Water Temperature Data Research Articles

Analysis of Sewage Volume by Decomposition of Time Series Water Temperature Data

Analysis of Sewage Volume by Decomposition of Time Series Water Temperature Data

Overwhelming Flow of Water using Machine Learning Techniques

Floods are rare and dangerous disaster in minimum duration, which have the most destructive impact within urban and rural areas. This research in flood prediction models contributed to risk reduction, to prevent the loss of human life, and reduce the property of damage in floods. This study implements the automated machine learning models, using the Support Vector Machine (SVM) and Artificial Neural Network (ANN). The rainfall data and various meteorological parameter which include temperature data are used in this study. Concurrent daily records of inflow and discharge are taken into consideration to calculate the water level to quantify the importance of the lake flow. It aims to discovering accurate and efficient for the flood forecasting model. This paper attempts to forecast flood by modelling water level, temperature and rainfall data in the region of Korattur lake, Chennai, India. In this study, ultrasonic sensor used to capture the measurement of water level to predict from ultrasonic waves and input of same implemented in BPNN and Support Vector Machine (SVM) were used for flood forecasting. The water level flow is deducted in this research using ultrasonic sensor, proves the best efficient models applied for flood forecasting. This study can be used as a predicting the flood by choosing the proper Machine Learning (ML) algorithm such as Support Vector Machine (SVM) and Artificial Neural Network (ANN) algorithm for showing higher accuracy. To get more accurate result of the models, three standard statistical performance evaluation parameters, Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and coefficient of determination ( ) were used to analyse the performance of the model developed. As a result, the proposed model proves the most efficiency and accuracy for predicting the flood forecasting

THE METHOD FOR CALCULATIONS THE VERTICAL DISTRIBUTION OF THE FIELDS OF THERMOHALINE CHARACTERISTICS FOR THE BLACK SEA DEEP-WATER AREA BY REMOTE MEASUREMENTS DATA

Problem Statement and Purpose. The results of studies on the development of methods for calculations of the vertical distribution of temperature and salinity fields in the active layer of the Black Sea by remote measurements data was presents in article. To solve the many practical problems, it is necessary to use vertical distribution of hydrological characteristics of the marine environment. Today there isn't an easy way to get a in situ data for evaluation of the vertical distribution of these characteristics. Indirect definitions of the vertical distribution of water temperature and salinity through the development of various methods for the calculation of the vertical profile of water temperature are used to date.Main purpose of this work is to estimate an ability of using of satellite data for calculation of the spatial distribution of thermohaline characteristics (on the example of the Black Sea).Data & Methods. The initial data of the actual water temperature and salinity values were station data or measurement from the ship data (OSD – Ocean Station data), data measured with the help of floats (PFL – Profiling float data) and satellite data of the sea surface temperature.Calculations of the vertical distribution of temperature and salinity fields in the active layer of the Black Sea by remote measurements data are based on original methods developed by the State Institution “Hydroacoustics Branch of Institute of Geophysics of NAS of Ukraine”. The development of methods was based on mathematical, physical and statistical methods of calculation.Study of vertical distribution of water temperature and salinity in the Black Sea were carried out in the deep-water part sea at standard levels (0, 10, 20, 25, 30, 50 meters) in spring – autumn period.Results. In the process of research, the following tasks were solved: the possibility of calculating the speed of sound from the values of water temperature calculated on the basis of satellite information are estimated; the possibility of calculating the salinity of water by the values of water temperature, sound speed in water and hydrostatic pressure are estimated; a method for calculations the vertical distribution of the fields of thermohaline characteristics in the active layer of the Black Sea by remote measurements data has been developed.A prototype of a computer program for calculations the vertical distribution of temperature and salinity fields in the Black Sea based on remote measurements data has been developed. The program automatically determines where and by what equations the vertical distribution of the fields of thermohaline characteristics in the active layer of the Black Sea can be calculated.The initial data for the calculations are only daily satellite data of the sea surface temperature and the month of the year.Designed by us, the prototype of a computer program to calculate the vertical distribution of the fields of thermohaline characteristics in the active layer of the Black Sea based on the remote measurements could serve as a basis for the establishment of a "Operational Forecast System of the fields of thermohaline characteristics in the Black Sea based on the remote measurements" (OFS). With the help of which the dynamics of characteristics and effects of their change on hydrobiological, hydrochemical, hydrophysical processes in the Black Sea and the ecosystem of the sea in general can be evaluated.In our opinion the developed method for calculating of the vertical distribution of the fields of thermohaline characteristics by remote measurements data can be applied to others water area of the World Ocean taking into account their hydrological conditions.

