scholarly journals Development of a hydro-environmental model for inland navigational canals

2013 ◽  
Vol 16 (3) ◽  
pp. 572-587 ◽  
Author(s):  
Dongfang Liang ◽  
Rebecca W. Zeckoski ◽  
Xiaolin Wang
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Algal Growth ◽  
Cohesive Sediment ◽  
Sediment Runoff ◽  
Environmental Model ◽  
Hydrological Simulation ◽  
Environmental Processes ◽  
Model Predictions ◽  
Boat Traffic

Before railroad and lorry traffic became common, many canals were built for transportation purposes. Water quality in canals has become a major concern as maintenance of these historically active canals has declined. A generic canal model has been developed to simulate the hydro-environmental processes specifically relevant to inland navigational canals, namely lockage, weir overflow, boat traffic, and algal growth. Apart from the movement of water, three types of particulate matter are tracked: algae (chlorophyll-a), inorganic non-cohesive sediment, and inorganic cohesive sediment. The newly developed model was applied to the Kennet and Avon Canal in southern England. The method of determining the input parameters for the model was documented herein, including setting up a Hydrological Simulation Program – Fortran model to obtain the landscape flow and sediment runoff to the canal. The model predictions were compared with the observed hydrological, sediment, and chlorophyll-a data at monitoring locations along the canal, and favourable agreements were achieved.

scholarly journals Influence of extended drought on water quality in tropical reservoirs in a semiarid region

2015 ◽  
Vol 27 (1) ◽  
pp. 15-23 ◽  
Author(s):  
Gustavo Girão Braga ◽  
Vanessa Becker ◽  
José Neuciano Pinheiro de Oliveira ◽  
Jurandir Rodrigues de Mendonça Junior ◽  
Anderson Felipe de Medeiros Bezerra ◽  
...  
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Suspended Solids ◽  
Algal Growth ◽  
Freshwater Ecosystems ◽  
Semiarid Region ◽  
Drought Period ◽  
Tropical Reservoirs ◽  
Quality Degradation ◽  
Brazilian Semiarid

AimDrought periods often occur in Brazilian semiarid region and are supposed to induce water quality degradation by changes in physical, chemical and biological properties of freshwater ecosystems. Reservoirs in this region are used as drinking-water supplies and are exposed to wide volume fluctuations during drought periods due to lack of precipitation and high evaporation rates. This study aimed to identify patterns on water quality of two reservoirs during a long drought period. It was expected that more arid and shallower conditions would favor algal growth by enhancing nutrient availability, causing a decrease on water quality.MethodsThe study was based on monthly sampling over 20 months (May 2011 to December 2012) at two tropical reservoirs on Brazilian semiarid region. Precipitation and volume data were obtained from environmental agencies. Transparency was measured on field using a Secchi disk and conductivity, nutrients, suspended solids and chlorophyll-a were analyzed on laboratory. Temporal changes in all environmental variables were analyzed in each reservoir using two-way cluster analysis and also principal component analysis (PCA).ResultsThe volume of both reservoirs decreased considerably over the study because of low or shortage of precipitation. It was possible to detect two opposite patterns of chlorophyll-a in each reservoir throughout the drought season: in the first one phytoplankton growth was favored, while in the second one chlorophyll-a decreased by high inorganic turbidity. Both reservoirs tended to increase their turbidity and conductivity during the drought period due to shallow conditions, which probably contributed to sediment resuspension.ConclusionsWater level reduction during the extended drought period, contributed for water quality degradation due to high algal biomass and also high turbidity found during drought period. Local factors, as the nature of suspended solids, play an important role on predicting water quality.

scholarly journals Effect of red algal bloom on growth and production of carps

Our Nature ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 48-54
Author(s):  
Ram Bhajan Mandal ◽  
Sunila Rai ◽  
Madhav Kumar Shrestha ◽  
Dilip Kumar Jha ◽  
Narayan Prasad Pandit
Keyword(s):  
Water Quality ◽  
Body Weight ◽  
Chlorophyll A ◽  
Total Nitrogen ◽  
Total Phosphorus ◽  
Algal Bloom ◽  
Total Dissolved Solids ◽  
Dissolved Solids ◽  
Aquaculture Farm ◽  
Red Algal

