Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. oioigtosas nmn iesadtemntrn aaichrn,s tcno rl eetthe reflect truly cannot it remote so (MODIS) incoherent, spectroradiometer sample imaging data makes resolution monitoring the which moderate the index, monitoring With quality and limitations, water eutrophication. rivers conventional technology water many the monitoring of in behind evolution of lagged sparse by Because has too caused water monitoring that blooms. in especially index water content deterioration, of algae environmental occurrence ecological frequent serious the increasingly spurring formation, Abstract Chen zhuo the of reaches lower China and River, middle Hanjiang the in inversion data from MODIS concentration chlorophyll-a of evolution Spatiotemporal ptoeprleouino hoohl- ocnrto rmMDSdt neso nthe in China inversion River, Hanjiang data Chen the Zhuo MODIS of from reaches lower concentration and chlorophyll-a middle of evolution Spatiotemporal various inversion of concentration influence chlorophyll-a the determine River to Hanjiang change. used the concentration we characteristics chlorophyll-a of evolution the reaches spatiotemporal lower on of and factors the analysis Subsequently, determine environmental inversion middle to inversion. the the chlorophyll-a compared of in River were results Hanjiang 2011 errors the the error and model to of of and 2000 reaches types lower trial for data, two and the model model, sensing middle network of algorithm of the remote neural use for reaches BP MODIS settings the lower and algorithm technology, Through and model optimal communication ratio the middle analysis. sensing band the correlation the remote considers concentration establish current chlorophyll-a to study important measured method the This has and on blooms. methods method cannot based remote water statistical This it China, of (MODIS) and so in control effectively. spectroradiometer River incoherent, and collected imaging warning Hanjiang data be resolution early the monitoring can the moderate the data for With water observation and significance conventional chlorophyll-a rivers guiding the continuous eutrophication. many behind monitoring, water Because in lagged data of sparse has increasingly sensing blooms. evolution too water spurring water the monitoring formation, in of reflect reservoir index sample occurrence truly lake content makes frequent and algae which river the the index, of by monitoring quality trend caused limitations, clear technology that a monitoring especially to of led deterioration, has environmental projects ecological water serious of construction global The Abstract 2021 24, May 2 1 orsodn Author: Corresponding China 100012, Beijing, Sciences, Environmental 3 2 1 hns eerhAaeyo niomna Sciences Environmental of Academy Research Chinese University Zhengzhou colo clg n niomn,ZeghuUiest,Zeghu 501 China 450001, Zhengzhou, University, Zhengzhou China Environment, 450001, and Zhengzhou, University, Ecology Zhengzhou of Engineering, School and Science Conservancy Water of School tt e aoaoyo niomna rtraadRs seset hns eerhAaeyof Academy Research Chinese Assessment, Risk and Criteria Environmental of Laboratory Key State h lblcntuto fwtrpoet a e oacertedo ie n aereservoir lake and river of trend clear a to led has projects water of construction global The : 1 1 igDou Ming , igDou ming , , * 1,2 1 igDuEmi address: E-mail Dou Ming u Xia Rui , u Xia Rui , 2 3,* uquLi Guiqiu , uquLi Guiqiu , 1,2 1 1 n ih Shen Lisha and , dou ih Shen Lisha , [email protected] 1,2 1 Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. ae nti,ti td dpstebn ai oe swl steB erlntokmdl n ae a takes and model, network neural BP the as well as model ratio band the adopts network study neural this 2015; inversion. as this, parameter al., such on quality et methods Based water Park optimization establishing into al., (e.g., relational by algorithms et researchers nonlinear generalizability genetic Telesca and introducing some and accuracy 2013; and reason, generalizability methods inversion model this al., and the For ratio improved et accuracy waveband continuously Tebbs inversion 2018). have a in 2009; al., 2015), shortcomings al., et al., et (Tao certain et Harvey have fault-tolerance Hu which poor 2000; mostly have 2019), are al., and al., data et et sensing remote (Shu Cannizzaro from models 2018; concentrations measured parameter semi-empirical quality the studies. water and characteristics. further invert interpolate empirical for to optical to used support often provides complex used which models be with data, The sensing can waters remote concentration the inland than chlorophyll-a to real-time for according of concentration and chlorophyll-a suitable model periodic, certain inversion is dynamic, estimation showing the which more indirect 1992), Furthermore, the is monitoring, Therefore, al., data 1994(b)), in 2020). manual reflectivity al., et change al., satellite significant et traditional et (Gitelson a from (Han (Jiang to nm) concentration nm) body leads water chlorophyll-a chlorophyll-a 665 700 a of of (near valleys (near of concentration band characteristics low absorption band red spectral or obvious reflectance high the infrared are the The and the there water. 