Historical modelling of changes in Lake Erken thermal conditions

Abstract. Historical lake water temperature records are a valuable source of information to assess the influence of climate change on lake thermal structure. However, in most cases such records span a short period of time and/or are incomplete, providing a less credible assessment of change. In this study, the hydrodynamic GOTM (General Ocean Turbulence Model, a hydrodynamic model configured in lake mode) was used to reconstruct daily profiles of water temperature in Lake Erken (Sweden) over the period 1961–2017 using seven climatic parameters as forcing data: wind speed (WS), air temperature (Air T), atmospheric pressure (Air P), relative humidity (RH), cloud cover (CC), precipitation (DP), and shortwave radiation (SWR). The model was calibrated against observed water temperature data collected during the study interval, and the calibrated model revealed a good match between modelled and observed temperature (RMSE =1.089 ∘C). From the long-term simulations of water temperature, this study focused on detecting possible trends in water temperature over the entire study interval 1961–2017 and in the sub-intervals 1961–1988 and 1989–2017, since an abrupt change in air temperature was detected in 1988. The analysis of the simulated temperature showed that epilimnetic temperature increased on average by 0.444 and 0.792 ∘C per decade in spring and autumn in the sub-interval 1989–2017. Summer epilimnetic temperature increased by 0.351 ∘C per decade over the entire interval 1961–2017. Hypolimnetic temperature increased significantly in spring over the entire interval 1961–2017, by 0.148 and by 0.816 ∘C per decade in autumn in the sub-interval 1989–2016. Whole-lake temperature showed a significant increasing trend in the sub-interval 1989–2017 during spring (0.404 ∘C per decade) and autumn (0.789 ∘C per decade, interval 1989–2016), while a significant trend was detected in summer over the entire study interval 1961–2017 (0.239 ∘C per decade). Moreover, this study showed that changes in the phenology of thermal stratification have occurred over the 57-year period of study. Since 1961, the stability of stratification (Schmidt stability) has increased by 5.365 J m−2 per decade. The duration of thermal stratification has increased by 7.297 d per decade, corresponding to an earlier onset of stratification of ∼16 d and to a delay of stratification termination of ∼26 d. The average thermocline depth during stratification became shallower by ∼1.345 m, and surface-bottom temperature difference increased over time by 0.249 ∘C per decade. The creation of a daily time step water temperature dataset not only provided evidence of changes in Erken thermal structure over the last decades, but is also a valuable resource of information that can help in future research on the ecology of Lake Erken. The use of readily available meteorological data to reconstruct Lake Erken's past water temperature is shown to be a useful method to evaluate long-term changes in lake thermal structure, and it is a method that can be extended to other lakes.

OPTIMASI DAYA TETAS TELUR IKAN GURAMI (Osphronemus gouramy, Lac) DENGAN PENGONTROLAN SUHU AIR

This study aims to determine the effect of different temperatures and stocking densities and the hatching rate of Gouramy eggs with Experimental Design of Factorial Complete Randomized Design The main treatments of temperature, including A1: Temperature 28ºC and A2: Temperature 30ºC. The main treatment of stocking density includes B1: Stocking density of 10 pcs/liters and B2: Stocking density of 20 pcs/liters. The results were obtained as follows: Different temperatures did not have a significant effect on the hatching rate of Gouramy eggs. Different stocking densities have a significant effect on the hatching rate of Gouramy eggs. The interaction of temperature and stocking density did not have a significant effect on the hatching rate of Gouramy eggs. From the results of measurements of water quality parameters obtained water temperature data 28 and 30 ° C, pH 7.3 - 8.5 and DO (dissolved oxygen) ranged from 4.68 to 5.00 ppm

Cold-related Florida manatee mortality in relation to air and water temperatures.

