Monitoring of Rivers and Streams Conditions Using Biological Indices with Emphasis on Algae: A Comprehensive Descriptive Review toward River Management

Abstract

Algal communities are robust indicators of the effect and impact of environmental flows on river-dependent ecosystems as they deflect directly and indirectly those physical chemical and biological changes induced by environmental flows, which alter nutrient concentration, salinity, and alkalinity. Algal periphyton communities are the deterministic indicators of many aspects of ecological disturbance and its response, providing valuable evidential data at intertemporal scale of riverine status in terms of both health and quality, and their collection is comparatively simple, inexpensive, and environmental friendly.

1. Introduction

River health is defined as follows:

“(i) the absence of distress defined by measured characteristics or indicators;

(ii) the ability of an ecosystem to handle stress, or bounce back its resilience [1];

(iii) the identification of risk factors such as industrial or sewage effluents.” [2].

River health consists of both ecological and human values, as shown in Figure 1, and is mostly dependent on river condition, which is measured mostly by a large variety of qualitative indices (poor-to-excellent scaling system) as seen in Ladson et al. [5], Hill et al. [6], Gordon et al. [7], Acreman and Ferguson [8], and Atazadeh et al. [3]. Physicochemical indices are the most common indices for lotic water, for example, in the U.S. as seen in Toxic and Priority Pollutants Under the Clean Water Act [9], which are extended to Chemical, Microbiological, Whole Effluent Toxicity, Radiochemical, Industry-Specific and Biosolids [10]. However, these proved inadequate in achieving full spectrum protection [11, 12].

Figure 1.

Ecological and human value contribution to river health as modified from [3, 4].

The first to point out that organic matter concentration areas in streams attract invertebrates was Hynes in [13] based on the previous works [14, 15] on the bottom fauna distribution and quantity. This was followed by the River Continuum Concept where “the structural and functional characteristics of stream communities are adapted to conform to the most probable position or mean sate of the physical system” [16], the framework for a spatiotemporal hierarchical classification system “among and within stream systems” [17] and the collection of articles in Boon and Raven [18]. These are some of the cornerstones that led to the employment of bioindicators, biomonitoring, and bioassessment. Biological indicators (bioindicators) are defined as “an organism (or part of an organism or a community of organisms) that contains information on the quality of the environment (or a part of the environment)” [19]. Biomonitoring is “the systematic use of living organisms or their responses to determine the condition or changes of the environment” [20]. Bioassessment is defined as “an evaluation of the condition of a waterbody using biological surveys and other direct measurements of the resident biota in surface water” [21].

Consequently, biological indicators fill in the gaps left by physiochemical indices as being more integrative [22] and range from lower trophic-level organisms (e.g., algae or benthic macroinvertebrates) all the way to upper trophic-level species (e.g., fish and mussels). These, combined with river geomorphological and hydrological indices [7], form a more dependable framework upon which river health assessment can rely [23]. Algae entered the phase of scientific study well over a hundred years ago and its connection with riverine environmental condition started in 1908 [24, 25, 26, 27, 28, 29, 30].

2. Methodology

The PRISMA method [31] was applied in the usual way with a multitude of pertinent keywords and exclusion of (sea, ocean, and lake) where appropriate. The goal of this review is to present a cogent well-sourced picture of the state of monitoring of rivers and streams condition using biological indices with a particular focus on algae. To this end, methods, frameworks, and diverse indices were descriptively enumerated and the general role of algae was expanded upon.

3. Results

3.1 Aggregate indices and monitoring frameworks

Indices may be simple or aggregate, that is, an index comprised of subindices. An example of the latter is the Aggregate Water Quality Index (AWQI). This was shown to have the capacity of being formulated without the problems of ambiguity (subindices show use-targeted acceptable water quality but the aggregated index fails to do so), eclipsing (aggregated index does not reflect sufficiently poor water quality shown by water quality variables), and rigidity (more variables have to be included targeted particular water quality aspects) as seen in Swamee and Tyagi [32]. To set up an AWQI, the process is as follows [33]:

• selecting the perceived to be significant water quality parameters

• forming subindices

• establishing weights for relative parameters

• selecting an aggregation process of the subindices

The aggregation process ranges from the simple weighted additive method to the modified additive method [34] and more complicated methods [35].

An example of river condition index is the aggregate-type River Condition Index in New South Wales, which is comprised of the following subindices:

• “River Styles® (River [36]) Geomorphic Condition assessment – surrogate input under FARWH “Physical Form” category (RSGC)” [37].