1994(a)) better in in and al., spectra can et 2019), peaks characteristic concentration (Han (Brigitte, reflection nm) chlorophyll-a bodies obvious 442 of water (near and distribution in band 2020). the blue bloom al., the algae, algal et in in of (Liu chlorophyll degree climate of the on support reflect component activities human provide main of can the atmospheric impact and As including the images, data, and multi-spectral (Naghdi observation climate instrument Earth and global sensing long-term understanding resource resolution, remote provides for monitoring, multi-spatial space which environmental coverage, spectroradiometer large NASA, of global a by fields imaging information, is developed the MODIS 2020) resolution in fields. al., used other et moderate the widely and strengthen are planning, technology, protection. data urban to environmental communication investigation, satellite meaningful water sensing more for of remote is bodies improvement (MODIS) water it mobile so the and blooms, rivers water With large to in hydrological prone blooms their more algal reservoirs, the only of and and abroad, occur lakes and monitoring complex rivers with home Compared more large at in are outbreaks transformed. projects outbreaks conservancy has bloom conditions and water rivers body and Algal 2019), of large water proliferate of al., body. operation situation is to et water and hydrological (Huo construction the problem algae the ponds polluting blue-green this with or thereby However, induces causing reservoirs, surface, rarely. lakes, factor body water inland key water the in on A a occur film usually in cases. algae drinking eutrophication blue-green serious also of a but in level form survival, health high organism and aquatic A and life frequently eutrophication. quality human occurring water 2012), and only al., safety not et affecting water (Yang worldwide, problem environmental bodies and water ecological in prominent a are blooms Algal INTRODUCTION 1. to used we characteristics change. concentration evolution concentration chlorophyll-a chlorophyll-a River spatiotemporal the Hanjiang of on the factors analysis Keywords: of environmental inversion various reaches lower of the influence algorithm and of the the middle Subsequently, results determine the inversion. the in chlorophyll-a settings and River algorithm 2011 BP optimal Hanjiang and inversion to the the model 2000 determine ratio of for to band reaches compared the lower model were establish and to errors middle method model the error of for and types concentration trial two chlorophyll-a the model, measured of network communication and use neural sensing the methods remote current Through statistical the and analysis. on the correlation data, based considers China, study sensing This in remote River blooms. MODIS Hanjiang water technology, the of of method control reaches This and lower warning effectively. and early middle collected the for be significance can guiding data important observation has chlorophyll-a continuous monitoring, data sensing OI;clrpyla la los ajagRiver Hanjiang blooms; algal chlorophyll-a; MODIS; 2 Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. ie orva h ehns fhdooia atr ffcigwtrbom nteHnin ie n to and River Hanjiang the in Hanjiang rivers. blooms the eutrophic water of in affecting reaches conditions lower flow factors in rate bloom and hydrological as flow blooms water middle such of (including water the the (Xie mechanism factors factors study in on al. hydrological hydrological the concentration of reveal et Project in chlorophyll-a effects Transfer to in Xie reflected the Water changes River mainly and analyze the South-North to is the Dou on important the River aggravate velocity) to is Hanjiang of to and According it the impact tended Therefore, 2017). velocity. of the has al., and reaches 2005), rate and et lower al., River, Zhou and et Hanjiang middle 2018; Xie the the al., hydro- 2004; of et the al., reaches (Kuo transformed lower et blooms has and water Project Transfer middle of Water the phenomenon South-North in the from situation water logical of transfer the Meanwhile, here] change 1. the Table studying [Insert by River River. meaningful Hanjiang here] Hanjiang lower is 2. lower and it Fig. and middle so [Insert 2009; middle concentration, the Corynebacterium. al., the chlorophyll-a in genus et in in the blooms concentration (Zheng increase to water chlorophyll-a an study belongs of occasional in by different bloom phenomenon with accompanied water the a is 2012), Hanjiang reveal to the algae al., to according of of et However, growth species (Liang Previous dominant rapid species. 