Gravity-Driven Listric Growth Fault and Sedimentation in the Lagoa do Peixe, Rio Grande do Sul Coastal Plain, Brazil

High frequency, high resolution GPR surveys are successfully applied to investigate near-surface stratification architecture of sedimentary units in coastal plains and to define their depositional conditions. However, low frequency GPR surveys to investigate fault-related depositional systems at greater depths are scarce. This survey was designed investigate a > 100 km long linear escarpment that controls the northwest margin of the Lagoa do Peixe, an important lagoon in Rio Grande do Sul Coastal Plain (RGSCP, Brazil). The traditional approach points that RGSCP was developed by juxtaposition of four lagoons/barrier systems as consequence of sea level changes;no deformational structure is admitted to exist before. The low frequency GPR (50 MHz, RTA antenna) and geological surveys carried out in the RGSCP showed the existence of a large, gravity-driven listric growth fault controlling the Lagoa do Peixe escarpment and hangingwall sedimentation. The radargrams in four subareas along the Lagoa do Peixe Growth Fault could be interpreted following the seismic expression of rift-related depositional systems. The radargrams enabled to distinguish three main lagoonal deposition radarfacies. The lower lagoonal radarfacies is a convex upward unit, thicker close to growth fault;the radarfacies geometry indicates that fault displacement rate surpasses the sedimentation rate, and its upper stratum is aged ~3500 l4C years BP. The second lagoonal radarfacies is a triangular wedge restricted to the lagoon depocenter, whose geometry indicates that fault displacement and the sedimentation rates kept pace. The upper lagoonal radarfacies is being deposited since 1060 ± 70 l4C years BP, under sedimentation rate higher than fault displacement rate. The results indicate that low frequency GPR surveys can help in investigating fault-related depositional systems in coastal zones. They also point to a new approach in dealing with RGSCP stratigraphy.

Weathering and accumulation of trace elements in the soils of the Porali Plain, Balochistan: repercussions in agriculture

This study is thefirst attempt to assess the nature of the soil,especially on the western side of the Porali Plain in Balochistan;a new emerging agriculture hub,using weathering and pollution indices supplemented by multi-variate analysis based on geochemical data.The outcomes of this study are expected to help farmers in soil manage-ment and selecting suitable crops for the region.Twenty-five soil samples were collected,mainly from the arable land of the Porali Plain.After drying and coning-quarter-ing,soil samples were analyzed for major and trace ele-ments using the XRF technique;sieving and hydrometric methods were employed for granulometric analysis.Esti-mated data were analyzed using Excel,SPSS,and Surfer software to calculate various indices,correlation matrix,and spatial distribution.The granulometric analysis showed that 76%of the samples belonged to loam types of soil,12%to sand type,and 8%to silt type.Weathering indices:CIA,CIW,PIA,PWI,WIP,CIX,and ICV were calculated to infer the level of alteration.These indices reflect mod-erate to intense weathering;supported by K_(2)O/AI_(2)O_(3),Rb/K_(2)O,Rb/Ti,and Rb/Sr ratios.Assessment of the geo-ac-cumulation and Nemerow Pollution indices pinpoint rela-tively high concentrations of Pb,Ni,and Cr concentration in the soils.The correlation matrix and Principal Compo-nent Analysis show that the soil in this study area is mainly derived from the weathering of igneous rocks of Bela Ophiolite(Cretaceous age)and Jurassic sedimentary rocks of Mor Range having SEDEX/MVT type mineralization.Weathering may result in the undesirable accumulation of certain trace elements which adversely affects crops.

Optimization of inter-seasonal nitrogen allocation increases yield and resource-use efficiency in a water-limited wheat-maize cropping system in the North China Plain

