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Article

Urban Growth and River Course Dynamics: Disconnected Floodplain and Urban Flood Risk in Manohara Watershed, Nepal

by
Shobha Shrestha
*,
Prem Sagar Chapagain
,
Kedar Dahal
,
Nirisha Adhikari
,
Prajjwal Shrestha
and
Laxmi Manandhar
Central Department of Geography, Tribhuvan University, Kathmandu 44618, Kirtipur, Nepal
*
Author to whom correspondence should be addressed.
Water 2025, 17(16), 2391; https://doi.org/10.3390/w17162391
Submission received: 12 June 2025 / Revised: 5 August 2025 / Accepted: 8 August 2025 / Published: 13 August 2025

Abstract

Human activities and river course change have a complex reciprocal interaction. The river channel is altered by human activity, and these alterations have an impact on the activities and settlements along the riverbank. Understanding the relationship between urbanization and changes in river morphology is crucial for effective river management, safeguarding the urban environment, and mitigating flood hazards. In this context, this study has been conducted to investigate the interrelationship between morphological dynamics, built-up growth, and urban flood risk along the Manohara River in Kathmandu Valley, Nepal. The Sinuosity Index was used to analyze variation in river courses and instability from 1996 to 2023. Built-up change analysis is carried out using supervised maximum likelihood classification method and rate of change is calculated for built-up area growth (2003–2023) and building construction between 2003 and 2021. Flood hazard risk manning was carried out using flood frequency estimation method integrating HEC-GeoRAS modeling. Linear regression and spatial overlay analysis was carried out to examine the interrelationship between river morphology, urban growth, and fold hazed risk. In recent years (2016–2023), the Manohara River has straightened, particularly after 2011. Before 2011, it had significant meandering with pronounced curves and bends, indicating a mature river system. However, the SI value of 1.45 in 2023 and 1.80 in 2003 indicates a significant straightening of high meandering over 20 years. A flood hazard modeling carried out within the active floodplain of the Manohara River shows that 26.4% of the area is under high flood risk and 21% is under moderate risk. Similarly, over 10 years from 2006 to 2016, the rate of built-up change was found to be 9.11, while it was 7.9 between 2011 and 2021. The calculated R2 value of 0.7918 at a significance level of 0.05 (with a p value of 0.0175, and a standard error value of 0.07877) indicates a strong positive relationship between decreasing sinuosity and increasing built-up, which demonstrates the effect of built-up expansion on river morphology, particularly the anthropogenic activities of encroachment and haphazard constructions, mining, dumping wastes, and squatter settlements along the active floodplain, causing instability on the river course and hence, lateral shift. The riverbank and active floodplain are not defined scientifically, which leads to the invasion of the river area. These activities, together with land use alteration in the floodplain, show an increased risk of flood hazards and other natural calamities. Therefore, sustainable protection measures must be prioritized in the active floodplain and flood risk areas, taking into account upstream–downstream linkages and chain effects caused by interaction between natural and adverse anthropogenic activities.