2000). the Chlorella The dominant 2011), al., be the al., et to as et the (Kuang Yin algae species River and Chen green dominant Hanjiang spring, 2019; the of the al., early in cases considered et dominating and mostly (Xin ( blooms winter have studies statistics diatom various late incomplete studies with of to in 2000, 2000) According March) al., after month. et whichincreased to one Lu during (February to 2007; blooms, month al., in period a water ( et resulting dry half odor of 2019), pungent from the outbreaks al., and varies during repeated and fishy duration et a and nitrogen mostly Cheng emits body, as 2016; occur and water such brown al., Hanjiang River the nutrients, appears et the in that body (Stephen of eutrophication water is standard reaches the of reason the lower Project degree main exceed Route and high The body, Middle middle a water 1990s. the the for the the of source in since quality water phosphorus deteriorated water important gradually the an has Transfer, and River Water River Yangtze South-to-North the the of of tributary industrial largest automobile the and industrial As new a here] as developed, 1. well 2014). is Fig. as al., [Insert economy China et in regional (Kuman base Province The 4.6 production Hubei is cities. grain in Province other important base Hubei and an of City, is area Wuhan it drainage and Xiaogan, total Jingmen, the and Xiangyang, km, Shiyan, 652 is River Hanjiang ihattllnt f17 madadang rao 5 9 15. of area drainage a and km 1577 of length total a (106 with River Hanjiang The area Study 2.1 METHODS AND MATERIALS 2. concentration 2011 chlorophyll-a to of 2000 characteristics from spatial River analyzed. and were Hanjiang temporal the body the inversion water of and errors. the optimal reaches model, model lower in It the comparing this and by determines using River area. middle ratio and inverted Hanjiang study the band the were method, the of in the reaches empirical concentrations as establishes lower chlorophyll-a an and China data, middle The through in sensing the River remote in model chlorophyll-a network Hanjiang satellite for MODIS the algorithm neural and of BP data reaches and quality lower model water and measured middle the the uses in section river typical ° 12’E–114 ° 4E 30 14’E, ° 08’N–34 al 1 Table 3 ° 1N satiuayo h agz ie nChina, in River Yangtze the of tributary a is 11’N) ,tewtrbomfeunyi h ajagRiver Hanjiang the in frequency bloom water the ), × 0 km 104 i.2 Fig. 2 ( i.1 Fig. .Wtrbom nteHanjiang the in blooms Water ). × .Temi temo the of stream main The ). 0 km 104 2 oigthrough flowing , Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. n h ae ult aao h culmaue ae oiswr orltdwt h synchronized the high with with 2008). bands (Anatoly, correlated of model combination were a the construct bodies or to band water fitted the measured and of out data actual reflectance screened the reflectance, the were band and correlation of the data, extract data reflectance to sensing processed quality and remote corrected water were 2007). et network the data al., neural (Le currently MODIS et and downloaded and is basis the (Chen ratio, that first this feasible band study, method on this and single-band, inversion In simple mainly images chlorophyll-a relatively are sensing a are models remote is construction processes of method fitted can whose empirical characteristics the and models, and The spectral bodies often, 2003). the water more al., of with used et characteristics link Darecki spectral a 2010; the establish al., on to effect used significant be a method has inversion concentration concentration Chlorophyll-a chlorophyll-a and data MODIS 2.4 reflectivity. near-infrared (3): and follows reflectivity as light accurate is more green NDWI (NDVI) and is the index atmosphere, reflectivity calculating the vegetation The by for difference affected formula less normalized The extraction influence, traditional extraction. for atmospheric water the adopted to for was sensitive with less 2016) Compared is al., areas. NDWI et method, water Choung other 1996; studied (Gao, and the (NDWI) vapor, in index water water ENVI difference illumination, in normalized module of The necessary correction images. influence atmospheric is the FLAASH the it correct The 2004), eliminate objects. to 2006). al., to ground used al., et of was image et Zheng spectrum the reflectivity Carol 2021; the (Feng, 2009; in on accurately al., atmosphere factors more et the objects (Lv correct calibration, ground (2) radiometric of to and called reflectance (1) step the Eqns. a obtain to To reflectance, according and ENVI brightness in radiance calculated absolute is value to which DN chlorophyll-a converted the the