This study uses geospatial technique to analyze the spatio-temporal changes of West Rapti River Channel from 1990 to 2023, to assess their impact in Deukhuri Valley. Using freely available Landsat satellite imagery we extracted water surface features through the Normalized Difference Water Index (NDWI) and generated 27 cross-sections (CS) to track channel shift. The results indicated the significant shifts, notably 1426.97 m northeast shift in CS-23 and 718.55 m south shift in CS-25 attributed to sand deposition during flooding. Nearly no shifting impact was observed from CS-12 to CS-17 showing embankment and mitigation efforts being effective within this range. Study shows river is naturally multi-channeled and exhibits braided planform with sinuosity index values ranging from 1.02 to 1.38, indicating highly braided during 2010 and 2015. The river channel was found to be driven by a high sediment deposit of about 15.35 Sq. km across the 53 km range. These results are crucial for formulating integrated river basin management plans in the West Rapti River basin laying foundation for future research to explore sustainable management practices in the future.
Research Article
GIS and Remote Sensing Based Assessment of West Rapti River Channel Migration in Nepal
https://doi.org/10.21203/rs.3.rs-4319789/v1
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Landsat
NDWI
River Channel Migration
West Rapti River
Sinuosity
Braided
Geospatial techniques have become the most frequently utilized technique for the study of diverse types of alluvial river channel planform dynamics, and their geomorphology [1, 33, 54]. River Channel Shifting, the geomorphological process mainly driven by the combination of bank erosion and point bar deposition over time [15] associated with the natural process of meandering [21], where a river forms sinuous curves [56] or bends as the river flows tends to shift river laterally within its floodplain [40, 72]. Over time, these bends can migrate laterally, causing the river channel to shift its position. Globally, many studies in fluvial geomorphology have been applying geospatial technology, such as those in the United States on the Lower Yuba River and Lower Mississippi River [28, 25], China on the Yellow River and the Ningxia-Inner Mongolia reaches of the Yellow River [69, 71, 72], Australia on the lower Pages River [20], Italy’s Piave river and Tammaro River [36, 59] , the Manu River of East India [17], Jamuna River of Bangladesh [11, 29], Spain on Jarama and Tagus rivers and several rivers reaches on Ebro basin [64, 9].
Studies by various researchers [11, 30, 34, 36] have highlighted the significance of examining channel shifts within the floodplains. River channel shifting is found to generate dynamic patterns of flow changes within alluvial river planforms distinguished by single and multi-channel [21, 56]. The complex and dynamic mechanisms involved in the evolution and alterations of channels are particularly noticeable in braided rivers [6, 19, 21]. A range of factors can influence the rate and direction of river channel migration, such as the stream power, the sediment load, the channel geometry, the floodplain topography, and the vegetation cover [39]. The progress in Remote Sensing and GIS tools has transformed how we detect changes in river channels, including erosion, accretion, and channels that remain unchanged [33]. Remotely Sensed imageries approach for studying river channel planform dynamics has been changing drastically from the collection of 6-10 band images i.e. LULC mapping to the collection of only two or three bands’ images utilization on Indices development (NDWI, MNDWI, NDVI, etc.) [60] by various researchers to identify and extract water features. Boothroyd et al. (2021) have introduced Google Earth Engine (GEE) for the study of river channel planform dynamics. Researchers have included erosion and accretion as well as landuse and land cover map to relate the channel shifting changes and its impact within the study area [15, 35].
Geographical and topographical complex country Nepal has been identified as a frequent disaster spot and was ranked 11th & 16th in the vulnerability of Earthquake and multi hazards respectively [53]. The Terai areas of Nepal experience higher rainfall intensity which results in higher soil erosion in the slopes of the Churia hills [13]. The rivers that flow from the hills of Churia carry a lot of silt, which erodes the riverbanks and the slopes of the hills [2]. The deposition of the sediments forces the river to change its courses driven due to frequent eating of the outer edges within the upstream channel [47, 48]. West Rapti River Basin (WRRB) found to have stages of risks in land degradation and sedimentation as the results showed that the WRRB experienced a significant decrease in forest cover and an increase in agricultural land and built-up area [14]. Stretching from Nepal's Mahabharat Range to the Chure Range, the West Rapti River (WRR) is an important watercourse that supplies water for agriculture and other purposes in the area [51, 68]. It has been identified as highly prone to floods over settlements proximity to 500 m from riverbanks [10], and soil erosion, resulting in severe losses to lives and property within local communities [27]. According to the 2019 Climate Change and Disaster Risk and Vulnerability Context Report for Province 5, certain areas face different major hazards. Tulsipur and Ghorahi sub-metropolitan cities, Lamahi municipality, Rajpur, Rapti, and Dangisharan Rural Municipality are most susceptible to flooding. Most of the river changes its course when it enters the lower part of the region i.e., the Terai region.
