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【Objective】Reference crop evapotranspiration (ET0) is a critical parameter for agricultural water management and irrigation scheduling, especially in arid oasis regions where water resources are scarce. While the FAO-56 Penman-Monteith (PM) model is a standard formula for estimating ET0, some of meteorological data required by the model are often unavailable in these areas. This paper proposes a simplified yet accurate model for estimating ET0 in such regions. 【Method】Daily meteorological data from 1955 to 2020 at the Shihezi Meteorological Station were used, with the FAO-56 PM model serving as the reference standard. We compared eight simplified models for calculating daily, monthly and annual ET0. The accuracy of each model was analyzed using statistical metrics, including coefficient of determination (R2), Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), normalized RMSE (nRMSE), mean absolute error (MAE), and a comprehensive general performance index (GPI).【Result】At daily scale, the radiation-based Priestley-Taylor (PT) model showed the closest agreement with the PM model, followed by the temperature-based Berti-Hargreaves (BH) model. At monthly scale, the PT model was most accurate, followed by the BH model. At annual scale, the PT model worked best, with an MAE of 35.78 mm/a and an nRMSE of 4.93%, whereas the mass transfer-based Roh model was least accurate, with an MAE of 340.18 mm/a and an nRMSE of 37.82%.【Conclusion】Among the eight models we compared, the Priestley-Taylor model is the most accurate simplified method for estimating ET0 in arid oasis regions where meteorological data for the FAO-56 PM model are incomplete or limited.

With the continuous operation of oil and gas stations and petrochemical equipment, it has been found that steel small bore pipelines have different degrees of corrosion defects, which have led to pipeline cracking and medium leakage, and have increasingly attracted great attention of their oil and gas and chemical enterprises. In order to ensure the safe operation of the small diameter pipes with external surface corrosion defects, the influence law of the size of corrosion defects on the bearing capacity of the small diameter pipes were studied by finite element analysis and test simulation method, and the damage mechanism and failure form were analyzed, and the failure pressure prediction formula of the small diameter pipes with defects was fitted. It provides technical guidance for the applicability evaluation of corrosion-containing steel small diameter pipes in oil and gas chemical stations or installations.

Shipping along the Northern Sea Route (NSR) has increased significantly, but fluctuating sea ice conditions continue to affect the shipping season. Despite the growing use of ocean reanalysis datasets in polar research, a comprehensive evaluation of these datasets' accuracy for the NSR is still lacking. This study evaluates five ocean reanalysis datasets—C-GLORSv7, GLORYS2 V4, ORAS5, GREPv2, and TOPAZ4—by comparing them to satellite observations of sea ice concentration (SIC), extent (SIE), and thickness (SIT) along the NSR. All datasets show a declining trend in SIC and SIE from 1993 to 2022, consistent with OSI-SAF satellite observations. GREPv2 exhibits slight negative deviations in SIC, with a spatial mean error of − 1.2%. GLORYS2 V4 presents the lowest mean absolute error for SIE at 1.8 × 10 4 km 2 . Both GREPv2 and GLORYS2 V4 offer the best replication of SIC and SIE, though deviations are most pronounced during summer. For SIT, considerable differences exist compared to CS2SMOS satellite data, with C-GLORSv7, GLORYS2 V4, ORAS5, and GREPv2 showing large positive deviations ranging from 0.2 to 0.4 m, while TOPAZ4, which incorporates satellite-derived SIT, shows the smallest deviation (< 0.1 m). Spatially, deviations are primarily concentrated near islands and along coastlines. Oceanic factors influencing SIC in winter vary, with dynamic mixing and ocean heat transport affecting the Laptev-East Siberian Sea and mixed layer heat content influencing the Chukchi Sea.