Winter wheat–summer maize cropping system in the North China Plain often experiences droughtinduced yield reduction in the wheat season and rainwater and nitrogen(N)fertilizer losses in the maize season.This study aimed to identify an optimal interseasonal water-and N-management strategy to alleviate these losses.Four ratios of allocation of 360 kg N ha^(-1)between the wheat and maize seasons under one-time presowing root-zone irrigation(W0)and additional jointing and anthesis irrigation(W2)in wheat and one irrigation after maize sowing were set as follows:N1(120:240),N2(180:180),N3(240:120)and N4(300:60).The results showed that under W0,the N3 treatment produced the highest annual yield,crop water productivity(WPC),and nitrogen partial factor productivity(PFPN).Increased N allocation in wheat under W0 improved wheat yield without affecting maize yield,as surplus nitrate after wheat harvest was retained in the topsoil layers and available for the subsequent maize.Under W2,annual yield was largest in the N2 treatment.The risk of nitrate leaching increased in W2 when N application rate in wheat exceeded that of the N2 treatment,especially in the wet year.Compared to W2N2,the W0N3 maintained 95.2%grain yield over two years.The WPCwas higher in the W0 treatment than in the W2 treatment.Therefore,following limited total N rate,an appropriate fertilizer N transfer from maize to wheat season had the potential of a“triple win”for high annual yield,WPCand PFPN in a water-limited wheat–maize cropping system.

Analysis on the turning point of dynamic in-plane compressive strength for a plain weave composite

Experimental investigations on dynamic in-plane compressive behavior of a plain weave composite were performed using the split Hopkinson pressure bar. A quantitative criterion for calculating the constant strain rate of composites was established. Then the upper limit of strain rate, restricted by stress equilibrium and constant loading rate, was rationally estimated and confirmed by tests. Within the achievable range of 0.001/s-895/s, it was found that the strength increased first and subsequently decreased as the strain rate increased. This feature was also reflected by the turning point(579/s) of the bilinear model for strength prediction. The transition in failure mechanism, from local opening damage to completely splitting destruction, was mainly responsible for such strain rate effects. And three major failure modes were summarized under microscopic observations: fiber fracture, inter-fiber fracture, and interface delamination. Finally, by introducing a nonlinear damage variable, a simplified ZWT model was developed to characterize the dynamic mechanical response. Excellent agreement was shown between the experimental and simulated results.

Improved simulation of winter wheat yield in North China Plain by using PRYM-Wheat integrated dry matter distribution coefficient

The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China.Presently,most remote sensing process models use the“biomass×harvest index(HI)”method to simulate regional-scale winter wheat yield.However,spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional scale.Time-series dry matter partition coefficients(Fr)can dynamically reflect the dry matter partition of winter wheat.In this study,Fr equations were fitted for each organ of winter wheat using site-scale data.These equations were then coupled into a process-based and remote sensingdriven crop yield model for wheat(PRYM-Wheat)to improve the regional simulation of winter wheat yield over the North China Plain(NCP).The improved PRYM-Wheat model integrated with the fitted Fr equations(PRYM-Wheat-Fr)was validated using data obtained from provincial yearbooks.A 3-year(2000-2002)averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination(R^(2)=0.55)and lower root mean square error(RMSE=0.94 t ha^(-1))than PRYM-Wheat with a stable HI(abbreviated as PRYM-Wheat-HI),which had R^(2) and RMSE values of 0.30 and 1.62 t ha^(-1),respectively.The PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years(2013-2015).In conclusion,the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model,making it a useful tool for the simulation of regional winter wheat yield.

Seismogenic model of the 2023 M_(W)5.5 Pingyuan earthquake in North China Plain and its tectonic implications

The 6 August 2023 M_(W)5.5 Pingyuan earthquake is the largest earthquake in the central North China Plain(NCP)over the past two decades.Due to the thick sedimentary cover,no corresponding active faults have been reported yet in the epicenter area.Thus,this earthquake presents a unique opportunity to delve into the buried active faults beneath the NCP.By integrating strong ground motion records,high-precision aftershock sequence relocation,and focal mechanism solutions,we gain insights into the seismotectonics of the Pingyuan earthquake.The aftershocks are clustered at depths ranging from 15 to 20 km and delineate a NE-SW trend,consistent with the distribution of ground motion records.A NE-SW nodal plane(226°)of the focal mechanism solutions is also derived from regional waveform inversion,suggesting that the mainshock was dominated by strike-slip motion with minor normal faulting component.Integrating regional geological data,we propose that an unrecognized fault between the NE-SW trending Gaotang and Lingxian-Yangxin faults is the seismogenic fault of this event.Based on the S-wave velocity structure beneath the NCP,this fault probably extends into the lower crust with a high angle.Considering the tectonic regime and stress state,we speculate that the interplay of shear strain between the Amurian and South China blocks and the hot upwelling magma from the subducted paleo Pacific flat slab significantly contributed to the generation of the Pingyuan earthquake.

