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As a result of climate warming, the frequency and intensity of droughts have increased. Potato planting and production activities in the single-cropping region in Northern China are affected by drought, which poses a threat to regional food security. Based on this, this paper took potatoes in the single-cropping region in Northern China as the research object and combined the Agricultural Production Systems Simulation (APSIM) model and mathematical statistics methods to complete the evaluation of the applicability of the APSIM model in the study area. The response of potato growth and yield to different drought scenarios was simulated and analysed in the single-cropping region in Northern China. The results showed that the validated APSIM-Potato was highly applicable to the single-cropping region in Northern China. The root mean square error (RMSE) of the simulated phenology was within 1.9 ~ 2.6 days. The normalized root mean square errors (NRMSEs) of the simulated LAI, above-ground biomass, and yield were all below 15%. Potato yield decreased with an increase in drought stress intensity and duration. In the simulation of water stress at a single developmental stage, the yield of potatoes during the budding-flowering stage was affected the most by water stress, with a yield reduction of between 4.8 and 35.8% compared to the control group (CG). High-intensity water stress during the entire growth period reduced the final potato yield by 28.9 to 60.9% compared to CG. Finally, through the simulation experiment of potato water control, it was found that under the same water control condition, the potato yield reduction rate in the northwestern region was greater than that in the southeastern region. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract 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.

[Objective] The aims of this study are to explore the applicability of remote sensing precipitation products in southwest China, to reveal the spatial and temporal characteristics of precipitation in Southwest China, and to provide scientific references for the assessment of droughts and floods in southwest China and the utilization of water resources. [Methods] Firstly, combined with precipitation data from 100 ground- based meteorological stations in the study region, the applicability of TRMM and GPM precipitation products were evaluated on both the multi-year average and inter-annual scales, as well as the meteorological station scale. Subsequently, based on the preferred remote sensing precipitation product, the coefficient of variation method, Theil-Sen median trend analysis coupled with Mann-Kendall significance test and Hurst exponent were adopted to analyze spatiotemporal changes of precipitation and assess their sustainability. Moreover, our effort predicted the precipitation trends in the future. [Results (1) Both TRMM and GPM products demonstrated good consistency and applicability in southwest China, albeit with some overestimation. However, compared with TRMM, GPM displayed a higher spatial resolution and better data quality, which was overall closer to the measured data. (2) Precipitation in southwest China had experienced low and moderate fluctuations over the past 19 years, with 87.54% of the region. The trend for precipitation changes in this region had mostly been increasing (83.71%), mainly weak to moderate sustainability (50.38% weak. 24.30% moderate). The prediction for future precipitation trend as a whole suggested a general increase in precipitation, with 62.24% of the region showing increasing trends, mainly in the central part of the study region, and 13.23% showing trends, mainly in the central Yunnan and southwestern Sichuan regions. This effort provided valuable insights for decision-making related to agricultural production and water resources management in southwest China. [Conclusion GPM is more suitable than TRMM to characterize the precipitation characteristics in southwest China and can be effectively used to carry out spatiotemporal dynamic analysis of precipitation. [ABSTRACT FROM AUTHOR]

Atmospheric water vapour is an important contributor to global energy and water cycles and its detection is necessary for precipitation forecasting and climate change research. To explore the applicability of reanalysis data for determining precipitable water vapour (PWV) content in the Tarim Basin, China, this study compared the reliability of two reanalysis PWV products, ERA-5 (PW ERA) and MERRA-2 (PW MER), using data from four ground-based global navigation satellite system stations representing basin ecosystems (Oasis, Gobi Desert, Central Desert, and Alpine; dataset: PW GNSS) as reference values. We conducted correlation analysis between PW GNSS and both reanalysis PWV products at different time scales to verify the products' accuracy. The results showed that the reanalysis PWV products were mostly overestimated at the Desert station, while they were mostly underestimated at the Oasis station. The applicability of PW ERA and PW MER varied by season and location, with better applicability at the Oasis station from spring to autumn. The applicability of reanalysis PWV products was lower during precipitation periods than during non-precipitation, and varied by location. During non-precipitation situation, the PW MER had better applicability at the Oasis station and at the Central Desert station when the PW GNSS exceeded 25 mm. Meanwhile, PW ERA had better applicability in precipitation situation at the Gobi Desert station from April to June and at Oasis station from August to September when PW GNSS was above 30 mm, at the Central Desert station from May to August, and when the PW GNSS exceeded 30 mm. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Drainage & Irrigation Machinery Engineering / Paiguan Jixie Gongcheng Xuebao is the property of Editorial Department of Drainage & Irrigation Machinery Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Accurate and reliable mid-to-long-term runoff prediction (MLTRP) is of great importance in water resource management. However, the MLTRP is not suitable in each basin, and how to evaluate the applicability of MLTRP is still a question. Therefore, the total mutual information (TMI) index is developed in this study based on the predictor selection method using mutual information (MI) and partial MI (PMI). The relationship between the TMI and the predictive performance of five AI models is analyzed by applying five models to 222 forecasting scenarios in Australia. This results in over 222 forecasting scenarios which demonstrate that, compared with the MI, the developed TMI index can better represent the available information in the predictors and has a more significant negative correlation with the RRMSE, with a correlation coefficient between −0.62 and −0.85. This means that the model's predictive performance will become better along with the increase in TMI, and therefore, the developed TMI index can be used to evaluate the applicability of MLTRP. When the TMI is more than 0.1, the available information in the predictors can support the construction of MLTRP models. In addition, the TMI can be used to partly explain the differences in predictive performance among five models. In general, the complex models, which can better utilize the contained information, are more sensitive to the TMI and have more significant improvement in terms of predictive performance along with the increase in TMI. [ABSTRACT FROM AUTHOR]

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.