The Rapti watershed, a major river system in the Mid-western Terai region of Nepal affected by land use land cover change (LULCC) in its surrounding areas. According to an article published by [14], the study of LULCC in the Sarada, Rapti, and Thuli Bheri river basins of Nepal during the 1995-2015 period using remote sensing revealed that an increase in agricultural lands at the expense of bare lands and forests escalated soil erosion through the years. The main issues affecting the lives and livelihoods of the people living in the lower West Rapti River basin are the deposition of sediments in the farmland by the torrents that originated in the Chure/Siwalik range, flooding, and bank cutting at various locations due to rapid geomorphological changes [62].
It is imperative to gain a comprehensive understanding of river channel shifting and braided regions along the West Rapti River, utilizing Geographical Information System (GIS) and Remote Sensing (RS) techniques to mitigate these water-related hazards. Geographic Information System (GIS) becomes suitable for analyzing and monitoring river erosion and its central line shifting [11, 32, 55, 58, 67]. The development of GIS has enhanced the capacity of the researcher to determine planform characteristics, e.g., changes in length, centerline migration, sinuosity index, etc. by combining the images of river planforms from different sources. To analyze their influence on the frequency and severity of floods in the Deukhuri Valley area of Dang district, this study intends to show the geographical and temporal patterns of river channel migration and its characteristics of the West Rapti River section from 1990 to 2023. The urgency of such efforts is underscored by the potential consequences of inaction. As highlighted by PERERA et al. (2013), failure to implement timely measures can lead to increased damage to human lives and property. By employing RS and GIS techniques, this study sheds light on the river's vulnerabilities, providing valuable data for informed decision-making.
The West Rapti River is selected as the study area whose length is 53 km, segment of whole West Rapti River Basin i.e., 257 km long situated in Lumbini Province of Nepal, that elongates from Bhalubang to Rihar; as shown in Fig. 1. The West Rapti River originates from the middle mountains of Nepal, then enters the lowlands, and finally drains to the Ghagra river in India, a tributary of the Ganges River [62]. Ransing River from south and Arjun River from North also drains this river. The West Rapti River is in the Lumbini province of Nepal and geographically the study area extends from 27˚47'0'' to 27˚55'30'' North latitudes and 82˚19'30'' to 82˚45'00'' East longitudes. The average annual precipitation for WRRB is about 1,534 mm and more than 80% of it occurs during the Monsoon season wets this Dune Valley i.e., study area. The study area falls within the elevation range 183 m to 1161 m. Fig 2 represent the warning and danger level of flow within the river from 1990 to 2023 in the study area. The river in Nepal's central highlands flows towards the plains and eventually empties into the Ghagra River in India (Karnali river in Nepal). The river is known as the West Rapti River because it is located downstream of where the Jhimruk and Madi Rivers drain Gadhawa, Rapti and Rajpur Rural Municipality and Lamahi Municipality of Dang district. Rainfall during the monsoon season and groundwater are the sources of runoff. People who live close to this river basin in Deukhuri (Dang), Nepal have suffered social and economic losses. The study area covers 5 wards of Gadhawa RM, 6 wards of Lamahi Municipality, 5 wards of Rajpur RM, and 5 wards of Rapti RM (Fig. 1).
3.1 Datasets Preparation
Remote Sensing data and GIS techniques were integrated for studying River channel shifting going through the process of collection, extraction, correction, visualization, overlay and analysis. Specifically, digital satellite imageries of Landsat 5 (Thematic Mapper), Landsat 7 (Enhanced Thematic Mapper plus), Landsat 8 (OLI), and Landsat 9 (OLI-2) datasets were used in this work. These datasets retrieved from Level 2 collection on the USGS (United States Geological Survey) server which belongs to row: 143 and path: 041. As shown in Table 1, Eight Landsat images were precisely selected for the study, covering the years 1990 to 2023, to analyze how river channels changed throughout that timeline.
