Region Models Research Articles

Comparison of ocean deoxygenation between CMIP models and an observational dataset in the North Pacific from 1958 to 2005

This study investigated the relationship between the observed and simulated dissolved oxygen (O2) inventory changes in the North Pacific by analyzing an observational dataset and the outputs of Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5/6) between 1958 and 2005. A total of 204 ensembles from 20 models were analyzed. Many of the models in the North Pacific subarctic region have higher climatological O2 concentrations than observed at deeper water depths. Therefore, the negative trend of O2 inventories tends to be larger, and in fact, several model ensemble members have a larger negative trend in O2 inventories than observed. The variability among model ensemble members is more influenced by the uncertainty due to internal variability than by the uncertainty resulting from model dependency. An inter-model empirical orthogonal function (EOF) analysis revealed that the different simulated magnitudes of the negative O2 trend is closely associated with the first EOF mode, and ensemble members with strong negative trends are characterized by large oxygen reduction in the subarctic North Pacific, especially around the boundaries between the North Pacific Ocean and the Sea of Okhotsk as well as the Bering Seas. The modeled strong O2 decrease in the subarctic North Pacific is consistent with the spatial pattern of the observed O2 trend. Further analysis of climate models indicated that the O2 decrease in the subarctic region was primarily caused by physical factors. This conclusion is supported by the significantly high correlation is present between the potential temperature and O2 inventory trend in the subarctic region, whereas an insignificant correlation coefficient is present between dissolved organic carbon and the O2 inventory trend. However, the observations have a larger ratio of O2 inventory trend to temperature trend than any of the ensembles, and thus the relationship between O2 and temperature change in the subarctic North Pacific seen in the CMIP5/6 simulations is not exact.

A two-phase pure slurry model for planetary cores: one-dimensional solutions and implications for Earth's F-layer

We develop and analyse a continuum model of two-phase slurry dynamics for planetary cores. Mixed solid–liquid slurry regions may be ubiquitous in the upper cores of small terrestrial bodies and have also been invoked to explain anomalous seismic structure in the F-layer at the base of Earth's liquid iron core. These layers are expected to influence the dynamics and evolution of planetary cores, including their capacity to generate global magnetic fields; however, to date, models of two-phase regions in planetary cores have largely ignored the complex fluid dynamics that arises from interactions between phases. As an initial application of our model, and to focus on fundamental fluid dynamical processes, we consider a non-rotating and non-magnetic slurry comprised of a single chemical component with a temperature that is tied to the liquidus. We study one-dimensional solutions in a configuration set up to mimic Earth's F-layer, varying gravitational strength$R$, the solid/liquid viscosity ratio$\lambda _{\mu }$and the interaction parameter$K$, which measures friction between the phases. We develop scalings describing behaviour in the limit$R \gg 1$and$\lambda _{\mu } \gg 1$, which are in excellent agreement with our numerical results. Application to Earth's core, where$R \sim 10^{28}$and$\lambda _{\mu } \sim 10^{22}$, suggests that a pure iron slurry F-layer would contain a mean solid fraction of at most 5 %.

Complex porphyry copper ore-magmatic systems of the andesitoid and basaltoid volcano-plutonic belts

A division of the porphyry copper family ore deposits into formational types associated with the basaltoid and andesitoid volcano-plutonic belts is proposed. It is shown that differences in the structure of the basement of these belts and in the composition of the ore-bearing magmatic chambers are reflected not only in the productive plutonogenic association petrology, alteration-mineralization zonality, and mineral composition of the mineral deposits, but also in the metallogenic zonality of the complex ore-magmatic systems centered by these deposits. The established differences should be taken into account for elaboration of the forecasiting and prospecting models of potential porphyry copper ore regions and clusters.

