Geology topics

Shuguang Liu

Publications and source records attributed to Shuguang Liu.

At least 19 recordsLinked to original sources

USGS2020

Critical land change information enhances the understanding of carbon balance in the United States

Large-scale terrestrial carbon (C) estimating studies using methods such as atmospheric inversion, biogeochemical modeling, and field inventories have produced different results. The goal of this study was to integrate fine-scale processes including land use and land cover change into a large-scale ecosystem framework. We analyzed the terrestrial C budget of the conterminous United States from 1971 to 2015 at 1-km resolution using an enhanced dynamic global vegetation model and comprehensive land cover change data. Effects of atmospheric CO 2 fertilization, nitrogen deposition, climate, wildland fire, harvest, and land use/land cover change (LUCC) were considered. We estimate annual C losses from cropland harvest, forest clearcut and thinning, fire, and LUCC were 436.8, 117.9, 10.5, and 10.4 TgC/year, respectively. C stored in ecosystems increased from 119,494 to 127,157 TgC between 1971 and 2015, indicating a mean annual net C sink of 170.3 TgC/year. Although ecosystem net primary production increased by approximately 12.3 TgC/year, most of it was offset by increased C loss from harvest and natural disturbance and increased ecosystem respiration related to forest aging. As a result, the strength of the overall ecosystem C sink did not increase over time. Our modeled results indicate the conterminous US C sink was about 30% smaller than previous modeling studies, but converged more closely with inventory data.

Global Change Biology↗

USGS2018

The North American carbon budget: Past, present, and future

This chapter nicely summarizes and synthesizes the latest scientific information on the North American carbon budget by incorporating terrestrial, anthropogenic, aquatic, and coastal margin CO 2 and CH 4 dynamics. Starting with a historical context, the chapter summarizes current understanding of the magnitudes and trends of carbon stocks and fluxes at the continental scale. It also provides a regional context by stratifying the continent to countries and climate assessment regions and discusses the societal drivers, impacts, and carbon management decisions. Knowledge gaps and research needs are also identified. This chapter is well-written and clearly organized, and provides a broad context beyond individual chapters. Some of the main ways the chapter can be improved include the following: some work is needed on the Key Findings (discussed below); the goals and objectives should be explicitly described; critical content areas missing from the chapter are interannual variability of carbon fluxes and impacts of severe and extended droughts; indicators and feedbacks are missing from Section 2.4; consistent use of units is recommended; numbers with 3-4 significant digits over-state the confidence the reader should have, and all numbers should include uncertainties. And one broader concern to note: This chapter follows the global overview in Chapter 1, where “sinks” are sinks in the cycle perturbed by anthropogenic CO 2 and CH 4 , and the assumption is that globally, the net unperturbed background sinks are zero summed across all reservoirs. Yet in this chapter, “sinks” are net fluxes out of the atmosphere, background + perturbation. For the coastal ocean, inland waters, etc.—where lateral transport is significant—these sources and sinks include background/pre-industrial fluxes that are balanced by fluxes elsewhere. These distinctions must be made clear so that the reader is not given an impression of a greater or lesser sink for anthropogenic CO 2 than is there (e.g., P74, lines 4-6).

Book chapter↗

USGS2018

Grasslands

Key findings: Total grassland carbon stocks in the conterminous United States, estimated to be about 7.4 petagrams of carbon (Pg C) in 2005, are projected to increase to about 8.2 Pg C by 2050. Although U.S. grasslands are expected to remain carbon sinks over this period, the uptake rate is projected to decline by about half. In the U.S. Great Plains, land-use and land-cover changes are expected to cause much of the change in carbon cycling as grasslands are converted to agricultural lands or to woody biomes (medium confidence). Increasing temperatures and rising atmospheric carbon dioxide (CO2) concentrations interact to increase productivity in northern North American grasslands, but this productivity response will be mediated by variable precipitation, soil moisture, and nutrient availability (high confidence, very likely). Soil carbon in grasslands is likely to be moderately responsive to changes in climate over the next several decades. Field experiments in grasslands suggest that altered precipitation can increase soil carbon, while warming and elevated CO2 may have only minimal effects despite altered productivity (medium confidence, likely). Carbon stocks and net carbon uptake in grasslands can be maintained with appropriate land management including moderate levels of grazing. Fire suppression can lead to encroachment of woody vegetation and increasing carbon storage in mesic regions, at the expense of grassland vegetation (high confidence, likely).