Many tropical and subtropical species are sensitive to sudden temperature changes, especially drops in temperature. During winters 2009–2010 and 2010–2011, unusually cold temperatures occurred in many parts of Florida, USA, resulting in increased mortality of Florida manatees, sea turtles, fish, corals, and other species. The Florida manatee, in particular, is highly susceptible to cold stress and death when water temperatures drop below 20°C. We sought to characterize the magnitude and timing of reports of cold-related manatee carcasses in relation to fluctuations in water and air temperatures in central-east and central-west Florida during the six winters from 2008 to 2014. We used a generalized linear model to predict counts of manatee carcasses with a cold-related cause of death reported over 7-day bins in relation to various short-term (two weeks or less) and cumulative (incrementally summed from the start of the winter) heating-degree-day effects (HDD; < 20°C) and a categorical winter variable. Using water temperature data, the top-ranked model in both regions included a short-term temperature effect (14-day HDD sum) that preceded increases in reports of cold-related manatee carcasses by 7 days. Cumulative exposure to cold weather over the winter amplified effects on mortality in the central-east region. Quantifying the relationship between cold events and manatee mortality helps us prepare for rescue and salvage operations when extremely cold weather is forecast. This is especially important because anticipated loss or degradation of warm-water refuges due to human activities and sea level rise could potentially impact the manatee population in the future. These methods could also be applied to other species susceptible to cold-related mortality.

Cod and climate: a systems approach for sustainable fisheries management of Atlantic cod (Gadus morhua) in coastal Danish waters

This study applied the Systems Approach Framework (SAF) to address the issue of declining Atlantic cod fishery in coastal areas. Interviews of 58 fishers from 26 harbours and meetings with national fisheries organisations and managers revealed the perception of an offshore movement of coastal cod. Numerical modelling based on fishing survey data did not substantiate these perceptions in the data-poor coastal waters. However, Data Storage Tag (DST) information combined with bottom sea water temperature data from the spatio-temporal hydrodynamic Baltic Sea Ice-Ocean Model showed changes in potential cod habitat distribution in the Skagerrak-Kattegat and western Baltic from 1979 to 2016. Subsequently, cod habitats were defined in three categories: (i) potentially suitable (T ≤ 12 °C); (ii) episodic (12 16 °C). The environmental changes were linked to the socio-economic component of cod fishery. Cod catches (weight and monetary value) were retrieved using logbook information and data from the Vessel Monitoring System (VMS, 2005–2016) and the Automatic Identification System (AIS, 2006-2016). General additive modelling significantly showed the largest proportion of catches took place in the potentially suitable habitat whereas catches were lower in the episodic habitat and rare in the unsuitable habitat. The results of this first large-scale SAF application are highly valuable for adapting existing fisheries management by: (i) providing information on habitat shrinkage for Maximum Sustainable Yield (MSY) based stock assessments; (ii) adding a spatio-temporal dimension for coastal productivity relative to the vessel-based Individual Transferable Quota (ITQ) system; and (iii) providing a predictive scenario simulation tool for sustainable management under changing environmental conditions.

Keeping an Eye on Wild Brown Trout (Salmo trutta) Populations: Correlation Between Temperature, Environmental Parameters, and Proliferative Kidney Disease.