Copyright of Landscape Architecture Frontiers is the property of Higher Education Press Limited Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary: Total antioxidant capacity (TAC) holds immense importance in evaluating the milk quality. However, achieving accuracy and comparability in TAC measurement requires a thorough examination of detection methods and the constituents of antioxidants. This research focussed on developing TAC evaluation system tailored for processed milk, and the applicability of four assays (ABTS, FRAP, DPPH and ORAC) was examined, considering their compatibility with antioxidants. For fractionated milk, defatting and deproteinisation processes targeted reduced fat‐soluble (phospholipids by 88.75%) and water‐soluble (ascorbic acid and riboflavin by 55.22% and 63.85%) components, respectively. ORAC assay proved effective for detecting deproteinised milk, whereas DPPD assay displayed heightened sensitivity to alterations in milk fat antioxidants. Regarding pressure‐ and heat‐treated milk, homogenisation increased the availability of phosphatidylcholine (36.59–57.53 mg/L) and sphingomyelin (5.56–10.35 mg/L). However, the TAC of heat‐treated milk experienced a significant reduction due to the degradation of various fat‐soluble antioxidants. ORAC and ABTS assays were found suitable for assessing homogenised and heat‐treated milk, respectively. The peroxide value of reconstituted processed milk fell within the range of 98.48%–104.57% compared to untreated whole milk, affirming the accuracy of key antioxidants and detection methods. This study provides valuable insights for the meticulous assessment and enhancement of antioxidant capacity in milk. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The calibration and validation of hydrological model simulation performance and model applicability evaluation in Gansu Province is the foundation of the application of the flash flood early warning and forecasting platform in Gansu Province. It is difficult to perform the simulation for Gansu Province due to the fact that it covers a wide range, from north to south, with multiple climate types and diverse landforms. The China Flash Flood Hydrological Model (CNFF) was implemented in this study. A total of 11 model clusters and 289 distributed hydrological models were divided based on hydrology, climate, and land-use factors, among others. A spatiotemporally mixed runoff method and the Event-Specific Geomorphological Instantaneous Unit Hydrograph (GIUH) were applied based on large-scale fast parallel computation. To improve model calibration and validation efficiency, the RSA method (Regionalized Sensitivity Analysis) was used for CNFF model parameter sensitivity analysis, which could reduce the number of model parameters that need to be adjusted during the calibration period. Based on the model sensitivity analysis results, the CNFF was established in Gansu Province to simulate flood events in eight representative watersheds. The average NSE, REQ, and ET were 0.76 and 0.73, 9.1% and 12.6%, and 1.2 h and 1.7 h, respectively, in the calibration and validation period. In general, the CNFF model shows a good performance in multiple temporal and spatial scales, thus providing a scientific basis for flash flood early warning and analysis in Gansu Province. [ABSTRACT FROM AUTHOR]

【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.

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A tropical cyclone dataset is an important data source for tropical cyclone disaster research, and the evaluation of its applicability is a necessary prerequisite. The Global Synthetic Tropical Cyclone Hazard (GSTCH) dataset is a dataset of global tropical cyclone activity for 10,000 years from 2018, and has become accepted as a major data source for the study of global tropical cyclone hazards. On the basis of the authoritative Tropical Cyclone Best Track (TCBT) dataset proposed by the China Meteorological Administration, this study evaluated the applicability of the GSTCH dataset in relation to two regions: the Northwest Pacific and China's coastal provinces. For the Northwest Pacific, the results show no significant differences in the means and standard deviations of landfall wind speed, landfall pressure, and annual occurrence number between the two datasets at the 95% confidence level. They also show the cumulative distributions of central minimum pressure and central maximum wind speed along the track passed the Kolmogorov–Smirnov (K-S) test at the 95% confidence level, thereby verifying that the GSTCH dataset is consistent with the TCBT dataset at sea-area scale. For China's coastal provinces, the results show that the means or standard deviations of tropical cyclone characteristics between the two datasets were not significantly different in provinces other than Guangdong and Hainan, and further analysis revealed that the cumulative distributions of the tropical cyclone characteristics in Guangdong and Hainan provinces passed the K-S test at the 95% confidence level, thereby verifying that the GSTCH dataset is consistent with the TCBT dataset at province scale. The applicability evaluation revealed that no significant differences exist between most of the tropical cyclone characteristics in the TCBT and GSTCH datasets, and that the GSTCH dataset is an available and reliable data source for tropical cyclone hazard studies in China's coastal areas. [ABSTRACT FROM AUTHOR]

Soil salinization can decrease soil productivity and is a significant factor in causing land degradation. Precision mapping of salinization in agricultural fields would improve farmland management. This study focuses on the cropland in the Manas River Basin, located in the arid region of northwest China. It explores the potential of a soil mapping method, the Soil–Land Inference Model (SoLIM), which only requires a small number of soil samples to infer soil salinization of farmlands in arid areas. The model was utilized to create spatial distribution maps of soil salinity for the years 2009 and 2017, and changes in the distribution were analyzed. The research results indicate: (1) Through the analysis of sample point data, it was observed that soil salinity in the study area tends to accumulate in the surface layer (0–30 cm) in spring and in the subsoil layer (60–90 cm) during the crop growing season, with significant spatial variability. Therefore, it is necessary to conduct detailed salinity mapping. (2) Using field measurements as validation data, the simulation results of the SoLIM were compared with spatial interpolation methods and regression models. The SoLIM showed higher inference accuracy, with R2 values for the simulation results of the three soil layers all exceeding 0.5. (3) The SoLIM spatial inference showed salt accumulation in the northern part and desalination in the southern part. The findings of this study suggest that the SoLIM has the potential to effectively map soil salinization of croplands in arid areas, offering an efficient solution for monitoring soil salinity in arid oasis croplands. [ABSTRACT FROM AUTHOR]