studies, be whereas follow-up For to value, reflectivity. and Number)DN needs brightness (Digital radiation the absolute saved used inversion data concentration MODIS the correction, orthorectifica- ENVI geometric for After The used error. was images. distortion 2002) sensing geometric (Guo, remote Workflow reduce of Orthorectification to tion RPC Solu- performed Information tool first Visual orthorectification was Exelis automatic (from correction software Geometric ENVI5.3 Company). using tions preprocessed total were images the remote-sensing of The 85.33% preprocessing for data accounting images, MODIS data sensing quality 2.3 water remote measured valid the 64 (NASA). resolution with rejection and spatial synchronized after a selected, with images filtered were nm were sensing 2013 2130 images, remote to to MODIS 469 2009 from (75) bands from water Several spectral Sciences). flow, to m. seven Environmental 2000 500 the has of from satellite of includes Academy sections, sensing Research which Zongguan remote Chinese and data, MODIS the Xiantao The hydrological from the the are in data monitored is above data part month), (the temperature cross-section a second water 2011 Zongguan times and The the three rate, at 2009). chlorophyll-a flow monitored monitored to level, including concentrations and (TP) 2003 data, in 2013, phosphorus from quality to total (monitored water (monitored and 2009 Zongguan (TN) the from and nitrogen October is total Qinguankou, and and one Baihezui, September, parts: April, cross-sections, two March, three include February, along study the monitored in concentrations data acquisition measured data The MODIS and data Actual 2.2 4 Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. ntpclyaswr odce ae nteivrinrsls h pcfi eut n nlssaea follows. as are analyses and results in specific variation The results. interannual inversion concentration, the on chlorophyll-a values based concentration in conducted chlorophyll-a were variation in years variation typical temporal interannual in performed, and and the was area, River 2.4, spatial distribution Hanjiang Section concentration the of chlorophyll-a in of proposed reaches analysis lower concentration an and chlorophyll-a middle and and the data in concentration MODIS chlorophyll-a of of inversion method inversion the on Based ANALYSIS AND RESULTS (4), are 3. formulas The value. RMSE. measured accuracy error the model was root-mean-square evaluates value and study predicted RE, this The error accurate, (6). relative more and model R2, (5), inverse coefficient the decision make the and by precision model the test To method validation Model 2.5 the of thresholds and weights here] the of Fig.3. adjust correlation [Insert combination to The high used model. network. was the the neural chlorophyll-a generate ( of BP of to the factors combination concentration network of input and the concentration reflectivity as study, chlorophyll-a band and used this of layer, be neural In input network can BP model. neural concentration network the BP chlorophyll-a neural characteristics, in with BP its diagram reflectance the wave schematic to chlorophyll- of the According and reflectance values in 2021). between output shown relationships al., nonlinear accurately as et complex concentration, of be (Feng chlorophyll-a problem a cannot the model affecting solve factors concentration linear better many chlorophyll-a can simple the network and and a function column reflectance rational using water between any reflected the approximate relationship in can properties the layer deviation optical concentration, complex output with the network linear of a a Because plus that layer proven 2017). implicit been al., has suitable S-shaped has et which are (Zhu one It 2000), which least relationships. al., mapping, at the nonlinear et nonlinear with and intricate (Le and networks, various neural self-organization, propagation simulating artificial self-learning, error used for self-adaptation, backward widely of and more functions the propagation of the signal one forward currently of is characteristics method network neural BP model established. The model was combination network model band neural function seven the a and BP between B4)), and 2.4.2 analysis + performed, B3 correlation was + chlorophyll-a a (B1/(B2 bands of two Then, bands concentration of four (B1)). measured subtraction for (ln for the modes modes logarithm and 10 20 B3)), natural (B1/B2), statistical combination (B1/(B2 MODIS for bands band bands the two 73 pre-processed modes three then of obtain for and division the to modes extracted, the band from 15 for was each (B1-B2), study, combine modes B7 to 21 to this used were B1 was surface There In from Company) water patterns. analysis, BIM bands bands. smooth correlation (form seven wave SPSS the of the software combining of reflectance analysis to influence by the According the images, the reduced 2009). to sensing and relevant be waves remote al., most electromagnetic can et is on microwaves (Le that atmosphere combination on modeling the the inversion of selects the interference and the perform bands to existing the data combines measured model ratio band The model ratio Band 2.4.1 5 i.3 Fig. where , X 1 X , 2 . . . , X 1 X , X n 2 . . . , r h nu and input the are X , n o the for ) Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. 