Economy and carbon emissions optimization of different provinces or regions in China using an improved temporal attention mechanism based on gate recurrent unit

With the implementation of 14th Five-Year Plan in China and the completion of the poverty alleviation task, the economy in China has made great progress. However, the carbon dioxide (CO2) emission has also increased, which will lead to the greenhouse effect for threatening economic development and affecting people's lives. Global warming has become the greatest challenge to contemporary economic and social development, and the transition to low-carbon economy has become a general trend of world economic development. Meanwhile, the traditional neural network method for predicting the economy and CO2 emissions is not accurate and objective because of the unbalanced labeling of training data and the inability to capture the relationship between time series data. Therefore, an economy and CO2 emission prediction model based on temporal attention Gate Recurrent Unit (GRU) (TA-GRU) with loss function Balanced Mean Square Error (BMSE) (BTA-GRU) mechanism is proposed to analyze and optimize the energy structure of 27 provincial-level administrative regions in China. Due to the unbalanced data labels in the different energy structure of different regions, the improved loss function BMSE is used to solve the problem of unbalanced labels from the perspective of statistics. Then, with coal, gasoline, petroleum, coke, fuel oil, diesel, natural gas and crude oil as inputs, the per capita Gross Domestic Product (GDP) as the desired output and the CO2 as the undesired output, the GRU can better capture time step dependencies in time series, and the attention mechanism can assign different weights to each time step, so that the proposed method can better learn data features and improve the accuracy of the an economic and CO2 emission prediction model. Finally, the CO2 emission and economic prediction model of different provincial-level administrative regions in China is established based on this proposed method. The experimental results show that compared with other mainstream time series data prediction models, this proposed model has better stability and practicability, and its mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE) reach 3.43, 3.28% and 2449.57, respectively. Furthermore, according to the actual situation of efficient provincial administrative regions, the energy structure of inefficient provincial administrative regions can be adjusted and optimized. Such as the energy structure of Hebei Province can be adjusted according to the energy structure of Beijing, it is estimated that the CO2 emissions of Hebei will be reduced by 82,972.43 ×10000 tons (WT) and its per capita GDP will be increased by 115,856 Yuan. Moreover, Chinese provincial governments should vigorously promote the use of clean energy, accelerate the establishment of a sound green low-carbon circular development economic system, and help achieve the goal of carbon neutrality.

Rapid Access Addiction Medicine Clinics for People With Problematic Opioid Use

New approaches are needed to provide care for individuals with problematic opioid use (POU). Rapid access addiction medicine (RAAM) clinics offer a flexible, low-barrier, rapid access care model for this population. To assess the associations of RAAM clinics with emergency department (ED) visits, hospitalizations, and mortality for people with POU. A retrospective cohort study involving a matched control group was performed using health administrative data from Ontario, Canada. Anonymized data from 4 Ontario RAAM clinics (cities of Ottawa, Toronto, Oshawa, and Sudbury) were linked with health administrative data. Analyses were performed on a cohort of individuals who received care at participating RAAM clinics and geographically matched controls who did not receive care at a RAAM clinic. All visits occurred between October 2, 2017, and October 30, 2019, and data analyses were completed in spring 2023. A propensity score-matching approach was used to balance confounding factors between groups, with adjustment for covariates that remained imbalanced after matching. Individuals who initiated care through the RAAM model (including assessment, pharmacotherapy, brief counseling, harm reduction, triage to appropriate level of care, navigation to community services and primary care, and related care) were compared with individuals who did not receive care through the RAAM model. The primary outcome was a composite measure of ED visits for any reason, hospitalization for any reason, and all-cause mortality (all measured up to 30 days after index date). Outcomes up to 90 days after index date, as well as outcomes looking at opioid-related ED visits and hospitalizations, were also assessed. In analyses of the sample of 876 patients formed using propensity score matching, 440 in the RAAM group (mean [SD] age, 36.5 [12.6] years; 276 [62.7%] male) and 436 in the control group (mean [SD] age, 36.8 [13.8] years; 258 [59.2%] male), the pooled odds ratio (OR) for the primary, 30-day composite outcome of all-cause ED visit, hospitalization, or mortality favored the RAAM model (OR, 0.68; 95% CI, 0.50-0.92). Analysis of the same outcome for opioid-related reasons only also favored the RAAM intervention (OR, 0.47; 95% CI, 0.29-0.76). Findings for the individual events of hospitalization, ED visit, and mortality at both 30-day and 90-day follow-up also favored the RAAM model, with comparisons reaching statistical significance in most cases. In this cohort study of individuals with POU, RAAM clinics were associated with reductions in ED visits, hospitalizations, and mortality. These findings provide valuable evidence toward a broadened adoption of the RAAM model in other regions of North America and beyond.

