Predicting the Impact of Coastal Development on Water Quality Using Remote Sensing and GIS‐assisted Hydrologic Modeling Techniques

The study of shoreline changes is essential for updating the changes in shoreline maps and management of natural resources as the shoreline is one of the most important features on the earth’s surface. Shorelines are the key element in coastal GIS that provide information on coastal landform dynamics. The purpose of this paper is to investigate shoreline changes in the study area and how it affects surface water quality using Landsat imagery from 1987 to 2016. The image processing techniques adopted involves supervised classification, object-based image analysis, shoreline extraction and image enhancement. The data obtained was analyzed and maps were generated and then integrated in a GIS environment. The results indicate that LULC changes in wetland areas increases rapidly during the years (1987-2016) from 34.83 to 38.96%, vegetation cover reduces drastically through the year which range from 30% to 20%. Polluted surface water was observed to have decreased from 30% to 20% during 1984-2010 and reduced by about 3% in 2016. In addition, the result revealed the highest level of erosion from 1987 to 2016 which is -49.60% against the highest level of accretion of 13.39% EPR and NSM -1400 erosion against 350 accretions. It was also observed that variations in shoreline changes affect the quality of surface water possibly due to shoreline movement hinterland. This study has demonstrated that through satellite remote sensing and GIS techniques, the Nigerian coastline can adequately be monitored for various changes that have taken place over the years.Key Words: Shoreline, Remote Sensing, Erosion, Accretion, GIS

Download Full-text

An Investigation on Sudden Change in Water Quality of Brahmaputra River Using Remote Sensing and GIS

National Academy Science Letters ◽

10.1007/s40009-020-00938-8 ◽

2020 ◽

Vol 43 (7) ◽

pp. 619-623

Author(s):

Thota Sivasankar ◽

Suranjana B. Borah ◽

Ranjit Das ◽

P. L. N. Raju

Keyword(s):

Remote Sensing ◽

Water Quality ◽

Sudden Change ◽

Remote Sensing And Gis ◽

Brahmaputra River

Download Full-text

Assessing the impact of arid area urbanization on flash floods using GIS, remote sensing, and HEC-HMS rainfall–runoff modeling

Hydrology Research ◽

10.2166/nh.2016.133 ◽

2016 ◽

Vol 47 (6) ◽

pp. 1142-1160 ◽

Cited By ~ 22

Author(s):

Mohamed El Alfy

Keyword(s):

Remote Sensing ◽

Hydrologic Modeling ◽

Integrated Approach ◽

Flash Floods ◽

Landsat 8 ◽

Arid Areas ◽

Rainfall Runoff ◽

Rapid Urbanization ◽

Runoff Modeling ◽

The Impact

This study uses an integrated approach, bringing together geographic information system (GIS), remote sensing, and rainfall–runoff modeling, to assess the urbanization impact on flash floods in arid areas. Runoff modeling was carried out as a function of the catchment characteristics and the maximum daily rainfall parameters. Land-use types were extracted from the supervised classification of SPOT-5 (2010) and Landsat-8 (2015) satellite images and were validated during field checks. Catchment morphometric characteristics were carried out using the correlated Topaz and Arc-Hydro tools. Maximum floods of the catchment were evaluated by coupling GIS and remote sensing with Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) hydrologic modeling. Peak discharges were estimated, and the abstraction losses were computed for different return periods. The model results were calibrated according to actual runoff event. The research shows that rapid urbanization adversely affects hydrological processes, since the sprawl on the alluvial channels is significant. This reduces infiltration into the underlying alluvium and increases runoff, leading to higher flood peaks and volumes even for short duration low intensity rainfall. To retain a considerable amount of water and sediments in these arid areas, construction of small dams at the fingertip channels at the outlet of the lower order sub-basins is recommended.

