scholarly journals Application of Remote Sensing and GIS Techniques for the Analysis of Lake Water Fluctuations: A Case Study of Ugii Lake, Mongolia

2021 ◽  
Vol 20 (5) ◽  
Author(s):  
Amgalan Magsar ◽  
Toru Matsumoto ◽  
Altanbold Enkhbold ◽  
Nandintsetseg Nyam-Osor
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Surface Area ◽  
Lake Water ◽  
Hydrological Regime ◽  
Water Extraction ◽  
Valuable Insight ◽  
Strong Positive Correlation ◽  
Topographic Map ◽  
Local Climate

Ugii Lake is a freshwater lake located in the steppe region of Mongolia and is an important breeding and staging area for a wide variety of waterfowl. Remote sensing and geographic information system techniques were used to estimate fluctuations in the surface area and water balance of Ugii Lake. To estimate the changes in lake water balance, lake water fluctuations should be analyzed using the most accurate methods. A different water extraction technique was applied, and the results were compared with field surveys conducted in May, July, and September 2020. The lake surface area using both NDWI and MNDWI-1 showed a strong, positive correlation (R=0.93, R=0.94, p < 0.01) with the water level of Ugii Lake. A topographic map of Ugii Lake was provided by the project (P2018-3568) conducted in August 2019 and used to estimate the volume of Ugii Lake in ArcGIS 10.1. This result was consistent with that of a previous study by JICA in 2005. Finally, the water balance of Ugii Lake was estimated, and the results proved that the influence of both surface and groundwater on Ugii Lake are valuable parameters, which are completely dependent on hydrological regime changes mostly due to local climate change in steppe regions. This study provides valuable insight into the most suitable water extraction methods for lakes in semi-arid steppe regions in Mongolia.

scholarly journals Investigation of surface area of lakes and marshes from satellite images by using remote sensing and geographic information system integration in Iraq

2018 ◽  
Vol 162 ◽  
pp. 03016
Author(s):  
Alaa Dawood ◽  
Yousif Kalaf ◽  
Nagham Abdulateef ◽  
Mohammed Falih
Keyword(s):  
Remote Sensing ◽  
Surface Area ◽  
System Integration ◽  
Hydrological Regime ◽  
Remotely Sensed ◽  
Total Surface Area ◽  
Water Levels ◽  
Remotely Sensed Data ◽  
Surface Areas ◽  
Water Volumes

Water level and distribution is very essential in almost all life aspects. Natural and artificial lakes represent a large percentage of these water bodies in Iraq. In this research the changes in water levels are observed by calculating the areas of five different lakes in five different regions and two different marshes in two different regions of the country, in a period of 12 years (2001 - 2012), archived remotely sensed images were used to determine surface areas around lakes and marshes in Iraq for the chosen years . Level of the lakes corresponding to satellite determined surface areas were retrieved from remotely sensed data .These data were collected to give explanations on lake level and surface area fluctuations. It is important to determine these areas at different water levels to know areas which are being flooded in addition to the total area inundated .The behavior of hydrological regime of these lakes during the period was assessed using an integration of remote sensing and GIS techniques which found that the total surface area of the lakes had diminished and their water volumes reduced. The study further revealed that the levels of the lakes surfaces had lowered through these years.

scholarly journals Empirical attribution of a drying Himalayan river through remote sensing and secondary data

2021 ◽  
Author(s):  
Gopal Penny ◽  
Zubair A. Dar ◽  
Marc F. Müller
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Water Policy ◽  
Secondary Data ◽  
Hydrological Regime ◽  
Hydrological Processes ◽  
Indus Basin ◽  
Hydrological Models ◽  
Catchment Scale ◽  
Holistic Understanding

Abstract. Streamflow regimes are rapidly changing in many regions of the world. The ability to attribute these changes to specific hydrological processes and their underlying climatic and anthropogenic drivers is essential to formulate effective water policy. Traditional approaches to hydrologic attribution rely on the ability to infer hydrological processes through the development of catchment-scale hydrological models. However, such approaches are challenging to implement in practice. In particular, models have difficulty capturing hydrological regime shifts, where changes in the dominant hydrological processes alters the relationship among hydrological fluxes. Additionally, observational uncertainties might preclude closure of the catchment-scale water balance, which is a pre-requisite for most catchment-scale hydrological models. Here we present an alternative approach to hydrological attribution that leverages the method of multiple hypotheses. We generate and empirically evaluate a series of alternative and complementary hypotheses that pertain to hydrological change. These hypotheses concern distinct components of the water balance and are evaluated independently. This process allows a holistic understanding of watershed-scale processes to be developed, even if the catchment-scale water balance remains open. We apply the approach to understand changes in the Upper Jhelum river, an important tributary headwaters of the Indus basin, where streamflow has declined dramatically since 2000 and has yet to be adequately attributed to its corresponding drivers. Using remote sensing and secondary data collected from the watershed, we explore changes in climate, surface water, and groundwater. The evidence reveals that climate, rather than land use, had a considerably stronger influence on reductions in streamflow, both through reduced precipitation and increased evapotranspiration.