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Table s0998 n the and 0.98918, is Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. itiue nabn rmZogin iyt hyn ony nFbur 4 08 h niemiddle Yuekou entire near the waters some 2008, body and 14, City, water February Zhongxiang downstream of On reaches the lower County. the in Shayang River, chlorophyll-a to Hanjiang City the of of Zhongxiang concentration reaches 10 from lower the The and band 3rd, high. a relatively the in was On distributed City Zhongxiang high. of not area was area study 7 of vicinity Fig. the to migrated here] bloom blocks Fig6. water of in [Insert the upstream distributed and and was improved Town it Yuekou phenomenon and of bloom County. Town, downstream was water Shayang Yuekou decreased chlorophyll-a the of concentration of and reaches Chlorophyll-a City, concentration upper Xiantao The bank. the west shore. and the the area County along from outbreak spreading Shayang channel gradually bloom of river and water reaches the Xiantao, the lower to of 4, Yuekou center March Shayang, the and to were to 24 Zhongxiang rest February from the with while spreading chlorophyll-a significantly, distribution, Compared with band-like increased riverbanks. a areas showing County, the both Shayang along and near scattered increase, and City in to Xiantao concentration continued of chlorophyll-a reaches River overall upper Hanjiang the the 2000, 4, of March reaches concentrations On lower County. and Shayang middle of the reaches the lower area in the chlorophyll-a the and was of City River in concentration Yuekou chlorophyll-a the the high, of of relatively section concentration was monitoring River the Hanjiang near the area of reaches lower and middle trend From the and of 25–35 2008 12 10–25 was of March was 0–10 was 14 chlorophyll-a chlorophyll-a and was chlorophyll-a March of of chlorophyll-a 4, and concentration of March concentration 2008 7, concentration the 24, and the March the When February 2000 14, When in on February analyzed. better. was period 3, MODIS was February area eruption of bloom 17, bloom data to the January the image February in 2, during late sensing January River from remote Hanjiang and lasted the concentration2000 the chlorophyll-a 2008 of from the reaches and study, inverted lower this 2000 was In and in respectively. middle March, blooms early the water to in January of late eruption from and the mid-March that shows investigation concentra- The chlorophyll-a annual typical the of from tion analysis arising variation problems nonlinear Spatiotemporal simulating 3.3 confirmed for study suitable the Additionally, more the bodies. simulation water of model. was the in network reaches model ratio and properties lower neural band network 21.4%, optical and BP the neural complex is middle the than BP the RE using error the in average less accurate concentrations that the predicted more chlorophyll-a 8%, model was of network is River inversion neural minimum Hanjiang the BP the that the 29.1%, indicating Therefore, is model, poor. 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Data may be preliminary. httecnetaino hoohl- a ih urpiainwshg,wtrqaiywspo,and chlorophyll-a poor, of was ratio quality area water The the high, occurred. 2008, already was and had eutrophication 2007, lower or high, easily and 2006, occurred was middle 2000, outbreaks chlorophyll-a the In bloom in of water period. in quality concentration this water line the during the trend that improved that The gradually chlorophyll-a indicating River of overall, low. concentrations Hanjiang trend relatively the downward was slight of concentration quality outbreaks chlorophyll-a reaches a water was with bloom the there ratio of time, respectively, but area this 75.8%, risk at and the the low 64.3%, that and remained 82.4%, shows waters 78.3%, good, most for generally in accounting concentration was 2009, chlorophyll-a and the 2005, that 2004, indicating 2001, in from high in seen relatively variation be the can study 2011 As To to 2000 in period, 2008). from in shown bloom period al., results the As bloom et the during the March). River Zhu during to Hanjiang distribution 2012; February the concentration Hanjiang (from chlorophyll-a of al., the the reaches of et lower reverses reaches (Yang section and lower this year middle and the each middle in the March concentration in chlorophyll-a and occur February blooms in water that River found investigation preliminary A distribution concentration chlorophyll-a in variation area interannual of Analysis 3.4 here] Fig7. [Insert concentration County. chlorophyll-a Shayang and trend. of City dissipating concentration area Zhongxiang chlorophyll-a was the from with area appeared 2008, areas study blooms 14, water the March and in denser, On chlorophyll-a were of was County concentration Shayang concentration chlorophyll-a and the the 2008, where areas 7, The March On likely. 