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Multisource meteorological precipitation products are an important way to make up for a lack of observation sites or a lack of precipitation data in areas with a complex topography. They have important value for local industrial, agricultural, and ecological water use calculations, as well as for water resource evaluation and management. The Yunnan-Kweichow Plateau is located in southwest China and has a relatively backward economy and few meteorological stations. At the same time, the terrain is dominated by mountain valleys, precipitation is greatly affected by the terrain, and meteorological data are lacking, making the calculation of local water resources difficult. In this study, the applicability of the 3-hourly merged high-quality/IR estimates (3B42) of the Tropical Rainfall Measuring Mission (TRMM), China Meteorological Forcing Dataset (CMFD), and China Meteorological Assimilation Driving Datasets (CMADS) in the Yunnan-Kweichow Plateau was analyzed using multiple evaluation indicators of different temporal scales and precipitation intensity levels as well as the spatial distribution of the indicators based on measured daily precipitation data from 59 national meteorological basic stations in the study area in 2008–2018. The results showed that (1) the three products had performed well and could be applied to the calculation of local water resources with CMFD performing the best; (2) the performance of precipitation products was slightly worse on the daily scale, and the overall performance of the yearly, quarterly, and monthly scales was better; (3) good results were achieved in most regions, but there were also some regions with prominent overestimation and underestimation; (4) the three precipitation products had the highest probabilities of detection and the lowest false alarm rates for no rain and light rain, and the probability of detection gradually decreased with an increase in the precipitation intensity; and (5) the mean absolute error of precipitation products in rainy months is large, so the accuracy of products in the calculation of heavy rain and flood will be limited. [ABSTRACT FROM AUTHOR]

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.

Soil salinization can decrease soil productivity and is a significant factor in causing land degradation. Precision mapping of salinization in agricultural fields would improve farmland management. This study focuses on the cropland in the Manas River Basin, located in the arid region of northwest China. It explores the potential of a soil mapping method, the Soil–Land Inference Model (SoLIM), which only requires a small number of soil samples to infer soil salinization of farmlands in arid areas. The model was utilized to create spatial distribution maps of soil salinity for the years 2009 and 2017, and changes in the distribution were analyzed. The research results indicate: (1) Through the analysis of sample point data, it was observed that soil salinity in the study area tends to accumulate in the surface layer (0–30 cm) in spring and in the subsoil layer (60–90 cm) during the crop growing season, with significant spatial variability. Therefore, it is necessary to conduct detailed salinity mapping. (2) Using field measurements as validation data, the simulation results of the SoLIM were compared with spatial interpolation methods and regression models. The SoLIM showed higher inference accuracy, with R2 values for the simulation results of the three soil layers all exceeding 0.5. (3) The SoLIM spatial inference showed salt accumulation in the northern part and desalination in the southern part. The findings of this study suggest that the SoLIM has the potential to effectively map soil salinization of croplands in arid areas, offering an efficient solution for monitoring soil salinity in arid oasis croplands.

A tropical cyclone dataset is an important data source for tropical cyclone disaster research, and the evaluation of its applicability is a necessary prerequisite. The Global Synthetic Tropical Cyclone Hazard (GSTCH) dataset is a dataset of global tropical cyclone activity for 10,000 years from 2018, and has become accepted as a major data source for the study of global tropical cyclone hazards. On the basis of the authoritative Tropical Cyclone Best Track (TCBT) dataset proposed by the China Meteorological Administration, this study evaluated the applicability of the GSTCH dataset in relation to two regions: the Northwest Pacific and China’s coastal provinces. For the Northwest Pacific, the results show no significant differences in the means and standard deviations of landfall wind speed, landfall pressure, and annual occurrence number between the two datasets at the 95% confidence level. They also show the cumulative distributions of central minimum pressure and central maximum wind speed along the track passed the Kolmogorov–Smirnov (K-S) test at the 95% confidence level, thereby verifying that the GSTCH dataset is consistent with the TCBT dataset at sea-area scale. For China’s coastal provinces, the results show that the means or standard deviations of tropical cyclone characteristics between the two datasets were not significantly different in provinces other than Guangdong and Hainan, and further analysis revealed that the cumulative distributions of the tropical cyclone characteristics in Guangdong and Hainan provinces passed the K-S test at the 95% confidence level, thereby verifying that the GSTCH dataset is consistent with the TCBT dataset at province scale. The applicability evaluation revealed that no significant differences exist between most of the tropical cyclone characteristics in the TCBT and GSTCH datasets, and that the GSTCH dataset is an available and reliable data source for tropical cyclone hazard studies in China’s coastal areas.

The general climate model (CMIP6) is the main means of large-scale simulation and prediction of future climate changes,but the simulation quality of its model data and applicability in different research regions need to be evaluated.Based on the measured data of 19 meteorological stations in the upper and middle reaches of the Huai River Basin from 1960 to 2014,this paper systematically evaluates the simulated climate data of 19 CMIP6 models using five precision indicators.The indicators include equidistant cumulative distribution function method,mean,dispersion coefficient (Cv),Pearson correlation coefficient (PCC),standard deviation (STD),and root-mean-square deviation (RMSE).Finally,the following conclusions are drawn:① Based on the simulation data of 19 CMIP6 models corrected for bias,the top two climate models for precipitation data simulation are preliminarily selected,including ACCESS-ESM1-5 and CMCC-ESM2.The top five climate models for simulating temperature data contain ACCESS-ESM1-5 and CMCC-ESM2;② The historical period data and measured historical climate data of the selected CMIP6 models are evaluated from two aspects of annual change trend and spatial distribution.Then,the CMIP6 model suitable for the upper and middle reaches of the Huai River Basin is verified and selected;③ Based on analyzing the influence of atmospheric circulation factors on climate,AO has a good correlation with the climate data of the upper and middle reaches of the studied basin,and the correlation between the model and atmospheric circulation data is close to the actual situation.The comprehensive evaluation shows that the most suitable models for simulating the upper and middle reaches of the Huai River Basin are ACCESS-ESM1-5 and CMCC-ESM2.The systematic evaluation of CMIP6 model data simulating the upper and middle reaches of the Huai River Basin provides theoretical and technical references for the rational selection and utilization of CMIP6 datasets for the research on climate change factors in future scenarios of the basin.