1. Introduction

Haphazard urbanization is a common phenomenon in cities of developing countries, which modifies the natural and built environment and has a degrading impact on the urban environment and ecosystem [1,2]. Built-up development (and construction) is a primary factor of urbanization, which exerts constant pressure on natural resources such as land and water. A river is a natural resource that has ecological and recreational functions. It provides valuable ecosystem services and is used for various purposes, ranging from water supply, transportation, to irrigation. It also plays a vital role as a cultural and recreational space and is an important urban landscape from an aesthetic viewpoint. However, urbanization with haphazard sprawl results in land use alteration, deforestation, and built-up expansion in marginal and environmentally sensitive areas, such as steep slopes, potential natural hazard zones, and river and stream banks, affecting the river course [3]. In addition, in many cities, poor and marginalized populations are using the riverbank for shelter purposes. Such an urbanization process has negatively affected the natural river environment. Although changes in river morphology and ecosystems can occur naturally, evidence suggests that human activities are the main cause of the degradation of the river environment and pose potential risks. Anthropogenic activities along and near riverbanks have caused vertical and lateral instability, impacted the natural river course, and even redirected its flow [4,5].
A river, in its natural form, has a characteristic of flowing from one side to the other, eroding or depositing different materials, and transporting them with different capacities. It deviates from its linear course on the way due to an imbalanced erosive power; there is an increased local deviation, which sets a meandering pattern. When a river transports sediment and water by maintaining its dimension, pattern, and profile without significant aggradation or degradation, it is regarded as a stable channel [6]. However, the complexity of urban land use interactions, an increasing urbanization response, impacts the channel structure and function [7,8]. As the population expands quickly and urban areas develop, various activities such as unregulated construction, river channel displacement, pollution from industrial waste, and the dumping of refuse into the river become frequent phenomena. Moreover, with the increasing impervious surfaces, urbanization can increase the risk of flooding by reducing the recharge capacity and increasing runoff volume.
The urban environment comprises four different components, namely, biotic, physical, social, and built environment. Interactions between these components and human activities produce complex spatial heterogeneity. The increasing population and associated activities and interactions are a driving force in altering the urban environment. The urban environment of the Kathmandu Valley is under the pressures of population growth, urbanization, and suburbanization processes, depleting environmental resources and living conditions [9,10,11]. Kathmandu Valley, with a population growth rate of 1.78% and 34.6% built-up growth between 2001 and 2021, is the most urbanized city in Nepal and is facing haphazard urbanization, which has caused settlements to grow along environmentally sensitive river and stream banks [12]. The Manohara River, a major tributary of the Bagmati River in the Valley, is also experiencing similar issues [13].
There are several earlier studies on urban-induced channel change in river systems, which highlight the interrelationship between urbanization and river morphology [14,15,16,17,18]. A significant impact of urbanization on river systems, including channel morphology and the overall river ecosystem, is also highlighted by Chin [19], who suggested a conceptual model of urbanization and river system interaction. The irreversible change that urbanization can bring is discussed in several studies [5,17,20,21].
Chin [19] has developed a model of change (river morphology) based on two phases of urbanization, which have a major impact (Figure 1). According to him (based on several case studies and observed data around the world), during the construction phase (increasing rate of urbanization), a river’s channel bed and floodplain are raised 2–10 times due to increased sediment production and deposition. Conversely, increasing sediment production follows reduction and an erosive regime encompassing channel enlargement. It will follow a new equilibrium where some river sections will adjust to the urbanization process, and others will be affected to an irreparable extent. However, morphological responses vary spatially depending on local conditions, particularly channel slope and lithology.
There are several standalone case studies on urban growth, hazard risk modeling, and river morphology of Kathmandu Valley [12,22,23,24,25], but very few studies have adopted an integrated analysis of the interrelationship and interaction between river morphology, built-up growth, and flood hazard risk and vulnerability. In this context, the current research highlights the effect of urban growth on river morphology and the resultant hazard risk in the Manohara River watershed, which is one of the most vulnerable watersheds in the Kathmandu Valley [26]. This is the first study conducted in the Manohara watershed to integrate regression analysis with spatial overlay techniques, offering a quantitative evaluation of how urbanization influences the dynamics of river morphology and increases the potential flood risk.

2. Materials and Methods

This study utilized an integrated approach that combined mapping tools with qualitative, quantitative, and field-based methods to explore river course dynamics, urban built-up growth, and flood hazard risks within the Manohara River and its watershed.

2.1. Study Area

The Manohara River watershed is selected as the study area. It is one of the major tributaries of the Bagmati River within Kathmandu Valley, Nepal (Figure 2). It originates (as a first-order stream/Strahler classification) from Manchuri hill (Manchuri Lekh) of the Nagarkot range at an elevation of 2320 m above mean sea level (amsl) in the northern part of the valley. From the origin to the upper 8.63 km length segment, it is known as Salinadi. It flows towards the southwest (as a fifth-order river) and confluences with the Bagmati River at Sankhamul at an elevation of 1293 m amsl. It exhibits the characteristics of a dendritic drainage pattern. It has four main tributaries: Hanumante Khola, Mahadev Khola, Ghatte Khola, and Satghatte Khola. Among them, Hanumante Khola is its major tributary. It flows through all three districts and seven municipalities of the Valley. The middle and lower sections of this river have a built-up and population concentration, including major infrastructures such as an airport, highway junctions, and institutional complexes.