35 are are blooms concentrations serious If higher. were hoohl- ocnrtosi aho h wleyas h hoohl- ocnrtosi 00 06 and 2006, 2000, in concentrations chlorophyll-a the years, twelve the of each con- chlorophyll-a in highest concentrations the chlorophyll-a 2011, 2.774 to was 2000 from concentration years twelve the 41.837 was during centration results, statistical the to According here] 6. results. Table inversion [Insert the on based here] variation Fig10. the interannual [Insert inverts the in section analyzes shown this and are 2011, results values, and The and concentration Xiantao, Yuekou, 2000 Shayang, chlorophyll-a (Huangzhuang, between in sections Zongguan) monitoring variation five of interannual values concentration the chlorophyll-a reflect value concentration better chlorophyll-a To of analysis variation Interannual 3.5 here] Fig9. [Insert period. bloom-prone with the here] compared during 2008, Fig8. 2011 to [Insert to 2006 2000 from high from but stable stable remained remained chlorophyll-a ratio and of 2005, ratio to area 2001 the from low and stable remained concentrations chlorophyll-a had Town μ /,adwsmr vnydsrbtdtruhu h td ra otycnetae nteshore. the on concentrated mostly area, study the throughout distributed evenly more was and g/L, i.9 Fig. . μ i.8 Fig. / nFbur 08a h hyn oioigscin n h oetchlorophyll-a lowest the and section, monitoring Shayang the at 2008 February in g/L μ i.10 Fig. / nOtbr20 tteHaghagmntrn eto.Fo h average the From section. monitoring Huangzhuang the at 2001 October in g/L < and > 10 n h ttsia eut r rsne in presented are results statistical the and , 25 i.9 Fig. > μ /.Acrigt h rn ie h hoohl- ocnrto area concentration chlorophyll-a the line, trend the to According g/L. μ / ee5.% 02,4.% n 01% epciey indicating respectively, 50.10%, and 49.3%, 70.2%, 57.9%, were g/L 35 > < i.8 Fig. μ 35 10 /,i niae httewtrbd shgl urpi,and eutrophic, highly is body water the that indicates it g/L, h ra ihclrpylaconcentrations chlorophyll-a with areas the , μ μ /.Na hyn ony h hoohl- concentrations chlorophyll-a the County, Shayang Near g/L. / lodcesd n h ae lo hwda overall an showed bloom water the and decreased, also g/L h hoohl- ocnrto itiuinacut for accounts distribution concentration chlorophyll-a the , 8 > 25 μ / erteuprrahso hnxagCity Zhongxiang of reaches upper the near g/L < < 10 10 μ / utae ewe 00ad2011, and 2000 between fluctuated g/L μ / ea ogaulyices,the increase, gradually to began g/L al 6 Table . < 10 i.9(1) 9 Fig. > μ / were g/L 25 μ g/L > Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. ac 08wr .6 /,016ms .6 /,020ms epciey n h vrg o aewas rate and flow 55.43% 2006, average 2003, was the 2000, and rate respectively, in flow sections m/s, average Zongguan 0.230 the the m/s, and m of 0.267 lower 23.71 rates m/s, was m flow 0.166 2008 The 1.67 m/s, and 2005. was 0.168 2003, and which the were 2000, 2004, m/s, to 2008 in 2001, March 474.3 According of station in was use hydrometric 2001). that the full rate al., than at make lower flow et of can average (Tang and level diatoms concentration the division River water chlorophyll-a bloom and cell average season Hanjiang time, in dry the facilitating the this increase River data, thereby in At Hanjiang an measured products, transparency. the outbreaks causing photosynthetic is good Bloom and accumulate which has proliferation year, 2004). and than and each lower photosynthesis al., low March significantly for et is to are sunlight February (Wang level River of level, water years spring Hanjiang the water previous early the when the in the of in occur, reaches period occur lower blooms same generally and when the middle velocity; of the and those of discharge, velocity level, and water discharge, concentration include chlorophyll-a conditions on Hydrological conditions hydrological the of Effect 2008, 4.2 March to 2000 February from example, 2 approximately an was 9 as at an 11.5 Xiantao 2010, chlorophyll-a, were and of Taking temperatures concentration higher. water the measured was therefore, average 2005); algae, (Zheng, of algae When indicator bloom 2005). al., diatomaceous 10 et of was (Xu range accumulation blooms temperature diatom optimal are the River Hanjiang but the in was blooms chlorophyll-a temperature water the of most that concentration show of studies on Most effects