Large-scale characteristics of thermokarst lakes across the source area of the Yellow River on the Qinghai-Tibetan Plateau

As significant evidence of permafrost degradation,thermokarst lakes play an important role in the permafrost regions by regulating hydrology,ecology,and biogeochemistry.In the Sources Area of the Yellow River(SAYR),permafrost degradation has accelerated since the 1980s,and numerous thermokarst lakes have been discovered.In this paper,we use Sentinel-2 images to extract thermokarst lake boundaries and perform a regional-scale study on their geometry across the permafrost region in the SAYR.We also explored the spatiotemporal variations and potential drivers from the perspectives of the permafrost,climate,terrain and vegetation conditions.The results showed that there were 47,518 thermokarst lakes in 2021 with a total area of 190.22×106 m^(2),with an average size of 4,003.3 m^(2).The 44,928 ponds(≤10,000 m^(2))predominated the whole lake number(94.1%)but contributed to a small portion of the total lake area(28.8%).With 2,590 features(5.9%),small-sized(10,000 to 100,000 m^(2))and large-sized lakes(>100,000 m^(2))constituted up to 71.2%of the total lake area.Thermokarst lakes developed more significantly in warm permafrost regions than in cold permafrost areas;74.1%of lakes with a total area of 119.6×106 m^(2)(62.9%),were distributed in warm permafrost regions.Most thermokarst lakes were likely to develop within the elevation range of 4,500~4,800 m,on flat terrain(slope<10°),on SE and S aspects and in alpine meadow areas.The thermokarst lakes in the study region experienced significant shrinkage between 1990 and 2021,characterized by obvious lake drainage;the lake numbers decreased by 5418(56.1%),with a decreasing area of 58.63×106 m^(2)(49.0%).This shrinkage of the thermokarst lake area was attributable mainly to the intensified degradation of rich-ice permafrost thawing arising from continued climate warming,despite the wetting climatic trend.

Impacts of degrading permafrost on streamflow in the source area of Yellow River on the Qinghai-Tibet Plateau,China

Many observations in and model simulations for northern basins have confirmed an increased streamflow from degrading permafrost,while the streamflow has declined in the source area of the Yellow River(SAYR,above the Tanag hydrological station)on the northeastern Qinghai-Tibet Plateau,West China.How and to what extent does the degrading permafrost change the flow in the SAYR?According to seasonal regimes of hydrological processes,the SAYR is divided intofour sub-basins with varied permafrost extents to detect impacts of permafrost degradation on the Yellow River streamflow.Results show that permafrost degradation may have released appreciable meltwater for recharging groundwater.The potential release rate of ground-ice melt-water in the Sub-basin 1(the headwater area of the Yellow River(HAYR),above the Huangheyan hydrological station)is the highest(5.6 mm per year),contributing to 14.4%of the annual Yellow River streamflow at Huangheyan.Seasonal/intra-and annual shifts of streamflow,a possible signal for the marked alteration of hydrological processes by permafrost degradation,is observed in the HAYR,but the shifts are minor in other sub-basins in the SAYR.Improved hydraulic connectivity is expected to occur during and after certain degrees of permafrost degradation.Direct impacts of permafrost degradation on the annual Yellow River streamflow in the SAYR at Tanag,i.e.,from the meltwater of ground-ice,is estimated at 4.9%that of the annual Yellow River discharge at Tanag,yet with a high uncertainty,due to neglecting of the improved hydraulic connections from permafrost degradation and the flow generation conditions for the ground-ice meltwater.Enhanced evapotranspiration,substantial weakening of the Southwest China Autumn Rain,and anthropogenic disturbances may largely account for the declined streamflow in the SAYR.