New Rural Community Construction or Retention Development:A Comparative Analysis of Rural Settlement Transition Mechanism in Plain Agriculture Area of China Based on Actor Network Theory

It is an important way to realize rural revitalization and sustainable development to guide rural settlement transition(RST)in an appropriate way.This paper uses actor network theory(ANT)to construct a theoretical framework for the study of RST.Taking two typical villages with different transition paths in rural areas of North China Plain as examples,this paper reveals the mechanism of RST and makes a comparative analysis.The results show that:1)after identifying problems and obligatory passage point,key actors recruit heterogeneous actors into the actor network by entrusting them with common interests,and realize RST under the system operation.2)Rural settlements under different transition paths have similarities in the problems to be solved,collective actions and policy factors,but there are differences in the transition process,mechanism and effect.The actor network and mechanism of RST through the path of new rural community construction are more complex and the transition effect is more thorough.In contrast,the degree of RST of retention development path is limited if there is no resource and location advantage.3)Based on the applicable conditions of different paths,this paper designs a logical framework of‘Situation-Structure-Behavior-Result’to scientifically guide the identification of RST paths under the background of rural revitalization.

Integration of Multiple Spectral Data via a Logistic Regression Algorithm for Detection of Crop Residue Burned Areas:A Case Study of Songnen Plain,Northeast China

The burning of crop residues in fields is a significant global biomass burning activity which is a key element of the terrestrial carbon cycle,and an important source of atmospheric trace gasses and aerosols.Accurate estimation of cropland burned area is both crucial and challenging,especially for the small and fragmented burned scars in China.Here we developed an automated burned area mapping algorithm that was implemented using Sentinel-2 Multi Spectral Instrument(MSI)data and its effectiveness was tested taking Songnen Plain,Northeast China as a case using satellite image of 2020.We employed a logistic regression method for integrating multiple spectral data into a synthetic indicator,and compared the results with manually interpreted burned area reference maps and the Moderate-Resolution Imaging Spectroradiometer(MODIS)MCD64A1 burned area product.The overall accuracy of the single variable logistic regression was 77.38%to 86.90%and 73.47%to 97.14%for the 52TCQ and 51TYM cases,respectively.In comparison,the accuracy of the burned area map was improved to 87.14%and 98.33%for the 52TCQ and 51TYM cases,respectively by multiple variable logistic regression of Sentind-2 images.The balance of omission error and commission error was also improved.The integration of multiple spectral data combined with a logistic regression method proves to be effective for burned area detection,offering a highly automated process with an automatic threshold determination mechanism.This method exhibits excellent extensibility and flexibility taking the image tile as the operating unit.It is suitable for burned area detection at a regional scale and can also be implemented with other satellite data.

Translation Strategies of Red Tourism Terms in the Central Plains-Taking Red Central Plains as an Example

In recent years,the Red Tourism in Central Plains has gradually become a new type of thematic tourism form,which is an important carrier to carry out patriotism and revolutionary traditional education and carry forward the national spirit.The translation of red tourism publicity is an important window for spreading Chinese culture,and the translation of professional terms is an important link in the red tourism publicity.How to spread the red culture of the Central Plains,glow the charm of the Central Plains culture,enhance the influence of the Central Plains culture,and spread the Central Plains culture to the world has become the mission of every child of the Central Plains.This paper adopts the case analysis method,combined with the specific and typical cases in“Red Central Plains”,and uses different translation strategies and methods to explore the difficulties and solutions of the translation of terms in the red tourism text.

Soil Organic Carbon Stock Variation under Different Soil Types and Land Uses in the Sub-Humid Noun Plain, Western Cameroon

This study was conducted to assess the current stock of soil organic carbon under different agricultural land uses, soil types and soil depths in the Noun plain in western Cameroon. Three sites were selected for the study, namely Mangoum, Makeka and Fossang, representative of the three dominant soil types of the noun plain (Andosols, Acrisols and Ferralsols). Three land uses were selected per site including natural vegetation, agroforest and crop field. Soil was sampled at three depths;0 - 20 cm, 20 - 40 cm, and 40 - 60 cm. Analysis of variance showed that soil type did not significantly influence carbon storage, but rather land uses and soil depth. SOCS decreased significantly with depth in all the sites, with an average stock of 66.3 ± 15.8 tC/ha at 0 - 20 cm, compared to an average stock of 33.3 ± 7.4 tC/ha at 40 - 60 cm. SOCS was significantly highest in the natural formation with 57.2 ± 19.7 tC/ha, and lowest in cultivated fields, at 37.7 ± 10.6 tC/ha. Andosols, with their high content of coarse fragments, stored less organic carbon than Ferralsols and Acrisols.