Report↗

USGS2017

Grand challenges in understanding the interplay of climate and land changes

Half of Earth’s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decision-making processes work in specific contexts.

Earth Interactions↗

USGS2017

Simulating the effects of management practices on cropland soil organic carbon changes in the Temperate Prairies Ecoregion of the United States from 1980 to 2012

Understanding the effects of management practices on soil organic carbon (SOC) is important for designing effective policies to mitigate greenhouse gas emissions in agriculture. In the Midwest United States, management practices in the croplands have been improved to increase crop production and reduce SOC loss since the 1980s. Many studies of SOC dynamics in croplands have been performed to understand the effects of management, but the results are still not conclusive. This study quantified SOC dynamics in the Midwest croplands from 1980 to 2012 with the General Ensemble Biogeochemical Modelling System (GEMS) and available management data. Our results showed that the total SOC in the croplands decreased from 1190 Tg C in 1980 to 1107 TgC in 1995, and then increased to 1176 TgC in 2012. Continuous cropping and intensive tillage may have driven SOC loss in the early period. The increase of crop production and adoption of conservation tillage increased the total SOC so that the decrease in the total SOC stock after 32 years was only 1%. The small change in average SOC did not reflect the large spatial variations of SOC change in the region. Major SOC losses occurred in the north and south of the region, where SOC baseline values were high and cropland production was low. The SOC gains took place in the central part of the region where SOC baseline values were moderate and cropland production was higher than the other areas. We simulated multiple land-use land-cover (LULC) change scenarios and analyzed the results. The analysis showed that among all the LULC changes, agricultural technology that increased cropland production had the greatest impact on SOC changes, followed by the tillage practices, changes in crop species, and the conversions of cropland to other land use. Information on management practice induced spatial variation in SOC can be useful for policy makers and farm managers to develop long-term management strategies for increasing SOC sequestration in different areas.

Ecological Modelling↗

USGS2016

Preface: Impacts of extreme climate events and disturbances on carbon dynamics

The impacts of extreme climate events and disturbances (ECE&D) on the carbon cycle have received growing attention in recent years. This special issue showcases a collection of recent advances in understanding the impacts of ECE&D on carbon cycling. Notable advances include quantifying how harvesting activities impact forest structure, carbon pool dynamics, and recovery processes; observed drastic increases of the concentrations of dissolved organic carbon and dissolved methane in thermokarst lakes in western Siberia during a summer warming event; disentangling the roles of herbivores and fire on forest carbon dioxide flux; direct and indirect impacts of fire on the global carbon balance; and improved atmospheric inversion of regional carbon sources and sinks by incorporating disturbances. Combined, studies herein indicate several major research needs. First, disturbances and extreme events can interact with one another, and it is important to understand their overall impacts and also disentangle their effects on the carbon cycle. Second, current ecosystem models are not skillful enough to correctly simulate the underlying processes and impacts of ECE&D (e.g., tree mortality and carbon consequences). Third, benchmark data characterizing the timing, location, type, and magnitude of disturbances must be systematically created to improve our ability to quantify carbon dynamics over large areas. Finally, improving the representation of ECE&D in regional climate/earth system models and accounting for the resulting feedbacks to climate are essential for understanding the interactions between climate and ecosystem dynamics.

Biogeosciences↗

USGS2016

Evaluating land cover influences on model uncertainties—A case study of cropland carbon dynamics in the Mid-Continent Intensive Campaign region

Quantifying spatial and temporal patterns of carbon sources and sinks and their uncertainties across agriculture-dominated areas remains challenging for understanding regional carbon cycles. Characteristics of local land cover inputs could impact the regional carbon estimates but the effect has not been fully evaluated in the past. Within the North American Carbon Program Mid-Continent Intensive (MCI) Campaign, three models were developed to estimate carbon fluxes on croplands: an inventory-based model, the Environmental Policy Integrated Climate (EPIC) model, and the General Ensemble biogeochemical Modeling System (GEMS) model. They all provided estimates of three major carbon fluxes on cropland: net primary production (NPP), net ecosystem production (NEP), and soil organic carbon (SOC) change. Using data mining and spatial statistics, we studied the spatial distribution of the carbon fluxes uncertainties and the relationships between the uncertainties and the land cover characteristics. Results indicated that uncertainties for all three carbon fluxes were not randomly distributed, but instead formed multiple clusters within the MCI region. We investigated the impacts of three land cover characteristics on the fluxes uncertainties: cropland percentage, cropland richness and cropland diversity. The results indicated that cropland percentage significantly influenced the uncertainties of NPP and NEP, but not on the uncertainties of SOC change. Greater uncertainties of NPP and NEP were found in counties with small cropland percentage than the counties with large cropland percentage. Cropland species richness and diversity also showed negative correlations with the model uncertainties. Our study demonstrated that the land cover characteristics contributed to the uncertainties of regional carbon fluxes estimates. The approaches we used in this study can be applied to other ecosystem models to identify the areas with high uncertainties and where models can be improved to reduce overall uncertainties for regional carbon flux estimates.