Potential of water balance and remote sensing-based evapotranspiration models to predict yields of spring barley and winter wheat in the Czech Republic

2021 ◽  
Vol 256 ◽  
pp. 107064
Author(s):  
František Jurečka ◽  
Milan Fischer ◽  
Petr Hlavinka ◽  
Jan Balek ◽  
Daniela Semerádová ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Czech Republic ◽  
Water Balance ◽  
Winter Wheat ◽  
Spring Barley ◽  
The Czech Republic

Hydrological regime, water availability and land use/land cover change impact on the water balance in a large agriculture basin in the Southern Brazilian Amazon

2021 ◽  
Vol 108 ◽  
pp. 103224
Author(s):  
Tárcio Rocha Lopes ◽  
Cornélio Alberto Zolin ◽  
Rafael Mingoti ◽  
Laurimar Gonçalves Vendrusculo ◽  
Frederico Terra de Almeida ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Water Balance ◽  
Land Cover Change ◽  
Water Availability ◽  
Hydrological Regime ◽  
Brazilian Amazon ◽  
Land Use Land Cover ◽  
Change Impact

scholarly journals Using a Groundwater Adjusted Water Balance Approach and Copulas to Evaluate Spatial Patterns and Dependence Structures in Remote Sensing Derived Evapotranspiration Products

2021 ◽  
Vol 13 (5) ◽  
pp. 853
Author(s):  
Mohsen Soltani ◽  
Julian Koch ◽  
Simon Stisen
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Principal Component ◽  
Small Scale ◽  
Dependence Structure ◽  
Test Case ◽  
Catchment Scale ◽  
Balance Approach

This study aims to improve the standard water balance evapotranspiration (WB ET) estimate, which is typically used as benchmark data for catchment-scale ET estimation, by accounting for net intercatchment groundwater flow in the ET calculation. Using the modified WB ET approach, we examine errors and shortcomings associated with the long-term annual mean (2002–2014) spatial patterns of three remote-sensing (RS) MODIS-based ET products from MODIS16, PML_V2, and TSEB algorithms at 1 km spatial resolution over Denmark, as a test case for small-scale, energy-limited regions. Our results indicate that the novel approach of adding groundwater net in water balance ET calculation results in a more trustworthy ET spatial pattern. This is especially relevant for smaller catchments where groundwater net can be a significant component of the catchment water balance. Nevertheless, large discrepancies are observed both amongst RS ET datasets and compared to modified water balance ET spatial pattern at the national scale; however, catchment-scale analysis highlights that difference in RS ET and WB ET decreases with increasing catchment size and that 90%, 87%, and 93% of all catchments have ∆ET < ±150 mm/year for MODIS16, PML_V2, and TSEB, respectively. In addition, Copula approach captures a nonlinear structure of the joint relationship with multiple densities amongst the RS/WB ET products, showing a complex dependence structure (correlation); however, among the three RS ET datasets, MODIS16 ET shows a closer spatial pattern to the modified WB ET, as identified by a principal component analysis also. This study will help improve the water balance approach by the addition of groundwater net in the ET estimation and contribute to better understand the true correlations amongst RS/WB ET products especially over energy-limited environments.

An assessment of the Dead Sea level change using remotely sensed data

2021 ◽  
Author(s):  
Musab Mbideen ◽  
Balázs Székely
Keyword(s):  
Remote Sensing ◽  
Water Level ◽  
Surface Area ◽  
Dead Sea ◽  
Spectral Radiance ◽  
Water Volume ◽  
Surface Model ◽  
Atmospheric Effects ◽  
Level 1 ◽  
The Dead