Table 1: Data types and its source
|
Data Type |
Sensor |
Date of Acquisition |
NDWI Bands |
Source |
|
Landsat 5/L05 L2SP 143041 |
TM |
1990/12/03, 1995/04/21, 2005/11/10, 2010/06/01 |
Bands 2 (GREEN) and Band 4(NIR) |
USGS Website (Earth Explorer (usgs.gov) |
|
Landsat 7 |
ETM+ |
2000/03/25 |
Band 2(GREEN) and Band 4(NIR) |
|
|
Landsat 8 |
OLI |
2015/10/05, 2020/05/11 |
Band 3(GREEN) and Band 5(NIR)
|
|
|
Landsat 9 |
OLI-2 |
2023/02/21 |
Band 3(GREEN) and Band 5(NIR) |
|
|
ASTER GDEM |
|
|
|
Japan Satellite System (https://asterweb.jpl.nasa.gov/gdem.asp) |
A sequence of image processing operations, such as geometric correction, atmospheric correction, image registration, normalization, masking, and picture resampling, were performed for remotely sensed images to eliminate location coordinate discrepancies [7]. Landsat 7 images contain scanline error and thus were mostly avoided for collection so only the year 2000 was selected for study. Since the Landsat 8 launched date 2013, It has been observing earth with two key instruments Optical Land Imager (OLI) and Thermal Infrared Sensor (TIRS) whereas since 2021 launch date of Landsat 9 has been designed to mitigate the visualization of Landsat 8 upgrading instruments to OLI-2 and TIRS-2. Both satellites image the entire earth every 16 days, respectively. We preferred using Landsat 5 images from 1990 to 2010 found with low cloud cover below 5%. Besides the motive was to study channel shifting within 5-year gap but the year 2023 was selected for study of the present condition of the river channel within the study area.
3.2 Image Processing and NDWI Analysis
All the Images, mainly NDWI bands were masked using the popular ArcGIS 10.8 software tool ‘Extract by Mask’ using a shape file of the study area and projected under Universal Transversal Mercator (UTM) zone 44N. Extracted image was prepared for processing in the form to extract water surface feature using Normalized Difference Water Index (NDWI) as feature tool [3, 38]. Specific spectral band images were categorized by USGS for the different remote sensing approaches as shown in Table 1 i.e., for NDWI calculation. The following formula with the help of Standard Query Language (SQL), was used to calculate NDWI in ‘Raster calculator’:
NDWI=float (GREEN-NIR)/float (GREEN+NIR) (1)
Separate water features of the study area for different years 1990, 1995, 2000, 2005, 2010, 2015, 2020, and 2023 were separated by reclassifying into two categories: waterbody and non-waterbody. The image was further converted to polygon using the tool ‘Raster to polygon’ within ArcGIS 10.8 environment for every NDWI image.
3.3 Digitization and Cross-section Development
Digitization is considered a major task within GIS while joining one points to another to develop a map. This technique was used to develop mid-channel line (MCL) of the regular river course of the channel creating different new shape file in ‘line’ format for each year categorized for study within the study area. 27 Cross-sections were developed using River Bathymetry Toolkit (RBT), for base year 1990 river MCL with reference to this channel line we studied the shifting of the channel for respective years from 1995-2023 respectively [5, 66]. This tool utilized DEM of the study area to develop perpendicular cross-sections for MCL keeping gap of 2000m between those cross-sections.
3.4 Sinuosity and Braiding Index (BI)
Sinuosity is a term that describes the degree of curviness or windingness of the line or a shape [18, 35]. Schumm (1963) defined sinuosity as “ratio of stream length to valley length”. There are different river channel patterns categorized according to sinuosity values. Friend & Sinha as well as Germanoski & Schumm in 1993 determined sinuosity to study river patterns for both single and multi-channel as they can be straight, meandering, braided and anastomosing within its planform. Sinuosity was assessed within 3 reach ‘A’, ‘B’ and ‘C’ from CS-1 to 9, CS-10 to 17 and CS-18 to 27 from 1990 to 2023 A.D respectively. The Sinuosity Index (SI) was calculated using the following reference Fig. 3 and formula as in the Eq. (2).