Diversity analysis of soil dematiaceous hyphomycetes from the Yellow River source area:Ⅰ

Twenty-four soil samples of eight ecosystem-types around the Yellow River source area were investigated for the number and specific composition of soil dematiaceous hyphomycetes by dilution plate technique. And then the co-relationship between genus species of soil dematiaceous hyphomycetes and ecosystem-types was analyzed. The results show that the amount and species distribution of soil dematiaceous hyphomycetes had an obvious variability in different ecosystem-types, and that the dominant genus species varied in the eight ecosystem-types studied, with Cladosporium being the dominant genus in seven of the eight ecosystem-types except wetland. The index of species diversity varied in different ecosystem-types. The niche breadth analysis showed that Cladosporium had the highest niche breadth and distributed in all ecosystem-types, while the genera with a narrow niche breadth distributed only in a few ecosystem-types. The results of niche overlap index analysis indicated that Stachybotrys and Torula, Doratomyces and Scolecobasidium, Cladosporium and Chrysosporium had a higher niche overlap, whereas Arthrinium and Gliomastix, Phialophora and Doratomyces, Oidiodendron and Ulocladium had no niche overlap.

Ice-wedge Pseudomorphs Showing Climatic Change Since the Late Pleistocene in the Source Area of the Yellow River, Northeast Tibet

The source area of the Yellow River is located in the northeastern Tibetan Plateau, and is a high-elevation region with the annual mean temperature of -3.9℃. The ice-wedge pseudomorphs discovered in this region are recognized as two types. One was found in sandy gravel beds of the second terrace of the Yellow River. This ice-wedge pseudomorph is characterized by higher ratio of breadth/depth, and are 1-1.4 m wide and about 1 m deep. The bottom border of the ice-wedge pseudomorph is round arc in section. Another discovered in the pedestal of the second terrace has lower ratio of width/depth, and is o.3-1.0 m wide and 1-2 m deep. Its bottom border is sharp. Based on the TL dating, the former was formed at the middleHolocene （5.69±0.43 ka BP and 5.43±0.41 ka BP）, that is, the Megathermal, and the latter was formed at the late Last Glacial Maximum （13.49±1.43 ka BP）. Additionally, the thawing-freezing folders discovered in the late Late Pleistocene proluvium are 39.83±3.84 ka BP in age. The study on the ice-wedge pseudomorphs showed that the air temperature was lowered by up to 6-7℃ in the source area of the Yellow River when the ice-wedge pseudomorphs and thawing-freezing folds developed.

An evaluation of soil moisture from AMSR-E over source area of the Yellow River, China

In this study,in-situ soil moisture measurements are used to evaluate the accuracy of three AMSR-E soil moisture prod ucts from NASA(National Aeronautics and Space Administration),JAXA(Japanese Aerospace Exploration Agency)and VUA(Vrije University Amsterdam and NASA)over Maqu County,Source Area of the Yellow River(SAYR),China.Re sults show that the VUA soil moisture product performs the best among the three AMSR-E soil moisture products in the study area,with a minimum RMSE(root mean square error)of 0.08(0.10)m3/m3 and smallest absolute error of 0.07(0.08)m3/m3 at the grassland area with ascending(descending)data.Therefore,the VUA soil moisture product is used to describe the spatial variation of soil moisture during the 2010 growing season over SAYR.The VUA soil moisture product shows that soil moisture presents a declining trend from east south(0.42 m3/m3)to west north(0.23 m3/m3),with good agreement with a general precipitation distribution.The center of SAYR presents extreme wetness(0.60 m3/m3)dur ing the whole study period,especially in July,while the head of SAYR presents a high level soil moisture(0.23 m3/m3)in July,August and September.