&lt;p&gt;Remote Sensing (RS) and Geographic Information System (GIS) instruments have spread rapidly in recent years to manage natural resources and monitor environmental changes. Remote sensing has a vast range of applications; one of them is lakes monitoring. The Dead Sea (DS) is subjected to very strong evaporation processes, leading to a remarkable shrinkage of its water level. The DS is being dried out due to a negative balance in its hydrological cycle during the last five decades. This research aims to study the spatial changes in the DS throughout the previous 48 years. Change detection technique has been performed to detect this change over the research period (1972-2020). 73 Landsat imageries have been used from four digital sensors; Landsat&amp;#160;1-5 MSS C1 Level-1, Landsat&amp;#160;4-5 TM C1 Level-1, Land&amp;#160;sat&amp;#160;7&amp;#160;ETM+ C1 &amp;#160;Level-1, and Landsat&amp;#160;8 OLI-TIRS C1 Level. After following certain selection criteria , the number of studied images decreased. Furthermore, the Digital Surface Model of the Space Shuttle Radar Topography Mission and a bathymetric map of the Dead Sea were used. The collected satellite imageries were pre-processed and normalized using ENVI 5.3 software by converting the Digital Number (DN) to spectral radiance, the spectral radiance was converted to apparent reflectance, atmospheric effects were removed, and finally, the black gaps were removed. It was important to distinguish between the DS lake and the surrounding area in order to have accurate results, this was done by performing classification techniques. The digital terrain model of the DS was used in ArcGIS (3D) to reconstruct the elevation of the shore lines. This model generated equations to detect the water level, surface area, and water volume of the DS. The results were compared to the bathymetric data as well. The research shows that the DS water level declined 65&amp;#160;m (1.35&amp;#160;m/a) in the studied period. The surface area and the water volume declined by 363.56&amp;#160;km&lt;sup&gt;2 &lt;/sup&gt;(7.57&amp;#160;km&lt;sup&gt;2&lt;/sup&gt;/a) and 53.56&amp;#160;km&lt;sup&gt;3&lt;/sup&gt; (1.11&amp;#160;km&lt;sup&gt;3&lt;/sup&gt;/a), respectively. The research also concluded that due to the bathymetry of the DS, the direction of this shrinkage is from the south to the north. We hypothesize that anthropogenic effects have contributed in the shrinkage of the DS more than the climate. The use of the DS water by both Israel and Jordan for industrial purposes is the main factor impacting the DS, another factor is the diversion of the Jordan and Yarmouk rivers. Our results also allow to give a prediction for the near future of the DS: the water level is expected to reach &amp;#8211;445&amp;#160;m in 2050, while the surface area and the water volume is expected to be 455&amp;#160;km&lt;sup&gt;2&lt;/sup&gt; and 142&amp;#160;km&lt;sup&gt;3&lt;/sup&gt;, respectively.&amp;#160;&lt;/p&gt;

scholarly journals Comparing of Landsat 8 and Sentinel 2A using Water Extraction Indexes over Volta River

2017 ◽  
Vol 10 (1) ◽  
pp. 1 ◽  
Author(s):  
Clement Kwang ◽  
Edward Matthew Osei Jnr ◽  
Adwoa Sarpong Amoah
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Unsupervised Classification ◽  
Water Bodies ◽  
Water Extraction ◽  
Landsat 8 ◽  
Sensing Data ◽  
Optimal Classifier ◽  
Sentinel 2A

Remote sensing data are most often used in water bodies’ extraction studies and the type of remote sensing data used also play a crucial role on the accuracy of the extracted water features. The performance of the proposed water indexes among the various satellite images is not well documented in literature. The proposed water indexes were initially developed with a particular type of data and with advancement and introduction of new satellite images especially Landsat 8 and Sentinel, therefore the need to test the level of performance of these water indexes as new image datasets emerged. Landsat 8 and Sentinel 2A image of part Volta River was used. The water indexes were performed and then ISODATA unsupervised classification was done. The overall accuracy and kappa coefficient values range from 98.0% to 99.8% and 0.94 to 0.98 respectively. Most of water bodies enhancement indexes work better on Sentinel 2A than on Landsat 8. Among the Landsat based water bodies enhancement ISODATA unsupervised classification, the modified normalized water difference index (MNDWI) and normalized water difference index (NDWI) were the best classifier while for Sentinel 2A, the MNDWI and the automatic water extraction index (AWEI_nsh) were the optimal classifier. The least performed classifier for both Landsat 8 and Sentinel 2A was the automatic water extraction index (AWEI_sh). The modified normalized water difference index (MNDWI) has proved to be the universal water bodies enhancement index because of its performance on both the Landsat 8 and Sentinel 2A image.

A simple distributed water balance model for an urbanized river basin using remote sensing and GIS techniques

2019 ◽  
Vol 35 (9) ◽  
pp. 954-975
Author(s):  
Olutoyin Adeola Fashae ◽  
Rotimi Oluseyi Obateru ◽  
Adeyemi Oludapo Olusola
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
River Basin ◽  
Remote Sensing And Gis ◽  
Water Balance Model ◽  
Balance Model ◽  
Gis Techniques
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