Where, SR is the sinuosity ratio. This formula also used by Arefin et al. (2021), Lalramchulloa et al. (2021), Naim & Hredoy (2021), and Verma et al. (2021).
Braid bars are the pattern of sediment/soil debris deposit throughout the river laid in the form of different irregular structures. Braiding Index is defined as the ratio of the twice of summation length of braid bar (Lr) to the length of channel reach (Lr) as shown in Fig. 4 below. The overall channel has been parted into 3 reaches. According to Brice et al. (1964) and Singh et al. (2019), Braiding Index was calculated using the following formula as provided in Eq. (3) below;
Where ‘Lr’ is the length of all the bars within the reach, ‘Lm’ is the length of the reach measured midway between the banks of the channel belt.
After calculating the BI value, the mean value evaluated within 3 reaches and tabulated within the MS Excel for 2D-line representation.
3.5 Determination of River channel migration and driving force
River pattern within its planform was identified using the SI value while the behavior of channel shifting from 1990 to 2023 AD was identified in 6 directions North, Northeast, Northwest, Southeast, Southwest, and South with specified distance. It was calculated using GIS-based ‘measure tool’ which identified the distance the river has shifted with reference to base year 1990 AD by overlaying the MCL of other years: 1995, 2000, 2005, 2010, 2015, 2020, and 2023 respectively. Measured Distance were tabulated and spatio-temporal map was developed to observe the behavior analysis and the shifting of river channel within its planform. Converted polygons of river channel from ‘1990-2023’ were superimposed to obtain the aggregate deposited area till 2023 determines the spatial coverage and driver of river migration within its planform since 1990. In order to understand the area covered and the historical deposition, the river channel and MCL of the years 1990 and 2023 were superimposed and examined. The given Figure 5 provides the flow model diagram that was used for this research work.
4.1 Sinuosity Index
Natural River channel usually shows unpredictable behavior thus to identify their patterns within the floodplain sinuosity has been identified. The Sinuosity Index (SI) was determined by digitizing the river channel's centerline to establish a consistent river pathway (Stream Length), which differed between 53.67 km and 52.82 km, as illustrated in Fig. 6. Additionally, an imaginary representation of the river channel's pathway (Valley Length) was considered. The resulting numerical outputs for the years 1990, 1995, 2000, 2005, 2010, 2015, 2020, and 2023 are presented in Fig. 6 and Fig. 7 below.
As shown in Fig. 7, reach wise river pattern of flow was assessed under respective years where the value ranges from 1.02 to 1.38 i.e. <1.5 where river found multi-channel determined as braided nature on its planform. A higher sinuosity value observed in the year 2015 which was 1.38 at Reach C (CS-18 to CS-27) and lower value at Reach A was 1.02 respectively. Fig. 6 graph trend looks matching the Fig. 7 graph trend where river sinuosity and mid channel line length observed higher at the same year 2015 i.e., 54.79 km and SI- 1.02 to 1.38.
The pattern of the river channel-braiding index determined from GIS in the form of map as shown in Fig. 8 and Fig 12. The river channel 2015 found highly braided from the GIS mapping and analysis the braided trend started in 2015 where the bifurcation observed higher at CS-13 to CS-16 and CS-18 to CS-21. After the construction of embankment along both side of the river in year 2020, we found the regular channel was brought under control upto CS-16 but channel found evolved beyond CS-18.
4.2 Channel Migration (Mid-line Migration)
West Rapti River (WRR) shifting trend was analyzed using Remote Sensing data and GIS techniques within its planform under 27 cross-sections from east to west over 53 km range. Spatio-temporal maps of river channel generated by overlapping the mid-channel line of the years 1990, 1995, 2000, 2005, 2010, 2015, 2020 and 2023 respectively as shown in Fig. 9. The Fig. 9 shows those cross-sections, MCL overlay, and locations where the channel flows. The river channel shift was observed in 6 directions only whereas the channel flows from East to West.
