Curuai Floodplain Research Articles

Surface water quality in Amazonian Floodplain Lakes, data set of the Lago Grande de Curuai Floodplain Lake, Pará‐Brazil

AbstractBetween 2013 and 2017, we carried out nine field missions in the Lago Grande de Curuai floodplain, located in Pará state – North of Brazil – to collect samples for monitoring surface water quality. This site separated from the river by a narrow bank is composed of a network of channels and shallow lakes, a morphology shared by the floodplains of the lower Amazon. A multiparameter probe was used in situ to measure electrical conductivity, temperature, pH, dissolved oxygen, chlorophyll, turbidity, depth and a Secchi disk to estimate transparency. Water grab samples were analysed for suspended material, alkalinity, humic acid, phosphorus, nitrogen, carbon and chlorophyll. Sampling stations were distributed over the seven larger lakes in the floodplain and sampled at different periods of the hydrological cycle. The number of samples varied with the floodplain water level, with a minimum of 25 samples for each field visit. This data set is a collection of water quality data to assist in the limnological or biogeochemical studies of surface waters in Amazonian floodplain lakes, and the product of successive French‐Brazilian projects: (1) the Clim‐FABIAM ‘Climate changes and Floodplain lake biodiversity in the Amazon Basin: how to cope and help the ecological and economic sustainability’ funded by the French Foundation for biodiversity research (FRB), (2) the project Bloom‐ALERT –‘Environmental sensitivity and population health vulnerability to cyanobacteria in the Amazon: towards shared indicators’ funded by the French‐Brazilian research program GUYAMAZON 2014, and the project (3) ‘Ecossistemas das várzeas e biodiversidade: Impactos das mudanças ambientais e climáticas considerando cenários de desenvolvimento sustentáveis’ (Project number 490634/2013‐3) funded by the Brazilian National scientific Research Council CNPq.

Mapping floodplain bathymetry in the middle-lower Amazon River using inundation frequency and field control

This paper presents the geomorphic classification and bathymetry (at 100 m) of 12 major floodplains along a 900 km reach of the middle-lower Amazon River (Manaus – Monte Alegre; total floodplain area of 5164 km2), based on the inundation frequency (IF) derived from 36 yr of Landsat data. Using a mathematical relationship between IF and surveyed depth at the Curuai floodplain in June 2004, this IF-depth model is applied across floodplains of the middle-lower Amazon to estimate bathymetry. The applicability of the model is justified by similar grain size distribution (dominantly silt and clay) of sediment in the surface water of floodplain lakes (the main materials constructing the floodplains), as well as a hydrogeomorphic classification of this reach: seven floodplains lying on the alluvial plain dominated by the Amazon-flood pulse (Type I), three floodplains incised in valleys dominated by sediment-poor upland tributaries (Type II) and two floodplains of mixed types. This classification is used to distinguish the sensitivity of floodplains to the IF-depth model, where Type I floodplains of higher sensitivity provide a more accurate depth estimation. The bathymetry for both types is validated with field survey data across eight floodplains (covering over 200 km survey distance) collected in June – July 2016 and adjusted by the difference between mean June 2004 and June/July 2016 water level. Correlation coefficients of 0.87 (Type I) and 0.94 (Type II) indicate a strong relationship between estimated and measured depth for both floodplain types, while the root mean square error of 1.03 m (Type I) and 1.02 m (Type II) suggest that bathymetry is estimated to around 1 m error, equivalent to 10.9% and 10.8% of maximum water level variability, respectively. We offer the first field-validated and complete bathymetry map for the middle-lower Amazon River with accuracy that can be used to evaluate the role of floodplains in influencing biodiversity, sedimentation, flood control and biogeochemical cycling.