• “Riparian vegetation cover assessment (native woody vegetation) – surrogate input under FARWH “Fringing Zone” category (RVC)” [37]

• “Macro water planning: hydrologic stress or risk rating – surrogate input under FARWH “Hydrological Change” category” [37].

• “River biodiversity condition data – surrogate input under FARWH “Aquatic Biota” category (RBCI)” [37]

• “Catchment Disturbance Index – surrogate input under FARWH “Catchment Disturbance” category (CDI)” [37].

The River Condition Index (RCI) score is computed by employing Euclidean distance for the subindices [38].

$$RCI=1-\frac{\surd \left(1–RSC\right)2+\left(1–CDI\right)2+\left(1–HS\right)2+\left(1–\mathit{RBCI}\right)2+\left(1-RVC\right)2}{\surd 5}$$

To interpret the results, Table 1 converts metric to qualitative results using the Framework for Assessing River and Wetland Health (FARWH) [39].

Score	Condition Bands
0.81–1	Very Good (equivalent to FARWH “Largely Unmodified”)
0.61–0.8	Good (equivalent to FARWH “Slightly Modified”)
0.41–0.6	Moderate (equivalent to FARWH “Moderately Modified”)
0.21–0.4	Poor (equivalent to FARWH “Substantially Modified”)
0–0.2	Very Poor (equivalent to FARWH “Severely modified”)

Table 1.

Conversion of metric to qualitative results [37].

The South African Government’s River Health Program in the process of assessing both river health and stream condition developed an Index of Stream Geomorphology based on the measurement of geomorphic variables in view of the fact that they are the main constituents of the channel morphology impacting river aquatic biota [7, 40, 41]. This is comparable to the underlying logic in Chessman et al. [42] associating downward geomorphology changes with downward changes in assemblages of macrophytes and macroinvertebrates, while the latter are seen to display new sensitivities [43], a reaction seen also in freshwater mussels [44]. Also, positive result of fluvial geomorphology is associated with maintaining river health framework structural elements [45].

The River Habitat Quality survey framework as seen in Fox et al. [46] is used extensively worldwide, especially in Europe and the U.S., to assess both river health and condition. Its field survey protocols converge with those of SERCON (System for Evaluating Rivers for Conservation) [47] and was compared to the Systeme d’Evaluation de la Qualite du Milieu Physique (SEQ-MP) from France, and the field survey method of the Landerarbeitsgemeinschaft Wasser (LAWA-vor-Ort) from Germany [48]. A subset of its features leads to distinguishing between lowland, Alpine, and southern European rivers in terms of hydromorphological character [49] and is amenable to prediction techniques [50]. In the U.K., it was used for the period 1994–1997 for quality assessment [51], for the determination of characteristics and controls of Gravel-Bed Riffles [52], for the classification of urban rivers [53], and for the aims of the WFD hydro-morphological assessment (STAR Project overview) [54]. Also, in exploring the interactions between flood defense maintenance works and river habitats [55], for environmental assessment and catchment planning [56] and for the evaluation of the effects of riparian restoration [57]. In Serbia, it was used in the Golijska Moravica and Jerma basins [58], in Austria for the identification of rivers with high-and-good habitat quality [59], in Germany for river habitat monitoring and assessment [60], in the U.S. for the measurement of Little Tallahatchie River in northern Mississippi [61], and in Portugal for fluvial hydromorphological assessment [62]. Also, in Poland regarding its seasonal diversification [63] and in Southern Europe [64].

River geomorphology is a characteristic often used for river health evaluation as seen [7] and is deemed to be quite important [65]. Geomorphology impacts water quality [66], and its assessment is used in place of “command-and-control” practices that cause environmental damaging biodiversity reduction and lessening provision of ecosystem services [67], and its change is associated with river rehabilitation [68] while via the River Styles framework links policy with action-on-the-ground. Also, along with ecology and river channel, habitats constitute a mesoscale approach to basin-scale challenges [69], assist in determining the ecological health of wadable streams [70], and affect riparian habitat within alluvial channel-floodplain river systems [71], and its spatial variability impacts the disturbance temporal patterns influencing ecosystem structure/dynamics [72], acting as a framework for the analysis of microplastics in riverine sediments [73].

The Index of Stream Condition (ISC) was developed, tested, and applied in Australian regions [5], for example, in Victoria [74] as seen in Figure 2.

Figure 2.

Third benchmark index of stream condition subindices and metrics of hydrology [75].