An experiment was carried to assess the effect of red algal bloom on growth and production of carp, water quality and profit from carp for 120 days at Aquaculture Farm of Agriculture and Forestry University, Chitwan. The experiment included two treatments: carp polyculture in non-red pond and carp polyculture in red pond with algal bloom each with three replicates. Carp fingerlings were stocked at 1 fish/m2 and fed with pellet containing 24% CP at 3% body weight. Net yield of rohu was found significantly higher (p<0.05) in non-red ponds (0.38±0.01 t ha-1) than red ponds (0.24±0.05 t ha-1). Survival of rohu (84.9±1.4%), bighead (95.2±2.0%) and mrigal (88.1±14.4%) were also significantly higher (p<0.05) in non-red ponds than red ponds. Red algal bloom affected DO, nitrate and chlorophyll-a, nitrite, total nitrogen, total phosphorus, total dissolved solids and conductivity. However, overall carp production and profit from carp remained unaffected.

Seagrass depth range and water quality in southern Moreton Bay, Queensland, Australia

1996 ◽  
Vol 47 (6) ◽  
pp. 763 ◽  
Author(s):  
EG Abal ◽  
WC Dennison
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Suspended Solids ◽  
Light Attenuation ◽  
River Mouth ◽  
Total Suspended Solids ◽  
Quality Parameters ◽  
Depth Range ◽  
Moreton Bay ◽  
A Site

Correlations between water quality parameters and seagrass depth penetration were developed for use as a biological indicator of integrated light availability and long-term trends in water quality. A year-long water quality monitoring programme in Moreton Bay was coupled with a series of seagrass depth transects. A strong gradient between the western (landward) and eastern (seaward) portions of Moreton Bay was observed in both water quality and seagrass depth range. Higher concentrations of chlorophyll a, total suspended solids, dissolved and total nutrients, and light attenuation coefficients in the water column and correspondingly shallower depth limits of the seagrass Zostera capricorni were observed in the western portions of the bay. Relatively high correlation coefficient values (r2 > 0.8) were observed between light attenuation coefficient, total suspended solids, chlorophyll a, total Kjeldahl nitrogen and Zostera capricorni depth range. Low correlation coefficient values (r2 < 0.8) between seagrass depth range and dissolved inorganic nutrients were observed. Seagrasses had disappeared over a five-year period near the mouth of the Logan River, a turbid river with increased land use in its watershed. At a site 9 km from the river mouth, a significant decrease in seagrass depth range corresponded to higher light attenuation, chlorophyll a, total suspended solids and total nitrogen content relative to a site 21 km from the river mouth. Seagrass depth penetration thus appears to be a sensitive bio-indicator of some water quality parameters, with application for water quality management.

A study of water quality in an urban river and potential improvement using a prototype instream aerator

1989 ◽  
Vol 16 (3) ◽  
pp. 308-316 ◽  
Author(s):  
C. A. Town ◽  
D. S. Mavinic ◽  
B. Moore
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Data Base ◽  
Chlorophyll A ◽  
Late Summer ◽  
Urban River ◽  
Agricultural Activity ◽  
Fish Kills ◽  
Low Dissolved Oxygen ◽  
Oxygen Levels

Urban encroachment and intensive agricultural activity within the Serpentine–Nicomekl watershed (near Vancouver, B.C.) have caused a series of fish (salmon) kills on the Serpentine River since 1980. Low dissolved oxygen was responsible for these kills. This field project investigated some of the dynamic chemical and biological relationships within the river, as well as the use of an instream aerator as a temporary, in situ, water quality improvement measure. Weekly sampling for a 6-month period during the latter half of 1985 established a solid data base for deriving and interpreting meaningful interrelationships. A strong correlation between chlorophyll a and dissolved oxygen levels before the algae die-off supported the hypothesis that algae blooms dying in the fall could create a serious oxygen demand. Because of these environmental conditions, the river is unable to sustain healthy dissolved oxygen levels during this period. As such, a prototype, 460 m artificial aeration line was designed, installed, and monitored to evaluate its potential for alleviating low dissolved oxygen conditions and improving overall water quality during the critical fall period.The instream aerator ran continuously for over 2 months, starting in September 1985. Despite better-than-expected weather conditions (i.e., cool, wet weather) and relatively high dissolved oxygen levels during the fall of 1985, the data base appeared to support the use of this prototype aeration unit as a means of "upgrading" a stretch of an urban river subject to periodic, low dissolved oxygen levels. As a result, a 2-year follow-up study and river monitoring was initiated. In both 1986 and 1987, late summer and early fall river conditions resulted in the potential for serious salmon kills, due to higher-than-normal river temperatures and very low dissolved oxygen. In both instances, the instream aerator prevented such fish kills in a key stretch of the river. Expansion of the system to include other critical stretches of the Serpentine and other urban river systems, near Vancouver, is being considered. Key words: algae, aerator, chlorophyll a, eutrophic, fish kills, instream aeration, river improvement, urban river.