Inferring floodplain bathymetry using inundation frequency

This study proposes a new method to retrieve the bathymetry of turbid-water floodplains from the inundation frequency (IF) data derived from over 32 years of composite optical remote sensing data. The new method was tested and validated over the Curuai floodplain in the lower Amazon River, where the entire bathymetry was surveyed in 2004, and water level gauge data has been available since 1960. The depth was estimated based on the relationship derived from IF and surveyed depth data, and the results were compared to those retrieved from bare-Earth DEM. We further assessed the sensitivity of the approach by analyzing the deepest part of the lake (i.e., permanent water body ~ 8m) with high IF, as well as the effect of gradual sedimentation in the lake over time. The results showed that the model is highly accurate and sensitive to IF changes even in the permanent water body areas, suggesting that this model can be used in other seasonal lakes worldwide with turbid-waters, where large-scale bathymetry surveys are not feasible due to high operation costs.

Biological index based on epiphytic diatom assemblages is more restrictive than the physicochemical index in water assessment on an Amazon floodplain, Brazil

Canadian Water Quality Index (CWQI) provides protection for freshwater life promoting healthy ecosystems and safeguarding human health. Biological Diatom Index (BDI) was developed to indicate the ecological status and water quality of freshwater systems. This paper evaluates the relations between the two different indices. During rising and falling, water samples were taken in the Curuai Floodplain, Brazil. CWQI was calculated using 14 physicochemical parameters and 1 microbiological parameter. The limits were established according to freshwater quality conditions and standards based on water use classes 1 and 2 determined in CONAMA 357 legislation and British Columbia. Canadian Water Quality Index categorization ranged from "marginal" to "excellent," most sampling units were "good" (71%), followed by "fair" (12%) and "excellent" (12%) water quality. Total phosphorus (38 times), chlorophyll a (20), dissolved oxygen (10), and total organic carbon (10) were the parameters that presented the most non-compliance values. Encyonema silesiacum (14%), Gomphonema parvulum (13%), and Navicula cryptotenella (12%) were the main taxa in the rising period, while G. lagenula, E. silesiacum, and Fragilaria capucina were the main taxa during the falling period. BDI ranges from I to V water quality classes. We observed "poor" to "very good" ecological status, with most sampling units "moderate" (52%) and "good" (29%). Water quality for class 2 was better than water quality for class 1, as the limits of the parameters evaluated were more restrictive in class 1 than in class 2 and the predominant uses of water require a higher degree of water purity. The biological index based on diatoms was the most restrictive index whose water classes and categorizations have shown an ecological status that could threaten the protection of aquatic communities on the Curuai floodplain. We suggest the combined use of both indices-physicochemical and biological for water quality assessment in this type of environment.

Role of the floodplain lakes in the methylmercury distribution and exchanges with the Amazon River, Brazil

Seasonal variability of dissolved and particulate methylmercury (F-MeHg, P-MeHg) concentrations was studied in the waters of the Amazon River and its associated Curuai floodplain during hydrological year 2005–2006, to understand the MeHg exchanges between these aquatic systems. In the oxic white water lakes, with neutral pH, high F-MeHg and P-MeHg concentrations were measured during the rising water stage (0.70±0.37pmol/L, n=26) and flood peak (14.19±9.32pmol/g, n=7) respectively, when the Amazon River water discharge into the lakes was at its maximum. The lowest mean values were reported during the dry season (0.18±0.07pmol/L F-MeHg, n=10 and 1.35±1.24pmol/g P-MeHg, n=8), when water and suspended sediments were outflowing from the lakes into the River. In these lakes, the MeHg concentrations were associated to the aluminium and organic carbon/nitrogen changes. In the black water lakes, with acidic pH and reducing conditions, elevated MeHg concentrations were recorded (0.58±0.32pmol/L F-MeHg, n=16 and 19.82±15.13pmol/g P-MeHg, n=6), and correlated with the organic carbon and manganese concentrations. Elevated values of MeHg partition coefficient (4.87<Kd<5.08log (L/kg) indicate that MeHg is mainly transported associated with the particulate phase. The P-MeHg enrichment detected in all lakes suggests autochthonous MeHg inputs from the sediments into the water column. The MeHg mass balance showed that the Curuai floodplain is not the source of P-MeHg for the Amazon River.