The basis of the ISC system lies in a subjective ranking system whereby the current condition of a river is compared to a known/modeled “pristine” condition across the index/subindex groups seen in Figure 1 which are scaled to (0–10) values and added as seen in Figure 3.

Figure 3.

North east region: (a) index of stream condition, (b) upper Murray index of stream condition, (c) part of the upper Murray calculation * [76]. *insufficient data are not added.

It should be noted that macro-benthos data are included [5, 7].

3.2 Biological monitoring systems

Biological monitoring systems are usually based on fish, benthic macro-invertebrates as well as macrophytes, riparian vegetation, and algae [7, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91].

In determining water quality from the assessment of river ecosystem health, macro-invertebrates are considered to be both important, as they are a critical part of the aquatic food framework [92] and preferable to other targets for the following reasons [93]:

1. They are both differentially sensitive to various pollutant types and rapidly reactive to them while being capable of responding in a graded way to a variety and different levels of stress.

2. They are abundant as well as ubiquitous and easily collectible and identifiable [79, 94, 95, 96, 97, 98, 99], while identification and enumeration are easy in comparison with microorganisms and plankton.

3. If they are benthic the fact that they are sedentary makes them more representational of local conditions.

4. Their lifespans are long enough to provide adequate environmental quality records, though temporal/seasonal variability in index calibration should be introduced [100, 101, 102].

5. Their communities include a number of phyla which makes them heterogeneous.

Generally, in-stream biomonitoring can be employed using some or all of the aforesaid macro- and micro-organisms as biological indicators/indices. However, from the point of view of spatial and temporal invariance this leads to problems.

Benthic macro-invertebrates are used by a large number of scientists because they are sensitive to water degradation and river health and depend on sediment quality [103]. A major issue is eutrophication, “excessive plant and algal growth due to the increased availability of one or more limiting growth factors needed for photosynthesis” [104], which usually occurs in rivers that are passing through urbanized/agricultural areas [105] and seems to depend strongly on the local stream and its surroundings characteristics [106] in case of which both reaction and response become limited [107, 108]. Another issue is that in order to assess human-influenced events separately from the naturally caused ones, that is, natural seasonal or successional variation [109], a stressor-specific multimetric approach is needed [110].

In a 2008 statistical analysis [111], the findings were as below:

• Benthic macro-invertebrates (19 sources) 68% reported sampling difficulties, 58% reported not enough taxonomic keys available, 42% reduced sensitivity to disturbance, and 21% drifting (not a good local indicator).

• In the case of algae (nine sources), 78% reported insufficient metrics/indices, 67% reported not enough taxonomic keys available, and 33% reported that the group is a poor accumulator.

• For fish (14 sources), 64% reported drifting (not a good local indicator), 36% reported sampling difficulties, and 21% reported insufficient metrics/indices.

• For zooplankton (nine sources), 67% reported sampling difficulties, 67% reported insufficient metrics/indices, 50% reported heavy affectation by non-anthropogenic conditions, 33% reported that the group is a poor accumulator, and 33% reported not regular occurrence in habitat under study.

In rivers where macrophytes are not abundant, bottom-lying biofilm is the main agent of nutrient uptake, a stratum that consists [112] of algae, bacteria, and fungi ensconced in a polysaccharide matrix. In the case of nutrient change, algae react directly but invertebrates generally respond indirectly depending on the water quality intensity of influence on the habitat. The mechanism explaining this [113, 114] is that an initial subsidy effect consisting of increasing nutrients leads to the direct stimulation of algal productivity and this, in the role of a mediator, causes, through increased trophic resources, the macroinvertebrate’s response stimulation. For this reason, some approaches to understanding river conditions have been based on As algal biofilm/diatom communities are sensitive and responsive to river physical, chemical, and biological changes [24, 29, 115, 116, 117, 118] and there are a lot of approaches for river condition assessment based on them.

Biofilms are a major element of river food webs [119] and important for stream biogeochemical and nutrient processes [120, 121, 122, 123, 124, 125, 126]. Microalgae are the main food source for fauna in freshwater ecosystems. Algae-based processes lead to the production and synthesis of organic matter (carbon) and allow its entry into the food web via which is available to higher trophic consumers such as fish and waterbirds [127, 128, 129], and consequently, algae, in terms of freshwater ecosystems [126], are considered to be the most essential part of food webs and biogeochemical cycling, for example, carbon cycling [130]. Epiphytic algae are one of the appropriate food sources for stream invertebrates in an interactive way [131] since freshwater algae carry high concentrations of polyunsaturated fatty acids and in stream food webs, high-quality algae enhances the food value of low-quality riparian leaf litter [129, 132, 133]. In terms of algal groups, diatoms and cryptophytes supply aquatic invertebrate food of higher quality due to long-chain omega-3 polyunsaturated fatty acids [132, 134, 135, 136], while omega-3 (n-3) long-chain essential fatty acids (EFA) are higher in running water than brackish [136] and are projected to decrease as world temperature rises [137]. As these species are the important indicators of river health, their primary production is equally important and may be decreased by turbidity and shading, due to light blocking [138, 139], while shear stress and low nutrients are important inhibitors particularly for algal primary production along with temperature and grazing [140].