A statistical–dynamical approach for probabilistic prediction of sub-seasonal precipitation anomalies over 17 hydroclimatic regions in China

Abstract. In this study, we develop a spatial–temporal projection-based calibration, bridging, and merging (STP-CBaM) method to improve probabilistic sub-seasonal precipitation forecast skill over 17 hydroclimatic regions in China. The calibration model is established by post-processing ECMWF raw forecasts using the Bayesian joint probability (BJP) approach. The bridging models are built using large-scale atmospheric intraseasonal predictors, including zonal wind at 200 hPa (U200) and 850 hPa (U850); an outgoing longwave radiation anomaly (OLRA); and geopotential height at 200 hPa (H200), 500 hPa (H500), and 850 hPa (H850) defined by the STP method. The calibration model and the bridging models are then merged through the Bayesian modelling averaging (BMA) method. Our results indicate that the forecast skill of the calibration model is higher compared to bridging models when the lead time is within 5–10 d. The U200- and OLRA-based bridging models outperform the calibration model in certain months and certain regions. The BMA-merged forecasts take advantage of both calibration models and bridging models. Meanwhile, the BMA-merged forecasts also show high reliability at longer lead times. However, some improvements to reliability are still needed at shorter lead times. These findings demonstrate the great potential to combine dynamical models and statistical models in improving sub-seasonal precipitation forecasts.

Flood hazard mapping using GIS-based statistical model in vulnerable riparian regions of sub-tropical environment

Floods are a recurrent natural calamity that presents substantial hazards to human lives and infrastructure. The study indicates that a significant proportion of the study area, specifically 27.05%, is classified as a moderate flood risk zone (FRZ), while 20.78% is designated as high or very high FRZ. The region’s low and very low FRZ are classified at 52.17%. The GIS-based AHP model demonstrated exceptional predictive precision, achieving a score of 0.749 (74.90%) as determined by the AUC-ROC, a widely used statistical evaluation tool. The current study has identified areas with high FRZ in the affected CD blocks, which are situated in low-lying flood plains, regions with gentle slopes, high drainage density, high TWI, low NDVI, high MNDWI, areas with high population density, intensive agricultural land. The findings of this research offer significant perspectives for decision-makers, city planners, and emergency management agencies in devising efficient measures to mitigate flood risks.

Electroweak corrections to Higgs boson decays in a Complex Singlet extension of the SM and their phenomenological impact

The complex singlet extension CxSM of the Standard Model (SM) is a simple extension of the SM with two visible Higgs bosons in the spectrum and a Dark Matter (DM) candidate. In this paper we complete the computation of the next-to-leading (NLO) electroweak (EW) corrections to on-shell and non-loop-induced Higgs decays. Our calculations are implemented in the code EWsHDECAY which also includes the relevant QCD corrections. Performing an extensive parameter scan in the model and including all relevant theoretical and experimental single- and di-Higgs as well as DM constraints, we obtain a viable parameter sample. We find that current DM constraints are able to test the model in DM mass regions where collider searches are not sensitive. The relative EW corrections turn out to be large for scenarios with relatively large couplings, threshold effects or small leading-order (LO) widths. Otherwise, they are of typical EW size and can amount up to about 20–25%. The theory uncertainty derived from the change of the renormalization scheme dependence then is of a few per cent. While the NLO corrections applied in the constraints due to single- and di-Higgs searches impact the validity of specific parameter points, the overall shape of the allowed parameter region is not yet sensitive to the EW corrections. This picture will change with further increased experimental precision in the future and necessitates precise predictions on the theory side as presented in this paper.

A region-based low-carbon operation analysis method for integrated electricity-hydrogen-gas systems