Response of warm season secondary pollutants to emissions and meteorology in the North China Plain region during 2018-2022

自2013年起中国空气质量虽改善,但华北平原(NCP)重污染仍存在且二次污染加剧,而人们对其成因和变化了解有限.本研究利用2018-2022年数据,借助CMAQ模型探讨此污染响应.结果显示,在2018-2022年间,PM_(2.5)浓度显著下降31%-37%,O_(3)和NO_(2)的年下降速率分别为1%和0.5%SIA和SOA也显著减少,每年分别减少9%和6%PM_(2.5)主要因排放减少而下降,而O_(3)则受气象影响而波动.硫酸盐和铵下降的主因是减排,而硝酸盐对气象变化敏感排放和气象变化对SOA的总体减少同样重要,但人为SOA对排放控制敏感生物SOA易受气象变化影响.研究强调了控制人为排放对缓解NCP地区夏季二次污染的重要性.

Tensile Mechanical Behavior and Failure Mechanism of a Plain-Woven SiCf/SiC Composites at Room and Elevated Temperatures

Ceramic matrix composites (CMCs) are the preferred materials for solving advanced aerospace high-temperature structural components;it has the comprehensive advantages of higher temperature (~1500˚C) and low density. In service environments, CMCs exhibit complex damage mechanisms and failure modes, which are affected by constituent materials, meso-architecture and inhere defects. In this paper, the in-plane tensile mechanical behavior of a plain-woven SiCf/SiC composite at room and elevated temperatures was investigated, and the factors affecting the tensile strength of the material were discussed in depth. The results show that the tensile modulus and strength of SiCf/SiC composites at high temperature are lower, but the fracture strain increases and the toughness of the composites is enhanced;the stitching holes significantly weaken the tensile strength of the material, resulting in the material is easy to break at the cross-section with stitching holes.

Variability of Raindrop Size Distribution during a Regional Freezing Rain Event in the Jianghan Plain of Central China

The characteristics of the raindrop size distribution(DSD)during regional freezing rain(FR)events that occur throughout the phase change(from liquid to solid)are poorly understood due to limited observations.We investigate the evolution of microphysical parameters and the key formation mechanisms of regional FR using the DSDs from five disdrometer sites in January 2018 in the Jianghan Plain(JHP)of Central China.FR is identified via the size and velocity distribution measured from a disdrometer,the discrete Fréchet distancemethod,surface temperature,human observations,and sounding data.With the persistence of precipitation,the emergence of graupel or snowflakes significantly reduces the proportion of FR.The enhancement of this regional FR event is mainly dominated by the increase in the number concentration of raindrops but weakly affected by the diameters.To improve the accuracy of quantitative precipitation estimation for the FR event,a modified second-degree polynomial relation between the shapeμand slopeΛof gamma DSDs is derived,and a new Z-R(radar reflectivity to rain rate)relationship is developed.The mean values of mass-weighted mean diameters(D_(m))and generalized intercepts(lgN_(w))in FR are close to the stratiform results in the northern region of China.Both the melting of tiny-rimed graupels and large-dry snowflakes are a response to the formation of this regional FR process in the JHP,dominated by the joint influence of the physical mechanism of warm rain,vapor deposition,and aggregation/riming coupled with the effect of weak convective motion in some periods.

Changes in groundwater resources and their influencing factors in Songnen Plain, China

The Songnen Plain is a crucial agricultural area in China,and in the past 20 years,a large number of dry fields have been developed into paddy fields in order to improve land output efficiency.As a result,the effective irrigation area of agriculture has increased annually,and the conversion mode and quantity between surface water and groundwater have changed considerably.It is essential to identify the changes in groundwater resources and their influencing factors for the sustainable development of economy and society.This study evaluates groundwater resources in the Songnen Plain using the water balance method based on meteorological,hydrological and groundwater monitoring data from 2000 to 2020.The results 3 show that the groundwater resources in the region amount to 15.945 billion m with precipitation infiltration being the most important component,accounting for 73.09%,which is followed surface water irrigation infiltration and river and ditch infiltration,constituting 14.55%and 10.32%,respectively.Different factors influence groundwater resources in different periods.Compared to 1985,the increase of surface water irrigation infiltration is the primary factor responsible for the increase of groundwater resources,while other recharge sources have decreased during the same period.Compared to 2005,all groundwater resources have increased,with the increase of surface water irrigation infiltration and river channel infiltration being the primary factors.