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Based on actual measurement precipitation data in Hunan Province, we have made a comparative evaluation of means, interannual variations and correlations for reanalysis precipitation data from China meteorological forcing dataset (CMFD) and Global land surface reanalysis of China for 40 years (CRA-40) in the corresponding period. The results show that (1) the two sets of reanalysis data have better ability to characterize low-rainfall areas in terms of the annual average precipitation distribution. CMFD shows better precipitation distribution in the northwestern Hunan and southern Hunan than CRA-40, while CRA-40 has a better performance in the eastern Hunan than CMFD data. (2) The absolute deviation of precipitation values of CMFD data and CRA-40 data are mainly concentrated in the range of 0-50 mm and 50.1-100 mm. CMFD data in the two ranges accounts for 56.8% and 20%, respectively, and CRA-40 data in the two ranges accounts for 40% and 35.8%, respectively. (3) In terms of the distribution of averaged precipitation in various seasons for many years, most of the averaged precipitation from CMFD are greater than the observations in all seasons, while most of that from CRA-40 are negative deviation in all seasons in northern Hunan and positive deviation in southern Hunan. (4) In terms of the inter-annual variation of the annual mean precipitation, their variation trends for the two sets of data are consistent with the observations in all periods. The annual mean precipitation from 1979 to 1984 and 1999 to 2010 show a decreasing trend, and there is an increasing trend from 1985 to 1998 and 2011 to 2018. Comparing the climate tendency rate of different periods, we can see that the precipitation from CMFD is closer to the observations than that from CRA-40. (5) The correlation coefficients between precipitation from the two sets of reanalysis data and observations are mostly above 0.75, and correlation coefficients at more than 90% of the stations pass the 0.05 significance level test. And the correlation of inter-annual variation rate between precipitation from the reanalysis dataset and the observations is the best in the northern and southern Hunan, and the worse in central Hunan.

Blockchain is an emerging technology that is increasingly being applied in both industrial and academic contexts. Cryptocurrency is a major application of blockchain in the financial sector, but the technology is expected to disrupt other industries. In fact, it has influenced many businesses and reshaped private and public sector activities. Therefore, there is growing interest in blockchain-based solutions, and applications have evolved in finance, insurance, logistics, government, education, and healthcare. Applications built on blockchains benefit from fair access, transparency, and immutability; these properties have attracted business owners and practitioners to explore blockchain opportunities beyond cryptocurrency, motivating them to investigate how they can benefit from the technology and also to evaluate its compatibility with their strategic orientation. Suitability evaluation (or applicability evaluation) has always been a crucial step for the successful adaptation of any innovative technology, including blockchain. Hence, this paper investigates how the current literature has addressed blockchain suitability evaluation for business cases beyond cryptocurrency. A scoping review is presented that examines the evaluation models and frameworks that have been developed to assist decision-makers regarding blockchain adoption. The results indicate that blockchain evaluation methodologies have utilized varied approaches and serve diverse objectives, which are applicable for different technology adoption stages. Through this scoping review, blockchain evaluation initiatives are classified into five categories, and a critical analysis is offered of the evaluation models under each category. As such, this scoping review overviews existing methodologies for blockchain evaluation approaches with a focus on context, identified assessments factors, assessment process, and evaluation dimensions.

Domestic sewage discharge has become one of the leading causes of environmental pollution in rural and pastoral areas. In order to promote sewage treatment in rural and rustic regions, according to the different geographical environments and economic conditions of other sites, it is essential to compare and select each scheme scientifically and effectively in terms of technology, economy, and reliability. This study combined with the environmental, economic, and social conditions of rural and pastoral areas in Inner Mongolia, took the commonly used wastewater treatment technology as the object, and built a wastewater treatment technology applicability evaluation system based on the comprehensive index evaluation method, which combined with the evaluation of the generality of the technology itself and the matching correction according to the characteristics of different regions. The applicability of 8 technologies for domestic sewage treatment in rural and pastoral areas was evaluated. The results show that according to the natural environment and economic conditions of each municipality in Inner Mongolia Autonomous Region, Engelbart SST integrated equipment, sequencing batch bioreactor (SBR), and constructed wetland are the technolo? gies with good comprehensive adaptability at present. [ABSTRACT FROM AUTHOR]

The objection was to evaluate the applicability of an automated method for aflatoxins analysis by using Immunoaffinity Magnetic Bead - UPLC. The results showed that the average recovery of the mmunoaffinity Magnetic Bead was above 95%, and the relative standard deviation was less than 3.3%. The results of the quality control samples were within the range of the reference uncertainty. The method was accurate and reliable.T testing (sig. (bilateral) = 0.533) proved that there was no significant difference between two independent purification instruments.62 researchers evaluated two methods of purifications with immunomagnetic beads and immunoaffinity column. T testing has proved that the results of the two methods were no significant difference.However, the dispersion degree of the immunomagnetic bead automated processing method was smaller than that of the immunoaffinity column method. Moreover, the z-value of all the test were less than 2 (| Z | ≤2). Hence, this method can detect cereals and oils. In addition, the method is environmentally friendly, simply, and lower-cost, which greatly improved detection efficiency and level.