When the channel shift was evaluated, the year 1990 was used as the base year. We observed that the channel shift was higher in the following years: 1995 under CS-19; 2000 under CS-14 and CS-23; 2005 under CS-11, CS-19, and CS-23; 2010 under CS-23; 2015 not found above 800 m but above 700 m on CS-11 and CS-14; 2020 under CS-23 and CS-25; as well as 2023 under CS-11 and CS-23 separately. In altogether the channel shifting was found highest over CS-11 and CS-23 from 1990 to 2023 i.e., 808.47 m and 1426.97 m respectively. While the channel movement was also recorded in 6 directions where we dig out that within CS-5, CS-8, CS-9, and CS-12 in Southwest direction since 1990 then within CS-11, CS-19, and CS-23 in Northeast direction and within CS-25 and CS-27 in South and Southeast direction respectively as shown in Table 2 and Fig. 11.
From Fig. 10 and table 2, We have figured out that there was highest shift of the river channel at CS-23 in Northeast direction, also at CS-19 channel shift was found in both direction North and South since year 1990.
Table 2: Tabular descriptions of WRR mid-channel line shifting distance and direction from 1990 to 2023 where year 1990 riverline taken as base year where N: North, NE:Northeast, NW: Northwest, SE: Southeast, SW:Southwest, and S:South. (Year_dist: shifting Distance and Year_dir: shifting direction)
Fig. 11 represents the channel pattern at different cross-sections from 1 to 27 where we can observe the shift of river channel from 1990 to 2023. The place where the channel was in 1990 and 2023 can be individually observed as provided from top to bottom CS-1 to CS-27 respectively with the flow, shift distance and direction. In CS-1 the river has shifted 304.98 m southeast whereas at CS-27 the river had shifted 386.73 m Southeast direction.
4.3 Braiding Index Calculation
Braiding pattern of the West Rapti River found decreasing in trend might be the impact of river embankments development by Nepal government. The trend was found decreasing from 1990 to 1995 then increasing until 2010 at last the trend decreased up to year 2023 i.e. 1.64 to 1.03. As provided in Fig. 12 below, maximum mean braiding index (BI) depicts that the channel has highest number of braid bars i.e. 1.76 in year 2010 and minimum mean BI depicts the lowest number i.e. 0.76 in year 1995 respectively throughout the river channel.
4.4 Geospatial determination of driver for channel migration
This study within the river area explains that the channel found braided according to SI and BI values and had undergone successive phases of erosion and deposition processes from 1990 to 2023. This clarifies that the channel had a higher deposition, about 15.35 Sq. km, at these cross-section areas as shown in Fig. 13, that forced river to shift higher and portions of river found colonized by the vegetation within the area.
Maximum historical deposition of sand bars found highly at CS-9 to 13 and CS-18 to 21 where the channel shifting found higher due the expansion and contraction of riverbed bars throughout the channel. Heavy deposition found halt at CS-13 to 16 after year 2020 due to engineering structures like embankment found on both sides of the channel at these cross-sections and others too.
Vegetation: As given in Fig. 14, 2023 google earth image showing vegetation colonized at CS-18 to CS-21 region that is comparable to Fig. 13(C) due to regular sediment deposition and the channel with island bar formed within the region since 2015.
4.5 Discussions
Every Monsoon brings a huge flood within the river channel. The dynamic nature of WRR from 1990 to 2023 within its planform enlightened through the GIS maps as shown above. We found irregular patterns of changes throughout the river channel under respective timeline of 33 years. These changes brought several shifting due to sandbars, point bars, braid bars, mid-channel bars, etc., formation as well as torrent rivers in the south which are the major drivers of west rapti river channel shifting. Confluence points were found to be the main widening part of this river channel that appeared differential patterns i.e., Arjun River, Ransing River and other torrent rivers within West Rapti River. Talchabhadel and Sharma (2014) found in his research that torrent river caused river channel shifting.
The channel shifting was maximum on CS-23 in the year 2023 i.e., 1426.97 m Northeast with respect to base year 1990. Also, within cross-section 25 there was instant shift from 54.39 m to 827.87 m from year 2005 to 2020. In average channel shifting was highly observed in between cross-section 18-21. Whereas CS-2 and CS-24 depict that the channel has been repositioned as it was in the year 1990.