Changes in lake area and water level in response to hydroclimate variations in the source area of the Yellow River:a case study from Lake Ngoring

In the north-eastern Qinghai-Tibet Plateau(QTP),the source area of the Yellow River(SAYR)has been experiencing significant changes in climatic and environmental conditions in recent decades.To date,few studies have combined modern hydrological conditions with paleoclimate records to explore the mechanism(s)of these changes.This study seeks to improve understanding of hydrological variability on decadal and centennial timescales in the SAYR and to identify its general cause.We first determined annual fluctuations in the surface area of Lake Ngoring from 1985 to 2020 using multi-temporal Landsat images.The results show that lake surface area changes were generally consistent with variations in precipitation,streamflow and the regional dry-wet index in the SAYR,suggesting that the water balance of the Lake Ngoring area is closely associated with regional hydroclimate changes.These records are also comparable to the stalagmite δ^(18)O monsoon record,as well fluctuations in the Southern Oscillation Index(SOI).Moreover,an association of high TSI(total solar insolation)anomalies and sunspot numbers with the expansion of Lake Ngoring surface area is observed,implying that solar activity is the key driving factor for hydrologic variability in the SAYR on a decadal timescale.Following this line of reasoning,we compared the δ^(13)C org-based lake level fluctuations of Lake Ngoring for the last millennium,as previously reported,with the hydroclimatic history and the reconstructed TSI record.We conclude that the hydrological regime of Lake Ngoring has been mainly controlled by centennial fluctuations in precipitation for the last millennium,which is also dominated by solar activity.In general,it appears that solar activity has exerted a dominant influence on the hydrological regime of the SAYR on both decadal and centennial timescales,which is clearly manifested in the variations of lake area and water level of Lake Ngoring.

What drives the change of nitrogen and phosphorus loads in the Yellow River Basin during 2006-2017?

The Yellow River Basin (YRB) plays a very important role in China’s economic and social development and ecological security.In particular,the ecosystem of the YRB is sensitive to climate change.However,the change of nutrient fluxes in this region during the past years and its main driving forces remain unclear.In this study,a hydrologic model R System for Spatially Referenced Regressions on Watershed Attributes (RSPARROW) was employed to simulate the spatio-temporal variations in the fluxes of total nitrogen (TN) and total phosphorus (TP) during the period of 2006-2017.The results suggested that the TN and TP loads increased by 138%and 38%during 2006-2014,respectively,and decreased by 66%and 71%from 2015 to 2017,respectively.During the period of 2006-2017,the annual mean fluxes of TN and TP in the YRB were in the range of 3.9 to 591.6 kg/km^(2)/year and 1.7 to 12.0 kg/km^(2)/year,respectively.TN flux was low in the upstream area of the Yellow River,and presented a high level in the middle and lower reaches.However,the flux of TP in Gansu and Ningxia section was slightly higher than that in the lower reaches of the Yellow River.Precipitation and point source are the key drivers for the inter-annual changes of TN loads in most regions of the YRB.While the inter-annual variations of TP loads in the whole basin are mainly driven by the point source.This study demonstrates the important impacts of climate change on nutrient loads in the YRB.Moreover,management measures should be taken to reduce pollution sources and thus provide solid basis for control of nitrogen and phosphorus in the YRB.

Evidence for a recent warming and wetting in the source area of the Yellow River （SAYR） and its hydrological impacts

Climate change investigation at a watershed-scale plays a significant role in re- vealing the historical evolution and future trend of the runoff variation in watershed. This study examines the multisource hydrological and meteorological variables over the source area of the Yellow River （SAYR） from 1961 to 2,012 and the future climate scenarios in the region during 2006-2100 based on the CMIP5 projection data. It recognizes the significant charac-teristics of the recent climate change in the SAYR and predicts the change trend of future flow in the region. It is found that （1） The climate in the SAYR has experienced a significant warm-wet change since the early 2000s, which is very different from the antecedent warm-dry trend since the late 1980s; （2） The warm-wet trend in the northwestern SAYR （the headwater area of the Yellow River （HAYR）, is more obvious than that in the whole SAYR; （3） With pre- cipitation increase, the runoff in the region also experienced an increasing process since 2006. The runoff variations in the region are sensitive to the changes of precipitation, PET and maximum air temperature, but not very sensitive to changes in mean and minimum air temperatures; （4） Based on the CMIP5 projection data, the warm-wet climate trend in SAYR are likely to continue until 2049 if considering three different （i.e. RCP2.6, RCP4.5 and RCP8.5） greenhouse gas emission scenarios, and the precipitation in SAYR will not be less than the current level before 2100; however, it is estimated that the recent flow increase in the SAYR is likely to be the decadal change and it will at most continue until the 2020s; （5） The inter-annual variations of the East Asian winter monsoon are found to be closely related to the variations of annual precipitation in the region. Meanwhile, the increased precipitation as well as the increase of potential evapotranspiration （PET） being far less than that of precipitation in the recent period are the main climate causes for the flow increase in the region.