Mid-Continent Intensive Campaign region↗

USGS2015

Ecosystem carbon stocks and sequestration potential of federal lands across the conterminous United States

Federal lands across the conterminous United States (CONUS) account for 23.5% of the CONUS terrestrial area but have received no systematic studies on their ecosystem carbon (C) dynamics and contribution to the national C budgets. The methodology for US Congress-mandated national biological C sequestration potential assessment was used to evaluate ecosystem C dynamics in CONUS federal lands at present and in the future under three Intergovernmental Panel on Climate Change Special Report on Emission Scenarios (IPCC SRES) A1B, A2, and B1. The total ecosystem C stock was estimated as 11,613 Tg C in 2005 and projected to be 13,965 Tg C in 2050, an average increase of 19.4% from the baseline. The projected annual C sequestration rate (in kilograms of carbon per hectare per year) from 2006 to 2050 would be sinks of 620 and 228 for forests and grasslands, respectively, and C sources of 13 for shrublands. The federal lands’ contribution to the national ecosystem C budget could decrease from 23.3% in 2005 to 20.8% in 2050. The C sequestration potential in the future depends not only on the footprint of individual ecosystems but also on each federal agency’s land use and management. The results presented here update our current knowledge about the baseline ecosystem C stock and sequestration potential of federal lands, which would be useful for federal agencies to decide management practices to achieve the national greenhouse gas (GHG) mitigation goal.

PNAS↗

USGS2015

Projection of corn production and stover-harvesting impacts on soil organic carbon dynamics in the U.S. Temperate Prairies

Terrestrial carbon sequestration potential is widely considered as a realistic option for mitigating greenhouse gas emissions. However, this potential may be threatened by global changes including climate, land use, and management changes such as increased corn stover harvesting for rising production of cellulosic biofuel. Therefore, it is critical to investigate the dynamics of soil organic carbon (SOC) at regional or global scale. This study simulated the corn production and spatiotemporal changes of SOC in the U.S. Temperate Prairies, which covers over one-third of the U.S. corn acreage, using a biogeochemical model with multiple climate and land-use change projections. The corn production (either grain yield or stover biomass) could reach 88.7–104.7 TgC as of 2050, 70–101% increase when compared to the base year of 2010. A removal of 50% stover at the regional scale could be a reasonable cap in view of maintaining SOC content and soil fertility especially in the beginning years. The projected SOC dynamics indicated that the average carbon sequestration potential across the entire region may vary from 12.7 to 19.6 g C/m 2 /yr (i.e., 6.6–10.2 g TgC/yr). This study not only helps understand SOC dynamics but also provides decision support for sustainable biofuel development.

Iowa, Kansas, Minnesota, Missouri, Nebraska, North↗

USGS2015

Projecting the spatiotemporal carbon dynamics of the Greater Yellowstone Ecosystem from 2006 to 2050

Background Climate change and the concurrent change in wildfire events and land use comprehensively affect carbon dynamics in both spatial and temporal dimensions. The purpose of this study was to project the spatial and temporal aspects of carbon storage in the Greater Yellowstone Ecosystem (GYE) under these changes from 2006 to 2050. We selected three emission scenarios and produced simulations with the CENTURY model using three General Circulation Models (GCMs) for each scenario. We also incorporated projected land use change and fire occurrence into the carbon accounting. Results The three GCMs showed increases in maximum and minimum temperature, but precipitation projections varied among GCMs. Total ecosystem carbon increased steadily from 7,942 gC/m 2 in 2006 to 10,234 gC/m 2 in 2050 with an annual rate increase of 53 gC/m 2 /year. About 56.6% and 27% of the increasing rate was attributed to total live carbon and total soil carbon, respectively. Net Primary Production (NPP) increased slightly from 260 gC/m 2 /year in 2006 to 310 gC/m 2 /year in 2050 with an annual rate increase of 1.22 gC/m 2 /year. Forest clear-cutting and fires resulted in direct carbon removal; however, the rate was low at 2.44 gC/m 2 /year during 2006–2050. The area of clear-cutting and wildfires in the GYE would account for 10.87% of total forested area during 2006–2050, but the predictive simulations demonstrated different spatial distributions in national forests and national parks. Conclusions The GYE is a carbon sink during 2006–2050. The capability of vegetation is almost double that of soil in terms of sequestering extra carbon. Clear-cutting and wildfires in GYE will affect 10.87% of total forested area, but direct carbon removal from clear-cutting and fires is 109.6 gC/m 2 , which accounts for only 1.2% of the mean ecosystem carbon level of 9,056 gC/m 2 , and thus is not significant.