The riverbanks were really conserved in the places where mitigation measures were implemented throughout the channel. Typical features like point bars, cut banks, meanders, anabranching, and braiding were found due to river channel migration. Baniya et. al., (2023) have also found a similar river pattern within Koshi river that shifted about 2 km from 1999 to 2019. The digitised imaginary line from the corresponding year follows the regular channel course, but since 2015, the channel has shifted primarily towards the northeast. We discovered that the trend of channel shifting was increasing, which led to continuous shifting that expanded the river floodplain structure within CS-18 to CS-21. Karnali river channel shifting study by Rakhal et. al., (2021) also found fang development i.e. heavy expansion of the river due to regular erosion and deposition.
With the observation of the field, we identified significant and transformative multichannel developments and movements within cross-sections 18 to 21, as well as in CS-9 to 13. Notably, cross-sections 13 to 16 exhibit a controlled channel behavior, attributed to the strategic implementation of embankments on both sides. This proactive measure, initiated in the year 2020, aims to effectively mitigate the impact of floods on human settlements. The channel's geomorphic characteristics reveal a distinctive meandering behavior, particularly evident from cross-section 22 onward. Noteworthy is the transition of the channel from a multichannel flow with braid bars to forming a single flow. Prior to this transition, the channel displayed a complex multichannel structure, characterized by the presence of braid bars throughout its course.
An additional observation of interest pertains to the colonization of the former riverbed area by vegetation. This phenomenon is indicative of dynamic changes and irregular shifts in the river channel. Such ecological alterations underscore the intricate interplay between geomorphological processes and ecological dynamics in the studied region. Further investigation reveals a discernible southwestward shift in the channel within CS-22 since the year 2000, albeit of minimal magnitude. This directional shift is a noteworthy aspect of the channel's trajectory and contributes to our understanding of its long-term spatial dynamics.
Bifurcation of the river channel first started at CS-14 where an expansion started to begin from year 2000 thus was brought into single channel from 2021. Similar changes in the pattern were found within CS-18 to CS-21 where it started to bifurcate from year 2015 expansion can be visualized in recent map i.e. year 2023.
Analysis of historical Landsat imagery on GIS environment reveals a dynamic pattern of river channel shifting within the West Rapti River over the past three decades plus 3 years sums up from 1990 to 2023. According to SI and BI values, the river channel displayed braided pattern within its planform, which is unpredictable in natural dynamics of river behavior. Spatially, it is observed that the river has experienced both lateral expansion and contractions showing rapid changes in river course like in CS-23 and CS-25 where channel shifting increase from 29.90 m to 1426.79 m NE whereas 72.45 m to 718.55 m S respectively from 1990 to 2023 while others exhibit more stable patterns. Heavy sediment deposits started to gather since 2010 in the downstream region of West Rapti River that is CS 16-27 at study area. As there was no research in past events thus this will be the guiding document for the Integrated watershed management programs and activities within the study area.
Since Nepal has been shown to be extremely vulnerable to water-related disasters, the Deukhuri valley in Dang has been discovered to be extremely vulnerable to these kinds of disasters, which may not be enough. While the focus of this study was not on the erosion and accretion of the river channel, tracking flood inundation is a significant area of interest for future research on this river using Sentinel-1 SAR imagery.
Acknowledgement:
We are thankful to known and unknown helping hands whose generous sharing of information and guidance have been crucial in shaping this research. Their on-the-ground knowledge and insights have provided a vital perspective that greatly enriched our findings. We acknowledge the Faculty of Forestry, Agriculture and Forestry University for providing an enriching academic environment that nurtured this research endeavor.
Consent for publication: The publishing of this research article has the complete approval of all its authors. We all concur that the material, conclusions, and submission for publication are sound.
Conflict of Interest/Competing Interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Data Availability: Not applicable.
Code Availability: Not applicable.
Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not for profit sectors.
Authorship:
S.G, P.P, and D.D conceptualized the article, critically revised the work. S.G and R.S performed the data curation. The original manuscript was prepared by S.G. Data analysis and software operation was carried out by S.G and D.D. Review and editing was done by S.G, D.D, R.S, and O.M.
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No competing interests reported.