Proliferative kidney disease (PKD) is an emerging disease of salmonids caused by the myxozoan parasite Tetracapsuloides bryosalmonae, which plays a major role in the decrease of wild brown trout (Salmo trutta) populations in Switzerland. Strong evidence demonstrated that water temperature modulates parasite infection. However, less knowledge exists on how seasonal water temperature fluctuations influence PKD manifestation under field conditions, how further environmental factors such as water quality may modulate the disease, and whether these factors coalesce with temperatures role possibly giving rise to cumulative effects on PKD. The aims of this study were to (1) determine the correlation between seasonal course of water temperature and PKD prevalence and intensity in wild brown trout populations, (2) assess if other factors such as water quality or ecomorphology correlate with the infection, and (3) quantitatively predict the implication of these factors on PKD prevalence with a statistical model. Young-of-the-year brown trout were sampled in 45 sites through the Canton of Vaud (Switzerland). For each site, longitudinal time series of water temperature, water quality (macroinvertebrate community index, presence of wastewater treatment plant effluent) and ecomorphological data were collected and correlated with PKD prevalence and intensity. 251 T. bryosalmonae-infected trout of 1,118 were found (overall prevalence 22.5%) at 19 of 45 study sites (42.2%). Relation between PKD infection and seasonal water temperature underlined that the mean water temperature for June and the number of days with mean temperature ≥15°C were the most significantly correlated parameters with parasite prevalence and intensity. The presence of a wastewater treatment plant effluent was significantly correlated with the prevalence and infection intensity. In contrast, macroinvertebrate diversity and river ecomorphology were shown to have little impact on disease parameters. Linear and logistic regressions highlighted quantitatively the prediction of PKD prevalence depending on environmental parameters at a given site and its possible increase due to rising temperatures. The model developed within this study could serve as a useful tool for identifying and predicting disease hot spots. These results support the importance of temperature for PKD in salmonids and provides evidence for a modulating influence of additional environmental stress factors.

Warm winters reduce landscape-scale variability in the duration of egg incubation for coho salmon (Oncorhynchus kisutch) on the Copper River Delta, Alaska

We quantified the sum of daily mean temperature above 0 °C and modeled incubation duration using water temperature data collected at 12 coho salmon (Oncorhynchus kisutch) spawning sites during two incubation periods with cool, snow-dominant conditions and three incubation periods with anomalously warm, rain-transitional conditions, a proxy for a future climate scenario. Warmer water temperatures during warm–rain-transitional winters yielded a 58-day reduction in the median duration of egg incubation; however, the magnitude of change at individual sites varied widely and was controlled by water source. At groundwater-fed sites, temperature variations were strongly attenuated, leading to small interannual differences in incubation duration that were relatively insensitive to short-term changes in air temperature. In contrast, modeled incubation duration was shortened by up to 3 months during warm–rain-transitional winters at precipitation-fed sites. Remarkably, our modeling showed increased uniformity in incubation duration across the landscape during warm–rain-transitional winters. The potential loss of diversity in incubation duration during warmer winters, in isolation, may reduce portfolio effects in this region’s coho salmon population by promoting greater synchronization in the time of spawning.

Multi-step ahead modelling of river water quality parameters using ensemble artificial intelligence-based approach

In this study, three single Artificial Intelligence (AI) based models i.e., Back Propagation Neural Network (BPNN), Adaptive Neuro Fuzzy Inference System (ANFIS), Support Vector Machine (SVM) and a linear Auto Regressive Integrated Moving Average (ARIMA) model as well as three different ensemble techniques i.e., Simple average ensemble (SAE), weighted average ensemble (WAE) and neural network ensemble (NNE) are applied for single and multi-step ahead modeling of dissolve oxygen (DO) in the Yamuna River, India. In this context, DO, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Discharge (Q), pH, Ammonia (NH3), Water Temperature (WT) data for three different stations i.e., Hathnikund (SL1), Nizamuddin (SL2) and Udi (SL3) recorded by central pollution control board were used. The performance accuracy of the models was determined using Determination Coefficient (DC) and Root Mean Square Error (RMSE). The obtained results of the single models showed that, ANFIS model outperformed all other three models and increased averagely up to 7% and 19% for SL1 and SL2 in performance accuracy while for SL3, SVM model performed better than other models and increased the average performance up to 16%. In the ensemble techniques, the results showed that, for all the three stations, NNE could increase the average performance by single models up to 14% in the verification phase. This justified the reliability and robustness of NNE in multi-step ahead modeling of DO due to its promising ability in solving nonlinear processes.