Greater Yellowstone Ecosystem↗

USGS2015

Quantitative attribution of major driving forces on soil organic carbon dynamics

Soil organic carbon (SOC) storage plays a major role in the global carbon cycle and is affected by many factors including land use/management changes (e.g., biofuel production-oriented changes). However, the contributions of various factors to SOC changes are not well understood and quantified. This study was designed to investigate the impacts of changing farming practices, initial SOC levels, and biological enhancement of grain production on SOC dynamics and to attribute the relative contributions of major driving forces (CO 2 enrichment and farming practices) using a fractional factorial modeling design. The case study at a crop site in Iowa in the United States demonstrated that the traditional corn-soybean (CS) rotation could still accumulate SOC over this century (from 4.2 to 6.8 kg C/m 2 ) under the current condition; whereas the continuous-corn (CC) system might have a higher SOC sequestration potential than CS. In either case, however, residue removal could reduce the sink potential substantially. Long-term simulation results also suggested that the equilibrium SOC level may vary greatly (∼5.7 to ∼11 kg C/m 2 ) depending on cropping systems and management practices, and projected growth enhancement could make the magnitudes higher (∼7.8 to ∼13 kg C/m 2 ). Importantly, the factorial design analysis indicated that residue management had the most significant impact (contributing 49.4%) on SOC changes, followed by CO 2 Enrichment (37%), Tillage (6.2%), the combination of CO 2 Enrichment-Residue removal (5.8%), and Fertilization (1.6%). In brief, this study is valuable for understanding the major forces driving SOC dynamics of agroecosystems and informative for decision-makers when seeking the enhancement of SOC sequestration potential and sustainability of biofuel production, especially in the Corn Belt region of the United States.

Journal of Advances in Modeling Earth Systems↗

USGS2015

Soil nutrient budgets following projected corn stover harvest for biofuel production in the conterminous United States

Increasing demand for food and biofuel feedstocks may substantially affect soil nutrient budgets, especially in the United States where there is great potential for corn ( Zea mays L) stover as a biofuel feedstock. This study was designed to evaluate impacts of projected stover harvest scenarios on budgets of soil nitrogen (N), phosphorus (P), and potassium (K) currently and in the future across the conterminous United States. The required and removed N, P, and K amounts under each scenario were estimated on the basis of both their average contents in grain and stover and from an empirical model. Our analyses indicate a small depletion of soil N (−4 ± 35 kg ha −1 ) and K (−6 ± 36 kg ha −1 ) and a moderate surplus of P (37 ± 21 kg ha −1 ) currently on the national average, but with a noticeable variation from state to state. After harvesting both grain and projected stover, the deficits of soil N, P, and K were estimated at 114–127, 26–27, and 36–53 kg ha −1 yr −1 , respectively, in 2006–2010; 131–173, 29–32, and 41–96 kg ha −1 yr −1 , respectively, in 2020; and 161–207, 35–39, and 51–111 kg ha −1 yr −1 , respectively, in 2050. This study indicates that the harvestable stover amount derived from the minimum stover requirement for maintaining soil organic carbon level scenarios under current fertilization rates can be sustainable for soil nutrient supply and corn production at present, but the deficit of P and K at the national scale would become larger in the future.

GCB Bioenergy↗

USGS2014

Differentiating moss from higher plants is critical in studying the carbon cycle of the boreal biome

The satellite-derived normalized difference vegetation index (NDVI), which is used for estimating gross primary production (GPP), often includes contributions from both mosses and vascular plants in boreal ecosystems. For the same NDVI, moss can generate only about one-third of the GPP that vascular plants can because of its much lower photosynthetic capacity. Here, based on eddy covariance measurements, we show that the difference in photosynthetic capacity between these two plant functional types has never been explicitly included when estimating regional GPP in the boreal region, resulting in a substantial overestimation. The magnitude of this overestimation could have important implications regarding a change from a current carbon sink to a carbon source in the boreal region. Moss abundance, associated with ecosystem disturbances, needs to be mapped and incorporated into GPP estimates in order to adequately assess the role of the boreal region in the global carbon cycle.