scholarly journals Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae and Turbidity

2018 ◽  
Vol 15 (9) ◽  
pp. 1881 ◽  
Author(s):  
Sina Keller ◽  
Philipp Maier ◽  
Felix Riese ◽  
Stefan Norra ◽  
Andreas Holbach ◽  
...  
Keyword(s):  
Machine Learning ◽  
Water Quality ◽  
Chlorophyll A ◽  
Green Algae ◽  
Hyperspectral Data ◽  
Coefficient Of Determination ◽  
Inland Waters ◽  
Learning Approaches ◽  
River Elbe ◽  
Regression Framework

Inland waters are of great importance for scientists as well as authorities since they are essential ecosystems and well known for their biodiversity. When monitoring their respective water quality, in situ measurements of water quality parameters are spatially limited, costly and time-consuming. In this paper, we propose a combination of hyperspectral data and machine learning methods to estimate and therefore to monitor different parameters for water quality. In contrast to commonly-applied techniques such as band ratios, this approach is data-driven and does not rely on any domain knowledge. We focus on CDOM, chlorophyll a and turbidity as well as the concentrations of the two algae types, diatoms and green algae. In order to investigate the potential of our proposal, we rely on measured data, which we sampled with three different sensors on the river Elbe in Germany from 24 June–12 July 2017. The measurement setup with two probe sensors and a hyperspectral sensor is described in detail. To estimate the five mentioned variables, we present an appropriate regression framework involving ten machine learning models and two preprocessing methods. This allows the regression performance of each model and variable to be evaluated. The best performing model for each variable results in a coefficient of determination R 2 in the range of 89.9% to 94.6%. That clearly reveals the potential of the machine learning approaches with hyperspectral data. In further investigations, we focus on the generalization of the regression framework to prepare its application to different types of inland waters.

scholarly journals Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2699 ◽  
Author(s):  
Jian Li ◽  
Liqiao Tian ◽  
Qingjun Song ◽  
Zhaohua Sun ◽  
Hongjing Yu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Chlorophyll Fluorescence ◽  
Chlorophyll A ◽  
Temporal Variations ◽  
Lake Area ◽  
Short Term ◽  
Chl A ◽  
Spatio Temporal

Monitoring of water quality changes in highly dynamic inland lakes is frequently impeded by insufficient spatial and temporal coverage, for both field surveys and remote sensing methods. To track short-term variations of chlorophyll fluorescence and chlorophyll-a concentrations in Poyang Lake, the largest freshwater lake in China, high-frequency, in-situ, measurements were collected from two fixed stations. The K-mean clustering method was also applied to identify clusters with similar spatio-temporal variations, using remote sensing Chl-a data products from the MERIS satellite, taken from 2003 to 2012. Four lake area classes were obtained with distinct spatio-temporal patterns, two of which were selected for in situ measurement. Distinct daily periodic variations were observed, with peaks at approximately 3:00 PM and troughs at night or early morning. Short-term variations of chlorophyll fluorescence and Chl-a levels were revealed, with a maximum intra-diurnal ratio of 5.1 and inter-diurnal ratio of 7.4, respectively. Using geostatistical analysis, the temporal range of chlorophyll fluorescence and corresponding Chl-a variations was determined to be 9.6 h, which indicates that there is a temporal discrepancy between Chl-a variations and the sampling frequency of current satellite missions. An analysis of the optimal sampling strategies demonstrated that the influence of the sampling time on the mean Chl-a concentrations observed was higher than 25%, and the uncertainty of any single Terra/MODIS or Aqua/MODIS observation was approximately 15%. Therefore, sampling twice a day is essential to resolve Chl-a variations with a bias level of 10% or less. The results highlight short-term variations of critical water quality parameters in freshwater, and they help identify specific design requirements for geostationary earth observation missions, so that they can better address the challenges of monitoring complex coastal and inland environments around the world.

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