Multispecies conservation of freshwater fish assemblages in response to climate change in the southeastern United States

AbstractAimStreamflow and water temperature are primary variables influencing the distribution of freshwater taxa. Climate‐induced changes in these variables are already causing shifts in species distributions, with continued changes projected in the coming decades. The Mobile River Basin (MRB), located in the southeastern United States, contains some of the highest levels of temperate freshwater biodiversity in North America. We integrated species distribution data with contemporary and future streamflow and water temperature data as well as other physical habitat data to characterize occurrence probabilities of fish species in the MRB with the goal of identifying current and future areas of high conservation value.LocationMobile River Basin, southeastern United States.MethodsWe used a maximum entropy approach to estimate baseline and future occurrence probability distributions for 88 fish species in the MRB based on model‐generated streamflow and water temperature as well as geologic, topographic and land cover data. Areas of conservation prioritization were identified based on regions that contain suitable habitat for high levels of biodiversity according to baseline and future conditions while accounting for uncertainty associated with multiple future climate projections.ResultsOn average, flow (28%), water temperature (28%) and geology (30%) contribute evenly to determining suitable habitat for fish species in the MRB. Based on baseline and future species distribution model estimates, high priority streams (best 10%) are largely concentrated in the eastern portion of the MRB, with a majority (51%) located within the Coosa and Tallapoosa River systems.Main conclusionWe provide a framework that uses relevant hydrologic and environmental data in the context of future climatic uncertainty to estimate areas of freshwater conservation opportunity in the coming decades. While streamflow and water temperature represent important habitat for freshwater fishes in the MRB, distributions are also constrained by other aspects of the physical environment.

Reexamination of the spawning migration of Anguilla dieffenbachii in relation to water temperature and the lunar cycle

ABSTRACTThe oceanic spawning migration of female Anguilla dieffenbachii eels was previously studied using pop-up satellite transmitting tags (PSAT). The swimming depths and experienced-temperature data of 3 eels released in May 2006 were re-examined in relation to water temperature data, and also lunar cycle and regional hydrography as these latter aspects were not considered in the original study. Eel 2 and Eel 3 initially experienced lower water temperature above 600 m, suggesting they remained south of the subtropical-convergence front longer than Eel 1. Their experienced nighttime minimum depths showed linear relationships with the lunar cycle, because they swam shallower during new moon than during full moon. The eels experienced narrow deep-day temperature ranges at a wide range of depths compared to experiencing narrow shallow-night depth ranges where temperatures varied more widely, indicating that several different factors determine their day and night depth ranges.

Quasi‐Real‐Time and High‐Resolution Spatiotemporal Distribution of Ocean Anthropogenic CO2

AbstractIncreasing marine uptake of anthropogenic CO2 (Cant) causes global ocean acidification. To obtain a high‐resolution spatiotemporal distribution of oceanic carbon chemistry, we developed new parameterizations of the seawater total alkalinity, and dissolved inorganic carbon from the ocean's surface to 2,000‐m depth by using dissolved oxygen, water temperature (T), salinity (S), and pressure (P) data. Using the values of total alkalinity and dissolved inorganic carbon predicted by dissolved oxygen, T, S, and P data derived from autonomous biogeochemical Argo floats, we described the distribution of oceanic Cant in the 2000s in the subarctic North Pacific at high spatiotemporal resolution. The Cant was found about 300 m deeper than during the 1990s; its average inventory to 2,000 m was 24.8 ± 10.2 mol/m2, about 20% higher than the 1990s average. Future application of parameterizations to global biogeochemical Argo floats data should allow the detailed global mapping of spatiotemporal distributions of CO2 parameters.