2.2. River Course Variation and Sinuosity Mapping

To identify the river course shifting pattern and sinuosity, the river was divided into 13 sections, with equal division of 1 km2 of aerial distance. The channel shifting pattern of the Manohara River over the 20 years was analyzed using geospatial tools, including topographical maps (for the year 1996) and high-resolution satellite images available on the Google Earth platform (2003–2023). The river centerline and river polygon were manually digitized using the Google Earth platform and processed in the ArcGIS environment. The highest shift channel was measured in GIS and noted for each year. Digital topographical sheets (1:25,000 scale) 2785 02D, 03C, 06A, 06B, and 07A were obtained from the Survey Department of Nepal and processed for the 1996 river course analysis.
Sinuosity is a measure of a river’s meandering. The morphological changes that occur over a certain time due to various factors, including flood events, affect the sinuosity of the river channel. Conversely, sinuosity also determines the intensity of flood occurrence [27]. Change in the sinuosity index value in the flood-prone area can be used to predict bank erosion and to evaluate channel stability, which aids in mitigating flood hazard. Leopold and Wolman introduced the Sinuosity Index (SI) as a way to characterize river channel patterns. It is the ratio of the curvilinear length (along the curve) of a river/stream and the Euclidean distance (straight line) between the source and mouth of the curve, i.e., a river. The SI value ranges from 1 (case of a straight line) to infinity (case of a closed-loop, where the shortest path length is zero, or for an infinitely long actual path [28]. In this study, SI is calculated using Equation (1) as suggested by [29]. According to Muller [29], channel index of river sinuosity (Equation (1)), is the total sinuosity that includes both hydraulic and topographic sinuosity. River sinuosity is calculated using channel index and SI value derived by dividing the actual channel length of a river (CL) by the straight line length from source to mouth of a river (Air).
S I = C L   ( C h a n n e l   L e n g t h ) A i r   ( S t r a i g h t l i n e   l e n g t h   b e t w e e n   s o u r c e   a n d   m o u t h )
A higher sinuosity value indicates a more meandering river, while a sinuosity of 1 represents a straight line and is a widely adopted standard [28,29,30]. Leopold et al. [28] interpreted river sinuosity (SI) value as SI < 1.05 = almost straight, SI 1.05 ≤ 1.25 = winding, SI 1.25 ≤ 1.50 = twisty, and SI > 1.5 = meandering. Conversely, Charlton [30] classified river sinuosity SI values as <1.1 = straight, 1.1–1.5 sinuous, and >1.5 as meandering.

2.3. Flood Hazard Mapping

WESC/DHM has suggested a method for flood estimates for ungauged rivers based on specific discharge measurement (instantaneous and daily average flood flow measurement) [31]. This method is particularly suitable for basins that are below 3000 m and are larger than 12 km2 [32]. Flood hazard mapping was carried out using the flood frequency estimation method developed by the Water and Energy Commission Secretariat/Department of Hydrology and Meteorology (WECS/DHM) in Nepal. This method utilizes empirical equations (Equation (2)) and statistical relationships to determine flood discharge based on basin area. Water discharge flow for the return period of 100 years was calculated using the WESC/DHM method [31]. However, it should be noted that no single model is appropriate at all times where the site characteristics (size, flow, land use, surface structure, etc.) vary with time and in space [33]. Flood risk zoning, based on the demarcation of areas likely to be affected by inundation or floods of different magnitudes and probability levels based on the rainwater flow accumulation (station-based), has also been suggested for effective land use planning and regulating land use to minimize flood risk and damage. This method analyzes sub-regions characterized by low, high, and long-term flow patterns, utilizing discharge data from 11 to 34 years. The required parameters used for this method include catchment area <5000 m elevation, catchment area of <3000 m elevation, and monsoon wetness index. The calculated Standard Normal Variety (S) value for a 100-year return period is 2.326, and the peak flow computation Equation (2) is as follows:
Q100 = 14.693(A < 3000)0.7342
where Q100 = 100-year flood in m3 /s and A < 3000 = catchment area below 3000 m in km2.
As the Manohara River lies in an elevation range below 3000 m and has a catchment area larger than 12 km2, the WESC/DHM method was adopted. Hydrologic parameters such as catchment area, cross-sections at 1.5 km intervals, floodplain properties, riverbank and centerlines, flow path geometry, and water discharge data were used. Water discharge measurements from six different locations for Mahadevkhola (1), Salinadi (1), Manohara (2), and Hanumante (2) were processed using a grid model (12.5 m ALOS PALSAR radiometric terrain-corrected (RTC) high-resolution (HR)) for floodwater peak discharge calculation. The flood hazard zoning is based on measured water discharge data (instantaneous and daily average flow measurement) of six locations in the Manohara River to determine peak discharge (with a maximum 24 h rainfall depth of 250 mm) as depicted in Table 3 which was used as input to HEC-GeoRAS tool (version 10.5) with threshold of 2 m depth for inundation and 4.2 m depth for flooding.
For the flood hazard zone mapping, the WECS/DHM method [31] was integrated with the HEC-GeoRAS tool [34], and a flood hazard zone map was created. The flow accumulation within the watershed area was determined using hydrological modeling tools in ArcGIS 10.5. Land cover data from Landsat 8 of 2021 was used for surface roughness.