Basin-filling processes and hydrocarbon source rock prediction of low-exploration degree areas in rift lacustrine basins:a case from the Wenchang Formation in low-exploration degree areas,northern Zhu I Depression,Pearl River Mouth Basin,E China

Hydrocarbon source rocks, as a main geologic factor of petroliferous systems in a sedimentary basin, play a key role in the accumulation of oil and gas and the formation of hydrocarbon accumulations. This study, which focuses on difficulties in prediction of hydrocarbon source rocks in basins or sags with low exploration degree and insufficient hydrocarbon source rock indicators, taking the Wenchang Formation of northern Zhu I Depression, Pearl River Mouth Basin as an example, proposed a hypothesis of “finding lakes and hydrocarbon source rocks”. Detailed steps include, first, determination of the lacustrine basin boundary according to analysis of seismic foreset facies, determination of the depositional area based on the compilation of strata residual thickness maps, determination of the lacustrine basin shape according to deciphering slope break belt system, determination of the fluctuation of paleo-water depth according to biogeochemical indicators of mature exploration areas, determination of the lacustrine basin scale based on analyses of tectonics intensity and accommodation space, which prove the existence of the lacustrine basin and identify the range of semi deep-deep lake;second, further analyses of tectonopalaeogeomorphology, paleo-provenance,palaeoclimate and paleo-water depth to reconstruct the geologic background of the original basin and semideep-deep lacustrine facies, to determine the distribution of semi-deep/deep lacustrine sediments in combination with studies of logging facies, core facies, seismic facies and sedimentary facies, and to rank the sags’ potential of developing hydrocarbon source rocks from controlling factors of source-to-sink system development;third, on the basis of regional sedimentary facies analysis, through identification and assessment of seismic facies types of semi-deep/deep lacustrine basins in mature areas, establishing “hydrocarbon source rock facies” in mature areas to instruct the identification and depicting of hydrocarbon source rocks in semideep/deep lacustrine basins with low exploration degree;fourth, through systematical summary of hydrocarbon-rich geological factors and lower limit index of hydrocarbon formation of the sags already revealed by drilling wells(e.g., sag area, tectonic subsidence amount, accommodation space, provenance characteristic, mudstone thickness, water body environment, sedimentary facies types of hydrocarbon source rocks), in correlation with corresponding indexes of sags with low exploration degree, then the evaluation and sorting of high-quality source rocks in areas with sparsely distributed or no drilling wells can be conducted with multi-factors and multiple dimensions. It is concluded that LF22 sag, HZ10 sag and HZ8 sag are II-order hydrocarbon rich sags;whereas HZS, HZ11 and HZ24 are the III-order hydrocarbon-generating sags.

Landslide susceptibility assessment in Western Henan Province based on a comparison of conventional and ensemble machine learning