Monsoonal and annual energy fluxes variations in the atmospheric surface layer over a coastal region of the tropical ocean

The tropical coastal ocean is a vital jigsaw-piece to understanding exchanges of energy, moisture, and carbon between the atmosphere and the ocean biospheres. Latent and sensible heat fluxes, micro-climate variables, and surface water temperature data in the atmospheric surface layer were collected using an instrumented tower at a tropical coastal ocean (5 ∘28’6”N, 100∘12’1”E). The instrumented tower was installed on a stainless-steel platform extending a pre-existing pier. Data were collected for two years, i.e., November 2015 to October 2017, which encompassed two annual cycles of the Monsoons. The first objective of this work is to describe the Monsoonal and annual patterns of latent (LE) and sensible (H) heats while the second objective is to link the micro-climate variables to the energy fluxes on the seasonal and annual time scales. The inter-annual variation of energy input into the study is minimal (3% and 4% in the values recorded for the RG and Rn). The average albedo was 0.29 and the Bowen ratio was 0.11. Annual changes in LE and H between the two years were apparent both at 14% increased and decreased, respectively. LE is largely modulated by the Monsoons, where it is higher in the Northeast Monsoon (dry and hot) than the Southwest Monsoon (wet and cold). Conversely, H did not exhibit appreciably changes with the Monsoon and mostly followed the downward Rn trend. Variations between Monsoons are ten times larger than between years, thus highlighting its significance in controlling the regional conditions. Between the Northeast and Southwest Monsoons, the change in LE, i.e., ΔLE recorded was −30% while that of H, i.e., ΔH was ＋18%. These results have important applications in improving numerical weather models and closing the energy budget.

High‐Resolution Global Water Temperature Modeling

AbstractThe temperature of river water plays a crucial role in many physical, chemical, and aquatic ecological processes. Despite the importance of having detailed information on this environmental variable at locally relevant scales (≤50 km), high‐resolution simulations of water temperature on a large scale are currently lacking. We have developed the dynamical 1‐D water energy routing model (DynWat), that solves both the energy and water balance, to simulate river temperatures for the period 1960–2014 at a nominal 10‐km and 50‐km resolution. The DynWat model accounts for surface water abstraction, reservoirs, riverine flooding, and formation of ice, enabling a realistic representation of the water temperature. We present a novel 10‐km water temperature data set at the global scale for all major rivers, lakes, and reservoirs. Validated results against 358 stations worldwide indicate a decrease in the simulated root‐mean‐square error (0.2 °C) and bias (0.7 °C), going from 50‐ to 10‐km simulations. We find an average global increase in water temperature of 0.16 °C per decade between 1960 and 2014, with more rapid warming toward 2014. Results show increasing trends for the annual daily maxima in the Northern Hemisphere (0.62 °C per decade) and the annual daily minima in the Southern Hemisphere (0.45 °C per decade) for 1960–2014. The high‐resolution modeling framework not only improves the model performance, it also positively impacts the relevance of the simulations for regional‐scale studies and impact assessments in a region without observations. The resulting global water temperature data set could help to improve the accuracy of decision‐support systems that depend on water temperature estimates.

Influence of seasonality, salinity and temperature on catch trend of Penaeus indicus H. Milne-Edwards, 1837 in a coastal lagoon, India

The catch pattern of P. indicus in coastal lagoons is influenced by seasonal changes in physicochemical parameters of the lagoon ecosystem. In this study the effects of seasonality, salinity and water emperature of lagoon on P. indicus catch were analysed using Structural Time Series Model (STSM) and ARIMAX (Auto Regressive Integrated Moving Average with explanatory variables) modeling approach using monthly time series catch, salinity and water temperature data of the Chilika Lagoon (a Ramsar site) in India for the period from 2001 to 2015. Results showed a significant (p&lt;0.05) increasing stochastic upward trend and two seasonal cycles for P. indicus catch in the lagoon. Salinity was found to have significant positive influence (p&lt;0.05) and temperature to have insignificant positive influence on P. indicus catch in the lagoon.