Solar radiation plays an important role in the cryospheric water cycle, especially in alpine regions. This study presents an evaluation of the Modern-Era Retrospective analysis for Research and Applications 2 (MERRA2), ERA5, High Asia Refined analysis version 2 (HAR v2), JRA-55, and National Centers for Environmental Prediction/Climate Forecast System Reanalysis datasets at different time scales by comparing observed datasets from July 2010 to December 2015 at 4,550 m in the Laohugou Basin. In terms of shortwave radiation, ERA5 performs significantly better than the other reanalysis radiation datasets. For downward shortwave radiation, HAR v2 performs better than ERA5 on only two timescales, 3 months and half-year, with mean absolute errors (MAEs) of 13.28 and 7.96 w/m2. The upward shortwave radiation, ERA5, outperforms the other reanalysis datasets on all 12 timescales. For downward longwave radiation, ERA5 also performs significantly better, with only MERRA2 outperforming ERA5 on the daily scale and annual scale, with R2, bias, root mean square error, and MAE of 0.6, 0.95, −9.51 w/m2, −9.41 w/m2, 34.98 w/m2, 9.46 w/m2, and 27.52 w/m2, 9.41 w/m2, respectively. In the upward longwave radiation, HAR v2 performs better than the other reanalysis datasets on all timescales, except for ERA5, which has a better R2 of 0.92 on the annual scale. All the reanalysis datasets can show the variation trend of the four radiation parameters in different seasons and achieve a better performance in winter. Therefore, ERA5 is recommended for regions without shortwave radiation observations, and HAR v2 and ERA5 are recommended for longwave radiation simulations. Although there are obvious shortcomings in the reanalysis radiation datasets, they still provide important supplementary information for research in high-altitude areas, where the observed datasets are too sparse.

Multisource meteorological precipitation products are an important way to make up for a lack of observation sites or a lack of precipitation data in areas with a complex topography. They have important value for local industrial, agricultural, and ecological water use calculations, as well as for water resource evaluation and management. The Yunnan-Kweichow Plateau is located in southwest China and has a relatively backward economy and few meteorological stations. At the same time, the terrain is dominated by mountain valleys, precipitation is greatly affected by the terrain, and meteorological data are lacking, making the calculation of local water resources difficult. In this study, the applicability of the 3-hourly merged high-quality/IR estimates (3B42) of the Tropical Rainfall Measuring Mission (TRMM), China Meteorological Forcing Dataset (CMFD), and China Meteorological Assimilation Driving Datasets (CMADS) in the Yunnan-Kweichow Plateau was analyzed using multiple evaluation indicators of different temporal scales and precipitation intensity levels as well as the spatial distribution of the indicators based on measured daily precipitation data from 59 national meteorological basic stations in the study area in 2008–2018. The results showed that (1) the three products had performed well and could be applied to the calculation of local water resources with CMFD performing the best; (2) the performance of precipitation products was slightly worse on the daily scale, and the overall performance of the yearly, quarterly, and monthly scales was better; (3) good results were achieved in most regions, but there were also some regions with prominent overestimation and underestimation; (4) the three precipitation products had the highest probabilities of detection and the lowest false alarm rates for no rain and light rain, and the probability of detection gradually decreased with an increase in the precipitation intensity; and (5) the mean absolute error of precipitation products in rainy months is large, so the accuracy of products in the calculation of heavy rain and flood will be limited.

The global solar radiation(Rs) is of great significance in the fields of agricultural production system, hydrometeorological research and clean energy development. Due to the complicated topography and various climate in Sichuan province, the distribution of global solar radiation is uneven. In order to explore the most suitable Rs estimation models for different zones of Sichuan, Sichuan was divided into three solar radiation zones in this paper (zone I: western Sichuan plateau, zone II: eastern Sichuan basin, and zone III: southwest Sichuan mountain) for research. Zone I(Ganzi and Hongyuan stations) has low temperature, sufficient sunshine and strong solar radiation; zone II(Chengdu, Mianyang and Luzhou stations) has high relative humidity, short sunshine duration and low radiation; zone III(Emeishan and Panzhihua stations) is abundant in solar radiation resources, but the air temperature and humidity vary greatly within the zone. In three solar radiation zones, based on the meteorological data from 1994 to 2016, the applicability of six Rs estimation models were evaluated under three weather types(sunny, partially cloudy and cloudy), and the simulation effect of combined models based on weather types in different zones were analyzed. The results showed that: (1) the empirical models performed well in Sichuan province(the coefficient of determination R2 ranged from 0.554 to 0.934, P<0.001). The most accurate simulation model in zone I was sunshine-based model A-P with mean absolute error (MAE) 2.210±0.714MJ-m_2-d_1. The hybrid model Chen was the best in zone II (MAE was 1.510±0.027MJ-m_2-d_1) and zone III (MAE was 1.510±0.027MJ-m_2-d_1). (2) The statistical performance of the six models under three weather types in Sichuan showed sunny>partially cloudy>cloudy. The sunshine-based models(A_P and Ba models) could better simulate the Rs in sunny days, while the hybrid modelsfChen and Ab models) had higher accuracy in simulating partially cloudy and cloudy days. The A_P(the global performance indicator GPI = 0.850), Ab(1.294) and Ba(0.862) models were the best models to simulate Rs of zone I in sunny, partially cloudy and cloudy, respectively. The A-P(GPI = 0.381), Chen(1.358) and Chen(1.742) models were the best models to simulate Rs of zone II under three weather types, respectively. The Chen model was the best model to simulate Rs of zone III in sunny, partially cloudy and cloudy with GPI 0.204, 0.857 and 0.526, respectively. (3) The Rs combined models(Mnew) based on weather types had the best simulation accuracy in each zone(GPI were 0.558, 0.582 and 0.134 in 3 zones, respectively). Therefore, it is recommended to use the Rs combined models based on weather types to estimate Rs in Sichuan province. [ABSTRACT FROM AUTHOR]