2.4. Built-Up Area and Building Growth Mapping

Built-up area change was analyzed using a change detection approach. Built-up land cover/use within a floodplain was also analyzed for 2003, 2013, and 2023 using the supervised maximum likelihood method with a total of 180 training samples. Built-up land cover/use category was derived from Landsat imagery: Landsat 7 ETM+ for 2003 and 2013, and Landsat 8-OLI for 2023. The thematic accuracy of land cover maps was analyzed through the Kappa index of agreement (KIA). High-resolution Google Earth images from 2003 and 2013 were used as reference for validation. Random onsite field verification (50 sites) and consultation with locals were carried out for ground truthing in December 2023. The rate of built-up change for each consecutive year is calculated using the standard annual rate of change (percent) formula of End year − Begin year/Begin year*100. The rate of built-up change is a percentage change in the built-up land cover/use category.
Building points within the active floodplain of Manohara River were screen digitized and extracted from the Google Earth images for a five-year interval of 2003, 2006, 2011, 2016, and 2021, respectively, and converted into a point shapefile for analysis. The rate of Building growth is the percent change in the number of building footprints derived from Google Earth imagery. The rate of change for building growth for each consecutive year is calculated using the same standard annual rate of change (percent) formula as follows: End year − Begin year/Begin year*100.
The relationship between urbanization and river course dynamics is quantified using the linear regression method to gain insight into the impact of urbanization on river systems, which can offer potential for flood risk along the Manohara River. Urban built-up change over time is set as an independent variable, and change in the sinuosity value over time, which indicates changes in meandering, is set as a dependent variable. A linear regression is set at the 95% confidence interval (p value 0.05) with an assumption that river course change is independent of built-up expansion over two decades (2003–2023) along the Manohara River, using the formula y = b0 + b1x + ε.
Similarly, spatial overlay analysis using a GIS platform was carried out to examine the interrelationship between river morphology, built-up growth, and potential flood hazard risk. Spatial overlay–intersection method was utilized using the ArcGIS tool (ArcGIS 10.5), and the overlapping area and shifted area of each subsequent year (e.g., 2006 river course overlap against 2003; 2011 against 2006, 2023 against 2021) were calculated. It was followed by calculating the built-up area (in hectares) within the shifted water surface area and the percentage share against the previous water surface area.
Consultation meetings were conducted with the ward-level authorities (the lowest administrative authority) along the river using a standard checklist. Informal discussions on factors, causes, and consequences of urbanization and changing river morphology, flood risk, and potential solutions were carried out with the locals and key informants. The discussion included fifteen locals residing near Manohara Riverbank, and ten key informants (urban planning authority, experts on river environment, and professionals working on river environment) were also interviewed.
Field observation and field measurements on each section of the Manohara River were also carried out to identify the course shift, potential flooding area, and existing built-up growth.

