scholarly journals SPATIO-TEMPORAL WATER QUALITY MAPPING USING SATELLITE DATA AROUND A MANGROVE PLANTATION IN CAGSAO, CALABANGA, CAMARINES SUR

2021 ◽  
Vol XLVI-4/W6-2021 ◽  
pp. 257-264
Author(s):  
K. C. M. Saddi
Keyword(s):  
Water Quality ◽  
Image Processing ◽  
Mangrove Forest ◽  
Satellite Images ◽  
River Mouth ◽  
Image Data ◽  
The United States ◽  
Point Sources ◽  
Spatio Temporal ◽  
Water Quality Mapping

Abstract. The Cagsao mangrove is a thriving young forest along the San Miguel Bay (SMB), Camarines Sur. To establish the Spatio-temporal Water Quality mapping, data from the Chesapeake Bay, an estuary in the United States of America (USA), was sourced as the train set for this study. Spatio-temporal maps of chlorophyll and dissolved oxygen were generated using Linear Regression (LR) models which were derived from the train set and satellite images of the SMB. GNU (GNU’s not UNIX) Octave was used for the image processing, computing, and analysis. There were three phases in the image processing conducted in this study, 1) extraction of image data of the corresponding measure points from the train area, 2) conversion of the satellite study area to a two-color raster image, and 3) generation of the spatio-temporal maps from the analysis. The study found that the SMB is in the range of Mesotrophic to Moderate Eutrophic classification. The decay from two other point sources (Manga River and Libmanan River) was compared to that of Tigman River, an adjacent river to the Cagsao mangrove forest to determine variations and impact of the mangrove forest in the water quality of the SMB. The presence of Cagsao mangrove forest was found to affect the gap of increasing chlorophyll levels from shore toward the bay center in the adjacent Tigman River unlike Manga River and Libmanan River, which have both no adjacent mangrove forest in the river mouth area. The corresponding satellite images for the dataset taken during and near the date of the train area measurements were also extracted.

scholarly journals Spatio-Temporality and Tribal Water Quality Governance in the United States

Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 99 ◽  
Author(s):  
Teresa Cavazos Cohn ◽  
Kate Berry ◽  
Kyle Powys Whyte ◽  
Emma Norman
Keyword(s):  
United States ◽  
Water Quality ◽  
Water Governance ◽  
Dynamic Network ◽  
The United States ◽  
Space Time ◽  
Cultural Bias ◽  
Ontological Pluralism ◽  
Political Relationships ◽  
Spatio Temporal

Hydrosocial spatio-temporalities—aspects of water belonging to space, time, or space-time—are central to water governance, providing a framework upon which overall hydrosocial relations are constructed, and are fundamental to the establishment of values and central to socio-cultural-political relationships. Moreover, spatio-temporal conceptions may differ among diverse governing entities and across scales, creating “variability” through ontological pluralism, as well as power asymmetries embedded in cultural bias. This paper explores spatio-temporal conceptions related to water quality governance, an aspect of water governance often biased toward technical and scientific space-time conceptions. We offer examples of different aspects of spatio-temporality in water quality issues among Tribes in the United States, highlighting several themes, including spatiotemporal cycles, technological mediation, and interrelationship and fluidity. Finally, we suggest that because water is part of a dynamic network of space-times, water quality may be best governed through more holistic practices that recognize tribal sovereignty and hydrosocial variability.

An Application of Landsat-5TM Image Data for Water Quality Mapping in Lake Beysehir, Turkey

2010 ◽  
Vol 212 (1-4) ◽  
pp. 183-197 ◽  
Author(s):  
Bilgehan Nas ◽  
Semih Ekercin ◽  
Hakan Karabörk ◽  
Ali Berktay ◽  
David J. Mulla
Keyword(s):  
Water Quality ◽  
Image Data ◽  
Water Quality Mapping ◽  
Lake Beysehir

Assessment of the Klang River Quality Using the Water Quality Indices

2012 ◽  
Vol 599 ◽  
pp. 237-240 ◽  
Author(s):  
Faridah Othman ◽  
Mohamed Elamin Alaa Eldin
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Water Quality Index ◽  
Quality Index ◽  
River Mouth ◽  
Peninsular Malaysia ◽  
Point Sources ◽  
Quality Data ◽  
Commercial Activity ◽  
Water Quality Data

The Klang river basin is located within the state of Selangor and Kuala Lumpur, Malaysia. The Klang River drains an area of 1,288 km2 from the steep mountain rain forests of the main Central Range along Peninsular Malaysia to the river mouth in Port Klang, covering a distance of 120 km. It originates from the northern part of Selangor, drains the Klang Valley, and finally discharges itself into the Straits of Malacca. The pollution discharges for various locations along the river basin was obtained from the Water Quality and GIS group. The pollutants can come from point sources (PS) such as industrial wastewater, municipal sewers, wet market, sand mining and landfill. Pollutants can also come from non-point sources (NPS) such as agricultural or urban runoff, and commercial activity such as forestry, and construction due to rainfall event. Mathematical–computational modeling of river water quality is possible but requires an extensive validation. Besides it requires previous knowledge of hydraulics and hydrodynamics. To overcome these difficulties, a water quality index (WQI) was developed. The water quality index (WQI) is a mathematical instrument used to transform large quantities of water quality data into a single number. The purpose of this research is to classify the upstream and downstream of the Klang main river based on WQI value.