Dual-season and full-polarimetric C band SAR assessment for vegetation mapping in the Amazon várzea wetlands

Abstract This study answered the following questions: 1) Is polarimetric C-band SAR (PolSAR) more efficient than dual-polarization (dual-pol) C-band SAR for mapping varzea floodplain vegetation types, when using images of a single hydrological period? 2) Are single-season C-band PolSAR images more accurate for mapping varzea vegetation types than dual-season dual-pol C-band SAR images? 3) What are the most efficient polarimetric descriptors for mapping varzea vegetation types? We applied the Random Forests algorithm to classify dual-pol SAR images and polarimetric descriptors derived from two full-polarimetric Radarsat-2 C-band images acquired during the low and high water seasons of Lago Grande de Curuai floodplain, lower Amazon, Brazil. We used the Kappa index of agreement (κ), Allocation Disagreement (AD) and Quantity Disagreement (QD), and Producer's and User's accuracy measurements to assess the classification results. Our results showed that single-season full-polarimetric C-band data can yield more accurate classifications than single-season dual-pol C-band SAR imagery and similar accuracies to dual-season dual-pol C-band SAR classifications. Still, dual-season PolSAR achieved the highest accuracies, showing that seasonality is paramount for obtaining high accuracies in wetland land cover classification, regardless of SAR image type. On average, single-season classifications of low-water periods were less accurate than high-water classifications, likely due to plant phenology and flooding conditions. Classifications using model-based polarimetric decompositions (such as Freeman–Durden, Yamaguchi and van Zyl) produced the highest accuracies (κ greater than 0.8; AD ranging from 7.5% to 2.5%; QD ranging from 15% to 12%), while eigenvector-based decompositions such as Touzi and Cloude–Pottier had the worst accuracies (κ ranging from 0.5 to 0.7; AD greater than 10%; QD smaller than 10%). Vegetation types with dense canopies (Shrubs, Floodable Forests and Emergent Macrophytes), whose classification is challenging using C-band, were accurately classified using dual-season full-polarimetric SAR data, with Producer's and User's accuracies between 80% and 90%. We conclude that full polarimetric C-band imagery can yield very accurate classifications of varzea vegetation (κ ~ 0.8, AD ~ 3% and QD ~ 10%) and can be used as an operational tool for forested wetland mapping.

Holocene land cover dynamics in the Curuai Floodplain inferred from lacustrine biomarkers

This study on Curuai Floodplain (Central Amazonia) sediments (last 5600calyr BP) focused in Rock‐Eval [RE; hydrogen (HI) and oxygen (OI) indices, Tmax, S2 curve and TpS2], organic petrography and molecular biomarkers [n-alkanes, hopanes, pentacyclic triterpene methyl ethers (PTMEs) and derivatives of pentacyclic triterpenes such as des-A-lupane and aromatic derivatives] analyses. Between 5600 and 5100calyr BP, the environment was waterlogged and dominated by emersed plants (Paq 0.27–0.38). The influence of the Amazon River was low. Terrestrial vs aquatic ratio (T/A, ~0.8), CPI values (3–4) and high contents of PTME (0.22–1.54μg/g sed) and aromatics (21–53μg/g sed) indicated a strong contribution of terrestrial material and anoxic OM deposition conditions. Between 5100 and 5000calyr BP more humid conditions due to heavier rainfalls were observed. Early in this period, terrestrial biomarker contents (253μg/g sed of aromatics, Paq ~0.17) increased due to input of watershed erosion material. This provoked a rapid burial and good preservation of terrestrial OM (CPI 3–4.5). From 5000calyr BP a strong sedimentation of carbonate minerals (OI~1600mg CO2·g−1) masked the OM signal and affecting RE parameters. Paq (~0.18), T/A ratio (~0.4) and the decrease of C31αβ/C31ββ hopanes (1.18) indicate increasing aquatic conditions up to 2700calyr BP. CPI ratio (~1.2) and degraded phytoclasts suggest intense degradation during transport to the sedimentation location. The PTMEs results showed that, from 3000yrcal BP, the Poaceae genera were different from those found at the bottom (middle-Holocene), suggesting a change of vegetation. The last 600calyr BP were marked by the seasonal influence of the Amazon River; during periods of low water level, the organic petrography and CPI values (~1.0) evidenced OM degradation and the return of rather drier conditions.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Sedimentary evidence of soil organic matter input to the Curuai Amazonian floodplain