3. Results

3.1. River Characteristics and Course Dynamics

The Manohara is a perennial river with an average calculated length of 23.99 km, which varied from 22.6 km in 1996 to 20.16 km in 2023 (Table 1). The river length was found to be the longest during the years 2009 and 2011, with the measured length of 26.35 and 26.02 km. The measured aerial length of the Manohara River (starting from the touching point in the valley plain to the confluence point of the Bagmati River) was found to be 14.64 km. The total active floodplain area (base year 2003) covers 780.65 ha (7.8065 sq. km), and the watershed area (catchment) comprises a total of 7318.37 hectares. The sinuosity index (SI) was calculated using Muller’s method [29] to explore the river channel instability and to analyze variation in river courses between 1996 and 2023. The sinuosity index is a valuable tool for understanding river morphology and its relationship to factors like flood hazard potential risk, sediment transport, and channel stability. The SI value for the Manohara River for nine years (ranging from 1.59 to 1.85 and again down to 1.45) indicates a variable degree of straightening and meandering. A low SI value (≤1.0) indicates a straight channel, while a higher SI (>1.5) indicates an increasingly meandering channel. It is evident that in recent years (2016–2023), the meandering of Manohara River is shrinking, with the decreasing SI value from 1.66 in 2016 to 1.45 in 2023. The shrinking meandering has been prominent since 2013. Before 2011, Manohara had significant meandering (SI ranging around 1.80 to 1.85 except for 1996) with pronounced curves and bends, indicating a mature river system. However, the decreasing SI value from 1.80 in 2003 to 1.45 in 2023 indicates significant straightening over 20 years. The average SI value of 1.69 for the 1996–2023 period indicates a relatively high meandering pattern. However, a linear trend of decreasing sinuosity is visible from Figure 3, which exhibits a slight deviation in 2013. It is imperative that the lower SI value in 1996 may be attributed to the river length calculation using a digital topographical sheet of 1:25,000 scale.
The meandering of the river course over a 20-year period between 2003 and 2023 exhibits variable characteristics in terms of space and time. A major variation is found between the meandering belt width and channel width in different sections, and it was variable in different years (Figure 4). It is followed by a variation in meander length against the river course. Variation in these characteristics demonstrates an unstable river course. The middle section (sections 5–8) of the river has the most variable characteristics. The largest lateral shift is found to be 329.8 m along sections 8–9 near Gothatar. Similarly, a lateral shift of 235.8 m at section 6 near Phuyalgaun and 278 m along section 8 near Thapagaun are other significant lateral shifts (Figure 5). The directional shifts in these three largest lateral shifts are from the northwest to the southeast direction.
Spatial layers of the river polygon from 2003, 2006, 2011, 2016, 2021, to 2023 were prepared to explore spatio-temporal deviation in the river course. Concerning deviations in channel flow, the Manohara River can be divided into eight different sections (Figure 5a–h). The upstream section on the valley floor (Figure 5a) from the Salinadi temple to the Changunarayan temple is found to be relatively stable with low deviation from 2003 to 2023, and the land use is predominantly agriculture. From Changunarayan to Mulpani area (Figure 5b), meandering and shift are higher as compared to upstream, where mixed land use of agriculture and built-up is prevailing. Spatially, major changes in meandering and lateral shifts are found in the middle section of the river, but with varying degrees in different parts (Figure 5c–g). The dominant shifting and meandering with temporal reference are found from 2003–2009 to 2011, and from 2011 to 2016–2023 (Table 2). The year 2011 exhibits a major deviation (decrease in area), whereas a net increase in 2023 is also evident. These changes are dominant in the high-density built-up area of the lower middle (Figure 5c–e) as compared to the end section (Figure 5h).

3.2. Flood Hazard Risk

For Kathmandu Valley, a common rainfall threshold adopted is a maximum 24 h rainfall depth of 250 mm for the 1 in 100-year return period. For this study, six locations in the Manohara River were set for water discharge measurement for the determination of peak water discharge. The highest flow rate of water expected to occur, on average, for a 100-year return period is 907.76 m3/s in station 1 of Manohara River, and the lowest is for Mahadevkhola with 83.01 m3/s (Table 3). The peak discharge for a 100-year return period at six different locations along Manohara is presented in Table 3.
HEC-GeoRAS tool with an assigned value of 2 m depth for inundation and 4.2 m depth for flooding. A flood hazard risk area was calculated for the watershed and an active floodplain area (Table 4). The study found that around 26% of the floodplain area is under high risk of flooding, while 2.8% of the watershed area is found to be under high flood risk. Nearly 50% of the active floodplain area is under flood risk. High flood risk areas are found along high-density built-up areas like Karkigaun, Thapagaun, and Gothatar on the northwestern side and Dhunchopakha and Magargaun in the southeastern part of the river (Figure 6). Flooding along the Manohara River will significantly affect built-up and agricultural land. A total of 26% of the built-up area within the active floodplain lies under high flood risk, whereas 13% is under moderate risk. Similarly, 23% of agriculture lies under a high flood risk zone, followed by 25% under a moderate risk zone. In addition, 12% of the forest area lies within a high-risk zone.