temperature the water analyzing of by Effect discussed 4.1 are In blooms relationships. algal ecological on these concentration. blooms factors environment, chlorophyll-a conditions affect algal environmental ecological on nutrient that Meanwhile, of the factors conditions the effects environmental and grow. meteorological on organisms the algae and aquatic only the section, hydrological other which not this 2017). and in in depends algae changes environment al., between as that ecological relationship et such problem the the (Le on ecological on environments depend also an formed also but ecological algae is growth, of and blooms algal aggregation algal conditions, of and of hydrological reproduction excessive outbreak climate, of The nutrition, phenomenon the certain to under refer outbreaks bloom Algal DISCUSSION 4. indicating than higher respectively, spring. was 2011, in sections concentrated river to predominantly Xiantao 2000 was and Shayang from and the sections, times in river two bloom other anal- water and in the of four, that on occurrence average two, of Based monthly probability five, years. the the three, remaining that section, the were monitoring in each sections frequently at monitoring less values and values concentration statistical period, 2008, concentration chlorophyll-a the this in chlorophyll-a interannual Among during times the increased three deteriorated. of River and quality ysis 2006, Hanjiang water in the the times and of bloom four 30 water reaches increased, exceeding lower with body concentrations indi- years and chlorophyll-a water 2004, data, the middle the and showing the of 2001 data eutrophication in and between historical the 2006, algae increased the 2000, the gradually with in that years concentration consistent higher chlorophyll-a cating the is were the showing which concentrations Furthermore, data chlorophyll-a years, historical outbreaks. the other the years, in chlorophyll-a twelve average with than the the consistent From 2008 of is increased. each which gradually concentrations in years, chlorophyll-a concentrations the other and in blooms, those water with than higher were 2008 ° n 10 and C ° > ihr ae eprtr soeo h atr ffcigclrpylaconcentration. chlorophyll-a affecting factors the of one is temperature Water higher. C 9 ° ° ,tegot fdaosbcm cie n rwwl ewe 15 between well grew and active, became diatoms of growth the C, ,rsetvl.I otat h ae eprtr ntebomeuto period eruption bloom the in temperature water the contrast, In respectively. C, > 30 μ / tHaghag hyn,Yeo,Xato n Zongguan and Xiantao, Yuekou, Shayang, Huangzhuang, at g/L ° o17 to C μ / curdfute ie,icuigtretmsi 2000, in times three including times, fourteen occurred g/L ° n 12 and C ° ,wihwsbnfiilt h eldvso n pigment and division cell the to beneficial was which C, 9 ° ,rsetvl,btn lo curdi 2009 in occurred bloom no but respectively, C, ° n 35 and C ° C, Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. n hshrs eeetbihda h anfcoslaigt nices nclrpylaconcentration chlorophyll-a in River. increase Hanjiang an the to nitrogen of leading including reaches nutrients, lower factors of and main ratio middle was the and the waters as the concentration in established most and analyzing were hydrolog- rate, By in and flow phosphorus, chlorophyll-a temperature poor. level, and water of water generally the chlorophyll-a, including concentration was of conditions, quality concentration the ical the water and concentration on and factors chlorophyll-a 2008, environmental high, with of and relatively influence area was 2007, The eutrophication relatively 2006, was high, waters good. 2000, relatively most relatively in in was concentration chlorophyll-a high chlorophyll-a of quality Hanjiang concentration with relatively water the the area the 2009, of the and of and reaches 2011, 2005, results the low, lower to 2004, calculation 2000 invert and 2001, the in from middle to to high period the relatively According used of bloom in process. reaches the distribution was outbreak lower during concentration bloom and River model chlorophyll-a the middle network of analyze typical the percentage to The neural in 2000–2011. used the outbreaks in was BP bloom River River the Hanjiang of Hanjiang the map the analysis, of distribution reaches correlation concentration lower chlorophyll-a and the annual middle of the in results concentration chlorophyll-a the on Based CONCLUSIONS 5. of concentrations nutrient variation phosphorus high here] the and affecting Fig.12. that factors nitrogen [Insert thus main shown in the column, variation also are nutrients water the have phosphorus concentration. the Therefore, and chlorophyll-a 2015) water. nitrogen in in of al., the ratios ratio in et the nitrogen–phosphorus and diatoms Guenther uncoordinated concentrations of trend 2019; to growth growth lead al., the diatom may affecting studies et River the numerous phosphorus Hanjiang However, Jing concentrations, the or column. 