Nature Communications↗

USGS2014

Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States

Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.

Massachusetts↗

USGS2014

Scale criticality in estimating ecosystem carbon dynamics

Scaling is central to ecology and Earth system sciences. However, the importance of scale (i.e. resolution and extent) for understanding carbon dynamics across scales is poorly understood and quantified. We simulated carbon dynamics under a wide range of combinations of resolution (nine spatial resolutions of 250 m, 500 m, 1 km, 2 km, 5 km, 10 km, 20 km, 50 km, and 100 km) and extent (57 geospatial extents ranging from 108 to 1 247 034 km 2 ) in the southeastern United States to explore the existence of scale dependence of the simulated regional carbon balance. Results clearly show the existence of a critical threshold resolution for estimating carbon sequestration within a given extent and an error limit. Furthermore, an invariant power law scaling relationship was found between the critical resolution and the spatial extent as the critical resolution is proportional to A n ( n is a constant, and A is the extent). Scale criticality and the power law relationship might be driven by the power law probability distributions of land surface and ecological quantities including disturbances at landscape to regional scales. The current overwhelming practices without considering scale criticality might have largely contributed to difficulties in balancing carbon budgets at regional and global scales.

Global Change Biology↗

USGS2014

Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006

Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y −1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

Remote Sensing↗

USGS2014

Development of a generic auto-calibration package for regional ecological modeling and application in the Central Plains of the United States

Process-oriented ecological models are frequently used for predicting potential impacts of global changes such as climate and land-cover changes, which can be useful for policy making. It is critical but challenging to automatically derive optimal parameter values at different scales, especially at regional scale, and validate the model performance. In this study, we developed an automatic calibration (auto-calibration) function for a well-established biogeochemical model—the General Ensemble Biogeochemical Modeling System (GEMS)-Erosion Deposition Carbon Model (EDCM)—using data assimilation technique: the Shuffled Complex Evolution algorithm and a model-inversion R package—Flexible Modeling Environment (FME). The new functionality can support multi-parameter and multi-objective auto-calibration of EDCM at the both pixel and regional levels. We also developed a post-processing procedure for GEMS to provide options to save the pixel-based or aggregated county-land cover specific parameter values for subsequent simulations. In our case study, we successfully applied the updated model (EDCM-Auto) for a single crop pixel with a corn–wheat rotation and a large ecological region (Level II)—Central USA Plains. The evaluation results indicate that EDCM-Auto is applicable at multiple scales and is capable to handle land cover changes (e.g., crop rotations). The model also performs well in capturing the spatial pattern of grain yield production for crops and net primary production (NPP) for other ecosystems across the region, which is a good example for implementing calibration and validation of ecological models with readily available survey data (grain yield) and remote sensing data (NPP) at regional and national levels. The developed platform for auto-calibration can be readily expanded to incorporate other model inversion algorithms and potential R packages, and also be applied to other ecological models.

Ecological Informatics↗

USGS2014

A suggestion for computing objective function in model calibration

A parameter-optimization process (model calibration) is usually required for numerical model applications, which involves the use of an objective function to determine the model cost (model-data errors). The sum of square errors (SSR) has been widely adopted as the objective function in various optimization procedures. However, ‘square error’ calculation was found to be more sensitive to extreme or high values. Thus, we proposed that the sum of absolute errors (SAR) may be a better option than SSR for model calibration. To test this hypothesis, we used two case studies—a hydrological model calibration and a biogeochemical model calibration—to investigate the behavior of a group of potential objective functions: SSR, SAR, sum of squared relative deviation (SSRD), and sum of absolute relative deviation (SARD). Mathematical evaluation of model performance demonstrates that ‘absolute error’ (SAR and SARD) are superior to ‘square error’ (SSR and SSRD) in calculating objective function for model calibration, and SAR behaved the best (with the least error and highest efficiency). This study suggests that SSR might be overly used in real applications, and SAR may be a reasonable choice in common optimization implementations without emphasizing either high or low values (e.g., modeling for supporting resources management).

Ecological Informatics↗