Download Full-text

The joint application of remote sensing and GIS technologies to network-based hydrologic modeling

IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174) ◽

10.1109/igarss.1998.699669 ◽

1998 ◽

Author(s):

Cheng-Hua Leu

Keyword(s):

Remote Sensing ◽

Hydrologic Modeling ◽

Remote Sensing And Gis ◽

Gis Technologies ◽

Joint Application

Download Full-text

Remote sensing and GIS application for river runoff and water quality modeling in a hilly forested watershed of Japan

Journal of Hydroinformatics ◽

10.2166/hydro.2010.055 ◽

2010 ◽

Vol 13 (2) ◽

pp. 198-216 ◽

Cited By ~ 3

Author(s):

Binaya R. Shivakoti ◽

Shigeo Fujii ◽

Shuhei Tanaka ◽

Hirotaka Ihara ◽

Masashi Moriya

Keyword(s):

Remote Sensing ◽

Water Quality ◽

Land Cover ◽

Spatial Information ◽

Remote Sensing And Gis ◽

Water Quality Modeling ◽

Model Verification ◽

Modeling Framework ◽

Area Index ◽

Distributed Modeling

The main objective of this study is to present a simplified distributed modeling framework based on the storage balance concept of a Tank Model and by utilizing inputs from remote sensing data and GIS analysis. The modeling process is simplified by (1) minimizing the number of parameters with unknown values and 2) retaining important characteristics (such as land cover, topography, geology) of the study area in order to account for spatial variability. Remote sensing is used as a main source of distributed data and the GIS environment is used to integrate spatial information into the model. Remote sensing is utilized mainly to derive land cover, leaf area index (Lai) and transpiration coefficient (Tc). Topographic variables such as slope, drainage direction and soil topographic index (Tindex) are derived from a digital elevation model (DEM) using GIS. The model is used to estimate evapotranspiration (Et) loss, river flow rate and selected water quality parameters (CODMn and TP). Model verification adopted a comparison of estimated results with observed data collected at different temporal scales (storm events, daily, alternate days and every 10 days). A simplified distributed modeling framework coupled with remote sensing and GIS is expected to be an alternative to complex distributed modeling processes, which required values of parameters usually unavailable at a grid scale.

Download Full-text

USING REMOTE SENSING AND GIS TECHNIQUES TO DETECT CHANGES TO THE PRINCE ALFRED HAMLET CONSERVATION AREA IN THE WESTERN CAPE, SOUTH AFRICA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b7-475-2016 ◽

2016 ◽

Vol XLI-B7 ◽

pp. 475-481

Author(s):

P. Duncan ◽

M. Lewarne

Keyword(s):

Remote Sensing ◽

Natural Resources ◽

Source Area ◽

Remote Sensing And Gis ◽

Western Cape ◽

Human Settlement ◽

Conservation Areas ◽

Conservation Area ◽

Gis Techniques ◽

The Impact

Understanding and identifying the spatial-temporal changes in the natural environment is crucial for monitoring and evaluating conservation efforts, as well as understanding the impact of human activities on natural resources, informing responsible land management, and promoting better decision-making. Conservation areas are often under pressure from expanding farming and related industry, invasive alien vegetation, and an ever-increasing human settlement footprint. This study focuses on detecting changes to the Prince Alfred Hamlet commonage, near Ceres in the Cape Floral Kingdom. It was chosen for its high conservation value and significance as a critical water source area. The study area includes a fast-growing human settlement footprint in a highly productive farming landscape. There are conflicting development needs as well as risks to agricultural production, and both of these threaten the integrity of the ecosystems which supply underlying services to both demands on the land. Using a multi-disciplinary approach and high-resolution satellite imagery, land use and land cover changes can be detected and classified, and the results used to support the conservation of biodiversity and wildlife, and protect our natural resources. The aim of this research is to study the efficacy of using remote sensing and GIS techniques to detect changes to critical conservation areas where disturbances can be understood, and therefore better managed and mitigated before these areas are degraded beyond repair.

Download Full-text