Landslide is a serious natural disaster next only to earthquake and flood,which will cause a great threat to people’s lives and property safety.The traditional research of landslide disaster based on experience-driven or statistical model and its assessment results are subjective,difficult to quantify,and no pertinence.As a new research method for landslide susceptibility assessment,machine learning can greatly improve the landslide susceptibility model’s accuracy by constructing statistical models.Taking Western Henan for example,the study selected 16 landslide influencing factors such as topography,geological environment,hydrological conditions,and human activities,and 11 landslide factors with the most significant influence on the landslide were selected by the recursive feature elimination(RFE)method.Five machine learning methods[Support Vector Machines(SVM),Logistic Regression(LR),Random Forest(RF),Extreme Gradient Boosting(XGBoost),and Linear Discriminant Analysis(LDA)]were used to construct the spatial distribution model of landslide susceptibility.The models were evaluated by the receiver operating characteristic curve and statistical index.After analysis and comparison,the XGBoost model(AUC 0.8759)performed the best and was suitable for dealing with regression problems.The model had a high adaptability to landslide data.According to the landslide susceptibility map of the five models,the overall distribution can be observed.The extremely high and high susceptibility areas are distributed in the Funiu Mountain range in the southwest,the Xiaoshan Mountain range in the west,and the Yellow River Basin in the north.These areas have large terrain fluctuations,complicated geological structural environments and frequent human engineering activities.The extremely high and highly prone areas were 12043.3 km^(2)and 3087.45 km^(2),accounting for 47.61%and 12.20%of the total area of the study area,respectively.Our study reflects the distribution of landslide susceptibility in western Henan Province,which provides a scientific basis for regional disaster warning,prediction,and resource protection.The study has important practical significance for subsequent landslide disaster management.

环境变化的径流效应研究进展及黄河水源涵养区研究展望

针对变化环境下黄河流域实测径流大幅度锐减,严重影响流域水资源与生态安全的问题,面向黄河生态保护和高质量发展的国家重大战略需求,梳理了变化环境下径流效应研究中亟待解决的关键科学问题与关键技术。以黄河水源涵养区为对象,以环境变化的径流效应和水资源预测为核心,细化了数据集构建、机理解析、模型研发、趋势预估4项具体研究内容与研究方案。预期研究成果将揭示黄河水源涵养区水文-生态过程的互馈耦合机理、创新变化环境下生态水文的模拟和预测技术,科学预测变化环境下流域水安全和生态环境风险趋势,有效支撑流域水资源可持续利用与生态环境保护决策。

基于遥感和通量观测的实际蒸散发时空变化特征——以黄河流域水源涵养区为例

蒸散发是地表水热平衡的关键要素,分析蒸散发的时空分布特征及其影响因素,对于深入理解区域水文循环与生态系统过程至关重要。基于通量观测站数据,评估GLEAM、MTE、GLDAS和AVHRR共4种蒸散发产品在黄河流域水源涵养区的适用性,利用水量平衡方法验证其在流域尺度上的精度,并探讨实际蒸散发的影响因素。结果表明:在站点尺度上,GLEAM蒸散发产品精度最高;在流域尺度上,校正后的GLEAM蒸散发产品与实际蒸散发的相对误差在渭河南山支流区最小,其次是兰州以上地区;1982—2015年黄河流域水源涵养区实际蒸散发整体呈增加趋势,空间分布上自西到东逐渐增加;不同植被类型年均蒸散发差异较大,阔叶林的蒸散发最大(575.2 mm),其次是农田(504.3 mm),高山草甸的蒸散发最小(358.2 mm);实际蒸散发变化主要受到太阳辐射与气温的影响。