3.3. Built-Up Growth

Building construction over 2006–2011–2016 and 2021 is unprecedented, particularly at the western side of Manohara, as evident from Figure 7. The building construction has increased at the rate of 38.28% per year within a floodplain. The rate of building growth from 2006 to 2011 was 1.99, while it increased to 2.37 between 2011 and 2016. Building construction rate from 2016 to 2021 was gradual (1.62) in comparison to the previous period of 2006 to 2011. This phenomenon is largely due to the increasing land value and limited availability of vacant residential land. It is interesting to note that the rate of building growth between 2006 and 2016 is higher (9.11) than between 2011 and 2021 (7.9).
Five major land use categories are found within the floodplain, namely, agriculture, built-up, forest, open/barren spaces, and water bodies (Figure 8). The predominant land use in the upstream floodplain (Figure 3: sections 1–4) is found to be agriculture, which gradually decreases towards the middle section (Figure 3, sections 5–7) and is almost non-existent in the downstream (Figure 3, sections 8–13), whereas this is quite the opposite in the case of the built-up area and residential land plots (Figure 8). Agricultural land use was dominant till 2021, though it decreased by 17% between 2003 and 2021 and by 36.7% in 2023. The conversion is predominantly built-up over 20 years (2003 to 2023), which increased by 29.5% (350.6 ha). Likewise, forest area shrank by 11% during the same period, whereas there is a slight increase in open space by 3.2%. Noteworthy is the increase of 1.2% of water area between 2003 and 2023. This result shows that the process of agriculture to build up, particularly along riverbanks in the middle and downstream, is significant, which has affected the overall river morphology as well as upstream–downstream interactions. The accuracy assessment of land use classification was carried out for each period, and the overall accuracy of land cover/use classes was 95.77% (2003), 95.77% (2013), and 96.38% (2023). The calculated overall KIA was 0.91, 0.93, and 0.92, respectively. In addition, onsite field verification was carried out randomly in fifty locations.

