidentifiable without additional data. As IPMs have been developed relatively recently, there is much to learn about model behaviour. Behaviour of parameters, such as estimates near boundaries, and the consequences of varying degrees of dependency among datasets, has been explored. However, the reliability of parameter estimates remains underexamined, particularly when models include parameters that are not identifiable from one data source, but are indirectly identifiable from multiple datasets and a presumed model structure, such as the estimation of immigration using capture‐recapture, fecundity and count data, combined with a life‐history model. To examine the behaviour of model parameter estimates, we simulated stable populations closed to immigration and emigration. We simulated two scenarios that might induce error into survival estimates: marker induced bias in the capture–mark–recapture data and heterogeneity in the mortality process. We subsequently fit capture–mark–recapture, state‐space and fecundity models, as well as IPMs that estimated additional parameters. Simulation results suggested that when model assumptions are violated, estimation of additional, previously unidentifiable, parameters using IPMs may be extremely sensitive to these violations of model assumption. For example, when annual marker loss was simulated, estimates of survival rates were low and estimates of immigration rate from an IPM were high. When heterogeneity in the mortality process was induced, there were substantial relative differences between the medians of posterior distributions and truth for juvenile survival and fecundity. Our results have important implications for biological inference when using IPMs, as well as future model development and implementation. Specifically, using multiple datasets to identify additional parameters resulted in the posterior distributions of additional parameters directly reflecting the effects of the violations of model assumptions in integrated modelling frameworks. We suggest that investigators interpret posterior distributions of these parameters as a combination of biological process and systematic error.

The Structural and Functional Diversity of Intrinsically Disordered Regions in Transmembrane Proteins.

The intrinsically disordered proteins and protein regions (IDPs/IDPRs) do not have unique structures, but are known to be functionally important and their conformational flexibility and structural plasticity have engendered a paradigmatic shift in the classical sequence-structure-function maxim. Fundamental understanding in this field has significantly evolved since the discovery of this class of proteins about 25years ago. Though the IDPRs of transmembrane proteins (TMP-IDPRs) comply with the broad definition of typical IDPs and IDPRs found in water-soluble globular proteins, much less is explored and known about them. In this review, we assimilate the key emerging biophysical principles from the limited studies on TMP-IDPRs and provide several context-specific biological examples to highlight the ubiquitous nature of TMP-IDPRs and their functional importance in cellular functions. Besides providing a spectrum of insights from sequence to structural disorder and functions, we also review the challenges and methodological advances in studying the structure-function relationship of TMP-IDPRs. We also lay stress upon the importance of an integrative framework, where ensemble-averaged (and mostly low-resolution) data from multiple experiments can be faithfully integrated with modelling techniques such as advanced sampling, coarse-graining, and free energy minimization methods for a high-fidelity characterization of TMP-IDPRs. We close the review by providing futuristic perspective with suggestions on how we could use the ideas and methods from the exciting field of protein engineering in conjunction with integrative modelling framework to advance the IDPR field and harness the sequence-disorder-function paradigm towards functional design of proteins.