scholarly journals PENGARUH PERUBAHAN LUAS HUTAN MANGROVE TERHADAP KONSENTRASI TOTAL SUSPENDED MATTER (TSM) DI MUARA PERANCAK, JEMBRANA – BALI

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Komang Iwan Suniada
Keyword(s):  
Suspended Matter ◽  
Mangrove Forest ◽  
Satellite Image ◽  
River Mouth ◽  
Remote Sensing Data ◽  
Image Data ◽  
Mangrove Ecosystem ◽  
Total Suspended Matter ◽  
Forest Area ◽  
Mangrove Forests

Study of the function of mangrove forests as a sediment trap has been largely undertaken using field measurement methods, but only a few researches that fully utilize remote sensing data to find out the influence of mangrove forest’s area changes against the Total Suspended Matter (TSM) making this study very interesting and important to do.  This research was conducted in Perancak estuary area which is one of mangrove ecosystem area in Bali besides West Bali National Park, Benoa Forest Park and Nusa Lembongan. The data used to generate TSM information and change of mangrove forest area in this research is medium resolution satellite image data, Landsat.  Tidal data and rainfall data were used as a supporting data. The information of TSM concentration obtained by using Budhiman (2004) algorithm, shows that along with the increasing of mangrove forest area has caused the decreasing of TSM concentration at mouth Perancak river. The decline was caused by sediments trapped and settled around trees or mangrove roots, especially the Rhizophora mangroves. In addition to the increasing of mangrove forest area, the tidal oceanography factor also greatly influences the TSM fluctuation around Perancak river mouth. 

Water quality trading in the United States: trading programs and one-time offset agreements

Water Policy ◽  
2007 ◽  
Vol 10 (1) ◽  
pp. 73-93 ◽  
Author(s):  
Cynthia Morgan ◽  
Ann Wolverton
Keyword(s):  
United States ◽  
Water Quality ◽  
Primary Source ◽  
The United States ◽  
Point Sources ◽  
Dartmouth College ◽  
Water Quality Trading ◽  
The Usa ◽  
Time Offset ◽  
Trading Program

This paper provides a systematic overview of water quality trading programs and one-time offset agreements in the USA. The primary source of information for this overview is a detailed database, collected and compiled by a team of researchers at Dartmouth College. Details discussed include: sources of the pollutant, types of pollutants traded, legal liability, main regulatory drivers, market structure, trading ratios, transaction and administrative costs and difficulties encountered in trading. We find that trading has often been explored as a way to meet more stringent discharge limits or watershed-wide caps. The most common type of trading program in the United States is between point sources and non-point sources. Point sources are usually held liable for non-point source reductions. The pollutants most commonly traded in the USA are nutrients such as phosphorus and nitrogen and almost all offset and trading programs focus on one pollutant only. However, market structures, trading ratios and other details of the trading framework vary widely among programs. No single characteristic appears to be a good predictor of a successful trading program.

scholarly journals Spatio-temporal controls of C–N–P dynamics across headwater catchments of a temperate agricultural region from public data analysis

2021 ◽  
Vol 25 (5) ◽  
pp. 2491-2511
Author(s):  
Stella Guillemot ◽  
Ophelie Fovet ◽  
Chantal Gascuel-Odoux ◽  
Gérard Gruau ◽  
Antoine Casquin ◽  
...  
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Spatial Variability ◽  
Base Flow ◽  
Point Sources ◽  
Quality Data ◽  
Flow Index ◽  
Annual Maximum ◽  
Headwater Catchments ◽  
Spatio Temporal