A region-based low-carbon operation analysis method for integrated electricity‑hydrogen-gas systems (IEHGSs) is proposed in this paper. The committed carbon emission operation region (CCE_OR) and the economic CCE_OR (ECCE_OR) are proposed to evaluate the low-carbon feasible space (LCFS) from the low-carbon, secure, and economic perspectives, which provides powerful tools for the low-carbon operation analyses of IEHGSs. Firstly, a coordinated mechanism of carbon flow and hydrogen flow is developed to excavate the low-carbon operation potential of IEHGSs. Then, based on the distributionally robust chance-constrained approach, the concepts and models of CCE_OR and ECCE_OR are defined and formulated considering uncertainties and hydrogen merits. Furthermore, a region model reformulation method is proposed to reformulate the uncertain and non-convex CCE_OR and ECCE_OR models into the deterministic and mixed-integer linear region models. The geometric properties of CCE_OR and ECCE_OR are both theoretically proven, which are the union set of finite convex and bounded polytopes. The united region solution methodology considering the geometric properties of CCE_OR and ECCE_OR is presented to effectively characterize CCE_OR and ECCE_OR. Finally, the numerical results on two test systems verify the effectiveness and applicability of the proposed methods. Simulation results indicate that the proposed methods can improve the LCFS, characterize visual coupling relationships between LCFS and observation variables, and provide comprehensive low-carbon operation information of operation points.

Development of pedotransfer functions for predicting hydraulic parameters of van Genuchten model by incorporating environmental variables on the Qinghai-Tibet Plateau

The Qinghai-Tibet Plateau (QTP) region lacks large database of soil hydraulic parameters (SHPs) due to difficulty in soil sampling, and time- and labor-consuming measurement, which prevents accurate modeling of hydrological and biogeochemical processes. Pedotransfer functions (PTFs) using easily measurable soil properties may provide an alternative way to indirectly estimate SHPs. In this study, soil properties (bulk density (BD), clay, silt, sand, soil organic carbon, porosity, fitting parameter related to inverse of air entry pressure (α) and soil pore distribution (n), residual and saturated soil water content (θr and θs), and environmental parameters (altitude, slope gradient, annual average precipitation, air temperature, and evaporation) were determined from a north-south transect (ca. 500 km) in Qinghai Province and an east-west transect (ca. 1800 km) in Tibet Autonomous Region for establishing PTFs for SHPs on the QTP. The coefficient of variation of α was the largest, followed by θr, θs, and n, suggesting that α had the greatest spatial variability at the regional scale. There were significant differences in BD among 0–10, 10–20, and 20–30 cm soil layers (p < 0.05), whereas there were no significant differences in α, n, θr, and θs among these soil layers (p > 0.05). The five most important variables from the random forest analysis were selected to establish the PTFs of the SHPs and BD for the 0–30 cm soil layer on the QTP. The established PTFs for predicting SHPs and BD using multiple linear regression analysis were jointly affected by relief, climate, and soil properties. The accuracy of our newly established PTFs with the consideration of gravel content (< 10% or 10–30%) and mattic epipedon (existence or non-existence) was higher than that of the existing PTFs. We developed the first PTFs of SHPs on the QTP, providing a foundation to construct SHPs prediction models for other alpine regions in the world.

C ii] Spectral Mapping of the Galactic Wind and Starbursting Disk of M82 with SOFIA

M82 is an archetypal starburst galaxy in the local Universe. The central burst of star formation, thought to be triggered by M82's interaction with other members in the M81 group, is driving a multiphase galaxy-scale wind away from the plane of the disk that has been studied across the electromagnetic spectrum. Here, we present new velocity-resolved observations of the [C ii] 158 μm line in the central disk and the southern outflow of M82 using the upGREAT instrument on board SOFIA. We also report the first detections of velocity-resolved (ΔV = 10 km s−1) [C ii] emission in the outflow of M82 at projected distances of ≈1–2 kpc south of the galaxy center. We compare the [C ii] line profiles to observations of CO and H i and find that likely the majority (>55%) of the [C ii] emission in the outflow is associated with the neutral atomic medium. We find that the fraction of [C ii] actually outflowing from M82 is small compared to the bulk gas outside the midplane (which may be in a halo or tidal streamers), which has important implications for observations of [C ii] outflows at higher redshift. Finally, by comparing the observed ratio of the [C ii] and CO intensities to models of photodissociation regions, we estimate that the far-ultraviolet (FUV) radiation field in the disk is ∼103.5 G 0, in agreement with previous estimates. In the outflow, however, the FUV radiation field is 2–3 orders of magnitudes lower, which may explain the high fraction of [C ii] arising from the neutral medium in the wind.