Satellite precipitation data with high spatial-temporal resolution provides a strong support for the study of hydrological processes in watersheds lacking ground stations. In this study, the applicability of satellite precipitation data TRMM 3B42 for streamflow simulation over the source region of the Yellow River from 2002 to 2015 was evaluated by using the VIC distributed hydrological model. The results show that the TRMM satellite precipitation data is consistent with the gauge data in the spatial and temporal distribution and change trend. The annual average bias between the TRMM data and the rain-gauge observations precipitation is -7.1% and the correlation coefficient reaches to 0.86. According to the simulation results of the VIC model, the TRMM data show good performance in monthly streamflow simulation. However, it gets poor performance for daily streamflow simulation. The simulation accuracy of the TRMM data in the wet years is higher than that in dry years. [ABSTRACT FROM AUTHOR]

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In this paper, typical earthquake disaster life loss assessment models are applied to verify and calculate the historical earthquake cases in the Gansu Province since 1966. The assessment accuracy and applicability of various models in the Gansu Province are studied by means of actual earthquake cases. Results show that: (1) For Ms6.0, characteristics of the assessed regions, such as physical geography and social economy, should be analyzed to correct the model calculation results and to receive comprehensive assessment results, so as to support emergency decisions. (2) Earthquake disaster life loss assessment models are regionalized and the assessment results are obviously regional. Assessment results of the earthquakes occurred in Hedong Region are not accurate for Hexi Region of Gansu Province.

Standard applicability is the ability of a standard to be suitable for the prescriptive purpose under specified conditions. There is no mature applicability-evaluation index system of standards worldwide at present. We aim to construct the index system for evaluating the applicability of forensic science standard. The index system of applicability evaluation is proposed using a statistical analysis on the applicability of forensic science standards in China. We summarize the major problems and reasons in developing and revising the national and industry standards in China. Based on these, we put forward measures to improve standards' applicability, provide policy support for rectifying the standards, and lay the theoretical foundation for the construction, adjustment, and optimization of the forensic science standard system.

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.

Reactive distillation (RD) is a great process intensification concept applicable to equilibrium limited reaction systems, but how can anyone decide quickly if RD is indeed worth applying? To answer this question, this study proposes a mapping method for checking the applicability of reactive distillation (RD). The initial development is for one of the most relevant subset of quaternary reversible reactions (A + B ⇄ C + D, with boiling points T b,C  < T b,A  < T b,B  < T b,D ), by using only basic chemical (equilibrium and kinetics) and physical (relative volatilities) parameters. Generic cases, assuming ideal thermodynamics and constant parameters, are used to obtain a set of RD applicability graphs that provide broad insights into the RD operation. In addition, the new mapping method provides reasonable estimates of the RD applicability to real (non-ideal) chemical systems based on the available pre-defined maps (which are actually applicability graphs of the generic ideal cases). This new approach leads to a straightforward estimation of the applicability of RD to real systems, prior to performing any rigorous process simulations and without any clear-cut decision making (as used in previous studies). [ABSTRACT FROM AUTHOR]

In this paper, we selected the middle and upper reaches of the Wuyuer River basin in the black soil region of Northeast China as the study area. We adopted the soil and water integrated model (SWIM) and evaluated the parameter sensitivity using partial correlation coefficient. We calibrated and validated our simulation results based on the daily runoff data from Yi'an hydrological station at the outlet of the river basin and the evaporation data recorded by various weather stations from 1961 to 1997. Following evaluation of the modeling data against the observed data, we present the applicability of SWIM in the river basin of the black soil region, and discuss the resulting errors and their probable causes. Results show that in the periods of calibration and validation, the Nash-Sutcliffe efficiency (NSE) coefficients of the monthly and daily runoffs were not less than 0.71 and 0.55, and the relative errors were less than 6.0%. Compared to daily runoffs, the simulation result of monthly runoffs was better. Additionally, the NSE coefficients of the potential monthly evaporation were not less than 0.81. Together, the results suggest that the calibrated SWIM can be utilized in various simulation analyses of runoffs on a monthly scale in the black soil region of Northeast China. On the contrary, the model had some limitations in simulating runoffs from snowmelt and frozen soil. Meanwhile, the stimulation data deviated from the measured data largely when applied to the years with spring and summer floods. The simulated annual runoffs were considerably higher than the measured data in the years with abrupt increases in annual precipitation. However, the model is capable of reproducing the changes in runoffs during flood seasons. In summary, this model can provide fundamental hydrological information for comprehensive management of the Wuyuer River basin water environment, and its application can be potentially extended to other river basins in the black soil region. [ABSTRACT FROM AUTHOR]