【Objective】 The purpose of this paper is to explore the applicability of China Meteorological Assimilation Datasets(CMADS) in hydrological simulation of Hulan River basin. 【Method】 The accuracy and spatiotemporal distribution characteristics of precipitation and temperature data from CMADS and traditional hydrological stations was analyzed, SWAT models driven by two types of meteorological data: CMADS and traditional hydrological stations was constructed, and SUFI-2 algorithm was used to calibrate and validate model parameters based on monthly measured cross-sectional runoff data. The applicability of this dataset as meteorological driven data and its substitutability for traditional hydrological station data were evaluated. 【Result】 ① The two types of meteorological data had strong linear correlation and corresponding relationships, and their spatiotemporal distribution characteristics were similar, with consistent trends within the year. ② In the main stream of Hulan River without reservoir, the evaluation index under the CMADS data-driven model were the rate regularly period R2=0.96, NSE=0.93, PBIAS=20.63%, and the validation period R2=0.98, NSE=0.97, PBIAS=7.51%; In the Tongken River system with a reservoir, the model had a regular flow rate of R2=0.88, NSE=0.80, and PBIAS=12.86%. During the validation period, the models had R2=0.97, NSE=0.96, and PBIAS=12.05%, and the simulation results all meet the evaluation criteria for runoff simulation. 【Conclusion】 CMADS+SWAT model had better overall effect, simulation accuracy and applicability than traditional hydrological stations in runoff simulation of Hulan River basin, and was closer to the measured value, which can provide data support for establishing SWAT model in the study area lacking meteorological data.

The Failure Assessment Diagram (FAD), as a significant method for evaluating the suitability of defective metallic structures, has been subject to considerable debate regarding its applicability in assessing ring welded joints for high-grade steel and large-diameter pipelines. To address this issue, this study first designed and conducted two sets of full-scale pressure-tension tests on large-diameter X80 pipeline ring welded joints, considering factors such as different welding processes, joint configurations, defect dimensions, and locations. Subsequently, three widely adopted failure assessment diagram methodologies—BS 7910, API 579, and API 1104—were selected. Corresponding assessment curves were established based on material performance parameters obtained from the ring weld tests. Finally, predictive outcomes from each assessment method were compared against experimental data to investigate the applicability of failure assessment diagrams for evaluating high-strength, large-diameter, thick-walled ring welds. The research findings indicate that, under the specific material and defect assessment conditions employed in this study, the API 1104 assessment results exhibited significant conservatism (two sets matched). Conversely, the BS 7910 and API 579 assessment results showed a high degree of agreement with the experimental data (eight sets matched), with the BS 7910 assessment providing a relatively higher safety margin compared to API 579. The data from this study provides valuable experimental reference for selecting assessment methods under specific conditions, such as similar materials, defects, and loading patterns.

It is not yet clear whether there is any difference in using remote sensing data of different spatial resolutions and filtering methods to improve the above-ground biomass (AGB) estimation accuracy of alpine meadow grassland. In this study, field measurements of AGB and spectral data at Sangke Town, Gansu Province, China, in three years (2013–2015) are combined to construct AGB estimation models of alpine meadow grassland based on these different remotely-sensed NDVI data: MODIS, HJ-1B CCD of China and Landsat 8 OLI (denoted as NDVIMOD, NDVICCD and NDVIOLI, respectively). This study aims to investigate the estimation errors of AGB from the three satellite sensors, to examine the influence of different filtering methods on MODIS NDVI for the estimation accuracy of AGB and to evaluate the feasibility of large-scale models applied to a small area. The results showed that: (1) filtering the MODIS NDVI using the Savitzky–Golay (SG), logistic and Gaussian approaches can reduce the AGB estimation error; in particular, the SG method performs the best, with the smallest errors at both the sample plot scale (250 m × 250 m) and the entire study area (33.9% and 34.9%, respectively); (2) the optimum estimation model of grassland AGB in the study area is the exponential model based on NDVIOLI, with estimation errors of 29.1% and 30.7% at the sample plot and the study area scales, respectively; and (3) the estimation errors of grassland AGB models previously constructed at different spatial scales (the Tibetan Plateau, Gannan Prefecture and Xiahe County) are higher than those directly constructed based on the small area of this study by 11.9%–36.4% and 5.3%–29.6% at the sample plot and study area scales, respectively. This study presents an improved monitoring algorithm of alpine natural grassland AGB estimation and provides a clear direction for future improvement of the grassland AGB estimation and grassland productivity from remote sensing technology.