Design and development of a stable supercritical CO2 centrifugal compressor

Introducing supercritical carbon dioxide (s-CO2) as a working fluid can enhance the power generation of Brayton cycles. However, various challenges are involved in designing, and developing a stable s-CO2 centrifugal compressor on a reasonably sized s-CO2 Brayton cycle. This article presents a 1-D design and development procedure for s-CO2 centrifugal compressors suitable for Brayton power cycles. The 1-D compressor design approach employs the Widom region, AMC, and internal and external loss models to optimize the compressor design. The 1-D design code is validated with CFD simulation and experimental data from Sandia. Further, a new stable compressor for a 10 MWe s-CO2 Brayton cycle is designed, proposed, and discussed in this paper. Based on the 1-D design code and the CFD results, the newly designed compressor exhibits an improved operational range. Additionally, a loss analysis of the designed s-CO2 compressor revealed that internal losses accounted for 75.8% of the total enthalpy loss. The compressor's internal flow behavior at choke is investigated by utilizing a novel analogy between the impeller at choke and a converging–diverging nozzle. The CFD results showed that condensation is inevitable in an s-CO2 centrifugal compressor operation; however, condensation does not significantly affect compressor performance near the design point.

Study on the supercooling and crystallization mechanism of saline soil based on thermodynamic framework

Quantifying the supercooling characteristics of saline soil–water systems is essential for engineering and agriculture in cold regions. However, the crystallization mechanism of supercooling remains unclear. We conducted experimental observations to investigate the impact of salinity on the soil supercooling properties. Additionally, a freezing nucleation thermodynamic model for saline soil was established based on the Negentropic Nucleation Framework (NNF). Statistical analysis methods were employed to analyze the sensitivity of the parameters and interpret the supercooling microscopic mechanism. The results indicated that the supercooling degree distribution of saline soil is best described by a normal distribution (hypothesis testing statistic Dn=0.176). The nucleation rate was primarily controlled by water activity and activation energy of water molecules. The concentration of salt solution played a crucial role in promoting the formation and growth of crystal nuclei. However, the promoting effect decreased with increasing solution concentration when the concentration was below 0.3 mol/L. Moreover, the nucleation potential energy barrier increased with salt concentration, with NaCl environment exhibiting a higher nucleation potential energy barrier compared to Na2SO4 environment at the same salt concentration. In summary, this research provides a theoretical reference for revealing the freezing-thawing hysteretic mechanism and improving the accuracy of numerical calculation models in cold regions.

Evaluation of sustainable development of the Bohai Sea Rim based on integrated land–sea management: a multi-system coupling and coordination study at coastal, provincial, and city level

Based on the Integrated Land–Sea Management, this study established a theoretical framework for the sustainability of coastal regions by combining sustainable development with coupling coordination theory. The improved coupling coordination model was used to analyze the sustainable development of the Bohai Rim and its coastal provinces and cities from 2006 to 2020. Our implications were as follows: (1) The theoretical framework showed an S-shaped spiral trend, and the empirical results on the Bohai Rim were consistent with the trajectory conclusions. (2) The economic subsystem played a crucial role in the system’s evolution toward sustainable development. (3) The region and city models demonstrated consistent coupling and coordination development degrees. However, the consistency was not completely synchronous. Conscious eco-environmental governance activities can promote benign interactions among systems and improve this relationship. (4) The sustainable development of coastal cities is different from that of the provinces in which they are located. It merely demonstrates their relative status among all coastal cities and does not fully represent the wider region in which they are located. The findings suggest that adaptive policies, whether economic, social or environmental, can promote sustainable development. Economic stimulus policies can promote a transition of sustainable development; in the economic downturn, the adaptive environmental policy is realized by adjusting the relationship between subsystems to promote the coordination of regional systems, preparing for the next sustainable system transition. The established theoretical model and improvised mathematical method can be extended to study various coastal regions

Optimal building retrofit pathways considering residential energy use variability: A case study of Nanjing city

The variation in energy usage patterns among occupants elucidates the disparity between projected and realized energy consumption following physical retrofitting, and serves as a significant determinant in the context of extensive building retrofit initiatives. This study involves the establishment of four representative building models in regions characterized by hot summers and cold winters. The study examines the diverse energy consumption patterns exhibited by occupants, and subsequently explores the potential strategies for implementing large-scale energy-efficient renovations in the hot summer and cold winter zones. The findings indicate that there is a prevalent occurrence of excessive energy consumption. Moreover, the energy usage patterns exhibited by occupants have a substantial influence on the overall energy consumption of buildings. The implementation of graded and progressive stepped-step electricity pricing should be prioritized during both summer and winter seasons. This entails appropriately increasing the price of stepped-step power tariffs and reducing the proportion of residents who consume excessive energy. Undoubtedly, the most successful large-scale retrofit scheme for hot summer and cold winter areas is the replacement of all air conditioning equipment in the existing residential areas, under the premise of adopting the seasonal progressive incremental ladder energy pricing.

Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub.

To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possible, and to turn the model into a useful framework for making predictions based on the principles governing the nature of neural cells. In such a context, the access to existing neural models and data outstandingly facilitates the work of computational neuroscientists and fosters its novelty, as the scientific community grows wider and neural models progressively increase in type, size, and number. Nonetheless, even when accessibility is guaranteed, data and models are rarely reused since it is difficult to retrieve, extract and/or understand relevant information and scientists are often required to download and modify individual files, perform neural data analysis, optimize model parameters, and run simulations, on their own and with their own resources. While focusing on the construction of biophysically and morphologically accurate models of hippocampal cells, we have created an online resource, the Build section of the Hippocampus Hub -a scientific portal for research on the hippocampus- that gathers data and models from different online open repositories and allows their collection as the first step of a single cell model building workflow. Interoperability of tools and data is the key feature of the work we are presenting. Through a simple click-and-collect procedure, like filling the shopping cart of an online store, researchers can intuitively select the files of interest (i.e., electrophysiological recordings, neural morphology, and model components), and get started with the construction of a data-driven hippocampal neuron model. Such a workflow importantly includes a model optimization process, which leverages high performance computing resources transparently granted to the users, and a framework for running simulations of the optimized model, both available through the EBRAINS Hodgkin-Huxley Neuron Builder online tool.

Exploring the Applicability of Regression Models and Artificial Neural Networks for Calculating Reference Evapotranspiration in Arid Regions

Reference evapotranspiration (ET0) is critical in agriculture and irrigation water management, particularly in arid and semi-arid regions. Our study aimed to develop an accurate and efficient model for estimating ET0 using various climatic variables as predictors. This research evaluated two model techniques, i.e., stepwise regression and artificial neural networks (ANNs), to identify the most effective model for calculating ET0. The two models were developed and tested based on climate data obtained from the whole climatic station of Egypt. The CLIMWAT 2.0 program was used to acquire the climate data for Egypt from a total of 32 stations. This software is a dedicated meteorological database created specifically to work with the CROPWAT computer program. The models were developed using average climate data spanning 29 years, from 1991 to 2020. The obtained data were utilized to compute reference evapotranspiration using CROPWAT 8, based on the Penman–Monteith equation. The results showed that the ANN model demonstrated superior performance in ET0 calculations compared to other methods, achieving a coefficient of determination (R2) of 0.99 and a mean absolute percentage error (MAPE) of 2.7%. In contrast, the stepwise model regression yielded an R2 of 0.95 and an MAPE of 8.06. On the other hand, the most influential climatic variables were maximum temperature, humidity, solar radiation, and wind speed. The findings of this study could be applied in various fields, such as agriculture, irrigation, and crop water requirements, to optimize crop growth under limited water resources and global environmental changes. Furthermore, our study identifies the limitations and challenges of applying these models in arid regions, such as data availability constraints and model complexity. We discuss the need for more extensive and reliable datasets and suggest future research directions, including ensemble modeling, remote sensing data integration, and evaluating climate change’s impact on ET0 estimation. Overall, this study contributes to the understanding of ET0 estimation in arid regions and provides valuable insights into the applicability of regression models and ANNs. The superior performance of ANNs offers potential advancements in water resource management and agricultural planning, enabling more accurate and informed decision-making processes.