4. Discussion

Three distinct conceptual frames have been common in the study of river morphology dynamics in urban areas, particularly with the increasing pace of urbanization: inclination towards equilibrium or steady state of river morphology at the final stage of the urbanization process, temporary disturbances with possible recovery (return to natural state) in relatively stable sections, and abrupt disturbance and changes which are irreversible [19,35]. This study found spatial variation in river morphology and structure along the Manohara River from 2003 to 2023. Morphological change, particularly meandering and lateral shifts, occurred at varying degrees in different sections. The highest lateral shift and largest meandering occurred in the middle section of the river, where built-up growth was very rapid. Manohara River has horizontally shifted nearly 549 m from its original floodplain bank within 20 years (2003–2023). This finding accords with the previous study, which identified a maximum shift of 441 m along the river course between Kageshwori Manohara and Changunarayan Municipality over 10 years from 2013 to 2023 [36]. Natural processes and anthropogenic activities have altered the Manohara floodplain, modified the riverbank environment and the river course, and disrupted the overall morphology, tending towards increasing inundation and flood risk as visible from photos in Figure 9. This study found that the middle section is highly vulnerable to flood hazard risk. This finding coincides with the recent study, which reveals that this section has been tremendously affected by recent flood events of 2019, 2020, 2022, and 2024 and it is found that the larger the meandering and the sinuosity, the higher the flood intensity [21,37].
It has been argued that the haphazard urbanization process has changed the natural river system and resulted in channel instability, geo-hydrological risks, affected ecosystem services, and even enlarged urban channels up to 15 times in comparison to those that are in their natural state [14]. The narrowing and shifting of river channels, the disappearance and submergence of minor networks, and disconnection with the tributaries are other reported instabilities [5,38,39]. However, the instability is minimal in the areas where anthropogenic interventions are limited. Such changes in river morphology have increased the exposure and vulnerability of urban infrastructure and settlements to flood hazards [16]. Construction in the natural drainage system by encroaching on its natural course has resulted in flood disasters as well as an increase in the number of flood events, causing loss and damage to human life and properties in South Asian countries [18,21,27].
The findings of this study show a slight decrease in built-up construction between 2016 and 2021, but a slight enlargement of the water surface area (increase by 0.84 Ha between 2016 and 2021 of Manohara River). This phenomenon coincides with a new equilibrium state of gradual urbanization and relatively stable river course [14] as the later stage of the urbanization process. A river network structure indicator, such as river length, water area, density, and water surface coverage area, significantly correlates with built-up land [39]. It disclosed that built-up construction is the major driving factor for the change in the river system pattern. A regression analysis was carried out using built-up area growth percentage data from 2003, 2006, 2011, 2016, 2021, to 2023 (2.5 to 47.6%) as an independent variable, and decreasing sinuosity data from 2003 to 2023 (1.80 to 1.45) as a dependent variable. The calculated R2 value of 0.7918 at a 95% confidence interval (with Y = −0.008763*X + 1.889, α = 0.05) shows a high level of correlation. A p-value of 0.0175 at a significance level of 0.05, and a standard error value of 0.07877 suggest rejection of the null hypothesis. This indicates that the observed results are unlikely to have occurred by random chance. The result is statistically significant, suggesting strong evidence against the null hypothesis and hence, indicating a strong positive relationship between decreasing sinuosity with increasing built-up along the Manohara River.
Similarly, a spatial overlay analysis was carried out to examine the interrelationship between built-up growth and the shifted river course area (e.g., built-up growth in 2006 against the 2003 river course area) to explore the channel shift by calculating spatial overlap percent coverage between former and later river courses (i.e., 2006 river course overlap against 2003). An increasing trend of built-up area expansion within the previous water surface area is evident between 2003 and 2023 (Table 4). The maximum growth of built-up in the previous water surface area is found between 2003 and 2006. More than 23% of the water surface area in 2003 was converted to built-up by 2006, and 42.3% of the water surface area remained constant. In contrast, between 2006 and 2021, built-up expansion in the previous water course remained steady, ranging from 14% between 2006 and 2011 to 19% between 2016 and 2021. In addition, the shift in water surface area coverage was higher with less than 25% overlapping water surface area. However, between 2021 and 2023 (2-year period), around 54% of the water area remained unchanged indicating river channelizing in the later period.
The upstream section of Manohara has higher transportation capacity, i.e., potential degradation (erosion), whereas the middle and lower sections are prone to aggradation (deposition). However, the study highlighted that river morphology and dynamics may play a major role in the latter [25]. It has also been suggested that the middle and lower sections (Mulpani–Thimi–Jadibuti–Koteshwor area) are vulnerable to lateral shift and flooding because aggradation will cause siltation and hence, a rise in the riverbed, which increases the potential of inundation and flooding in the surrounding area. The water body has decreased by 5.4% between 2006 and 2014 due to encroachment of riverbanks [38].
The frequency and severity of floods and inundations have increased in the last five years in the Kathmandu Valley, including the Manohara River, causing greater damage to property and human life. All rivers in Kathmandu Valley have a fixed standard river flow area of 10 to 20 m (a horizontal distance from the river course) for constructing permanent structures near the riverbank. However, the river course is dynamic and shifts from time to time. The fixed horizontal distance along the river course is not a permanent solution to maintain the river environment and minimize disaster risk. In addition, informal settlements along the Manohara bank (a total of 16 squatter settlements were observed in the field) have harmed river morphology and the river environment. Informal settlements and slum development along riverbanks have been a major urban environmental issue in Kathmandu Valley since the 1980s [40]. These informal settlements have caused river pollution and a negative visual impression along the river. The Manohara River is experiencing significant encroachment, as evident by the conversion of 51 parcels recorded as public in 1964 into private parcels by 2021 [36]. On the contrary, with the changing river course and regular flooding and inundation occurrences, these settlements are at high hazard risk. In addition, households of these settlements are marginalized communities with poor living conditions and are the most vulnerable. Social vulnerability is inherently embedded in disaster risks (like floods, landslides, liquefaction, fire, etc.) since the highly socially vulnerable groups are associated with a higher effect and greater loss to bear. Housing and housing conditions, and the built environment, directly affect hazards and potential risks. Therefore, the urbanization process and trends along the river floodplain are important causal factors of social vulnerability, which play a key role in either increasing or reducing loss from disaster risks [23].
The causes for increasing flooding events in Kathmandu Valley rivers are primarily divided into four categories: catchment characteristics, meteorological factors, anthropogenic activities and processes, and institutional structures [26]. In September 2020, the flood level rose to 4.2 m near the outlet of Manohara in Baalkumari. It has been projected that the current 100-year return period flooding risk area may experience flooding in 25 years because the 100 years’ discharge will likely increase by 72% in the 25-year future period due to climate change, and the inundation area will expand from 11.7 to 23 km2 [41]. A study found that shrinking the river channel, slum, and squatter encroachment (Figure 10), and a narrowed river width are not only increasing flooding in the densely built-up area but also increasing inundation laterally to distant distances from the riverbank [42].
From the onsite field visit and consultations with the locals, it was found that the unscientific river demarcation method (e.g., same setback/right of way measures along the whole riverbank section), failure to ascertain the river territory, and weak legislation and regulation upon encroachment enabled easy access to the riverbank for slum and squatter dwellers. The locals have highlighted the haphazard construction of temporary structures and increasing squatters (Photos 1 and 2) and emphasized proper utilization of riverbanks to mitigate flood/inundation risk. However, the role of institutions in the approval of major building structures, such as healthcare facilities and public markets, along the river floodplain is debated, as well as the inadequate regulatory environment for informal settlements has also been pointed out.
As such, a geomorphological/hydrological approach to defining river flow areas is suggested. Such an approach helps to minimize the damage and loss caused by flooding and inundation events. Detailed studies on mapping and identification of historically active floodplains should be carried out at the municipal level and monitored accordingly. The new construction within such active flood zones should be restricted where no permanent structures exist and should be controlled and monitored or encouraged to relocate where permanent structures are built. Green infrastructure and building construction should be encouraged with carrot-and-stick incentives and punishments. This will enhance resilience by reducing vulnerability and ensuring the sustainability of marginal areas. Improvement in slums and squatters through a community-based self-help approach is suggested. Co-production of livable urban space by stakeholder engagement should be designed by local government authorities and public/private development institutions.
An integration of scientific, social, and economic factors is suggested for urban river management, focusing on socially warranted and culturally conformed comprehensive assessment [14,17]. A balance between the urbanization rate and the carrying capacity of the river water environment is also emphasized for sustainable urban development [5]. Nature-based local solutions and restoration through natural function are more recent suggestions to maintain and mitigate the urban river environment [43,44]. Some of the suggested strategies include reconstructing the former channel shapes, reconnecting older channels, and floodplains [45].