A global assessment of freshwater mollusk shell oxygen isotope signatures and their relation to precipitation and stream water

Records of δ18O in stream flow are critical for understanding and modeling hydrological, ecological, biogeochemical and atmospheric processes. However, the number of such records are extremely limited globally and the length of such time series are usually less than a decade. This situation severely handicaps their use in model testing and evaluation. Here we present a global assessment of freshwater mollusk (bivalves & gastropods) isotope data from 25 river basins that have stream water isotope values, water temperature data and shell material isotope signatures. Our data span a latitude range of 37.50°S to 52.06°N. We show that δ18O signatures in freshwater mollusks are able to explain 95% of the variance of stream water δ18O. We use shell δ18O values and water temperature data to reconstruct stream water δ18O signatures. With freshwater mussel life expectancy ranging from a few years up to 200 years, this translation of mollusk metabolic properties into long term stream water isotope records is a promising approach for substantially extending global stream water isotope records in time and space.

Using ambient noise to evaluate the acoustic Green’s function for a passive geoacoustic inversion in a dynamic shallow-water environment

Cross-correlation functions (CCFs) of ambient and shipping noise recorded by two hydrophones approximate the deterministic Green’s function and contain information about the propagation environment. This paper employs the data collected in the Shallow Water 2006 experiment on the New Jersey continental shelf to investigate the factors that affect the emergence of approximate Green’s functions from noise CCF estimates and accuracy of the approximation. One month-long continuous records of noise obtained by moored single-hydrophone receivers are analyzed. Hydrophones are located in 80–100-m deep water at distances of several kilometers from each other. Rapid variations of the water sound speed profile, which are primarily due to propagation of trains of strong nonlinear internal gravity waves, limit useful noise-averaging time. Available water temperature data are used to guide the selection of time windows for noise averaging and improve CCF evaluation and retrieval of information on seafloor properties. Various approaches to coherent stacking of CCFs are compared. Time warping transform is applied to the resultant noise CCF to extract dispersion curves of acoustic normal modes. The results of the geoacoustic inversion based on the passively measured dispersion curves are compared with the earlier results obtained using controlled sound sources. [Work supported by NSF and BSF.]

ESA Historical Records Committee Newsletter January 2019

ESA Historical Records Committee Newsletter January 2019

KARAKTERISTIK HABITAT KEPITING BAKAU (Scylla sp.) DI EKOSISTEM MANGROVE SILANG CADEK KECAMATAN BAITUSSALAM KABUPATEN ACEH BESAR, PROVINSI ACEH

Research on the characteristics of Mangrove Crab Habit (Scylla sp) in Silang Cadek Mangrove Ecosystem, Baitussalam Subdistrict, Aceh Besar District, Aceh Province. This study aims to determine the habitat characteristics of Mangrove Crab (Scylla sp) in the Mangrove Ecosystem of Silang Cadek. The research method is survey with purposive sampling technique. The results of the survey are described. The results of the research showed that the water temperature data ranged from 22 s.d 25°C, the pH ranged from 7.5 to 7.7, the water salinity ranged from 30‰ -34‰. Substrate loamy sand, sandy loam, sandy clay loam. There are 4 constituent species of mangrove plants namely Bruguiera gymnorrhiza, Rhizopora stylosa, Rhizopora apiculata, Avicennia marina. Macrozoobenthos found were Nerita lineata, Uca crassipes, Terebralia palustris, Terebralia sulcata, Isognomon ephippium, Saccostrea cucculata, Uca demani, Scylla serrata, Scylla olivacea, Scylla paramamosain.