2021; phosphorus in water nitrogen al., diatoms the and in of nitrogen et concentration proliferation in chlorophyll-a (Luo the the increase water of in increased the the needs which increase in with the improved, an content meet and by phosphorus could and bloom, accompanied bloom years nitrogen was water water all the values in the that concentration phosphorus shows during chlorophyll-a and This column the in nitrogen concentrations. in with increase of phosphorus shown and that the compared are nitrogen to is, were the results similar that section values in was the 2005, concentration this values concentration and chlorophyll-a chlorophyll-a except in concentration values, in the chlorophyll-a section phosphorus variation 2009, monitoring the in total to that Zongguan variation and 2003 the nitrogen large from total of the River measured performance of Hanjiang (Lin inverse the Because growth the of and 2021). from reaches reproduction al., lower phytoplankton et and for Liu required middle nutrients 2021; main al., the et are phosphorus concentration and chlorophyll-a Nitrogen on nutrient of Effect 4.3 here] 8. Table [Insert here] 7. velocity. Table and variation [Insert discharge, the level, Therefore, water lower. from as here] is such seen Fig.11. factors level be [Insert hydrological water can by and the affected As m/s, and is 28.02%. 0.289 concentration smaller was by chlorophyll-a March is diatom decreased in to discharge the section January of the Zongguan from area concentrations, section cross-sectional the chlorophyll-a Zongguan the of from the velocity calculated of average rate velocity flow the average the the and contrast, data In flow bloom. the to according m/s, 0.208 10 i.12 Fig. i.11 Fig. > < twsfound was It . 25 10 μ μ thigher at / was g/L / was g/L Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. 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(02), , Oceanologia 0) 21-23. (05), , 3,92-106. 135, , 01,76-85. 60(1), , ora fGoIfrainScience Geo-Information of Journal 114. , ora fIfae n ilmtrWaves Millimeter and Infrared of Journal cec fTeTtlEnvironment Total The of Science 51J,13 116. 113- 35(12J), , eerho niomna Sciences Environmental of Research 13 rvt Technology Private topei olto Research Pollution Atmospheric 10) 104-110. 11(01), , 5,141681. 751, . 1) 97-98. (12), , 0) 273-276. (04), , ora fGetLakes Great of Journal aueCommunica- Nature aueGeoscience Nature ora fSichuan of Journal 30) 28-31. 13(02), , 19,1637- 11(9), , Chongqing Remote , Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. lower-reaches-of-the-hanjiang-river-china evolution-of-chlorophyll-a-concentration-from-modis-data-inversion-in-the-middle-and- Table.docx River. Hanjiang Project of file Diversion Hosted quality Water water South–North the the of on study Influence projects network. The 406(1). (2008). neural J.F. mitigation (2017). Zhao, BP the Y.Z. L., and and Chen, X.,Zhang, image H.P., Ju, WFV Zhang, Y.P., H.Q., GF-1 Zhu, Hou, on based Y.H., Taihu Zhang, in Y.J., a Circumstantiae Chen, chlorophyll J.G., of inversion Li, Images. of L., Sensing Zhu, Remote for Y.F., Correction Zhu, Atmospheric of Methods on from information Review gene A sensing 18SrDNA Remote (2004). and Z.Y. morphology Zeng, River. of W., Hangjiang Analysis Zheng, in bloom (2009). diatom H.R. related Zhuang, specie X.H., causative Wu, the L.R., Song, L.L., Zheng, bloom ditom (2005). L.L. on Zheng, assessment River:Spatio- Hangjiang impact The Systematic in bloom hantzschii forces. 451-458. 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M.A. , 706. , vial at available 70) 130-137. 37(01), , h hsooia n clgclrsac bu h oiatseisi agin River Hangjiang in species dominant the about research ecological and physiological The 0) 66-70. (04), , https://authorea.com/users/415405/articles/523286-spatiotemporal- ae Research Water eore n niomn nteYnteBasin Yangtze the in Environment and Resources hieeJunlo elhlbrtr technology laboratory Health of Journal Cheinese ot-oNrhWtrTase n ae cec and Science Water and Transfer Water South-to-North 14 ae Research Water eore n niomn nteYnteBasin Yangtze the in Environment and Resources CAhdoilgc sinca hydrobiologica ACTA 68,2525-2534. 46(8), , cec fteTtlEnvironment Total the of Science 46(8). , Elsevier ora fntrlresources natural of Journal 5,584-595. 553, , cec fteTotal the of Science 10) 562-565. 31(03), , caScientiae Acta 20(04), , (11), , , , Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. 15 Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. 16 Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. 17 Posted on Authorea 24 May 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.162184327.74824330/v1 — This a preprint and has not been peer reviewed. 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