Modelling the crop yield gap with a remote sensing-based process model:A case study of winter wheat in the North China Plain

Understanding the spatial distribution of the crop yield gap(YG)is essential for improving crop yields.Recent studies have typically focused on the site scale,which may lead to considerable uncertainties when scaled to the regional scale.To mitigate this issue,this study used a process-based and remote sensing driven crop yield model for winter wheat(PRYM-Wheat),which was derived from the boreal ecosystem productivity simulator(BEPS),to simulate the YG of winter wheat in the North China Plain from 2015 to 2019.Yield validation based on statistical yield data revealed good performance of the PRYM-Wheat Model in simulating winter wheat actual yield(Ya).The distribution of Ya across the North China Plain showed great heterogeneity,decreasing from southeast to northwest.The remote sensing-estimated results show that the average YG of the study area was 6400.6 kg ha^(–1).The YG of Jiangsu Province was the largest,at7307.4 kg ha^(–1),while the YG of Anhui Province was the smallest,at 5842.1 kg ha^(–1).An analysis of the responses of YG to environmental factors showed no obvious correlation between YG and precipitation,but there was a weak negative correlation between YG and accumulated temperature.In addition,the YG was positively correlated with elevation.In general,studying the specific features of the YG can provide directions for increasing crop yields in the future.

Integrating a novel irrigation approximation method with a process-based remote sensing model to estimate multi-years'winter wheat yield over the North China Plain

Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.However,using the existing remote sensing-based crop yield models to accurately reproduce the inter-annual and spatial variations in winter wheat yields remains challenging due to the limited ability to acquire irrigation information in water-limited regions.Thus,we proposed a new approach to approximating irrigations of winter wheat over the North China Plain(NCP),where irrigation occurs extensively during the winter wheat growing season.This approach used irrigation pattern parameters(IPPs)to define the irrigation frequency and timing.Then,they were incorporated into a newly-developed process-based and remote sensing-driven crop yield model for winter wheat(PRYM–Wheat),to improve the regional estimates of winter wheat over the NCP.The IPPs were determined using statistical yield data of reference years(2010–2015)over the NCP.Our findings showed that PRYM–Wheat with the optimal IPPs could improve the regional estimate of winter wheat yield,with an increase and decrease in the correlation coefficient(R)and root mean square error(RMSE)of 0.15(about 37%)and 0.90 t ha–1(about 41%),respectively.The data in validation years(2001–2009 and 2016–2019)were used to validate PRYM–Wheat.In addition,our findings also showed R(RMSE)of 0.80(0.62 t ha–1)on a site level,0.61(0.91 t ha–1)for Hebei Province on a county level,0.73(0.97 t ha–1)for Henan Province on a county level,and 0.55(0.75 t ha–1)for Shandong Province on a city level.Overall,PRYM–Wheat can offer a stable and robust approach to estimating regional winter wheat yield across multiple years,providing a scientific basis for ensuring regional food security.

Determine the most appropriate strategy for groundwater management in arid and semi-arid regions, Abhar Plain, Iran

Due to growing demand and reduction of water resources and increasing pollution of water,driven by dramatic population and economic growth, arid and semi-arid land's imminent water problems are nowadays aggravating. This study aims to determine the most appropriate management strategies for balancing the Abhar plain aquifer using the SWOT coupled with AHP technique. The results indicate that weaknesses prevail over strengths as well as threats over opportunities. The placement in the quarter of weaknesses-threats with a defensive strategy indicates the critical condition of the Abhar plain aquifer. The most appropriate solutions to achieve the goal of balancing the groundwater were prioritized by AHP method. According to results, improper management of water consumption with a weight of 72.5% is the most destructive factor in reducing groundwater resources. Among the types of consumption, the effect of an agricultural factor carries a weight of 74.2%. The exploitation of illegal wells, overdraft of exploitation license provisions of wells, reduction of precipitation and traditional irrigation methods were selected as the destructive factors causing the deteriration of groundwater resources. Also, with filling the illegal wells,changing the type of cultivation and greenhouse crops cultivation, installing a smart water meter,observance the provisions of the water exploitation license, implementing integrated pressurized irrigation systems, benefiting from suitable climatic conditions and geographical location for cultivating and developing the low-water use species and industries and on the other hand, with implementing artificial recharge to control the surface water resources and reduce abstraction from groundwater aquifers, the adverse trend of Abhar Plain groundwater resources can be controlled.