In coastal erosion studies, the erosion and accretion index is a vital research tool for analyzing types of erosion and accretion. This index is primarily empirical or semi-empirical and is usually validated through tank experiments or open beach datasets, resulting in significant variation across different beach environments. In this study, 11 beach profiles of eight beaches measured along the Qiongzhou Strait in China, measured from 2018 to 2021, were analyzed to quantitatively determine coastal erosion or accretion by calculating each profile’s volume change per unit width. Additionally, sediment and wave data were used to calculate five erosion and accretion indices monthly to determine erosion and accretion conditions. These conditions were then compared with actual beach erosion and accretion data to evaluate the applicability of various discriminant indices. Furthermore, optimizing the threshold values of discriminant indices. The results show that: (1) Overall annual erosion and accretion are minimal, but seasonal variation is significant for beaches on both sides of the Qiongzhou Strait; (2) The five discriminant indices have some limitations in this study area, necessitating careful consideration when applying them to headland bay arc-shaped beaches with fetch-limited environments like the Qiongzhou Strait; (3) The selection of discriminant index parameters and their respective contribution degree of each parameter affects the formula’s applicability, with two-parameter formulas proving superior to the three-parameter formula in the study area; (4) Beach environmental factors, particularly those influenced by headlands and fetch-limited environments, impact the indices’ applicability; (5) Increasing the threshold value to a certain extent can improve the formula’s applicability.

Global Satellite Mapping of Precipitation (GSMaP), Climate Hazards Group InfraRed Preconception with Station data (CHIRPS), Tropical Rain Measurement Mission Multisatellite Precipitation Analysis (TRMM 3B42 V7) and Rainfall Estimation from Soil Moisture Observations (SM2RAIN) are satellite precipitation products with high applicability, but their applicability in hydrological research in arid mountainous areas is not clear. Based on precipitation and runoff data, this study evaluated the applicability of each product to hydrological research in a typical mountainous basin (the Qaraqash River basin) in an arid region by using two methods: a statistical index and a hydrological model (Soil and Water Assessment Tool, SWAT). Simulation results were evaluated by Nash efficiency coefficient (NS), relative error (PBIAS) and determination coefficient (R2). The results show that: (1) The spatial distributions of precipitation estimated by these four products in the Qaraqash River basin are significantly different, and the multi-year average annual precipitation of GSMaP is 97.11 mm, which is the closest to the weather station interpolation results. (2) On the annual and monthly scales, GSMaP has the highest correlation (R ≥ 0.82) with the observed precipitation and the smallest relative error (BIAS < 6%). On the seasonal scale, the inversion accuracy of GSMaP in spring, summer and autumn is significantly higher than other products. In winter, all four sets of products perform poorly in estimating the actual precipitation. (3) Monthly runoff simulations based on SM2RAIN and GSMaP show good fitting (R2 > 0.6). In daily runoff simulation, GSMaP has the greatest ability to reproduce runoff changes. The study provides a reference for the optimization of precipitation image data and hydrological simulation in data-scarce areas.

The effective ionic capacities of strong cation ion-exchange resins were investigated and compared using conditions similar to those found in white goods, in order to establish behavioral differences between commercial products and evaluate their capacity in a broader business context. Nine different products of equivalent TDS (Technical Data Sheet) capacity were observed to examine their differences in approximately real-life conditions. For a broader context of applicability analysis, besides the absolute ionic operating capacity, the following additional factors were included in the evaluation: the standard deviation in the resins’ performances and their relative prices. A complete method for material applicability evaluation was hereby proposed and shown to offer cost factor benefits of up to 21.1% within the range of products examined, in comparison to a cost-only evaluation for equivalent materials.

Due to the scarcity of meteorological stations on the Tibetan Plateau (TP), owing to the high altitude and harsh climate, studies often resort to satellite, reanalysis, and merged multi-source precipitation data. This necessitates an evaluation of TP precipitation data applicability. Here, we assess the following three high-resolution gridded precipitation datasets: the China Meteorological Forcing Dataset (CMFD), the European Center for Medium-Range Weather Forecasts Reanalysis V5-Land (ERA5-Land), and Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) during TP summers. Using observations from the original 133 China Meteorological Administration stations on the TP as a reference, the evaluation yielded the following conclusions: (1) In summer, from 2000 to 2018, discrepancies among the datasets were largest in the western TP. The CMFD showed the smallest deviation from the observations, and the annual summer precipitation was only overestimated by 12.3 mm. ERA5-Land had the closest trend (0.41 mm/y) to the annual mean summer precipitation, whereas it overestimated the highest precipitation (>150 mm). (2) The reliability of the three datasets at annual and monthly scales was in the following order: CMFD, ERA5-Land, and IMERG. The daily scales exhibited a lower accuracy than the monthly scales (correlation coefficient CC of 0.51, 0.38, and 0.26, respectively). (3) The CMFD assessments, referencing the 114 new stations post-2016, had a notably lower accuracy and precipitation capture capability at the daily scale (CC and critical success index (CSI) decreased by 0.18 and 0.1, respectively). These results can aid in selecting appropriate datasets for refined climate predictions on the TP.