Drought index is the basic parameter for drought monitoring and evaluation, which is the foundation of drought management and decision-making. Based on the monthly precipitation data collected from 18 stations in Henan Province, China from 1953 to 2012, we select Pa, Z and M as three typical drought indexes to analyze the evolution rules of arid from drought variations and the characteristics of drought index sequence values, and evaluate the applicability of the three kinds of drought indexes in the arid region. The results show that high frequency and evident seasonal variations are the characteristics of drought areas in Henan Province. Meanwhile, the drought strength and duration have an evident interannual fluctuation and increase slowly as a whole. The evaluation result shows that the Pa (M) index has a lower (higher) reflection than the reality, but the Z index can provide a more realistic result. Pa index is much more dependent on the average value, and has a slow response to the drought and can't indicate extremely dry conditions. M index is more sensitive to the drought but may exaggerate the actual situations sometimes. Z index not only considers the reality that precipitation varies according to partial distribution (PD), but also uses the normalization method to avoid errors from different spatial and temporal scales. Therefore, the result is more consistent with the real situation. The results can provide references for evaluating the agricultural drought in Henan Province. [ABSTRACT FROM AUTHOR]

In recent years, global reanalysis weather data has been widely used in hydrological modeling around the world, but the results of simulations vary greatly. To consider the applicability of Climate Forecast System Reanalysis (CFSR) data in the hydrologic simulation of watersheds, the Bahe River Basin was used as a case study. Two types of weather data (conventional weather data and CFSR weather data) were considered to establish a Soil and Water Assessment Tool (SWAT) model, which was used to simulate runoff from 2001 to 2012 in the basin at annual and monthly scales. The effect of both datasets on the simulation was assessed using regression analysis, Nash-Sutcliffe Efficiency ( NSE), and Percent Bias ( PBIAS). A CFSR weather data correction method was proposed. The main results were as follows. (1) The CFSR climate data was applicable for hydrologic simulation in the Bahe River Basin ( R of the simulated results above 0.50, NSE above 0.33, and | PBIAS| below 14.8. Although the quality of the CFSR weather data is not perfect, it achieved a satisfactory hydrological simulation after rainfall data correction. (2) The simulated streamflow using the CFSR data was higher than the observed streamflow, which was likely because the estimation of daily rainfall data by CFSR weather data resulted in more rainy days and stronger rainfall intensity than was actually observed. Therefore, the data simulated a higher base flow and flood peak discharge in terms of the water balance, except for some individual years. (3) The relation between the CFSR rainfall data ( x) and the observed rainfall data ( y) could be represented by a power exponent equation: y=1.4789 x ( R =0.98, P<0.001). There was a slight variation between the fitted equations for each station. The equation provides a theoretical basis for the correction of CFSR rainfall data. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Six types of runoff plots were set up and an experimental study was carried out to examine natural rate of soil and water loss in the granite gneiss region of northern Jiangsu Province in China. Through correlation analysis of runoff and soil loss during 364 rainfall events, a simplified and convenient mathematical formula suitable for calculating the rainfall erosivity factor (R) for the local region was established. Other factors of the universal soil loss equation (USLE model) were also determined. Relative error analysis of the soil loss of various plots calculated by the USLE model on the basis of the observed values showed that the relative error ranged from -3.5% to 9.9% and the confidence level was more than 90%. In addition, the relative error was 5.64% for the terraced field and 12.36% for the sloping field in the practical application. Thus, the confidence level was above 87.64%. These results provide a scientific basis for forecasting and monitoring soil and water loss, for comprehensive management of small watersheds, and for soil and water conservation planning in the region.

Reference crop evapotranspiration (ET0) is an important parameter in water cycle and water balance. Accurate estimation of ET0 becomes vital in planning and optimizing irrigation schedules and irrigation system management. Numerous methods have been proposed for estimating ET0, among which the Penman-Monteith (P-M) method recommended by Food and Agriculture Organization of the United Nations (FAO) in 1998 provides the most accurate results across the world wherever in arid or humid environment. But the main problems when computing ET0 by the P-M method are its complicated nonlinear process and requirements of many climatic variables. Thus, there is an urgent need to develop a much simpler and more appropriate method in areas with limited data, such as the Hargreaves-Samani (H-S) method. In order to improve the ET0 calculation accuracy of the H-S method, in this research the daily data of 13 representative meteorological stations from 1954 to 2013 in hilly area of central Sichuan was used to calculate the ET0. The H-S method was modified based on the Bayesian principle and the impact of the radiation, and at the same time the accuracy of the modified method was evaluated. The result showed that in Zone I the parameter a was 0.915, in Zone II was 0.922, in Zone III was 0.912, and the parameter b was the function of radiation. The trend of the modified method's computing result was similar to the P-M method and both showed a parabolic shape. Compared with the H-S method, the average absolute error of ten-day ET0 with the modified H-S method decreased from 0.93 to 0.15 mm/d in Zone II, from 0.95 to 0.19 mm/d in Zone II and from 0.93 to 0.28 mm/d in Zone III. The fitting equation slope of ten-day ET0 was 0.89, 0.94 and 0.90 respectively in these areas using the modified method, and the calculation accuracy was enhanced remarkably. During the period between March and October, the average absolute error of monthly ET0 decreased from 0.89 to 0.46 mm/d in ZoneI, from 1.14 to 0.29 mm/d in ZoneII and from 1.28 to 0.21 mm/d in Zone III, respectively. In January, February and December, the average absolute error of monthly ET0 changed from 0.14 to 0.35 mm/d in ZoneI, decreased from 0.31 to 0.30 mm/d in Zone II and from 0.32 to 0.28 mm/d in Zone III. The fitting equation slope of monthly ET0 was 0.83, 0.89 and 0.90 respectively in these areas using the modified method. The accuracy of modified method decreased when the altitude increased. In the whole year, the accuracy increased by 47%, the accuracy in Zone I increased by 35% and the accuracy in Zone II increased by 48% especially in the main crop growth period. Therefore, the modified H-S method based on the Bayesian theory is more adaptive and accurate, and can be used as a simple method for the calculation of ET0 in hilly area of central Sichuan Basin. [ABSTRACT FROM AUTHOR]