A multi-proxy study has been performed on a sediment core from the Curuai floodplain, Central Amazonia. The combination of elemental, isotopic and molecular analysis of a 110cm core (a record of ca. the last 100yr) allowed reconstruction of the hydrological conditions of organic matter (OM) deposition. Two units could be delineated. The first (UI) was composed of three sub-units: UIa (0–15cm), composed of highly degraded organic particles originating from the surrounding soil and indicative of restricted transport; UIb (15–48cm), during which the region was permanently flooded and the material stored came from soil runoff, mainly from alluvial forest; and UIc (48–88cm) composed of material from Amazon River suspended sediment, itself originating from OM degradation in forest soil. In UII (88–111cm), the OM originated mainly from the forest soil and other plant remains in the floodplain. The data reveal that, during the four distinct depositional periods, the sedimentary OM alternated between land derived soil and alluvial vegetation due to changes in hydrodynamics.

Assessment of in vivo fluorescence method for chlorophyll-a estimation in optically complex waters (Curuai floodplain, Pará - Brazil)

AIM: This paper describes an experiment carried out to evaluate in vivo fluorescence (IVF) as an alternative method for chlorophyll-a estimation in optically complex aquatic environment (Amazon floodplain lakes) METHODS: The experiment consisted of collecting in situ measurements at 26 sampling stations distributed throughout Curuai floodplain lakes. For each sampling station the following parameters were measured: temperature, turbidity, depth, Secchi depth, chlorophyll-a (Chl-a) concentration, total suspended solids (TSS) and dissolved organic carbon (DOC), concurrently with several transects of IVF. Two methods were tested for quantifying the fluorescence measurement to be used as input for the chlorophyll-a estimates: instantaneous IFV and average IVF. Global and regional models were tested and assessed by analyzing optically active components (Chl-a, DOC and TSS) of the water. RESULTS: Regardless of fluorescence estimating method, the results indicate that it was not possible to fit a global model for estimating Chl-a from IVF for all the lakes in the Curuai floodplain. Regional models provided contrasting results according to the concentration of optically active components. The best results were observed for aquatic systems with a single dominant component homogenously distributed throughout the lake. The results highlight the influence of the ratios Chl-a/TSS, Chl-a/DOC and Phaephytin/Chl-a in the relationship between IVF and chlorophyll concentration. CONCLUSIONS: It was not possible to develop a global model to account for the entire region of Curuai floodplain. The search for regional models provided insights on the main factors affecting the relationship between IVF and Chl-a concentration. Nevertheless this work reinforces the great potential of fluorometry technique, since even with a small number of samples it was possible to set a good model in the main lake of the Curuai floodplain. In spite the fact that this is not an accurate method, it is very useful for assessing the chlorophyll spatial distribution with relatively low cost. These possibilities are very interesting in the execution of field missions in the Amazon region.

Seasonal variability in concentration, composition, age, and fluxes of particulate organic carbon exchanged between the floodplain and Amazon River

The composition, sources, and age of particulate organic matter were determined in an Amazonian river‐floodplain system during rising, high, falling, and low water periods over 7 yr (1999–2006), and a mass balance for total organic carbon (dissolved and particulate) was estimated. The Curuai floodplain, composed of several temporally interconnected lakes, is permanently connected to the Amazon River via channels. Organic matter (OM) is imported to the floodplain from the Amazon River mainly during the rising water period and produced in the floodplain and exported to the river during high and falling water periods. No significant exchanges occurred during low water periods. The OM produced in the floodplain is characterized by low C/N ratios and by high chlorophyll a concentrations (Chl‐a). The δ13C signature has a seasonal trend, with more negative δ13C values during the high water period than other periods. Δ14C results indicate that the bulk OM present in floodplain lakes is predominantly post‐bomb (i.e., post‐1950). Particulate organic carbon (POC) and dissolved organic carbon (DOC) fluxes exported by the Curuai floodplain represent 1.3% and 0.1%, respectively, of the POC and DOC annual fluxes in the mainstem Amazon River at Óbidos but may reach up to 3.3% and 0.8% during falling water. Based on Δ14C, δ13C, Chl‐a, and elemental analysis of the particulate organic matter, we demonstrate that floodplain lakes have intense phytoplankton and macrophyte primary production, which is partly exported to the main river channel. Floodplains are thus a significant source of modern and labile organic carbon to the river mainstem, where it can be rapidly degraded and recycled back to the atmosphere.