Primary producer community structure (PPCS) in rivers and streams is influenced by the general state of hydrodynamics [141, 142] as flow velocity increase is correlated positively with increased nutrient delivery by increasing PPCS productivity through thinning the diffusive boundary layer up to a point where it becomes negatively correlated due to dislodgement [143, 144, 145]. As seen in Gurnell [146], PPCS influences ecosystem structure via their hydrodynamics and morphology by flow-vegetation-sediment feedbacks.

Algae, having increased sensitivity, often signal changes in environmental conditions by responding well before effects on higher organisms manifest themselves [29, 78]. The reduction of river flow affects biofilm structure [125], for example, in terms of causing increased algae bloom [147], which prevents sunlight from penetrating the water surface [148] as well as ecosystem processes in general [149, 150, 151]. In the biofilm structure, diatom assemblages are shown to be highly responsive to water quality variation [152] since their assemblages are used to measure water quality [153].

3.3 Biological indices

There are many biological indices for water quality assessment, which may depend either on many parameters or on a particular one. The algal periphyton system, in terms of similarity, diversity, evenness, structure, and dominance, has been employed in the construction of a variety of biological indices of both kinds [154, 155, 156]. There has been criticism regarding the processes, which reduces the indices to a single quantitative or qualitative result regarding its representational effect [157] due to seasonal variability [158, 159, 160, 161] or regionality [162, 163]. Despite the objections, this type of indices has been employed in many countries including the U.K., the U.S.A, Spain, and Canada. Most countries have passed legislation according to which government entities controlling rivers and water bodies in general are obliged to use biological indices, for example, Italy [164], in order to assess stream condition in terms of water quality and water abstraction impact [7]. The European Water Framework Directive [165] included biological monitoring as a stream health assessment tool, and in the U.S.A., macroinvertebrate community assessment is used under the Clean Water Act [166].

Biological indices are used by conjunctive employment with multivariate statistical analysis, which leads to a good understanding of aquatic biota-sensitivity and to the determination of the driver-response relationship [7, 91, 167, 168, 169]. Biological indices resulting from multivariate analysis techniques are as follows:

• The U.K. derived RIVPACS (River Invertebrate Prediction And Classification Scheme) [170, 171, 172, 173, 174].

• The Canadian BEAST (BEnthic Assessment of SedimenT) [99, 175].

• The Australian AusRivAS (Australian River Assessment System) [176, 177] but according to Chessman [178], its applications in terms of biological health assessment do not have consistent or quantified status of any nature rendering them virtually meaningless.

• The Australian SIGNAL (Stream Invertebrate Grade Number Average Level) [43, 179].

• The South African Scoring System (SASS) [180, 181].

Multi-metric techniques (biotic integrity indices) [182] are employed as an approach where an integrated balance is maintained in adaptive biological systems between elements and processes such as species, genus, assemblage and biotic interaction, nutrient and energy dynamic, meta-population process respectively in natural habitats [183, 184]. The initial concept of biotic integrity, the Index of Biotic Integrity (IBI) has been developed for fish in shallow rivers [185] in the USA measuring trophic composition, species composition, and abundance and health of fish [183, 186], and Karr’s work is re-evaluated in Capmourteres et al. [187]. According to Gordon et al. [7], in the case of the biotic integrity index small disturbance to the system has negligible effect on the biological integrity of the system, which was one of the presuppositions of its design [185]. However, a unified conclusion regarding the regularity of different group-based IBI evaluation results has not been reached [188, 189, 190] as seen in Huang et al. [191]. Various biotic integrity-based biotic indices besides IBI exist:

• BIBI (Benthic Index for Biotic Integrity) employing macro-invertebrates [192] uses 10 metrics of stream macroinvertebrate communities integrated into one value that has numerical/qualitative range 10 (poor) to 50 (excellent) [193]. Also, it is related to environmental factors [194], upon occasion may show opposite results to those obtained using the Organism – Sediment Index (OSI) [195], and in a Korean study [196], the BIBI Korean variant by [197] was found to be negatively correlated with the Korean Saprobic Index (KSI), which is based on the saprobic valency concept as seen in Zelinka and Marvan [198].