Optimizing groundwater recharge plan in North China Plain to repair shallow groundwater depression zone, China

The North China Plain is one of the main grain producing areas in China. However, overexploitation has long been unsustainable since the water supply is mainly from groundwater. Since 2014,the South-to-North Water Diversion Project's central route has been charted to the integrated management of water supply and over-exploitation, which has alleviated the problem to a certain extent. Although the Ministry of Water Resources has made many efforts on groundwater recharge since 2018 most of which have been successful, the recharge has not yet been sufficiently focused on the repair of shallow groundwater depression zones. It still needs further optimization. This paper discusses this particular issue,proposes optimized recharge plan and provides the following recommendations:(1) Seven priority target areas are selected for groundwater recharge in alluvial and proluvial fans in the piedmont plain, and the storage capacity is estimated to be 181.00×10~8 m~3;(2) A recharge of 31.18×10~8 m~3/a is required by 2035 to achieve the repair target;(3) It is proposed to increase the recharge of Hutuo River, Dasha River and Tanghe River to 19.00×10~8 m~3/a and to rehabilitate Gaoliqing-Ningbailong Depression Zone;increase the recharge of Fuyang River, Zhanghe River and Anyang River to 7.05×10~8 m~3/a and rehabilitate Handan Feixiang-Guangping Depression Zone;increase the recharge of Luanhe River by 0.56×10~8 m~3/a and restore Tanghai Depression Zone and Luanan-Leting Depression Zone;moderately reduce the amount of water recharged to North Canal and Yongding River to prevent excessive rebound of groundwater;(4) Recharge through well is implemented on a pilot basis in areas of severe urban ground subsidence and coastal saltwater intrusion;(5) An early warning mechanism for groundwater quality risks in recharge areas is established to ensure the safety. The numerical groundwater flow model also proves reasonable groundwater level restoration in the depression zones by 2035.

Estimation and inter-comparison of infiltration models in the agricultural area of the Mitidja Plain, Algeria

Infiltration is an important part of the hydrological cycle, and it is one of the main abstractions accounted for in the rainfall-runoff modeling. The main purpose of this study is to compare the infiltration models that were used to assess the infiltration rate of the Mitidja Plain in Algeria. Field infiltration tests were conducted at 40 different sites using a double ring infiltrometer. Five statistical comparison criteria including root mean squared error(RMSE), normalized root mean squared error(NRMSE), coefficient of correlation(CC), Nash-Sutcliffe efficiency(NSE), and Kling-Gupta efficiency(KGE) were used to determine the best performing infiltration model and to confirm anomalies between predicted and observed values. Then we evaluated performance of five models(i.e., the Philip model, Kostiakov model, Modified Kostiakov model, Novel model, and Horton model) in simulating the infiltration process based on the adjusted performance parameters cited above. Results indicated that the Novel model had the best simulated water infiltration process in the Mitidja Plain in Algeria. However, the Philip model was the weakest to simulate the infiltration process. The conclusion of this study can be useful for estimating infiltration rate at various sites using a Novel model when measured infiltration data are not available and are useful for planning and managing water resources in the study area.

Value-Added Products Derived from 15 Years of High-Quality Surface Solar Radiation Measurements at Xianghe,a Suburban Site in the North China Plain

Surface solar radiation(SSR) is a key component of the energy budget of the Earth’s surface, and it varies at different spatial and temporal scales. Considerable knowledge of how and why SSR varies is crucial to a better understanding of climate change, which surely requires long-term measurements of high quality. The objective of this study is to introduce a value-added SSR dataset from Oct 2004 to Oct 2019 based on measurements taken at Xianghe, a suburban site in the North China Plain;two value-added products based on the 1-minute SSR measurements are developed. The first is clear sky detection by using a machine learning model. The second is cloud fraction estimation derived from an effective semiempirical method. A “brightening” of global horizontal irradiance(GHI) was revealed and found to occur under both clear and cloudy conditions. This could likely be attributed to a reduction in aerosol loading and cloud fraction. This dataset could not only improve our knowledge of the variability and trend of SSR in the North China Plain, but also be beneficial for solar energy assessment and forecasting.