Determinants of beta diversity: the relative importance of environmental and spatial processes in structuring phytoplankton communities in an Amazonian floodplain

AIM: Beta diversity is defined as the change in species composition along environmental gradients, and in the present study, we investigated the influence of local (i.e., environmental) and regional (i.e., dispersal) factors in community structure. The aims of this study were to evaluate the beta diversity of phytoplankton communities in the Curuai floodplain and to determine the relative importance of environmental and spatial processes in shaping phytoplankton community structure; METHOD: The phytoplankton communities were sampled in 16 lakes of the Curuai floodplain (Amazon Basin) during high-water periods in 2002 and 2003. We used partial redundancy analysis (pRDA) to evaluate the pure effect of environmental (six variables) and spatial (spatial filter) variability on phytoplankton community composition; RESULTS: There were 156 taxa recorded in the two study years, including 122 algae species in 2002 and 66 algae species in 2003. The beta diversity that we measured (βSIM index) was 0.889 in 2002 and 0.789 in 2003. The partitioning variation demonstrated that the majority of variation in phytoplankton community structure was not significantly explained by pure environmental and pure spatial components. However, environmental variables presented a larger coefficient of determination than the spatial variable; CONCLUSION: Other factors than those we measured in this study, such as local variables (i.e., biotic interactions, hydrology, etc.) and stochastic events, affected the absence of significant results in our data. Therefore, we suggest that additional variables, such as biological interactions and other local factors, should be considered in this type of analysis to increase its explanatory power for understanding the variation of diversity in these communities.

Mercury distribution and exchanges between the Amazon River and connected floodplain lakes

This work presents the distribution and the partition of mercury (Hg) in the Curuai floodplain lakes along the Amazon River. The maximum Total Filtered Hg (T-FHg) concentrations in the floodplain lakes (28 to 52 pmol L − 1 ) coincide with the maximum T-FHg concentrations of the Amazon River and are measured during the flooding period. The lowest T-FHg values (3 to 5 pmol L − 1 ) are observed during the flood peak of the mainstream, during the rainy season, when waters are diluted by the local rainfall. In this system, Hg is mainly transported in the particulate phase, confirmed by elevated values of the Hg partition coefficient (4.77 < K d (Hg) < 5.83 L kg − 1 ). The highest Total Particulate Hg (T-PHg) concentrations (47–478 pmol L − 1 ) in the lakes are measured during the dry season when they are isolated from the mainstream. This enrichment is due to the elevated TSS content associated to the re-suspension of the bottom sediments by the wind action and the bioturbation in shallow water lakes. In the flooded system, the lakes show different geochemical characteristics that control the Hg distribution and partition. In the white water (WW) lakes, characterized by oxidative neutral waters and highest TSS contents (till 2041 mg L − 1 ), the T-PHg is associated to the particulate organic matter mainly during the dry season, while the T-FHg and T-FMn concentrations are correlated. In the black water (BW) lakes that show reductive pH conditions and lowest TSS load (2 to 52 mg L − 1 ), P-iron and T-PHg display a positive relationship whereas the redox conditions favor the desorption of Hg from the particulate to the filtered phase. The mercury mass budget estimated in this study confirms that the Curuai floodplain system acts as a particulate mercury trap, with a net storage of particulate Hg of 150 kg PHg year − 1 .