• PIBI (Periphyton Index for Biotic Integrity) where algal periphyton is the main element [6, 24, 199, 200].

• DSIAR (Diatom Species Index for Australian Rivers) based on diatoms is correlated at a significant level to ARC_E (Assessment of River Condition, Environment) [116, 201].

• BII (Biotic Integrity Index) that employs diatom community structural metrics [202].

• MBII (Macroinvertebrate Biotic Integrity Index) where data collection is performed by employing a probability design, evaluating five characteristics (precision, range, responsiveness to disturbance, relationship to catchment area, and redundancy with respect to other metrics), while a continuous scale is employed for scoring [203].

3.4 Riverine ecological assessment: The role of algae

Algae are in general one of the primary producers in aquatic ecosystems [204, 205] taking into consideration that Water N:P molar ratios could result in being restrictive for river algal communities’ population dynamics and species coexistence [206].

Algae react to riverine ecosystem disturbances and show sensitivity to changes in environmental conditions [29, 126, 150, 207, 208, 209, 210, 211, 212, 213, 214]. However, riverine algae are not as sensitive to changes in environmental conditions as periphytic algae, which grow by substrate attachment, and in case of negative environmental changes move away [215].

In effect, they have the characteristics necessary to become prime environmental conditions monitors in aquatic ecosystems at a global applicative level [28, 29, 90, 108, 126, 216, 217, 218, 219, 220, 221]. In particular, their properties [120, 220, 222, 223] are seen below:

• high sensitivity to environmental changes

• easy to sample

• the majority of species are both cosmopolitan and with well-known autecology

• possess a wide spectrum of structural (biomass, composition) and functional (metabolism) attributes are valuable for their use in monitoring ecosystems.

Community structure, biomass standing crop, and species composition have been employed in the assessment of riverine ecological condition both directly and indirectly [224, 225, 226, 227]. Riverine biofilm structure [125, 207, 228, 229, 230, 231, 232] and ecosystem processes [151] have been shown to be affected by flow variation. Within the biofilm, diatom algal assemblages within the biofilm are highly responsive to water chemistry variations [152], and consequently, their composition can give away any ecological responses to flow-driven changes occurring in stream water quality. Using algae as an ecological state assessment tool leads to the detection of harmful riverine ecosystem human activity [126, 233, 234], providing thus the evidence necessary for carrying out water resource managerial decisions.

Flow current exerts influence over algal immigration [235], reproduction by varying nutrient supply rates [236], and community physiognomy by decreasing attachment strength [237].

High stream discharge velocities may affect benthic algae in different ways, which depend on both frequency and intensity [238, 239] and change both physiological and structural properties of the community [240, 241].

In lotic and lentic freshwater ecosystems, algae are the main primary producers as, for example, trophic status via the trophic state index (TSI) is determined by algal levels [242], seen in Round [243], Stevenson et al. [244], and Allan and Castillo [245] and being the main source of energy for first-order consumers such as small herbivores places them in an important role in the food web. Algae growth is dependent on riverine nutrient concentration, mainly on phosphorus and nitrogen, and also on benthos-concentrated ones [244, 246], while other factors, such as predation and hydrology, have a significant contribution [141, 244, 247, 248, 249, 250].

As seen in Steinman [251], there are various forms of benthic algae assembly, for example, stalked (colonial) aggregates, unicellular states [252], and filamentous [253]. Benthic algal biomass constitutes an excellent water quality indicator [254, 255, 256, 257] and, through that, of river condition and therefore health [258]. Algal biomass analyses are often used for river health evaluation [259] as well as of riverine ecosystems anthropogenic modifications analysis, for example, of dry mass [260], of chlorophyll-a concentration [261, 262, 263], bio-volume and peak biomass [244, 260, 264], and ash-free dry mass.

The flow regime, stream velocity in effect, is in negative correlation negatively with chlorophyll-a concentration [228, 265, 266]. While chlorophyll-a concentration tends to increase downstream in a state of constant flow, there are also upstream-caused downstream effects [267]. The flow-related disturbance effect on biomass is also [228, 265, 266, 268, 269, 270] as well as in rainforest streams [271] and in the creation of gradient of metacommunity types within stream networks [272]. Algal biomass is seen to decrease due to suspended solids and grazers, that is, fish and invertebrates, substratum instability, flow disturbance, that is, velocity where stream algal biomass responds to nutrient enrichment depending on the velocity [273]. Conversely, light, temperature, and nutrients are seen to be the main promoting resources of algal biomass [141, 274].