黄河流域煤炭-煤电-煤化工场地特征精准智能识别方法及应用

黄河流域是“能源流域”,兼具生态环境治理和经济社会发展的重任,涉煤产业场地类型、数量及特征的精准智能识别是流域能源资源-低碳发展-生态保护的关键基础问题。研究融合多源数据与深度学习算法,从流域-基地-场地尺度对黄河流域13个大型煤电基地的煤基场地特征精准解析,获得煤电基地高精度、高质量的本底信息,提出一种实时实景智能识别涉煤产业空间特征的新方法。(1)筛选Google image、GF-6影像、Sentinel-2影像等多源数据,采集13个大型煤电基地煤基场地样本,构建煤炭场地(露天)、煤炭场地(井工)、煤电场地、煤化工场地4类数据集,涵盖21种样本类型。按照每种样本六面体设定6×10个样本,共计1 260个场地样本,分析得出最适样本数量-最高识别效率-最优识别模型的置信区间为80%~86%。(2)建立了煤基场地类型量化模型(Coal-based Site Classification Quantitative Model, CSCQM)和煤基场地范围特征模型(Coalbased Site Range Characteristic Model, CSRCM),模型平均精准度为0.837。明析了黄河流域涉煤产业场地本底信息,提出Google image底图叠加场地智能识别模型解算结果的高精度场地智能识别方法。(3)解析了流域神东煤炭-煤电产业集聚区精准本底数据,依据遥感生态指数(Remote Sensing Based Ecological Index,IRSE)分析,煤基场地分布2 km核心区地表生态质量受煤炭、煤电产业影响明显,5 km缓冲区则影响不明显,而8 km控制区基本不受煤炭、煤电产业影响,从而给出了“动态修复”与分区域、分阶段重点治理等低碳路径。(4)解析了流域宁东煤炭-煤电-煤化工产业集聚区精准本底数据,2022年煤炭场地17.81 km^(2)、占比34.1%,煤化工场地22.3 km^(2)、占比42.6%,煤电场地12.2 km^(2)、占比23.3%,煤化工场地>煤炭场地>煤电场地。进而采用PSR(Pressure-State-Response)模型得到风险管控综合得分53.93分,较2003年提高了27.2%。划分生态维护区、生产监测预警区、损毁修复重建区、其他调控区的分区管控模式。研究为涉煤产业煤基场地潜在污染控制、场地治理及区域生态修复提供技术方法与实践支撑。

砒砂岩区生态治理-生态衍生产业协同发展关键技术与模式

探索生态治理与生态衍生产业协同发展的关键技术与途径,是促进水土保持生态治理高质量发展的重要课题。为此,以生态治理难度极大的黄河流域砒砂岩区为研究对象,基于生态经济学、生态产业技术的理论与方法,提出了生态治理-生态衍生产业协同发展的基本原理和应遵循的原则,探索了生态治理与生态衍生产业协同发展的关键技术与模式,并开展了示范应用。1)生态治理-生态衍生产业协同发展的原理是行为互驱动、效应互补偿,应遵循的原则是“双律适应、适地适生、三方意愿”;2)鉴于砒砂岩覆土区、覆沙区、裸露区生态环境有明显差异,分别构建了小流域生态治理-生态衍生产业协同发展的综合治理措施体系和模式,以坡顶、坡面和沟道为水土保持措施配置的3个地貌单元,选择兼具水土保持功能和饲用、药用、食用等经济开发价值的作物进行生物措施配置,配合注浆固结、抗蚀促生、砒砂岩改性等新的工程技术措施进行生态治理;3)研发了物理-化学-生物综合改良砒砂岩土壤、砒砂岩复配风沙土+生物改良提质、灌草优化平茬及饲料加工、煤矸石改性资源化利用、高陡边坡抗蚀+控渗+植生固稳、生态果园建植等关键技术;4)基于砒砂岩覆沙区“土壤改良固沙+”(如土壤改良固沙+经济林种植、土壤改良固沙+梭梭草套种甘草等)生态治理模式的实践与示范,探索实施了“政府支持,科技支撑,企业产业化+公益性投资,农牧民市场化参与”的多元投资、多方参与、共同受益运行机制与模式。通过灌草平茬饲料加工、土壤改良、经济作物种植等产业化中试,以及矿区回填区生态恢复、小流域生态治理-生态衍生产业协同发展示范性实践,表明脆弱生态区治理中发展生态衍生产业具有广阔的前景。