Abstract. Characterizing and understanding spatial variability in water quality for a variety of chemical elements is an issue for present and future water resource management. However, most studies of spatial variability in water quality focus on a single element and rarely consider headwater catchments. Moreover, they assess few catchments and focus on annual means without considering seasonal variations. To overcome these limitations, we studied spatial variability and seasonal variation in dissolved C, N, and P concentrations at the scale of an intensively farmed region of France (Brittany). We analysed 185 headwater catchments (from 5–179 km2) for which 10-year time series of monthly concentrations and daily stream flow were available from public databases. We calculated interannual loads, concentration percentiles, and seasonal metrics for each element to assess their spatial patterns and correlations. We then performed rank correlation analyses between water quality, human pressures, and soil and climate features. Results show that nitrate (NO3) concentrations increased with increasing agricultural pressures and base flow contribution; dissolved organic carbon (DOC) concentrations decreased with increasing rainfall, base flow contribution, and topography; and soluble reactive phosphorus (SRP) concentrations showed weaker positive correlations with diffuse and point sources, rainfall and topography. An opposite pattern was found between DOC and NO3: spatially, between their median concentrations, and temporally, according to their seasonal cycles. In addition, the quality of annual maximum NO3 concentration was in phase with maximum flow when the base flow index was low, but this synchrony disappeared when flow flashiness was lower. These DOC–NO3 seasonal cycle types were related to the mixing of flow paths combined with the spatial variability of their respective sources and to local biogeochemical processes. The annual maximum SRP concentration occurred during the low-flow period in nearly all catchments. This likely resulted from the dominance of P point sources. The approach shows that despite the relatively low frequency of public water quality data, such databases can provide consistent pictures of the spatio-temporal variability of water quality and of its drivers as soon as they contain a large number of catchments to compare and a sufficient length of concentration time series.

scholarly journals Spatio-temporal controls of C-N-P dynamics across headwater catchments of a temperate agricultural region from public data analysis

2020 ◽  
Author(s):  
Stella Guillemot ◽  
Ophelie Fovet ◽  
Chantal Gascuel-Odoux ◽  
Gérard Gruau ◽  
Antoine Casquin ◽  
...  
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Spatial Variability ◽  
Base Flow ◽  
Point Sources ◽  
Quality Data ◽  
Flow Index ◽  
Annual Maximum ◽  
Headwater Catchments ◽  
Spatio Temporal

Abstract. Characterizing and understanding spatial variability in water quality for a variety of chemical elements is an issue for present and future water resource management. However, most studies of spatial variability in water quality focus on a single element and rarely consider headwater catchments. Moreover, they assess few catchments and focus on annual means without considering seasonal variations. To overcome these limitations, we studied spatial variability and seasonal variation in dissolved C, N, and P concentrations at the scale of an intensively farmed region of France (Brittany). We analyzed 185 headwater catchments (from 5–179 km2) for which 10-year time series of monthly concentrations and daily stream flow were available from public databases. We calculated interannual loads, concentration percentiles, and seasonal metrics for each element to assess their spatial patterns and correlations. We then performed rank correlation analyses between water quality, human pressures, and soil and climate features. Results show that nitrate (NO3) concentrations increased with increasing agricultural pressures and base flow contribution; dissolved organic carbon (DOC) concentrations decreased with increasing rainfall, base flow contribution, and topography; and soluble reactive phosphorus (SRP) concentrations showed weaker positive correlations with diffuse and point sources, rainfall and topography. An opposite pattern was found between DOC and NO3: spatially, between their median concentrations, and temporally, according to their seasonal cycles. The annual maximum NO3 concentration was in-phase with maximum flow when the base flow index was low, but this synchrony disappeared when flow flashiness was lower. The annual maximum SRP concentration occurred during the low-flow period in nearly all catchments. The approach shows that despite the relatively low frequency of public water quality data, such databases can provide consistent pictures of the spatio-temporal variability of water quality and of its drivers as soon as they contain a large number of catchments to compare and a sufficient length of concentration time series.

scholarly journals Integration of remote sensing, RUSLE and GIS to model potential soil loss and sediment yield (SY)

2013 ◽  
Vol 10 (4) ◽  
pp. 4567-4596 ◽  
Author(s):  
H. Kamaludin ◽  
T. Lihan ◽  
Z. Ali Rahman ◽  
M. A. Mustapha ◽  
W. M. R. Idris ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
River Water ◽  
Sediment Yield ◽  
Soil Loss ◽  
Satellite Images ◽  
River Mouth ◽  
Geographical Information ◽  
Rainfall Erosivity ◽  
Potential Soil Loss

Abstract. Land use activities within a basin serve as one of the contributing factors which cause deterioration of river water quality through its potential effect on erosion. Sediment yield in the form of suspended solid in the river water body which is transported to the coastal area occurs as a sign of lowering of the water quality. Hence, the aim of this study was to determine potential soil loss using the Revised Universal Soil Loss Equation (RUSLE) model and the sediment yield, in the Geographical Information Systems (GIS) environment within selected sub-catchments of Pahang River Basin. RUSLE was used to estimate potential soil losses and sediment yield by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using field measurement and soil map, vegetation cover (C) using satellite images, topography (LS) using DEM and conservation practices (P) using satellite images. The results indicated that the rate of potential soil loss in these sub-catchments ranged from very low to extremely high. The area covered by very low to low potential soil loss was about 99%, whereas moderate to extremely high soil loss potential covered only about 1% of the study area. Sediment yield represented only 1% of the potential soil loss. The sediment yield (SY) value in Pahang River turned out to be higher closer to the river mouth because of the topographic character, climate, vegetation type and density, and land use within the drainage basin.

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