Model of WebGIS Based Sustainable Smart Land Use for Merauke Regency South Papua

This Smart and sustainable land use is the key to answering development challenges in the modern era. In the context of Merauke Regency, South Papua, rapid economic growth and significant environmental changes demand an integrated approach to managing land use. This research presents an innovative WebGIS-based model that combines geospatial information technology with land use analysis to provide sustainable solutions. Through the integration of spatial data, predictive analysis and stakeholder participation, this model enables stakeholders to explore alternative land use scenarios and evaluate their environmental, economic and societal impacts. The performance evaluation stage of the model shows its ability to accurately represent existing land use patterns. Validation with actual land use data confirms the ability of the model to reproduce the distribution of agricultural areas and protected forest areas. Furthermore, the evaluation of the environmental impact of the model results indicates that the model is capable of predicting the environmental impact of alternative land use scenarios. Consultation sessions with stakeholders proved the importance of their participation in the validation and adaptation of sustainable solutions. The results of this study indicate that WebGIS-based Smart Land Use model has great potential in assisting sustainable planning and decision-making in Merauke Regency. However, further validation and improvement of the model is needed to strengthen its accuracy and validity. This research provides valuable insights on the integration of geospatial information technology in sustainable development and provides guidance for the development of similar models in other regions.

Nocturnal Water Use Partitioning and Its Environmental and Stomatal Control Mechanism in Caragana korshinskii Kom in a Semi-Arid Region of Northern China

As an important aspect of plant water consumption, nocturnal water use (En) behavior provides reliable information on the effect of plantation carbon and water budgets at stand and regional scales. Therefore, quantifying En and its environmental and stomatal controlling mechanisms is urgent to establish adaptation strategies for plantation management in semiarid regions. With the help of the sap flow technique, our study investigated the seasonal variations in canopy transpiration and canopy conductance in a Caragana korshinskii Kom plantation. Environmental variables were measured concurrently during the growing seasons of 2020 and 2021. The results indicated that the average En values were 0.10 mm d−1 and 0.09 mm d−1, which accounted for 14% and 13% of daily water use, respectively, over two years. The proportions of nocturnal transpiration (Tn) to En were approximately 49.76% and 54.44%, while stem refilling (Re) accounted for 50.24% and 45.56% of En in 2020 and 2021, respectively, indicating that C. korshinskii was able to draw on stored stem water to support transpiration. En was predominantly affected by nocturnal canopy conductance (Gc–n), air temperature (Ta–n) and wind speed (u2-n). In contrast, Gc–n and Ta–n explained the highest variation in Tn and nocturnal vapor pressure (VPDn), and u2-n explained the highest variation in Re. Total effects of the five environmental and stomatal variables explained 50%, 36% and 32% of En, Tn and Re variation, respectively. These findings could enable a better understanding of nocturnal water use dynamics and their allocation patterns in C. korshinskii plantations on the Bashang Plateau. Moreover, our results reveal the water use strategies of artificial shrubs and highlight the importance of incorporating nocturnal water use processes into large-scale ecohydrological models in semiarid regions.

Developing SWAT‐S to strengthen the soil erosion forecasting performance of the SWAT model

AbstractSoil erosion is an important cause of global land degradation, and accurate monitoring of it is essential. The Soil and Water Assessment Tool (SWAT), a distributed hydrological model, is an advanced technique for predicting soil erosion at watershed scale. However, as the erosion framework was established in gently sloping land, SWAT is limited in predicting soil erosion in some highland and mountainous regions. Therefore, this study suggested a method to integrate the sediment transport theoretical formula that can reflect the morphology of gully regions into SWAT to obtain SWAT‐S to enhance the calculation performance of sediment load, and the SWAT‐S was evaluated according to the coefficient of determination (R2), Nash‐Sutcliffe coefficient (NSE), Percent‐Bias (P‐BIAS) and root mean square errors (RMSE)‐observations SD ratio (RSR) in the Yanhe basin on the Chinese Loess Plateau. The results showed that SWAT‐S is more successful in reproducing the monthly sediment load, with R2, NSE, |P‐BIAS| and RSR were changed by 5.08%, 17.65%, −2.92% and −10.00% in the calibration, as well as by 1.18%, 10.39%, 45.45% and −18.75% in the validation of the SWAT‐S compared to SWAT. Meanwhile, SWAT‐S estimates 2.66 × 106 t more sediment than SWAT during the June–September flood season and better matches observed data. In total, the revised SWAT can improve the performance of sediment estimation, which is beneficial for the wider application of the model in more regions of the world.