In order to making true the exact calculation of reference crop evapotranspiration(ET0) and increase the accuracy with the lack of meteorological data in the large area, the Yangtze River Basin is divided into upstream, midstream and downstream according to the altitude of the stations.A new method of space distribution based on Inverse Distance Weighted Interpolation method is raised which can present every substream, including upstream, midstream and downstream.This method can include the connection of different stations.There are 102 meteorological stations which can provide 50 years of daily meteorological data from 1963 to 2013.In this research, we used the methods of Penman Monteith(P M), Hargreaves Samani(H S), Irmark ALLEN(I A), Pristley Taylor(P T), Makkink(M K), Penman Van Bavel(PVB), 1948 Penman(48 PM) to calculate daily ET0 of every stations of the Yangtze River Basin.The method of Penman Monteith can be used to be the standard method to calculate standard daily ET0 to evaluate other methods because of its accuracy.The coefficient of Nash Sutcliffe, the daily relative root mean square error, the consistency coefficient of Kendall can be used to evaluate the precision index of the method.The result showed that the best method of daily ET0 imitative effect compared with P M is PVB in the three substreams, because the slope of the imitative equation of PVB in upstream is 0.946, the slope in midstream is 1.065, and the slope in downstream is 1.005.The method of Pristley Taylor has a better effect in the midstream and downstream, and the slopes of the imitative equation are 1.030 and 1.201.The method of Makkink also has a good effect in the midstream and downstream, and the slopes are 0.857 and 0.936.The determination coefficient of daily ET0 imitative equation of these six methods all achieved very significant levels(α=0.01) in three substreams.The methods of Pristley Taylor and Penman Van Bavel have high calculation accuracy in all area of the Yangtze River Basin, and the highest absolute error of monthly ET0 is 0.55 mm/d using the method of Pristley Taylor, at the same time the highest absolute error of monthly ET0 is 0.48 mm/d using the method of Penman Van Bavel.The effect of the methods of Hargreaves Samani and Irmark ALLEN are worse than other methods to calculate monthly ET0 in the whole Yangtze River Basin.The method of Pristley Taylor is the best method to calculate ET0 in the upstream of the Yangtze River Basin, because the daily relative root mean square error is 0.341 mm/d, the coefficient of Nash Sutcliffe is 0.886, and the consistency coefficient of Kendall is 0.829.The method of Penman Van Bavel is the best method to calculate ET0 in the midstream and downstream of the Yangtze River Basin.In the midstream, the daily relative root mean square error is 0.201 mm/d, the coefficient of Nash Sutcliffe is 0.973, and the coefficient of Nash Sutcliffe is 0.926.In the downstream, the daily relative root mean square error is 0.306 mm/d, the coefficient of Nash Sutcliffe is 0.954, and the consistency coefficient of Kendall is 0.869.In the Yangtze River Basin, the relative error of Pristley Taylor and Penman Van Bavel are the lowest among these methods which are less than 35%, the relative error of is the highest among these methods which is more than 40%.In conclusion, the method of Pristley Taylor and Penman Van Bavel are the best methods to calculate ET0 in the Yangtze River Basin, the calculation process are simple at the same time.The method of Pristley Taylor and Penman Van Bavel can be a simplified recommendation of calculating ET0 in the Yangtze River Basin. [ABSTRACT FROM AUTHOR]

This study evaluated the optimized operational conditions of a modified four-stage Bardenpho process via modeling for livestock wastewater treatment. The objective is to determine whether the effluent Korean water quality standards can be met using the modified process and ozone/activated carbon reactors. The parameters related to microbial respiration (i.e., Y H , Y A , μ H , b H , and i XB ) and effluent concentrations (i.e., f p , η g , K h , and η h ) in GPS-X based on ASM1 were calibrated according to the influent characteristics. Consequently, the differences in the COD and TN concentrations of the calibrated and experimental results were 29.58 and 19.15 mg/L, respectively. A modeling method based on multiple RSM was used to determine the optimized operational conditions, resulting in a DO concentration of 6.6 mg/L in each aerobic reactor, an internal recycling rate of 4.9 Q in , and a sludge recycling rate of 1.4 Q in . Although the COD and TN concentrations during actual operation using the optimized conditions were slightly different than those predicted by GPS-X, the differences were not significant; therefore, the effluent Korean water quality standards were satisfied. With more specific criteria that reduce the differences between the predicted and actual concentrations, the modeling method for operational optimization would be sufficient under any circumstances. [ABSTRACT FROM AUTHOR]

The coincidence of design weather data means the simultaneous occurrence of design weather elements. Correlative studies have indicated that the generation of coincident design weather data (CDWD) is affected by the building parameter characteristics and indoor cooling load. The transfer function method and periodic response factor method are commonly used to calculate the indoor cooling load. In previous studies on CDWD generation, the transfer function method was primarily used to calculate the cooling load, as it reflects the actual thermal process more accurately. However, the periodic response factor method may have more significant advantages, as it matches better with practical engineering application method. There no researcher has proposed the CDWD generation method based on the periodic response factor method, or has evaluated the applicability of the transfer function method and periodic response factor method in the study on CDWD generation. In this study, taking the accuracy of cooling load calculated by the generated CDWD as evaluation index, the applicability of transfer function method and periodic response factor method in the generation of CDWD was evaluated. The results show that for the practical engineering application, the correct rate of CDWD generated based on the periodic response factor method is significantly higher than that based on the transfer function method. Moreover, there is no significant difference between the design cooling load calculated based on the transfer function method and that based on the periodic response factor method. The conclusion indicates that the periodic response factor method is more applicable for the generation of (and engineering applications regarding) CDWD. [ABSTRACT FROM AUTHOR]