黄河流域水资源超载地区和短缺地区的判定与动态管理

黄河流域水资源短缺,而能源富集,工业用水需求强劲,水资源开发利用率高达80%,如何协调生态保护和高质量发展的关系,实现对水资源超载地区、短缺地区的动态管理,至关重要。在分析水资源承载能力的概念定义和内涵发展的基础上,总结了水资源超载地区和短缺地区的定义和判定标准,对黄河流域九省(自治区)进行了综合研判,并从水资源刚性约束、水资源监测和管控策略等方面提出了水资源动态管理的关键措施,以期为黄河流域生态保护和高质量发展国家战略的水安全保障提供决策参考。

基于CNN-OBIA的黄河源区水体提取及时空变化

准确识别水体信息是分析地表水时空动态变化的重要技术手段。针对目前各种长时序水体信息提取方法精度低的问题,基于Landsat遥感影像,选用1986~2022年5484景黄河源区遥感影像,分别运用卷积神经网络结合面向对象(CNN-OBIA)和多指数水体检测规则(MIWDR)两种方法提取了黄河源区的地表水体,并对两种方法的提取精度进行了对比分析。在此基础上,探究了1986~2022年黄河源区水体信息的时空变化特征,并对其主要气候因素进行相关分析。结果表明:①CNN-OBIA的总体精度和Kappa系数分别为96.78%和0.93,MIWDR的总体精度和Kappa系数分别为94.28%和0.88,总体而言,CNN-OBIA的提取精度高于MIWDR方法。CNN-OBIA的提取结果可以很好地保持水体边界完整性和有效去除山体阴影,可以较好地对细小河流进行提取。②研究区水体总面积呈现出先减少(1986~2001年)后增加(2001~2022年)的变化趋势。③相关性分析表明,降水和气温与水体面积的变化均表现出显著正相关。

龙羊峡水库后汛期入库径流特征及可蓄水量分析

以1956—2022年唐乃亥水文站实测水文数据为基础,采用数理统计方法,重点分析黄河源区后汛期径流特征,并结合龙羊峡水库满负荷发电流量,对龙羊峡水库在后汛期可蓄水量进行不同情景的分析讨论。研究表明:1)唐乃亥水文站后汛期径流量年际变化较大,丰枯不均,以正常偏枯为主,多年平均后汛期径流量占汛期径流量的29.1%;2)唐乃亥水文站后汛期日平均流量在1000 m^(3)/s以上的径流量平均为8.96亿m^(3),年际变化极大,以1000 m^(3)/s发电流量运用,龙羊峡水库蓄至正常蓄水位的保证率仅为10%,多数年份汛期结束后水位无法达到正常蓄水位2600 m。建议根据后期来水,适时调整进入后汛期的时机,优化和调整龙羊峡水库年度调度方案,为高效合理利用黄河源区后汛期水资源奠定基础。

基于SWAT模型的武强溪流域非点源污染关键源区界定与控制策略

随着点源污染的控制与处理技术日趋完善,非点源污染成为重要的水污染源。武强溪作为流入千岛湖的第二大支流,量化武强溪流域非点源污染负荷,解析非点源污染时空分布特征,提出适合削减武强溪流域污染物的最佳管理措施(best management practices,BMPs)对千岛湖水污染高效治理至关重要。该研究基于土壤水分评估工具(Soil and water assessment tool,SWAT)分析了武强溪流域径流量、总氮输出负荷量的时空分布特征,探究了不同管理措施及组合的削减效果,提出了武强溪流域非点源污染针对性的治理措施。结果表明:1)SWAT模型对于武强溪流域径流量和总氮输出负荷量的模拟具有较好的适用性,径流量校准期和验证期的决定系数(coefficient of determination,R^(2))分别为0.86、0.97,纳什系数(nash-sutcliffe coefficient,NSE)分别为0.83、0.96,百分比偏差(percent bias,PBIAS)分别为15.8%、-6.3%,总氮校准期和验证期的决定系数分别为0.87、0.74,纳什系数分别为0.63、0.66,百分比偏差分别为31.6%、21.2%;2)该流域径流量和总氮负荷主要集中在3—7月,分别占全年输出量的71.67%和75.76%。综合考虑氮的来源和流失途径,将耕地和林地面积占比大、坡度陡的子流域设置为总氮的关键污染源区。考虑调整化肥施用量/配方、改变耕作方式和设置植被缓冲带等削减非点源污染的手段,进行总氮输出负荷削减效率的情景模拟,表明10 m植被缓冲带是减少总氮输出负荷的最佳单一控制策略,总氮削减率可达到69.90%;实施综合管理措施对总氮的污染削减效果更佳,10 m植被缓冲带与施肥量减少20%可使总氮削减率达到74.79%。研究结果可为千岛湖水质管理与控制提供理论基础。