Νutrients as well as grazing pressure and light influence algal growth and community structure [275, 276]. In terms of algal biomass control, the main top-down controllers are nutrients and light are top-down and grazers, mainly fish and snails, are the main bottom-up [207, 251, 277], while under certain conditions there is feedback between the two processes [278]. A controller of algal community structure is lotic system flow disturbance [245, 279, 280, 281].

Shifts in water quality and flow variation affect algal colonization and structure [125, 228, 245, 282, 283, 284, 285]. Flow regime impacts on both water quality, that is, temperature, suspended solids, oxygen level, organic matters, and other nutrients in general, and the metabolism of rivers or streams and biotic structure and function [7, 149, 286, 287]. Climate change impacts water quality [288], and as seen in Baron et al. [289], environmental factors impact the structure and function of aquatic ecosystems and flow regimes, sediment and organic materials, water quality, nutrients and other chemicals elements, light, temperature, for example, “brownification” where, as seen in De Wit et al. [290], a 10% increase in precipitation will result in increasing by 30% the soil transfer of OC to freshwaters.

The list of environmental factors affecting the structure and function of benthic algae in riverine ecosystems was compiled and analyzed, in particular grazers, temperature, pH, light, hydraulics, and nutrients (N, P, Si). While, under fast flow and low nutrients algal community structure, species composition, biomass, and standing crop decrease slow flow and a high concentration of nutrients increase algal biomass and community structure.

Climate variability/change is seen to affect algae directly [291, 292, 293, 294]. As seen in Sinha and Michalak [295], precipitation, which is climate induced, is a pre-eminent factor in the variability of riverine nitrogen. Moreover, precipitation plays a role in algae affecting stream flow velocity [296, 297] as seen in the Heavy Precipitation Index [298], which is a part of the Streamflow Indicator as defined in [299]. This makes the climate/precipitation mechanisms in [300, 301, 302, 303], and flood events [304] lead to effects, which influence algae in an important and multifaceted way.

3.5 Algae in the role of indicators in the assessment of stream condition

Algae are considered to be primary producers in aquatic ecosystems powering both food webs and biogeochemical cycling [126], even rare metals [305]. Algae are present in almost every aquatic environment including fresh, brackish, marine, and hypersaline water [306, 307]. Algae communities in rivers are usually diverse and inhomogeneous [308, 309], and their types are as in Table 2.

Epilithon	on rock
epidendron or epixylon	on woody debris
epiphyton	on plants
episammon	on sand
epipelon	on mud
epizoon	on animals

Table 2.

Algae community types [308, 310].

The floristic composition of algae in the benthos could be employed in water quality, stream condition, and eutrophication monitoring [24, 90, 108, 311, 312, 313, 314, 315]. A number of studies show a preference for diatoms since diatom-based methods in bio-monitoring approaches demonstrating a tendency for higher success rate to be the most successful [29, 316]. In practice, other algal groups present bigger difficulties in sampling and quantitative estimation in comparison with diatoms. Moreover, common river algae, in particular the green algae [78], show a demonstrable lack of identification keys although partial country-wide lists exist, for example, [317] where 321 out of 500 genera are identified. However, these other groups may provide information that diatom-based measures cannot provide easily; for example, eutrophication can be monitored by cyanobacterial and green algae biomass and diversity could be used to monitor eutrophication [108, 313, 318, 319, 320].

Diatoms also play important roles in biotechnology, engineering, biology, and material science [321] but their main role in the general riverine environmental condition [29, 322, 323], water quality ecological assessment of aquatic systems [107, 152, 324, 325, 326, 327, 328], eutrophication [78, 314, 329], pollution [330, 331], bioassessment [107, 116, 332, 333, 334], and urbanization [335, 336, 337, 338].

3.6 Biological index-based water body classification

Water body classification is now a function of water chemistry, biological, and hydrological characteristics as it is necessary to include pollutant effects on biota since the nature of the receiving waters influences the effect on water quality as seen in Figure 4. Also, river water is classifiable on the basis of biology, hydrology, and quality, into different condition ecological categories in the qualitative scale of bad, poor, moderate, good, or high [8].

Figure 4.

Water body classification employing ecological models biological indices, and adaptive management.