Reconstituição paleoambiental do Lago Santa Ninha, Várzea do Lago Grande de Curuai, Pará, Brasil

Este estudo teve por objetivo reconstituir as mudanças paleoambientais e paleohidrológicas no baixo Amazonas. Um testemunho de sedimento foi coletado no Lago Santa Ninha, na várzea do Lago Grande de Curuai, localizada na margem direita do Rio Amazonas a aproximadamente 850 km da foz. O teor de água, a granulometria, as datações com carbono 14, os conteúdos de carbono orgânico e nitrogênio total e o isótopo estável do carbono (δ13C) foram utilizados para determinar os processos sedimentares a que o meio esteve submetido. O testemunho estudado possui 270 cm de comprimento que corresponde a um período de 5600 anos cal AP. Este estudo colocou em evidência diferentes ambientes sedimentares: na base do testemunho até 4900 anos cal AP há uma vegetação inundada que foi gradualmente substituida por bancos de gramíneas e por uma planicie com secas sazonais em 4000 anos cal AP até alcançar, desde 600 anos AP as condições atuais deste lago. Estas alterações podem ter ocorrido em decorrência de mudanças no ciclo hidrológico do Rio Amazonas que, por sua vez, também são reflexos de alterações climáticas.

Improving the spectral unmixing algorithm to map water turbidity Distributions

In this paper we evaluate the suitability of the spectral unmixing algorithm to map the turbidity in the Curuai floodplain lake and enhance its applicability using autocorrelation modelling. The Spectral Unmixing Model (SMM) was applied to a Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance (MOD09) image, taking in-situ measurements close to the acquisition date. Fraction images of inorganic matter-laden water, dissolved organic matter-laden water, and phytoplankton-laden water were generated by SMM, using 4 MODIS spectral bands (blue, green, red, and near infrared). These endmembers were selected based on the dominance of these components, which affect water turbidity. These fraction images allowed assessing the turbidity distribution in the study area but showing only places with high or low turbidity. The kernel estimation algorithm was then used to verify the spatial correlation among the in-situ measurement data. The occurrence of clusters suggests that there are different spatial water regimes. One spatial regression model was then compiled for each water regime, each of which presented a better turbidity estimation as opposed to the one derived from the Ordinary Least Square (OLS). The methodology applied was hence useful to analyze the spatial distribution of turbidity in the Curuai floodplain lake.

Origem e dinâmica da deposição dos sedimentos superficiais na Várzea do Lago Grande de Curuai, Pará, Brasil

Este estudo tem por objetivo caracterizar os sedimentos superficiais de um sistema de Várzea do Rio Amazonas, quanto a sua granulometria e ao seu teor orgânico, assim como compreender a origem e a hidrodinâmica destes sedimentos. 51 amostras de sedimento superficial foram coletadas na Várzea do Lago Grande de Curuai, localizada na margem direita do Rio Amazonas à aproximadamente 850km da foz. A granulometria, o teor em carbono orgânico e nitrogênio total, a razão entre o carbono e o nitrogênio (C/N), assim como o isótopo estável do carbono (δ13C) e do nitrogênio (δ15N) foram utilisados para este fim. Este estudo colocou em evidência que os sedimentos da várzea são finos, caracterizados principalmente pela presença de silte (médio à fino), seguido de argila e tem como principal fonte o Rio Amazonas e a Formação Alter do Chão. A presença de areia é pequena e extremamente localizada, próxima as áreas de deságue dos igarapés de terra firme que representam sua maior fonte. O teor de matéria orgânica nestes sedimentos varia entre 1,5 à 37% de carbono. Os resultados do isótopo do carbono (13C) e da razão C/N evidenciam a presença de matéria orgânica composta por diferentes fontes: material orgânico terrígeno, macrofítico, solos, material orgânico transportado pelo rio, e um componente fitoplanctônico.

Turbidity in the Amazon Floodplain Assessed Through a Spatial Regression Model Applied to Fraction Images Derived From MODIS/Terra

The objective of this paper was to estimate turbidity in the Curuai floodplain during the high water level period. Spatial regression models were developed by using fraction images derived from a linear spectral mixture model applied to a Moderate Resolution Imaging Spectroradiometer/Terra image and turbidity <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">situ</i> data. As the turbidity in situ data showed spatial autocorrelation, they were divided into four spatial regimes (clusters). Thus, a spatial regression model was developed for each spatial regime. Through the Akaike information criterion, it was verified which spatial regime showed the best fit in the spatial regression model. The best fit was presented by the spatial regime 4 ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.80,p < 0.05). Then, the spatial regression model developed for the spatial regime 4 was applied to all floodplain lakes. The spatial regression models show potential for assessing the water turbidity in aquatic systems by considering a spatial dependence between samples.