黄河流域上游煤矿区土地利用类型变化及其对固碳服务的影响

明晰矿区土地利用变化及其对区域碳储量的影响,是“双碳”目标背景下推进矿区低碳减排和绿色高质量发展的重要手段.基于多源数据集,使用InVEST模型、土地利用动态度、转移矩阵、缓冲区分析和灰色关联度等方法,识别了1990-2020年黄河流域上游13个大中型煤矿区的土地利用类型时空变化,评估了不同矿区及其周边不同距离缓冲区的固碳服务能力,并对二者的关联度进行分析,旨在厘清矿区土地利用变化对固碳服务的影响.结果表明:(1)1990-2020年煤矿区土地利用类型主要以草地、未利用地、林地和耕地向城乡工矿居民用地转移为主,城乡工矿居民用地面积以288.8 hm^(2)/a的速度持续扩张.(2)1990-2020年不同时段城乡工矿居民用地的单一动态度均为正值,草地和未利用地则均为负值,其中2010-2015年各土地利用类型的综合动态度均较高,2015-2020年则均相对较低,并且露天开采方式矿区土地利用强度远高于井工开采方式.(3)1990-2020年各矿区内单位面积年固碳量在0.7~4.1 Mg/hm^(2)之间,在时间上呈先下降后升高再下降的趋势,并且在距离矿区50 km范围内,距离越远,平均单位面积年固碳量越高,影响程度逐渐下降.(4)不同土地利用类型与单位面积年固碳量的平均关联度从高到低表现为未利用地>耕地>草地>林地>水体.研究显示,黄河流域上游煤矿区开发过程中未利用地和耕地面积的变化是矿区生态系统固碳服务变化的重要原因.

2014—2022年黄河流域甘肃段农村饮用水水质卫生状况分析

目的通过对甘肃省境内黄河流域地区的农村饮用水水质卫生状况分析,识别影响黄河流域甘肃省段农村饮用水安全的主要因素。方法通过“全国饮用水水质卫生监测信息系统”收集2014—2022年甘肃省境内黄河干流及较大支流流经的58县(区)的农村饮用水水质监测数据,采用卡方检验和多因素Logistic回归分析影响黄河流域甘肃段农村饮用水水质的因素。结果2014—2022年共监测黄河流域甘肃段农村饮用水水样38076份,达标率为63.3%;影响达标率的主要指标为总大肠菌群,达标率为76.7%。多因素Logistic回归分析结果显示,不同区域、水期、水源类型、供水类型及消毒与否均会影响农村饮用水水质达标率,其中与集中式供水、消毒、枯水期、地表水水样相比,分散式供水、不消毒、丰水期、地下水水样达标率较低,OR(95%CI)分别为1.794(1.601,2.011)、1.650(1.564,1.740)、1.317(1.262,1.374)和1.123(1.065,1.183);与黄土高原沟壑区相比,甘南高原草原区、黄土丘陵沟壑区水样达标率较高,OR(95%CI)分别为:0.795(0.756,0.835)、0.663(0.607,0.725)。结论黄河流域甘肃段农村饮用水水质有待改善,微生物污染是其主要卫生问题,供水类型及消毒与否作为影响水质状况的重要因素应引起重视,建议应因地制宜,多措并举保障农村饮水卫生安全。