5. Conclusions

The Manohara River flows mainly through the suburban and urban region of the Kathmandu Valley and has been strained by both anthropogenic and natural processes. Highly erodible bank material in the upstream, aggradation, and the lateral shifting process midstream, and rapid and extensive urbanization in the midstream and downstream sections make the river environment fragile and sensitive to inundation and hazard risk. The study recommends that priority should be given to the middle section of the Manohara River channel by adopting a sustainable land management strategy that emphasizes bio-engineering techniques, such as agroforestry-based natural floodplain management and the construction of natural spurs. A regulation of a variable setback/ right of way and geotechnical monitoring along highly dynamic river course locations is also suggested, particularly from the Brahmakhel to the Gothatar area. A geomorphic approach is foreseeable for managing river morphology and associated direct or less obvious disturbances and hazards for sustainable urban development and the river environment. This study adopted a semi-automated and manual data generation approach utilizing existing spatial data sources. An accuracy assessment and KIA calculation for built-up change analysis was also carried out, but the uncertainty and error assessment, as well as the inherent error of existing secondary data and methods, were not examined in this study. To bridge the current gap in comprehending the intricate relationship and interactions between urban growth, river course dynamics, and flood hazard risk, advanced hydrological modeling based on field measurement, such as cross-section surveys and rain-gauge networks, is suggested. Field measurement data should be coupled with anthropogenic factors to explore the combined effect of humans and nature on river morphological dynamics and potential flood hazard risk. Such research investigations would aid in understanding the impact of urbanization on the river system and vice versa, facilitating proper land use planning and addressing the associated issues efficiently.

Author Contributions

Conceptualization, S.S.; methodology, S.S.; software, S.S., N.A., P.S. and L.M.; formal analysis, S.S.; investigation, S.S., P.S.C., K.D., N.A., P.S. and L.M.; resources, S.S. and P.S.C.; data curation, N.A., P.S. and L.M.; writing—original draft, S.S.; writing—review and editing, P.S.C. and K.D.; visualization, P.S.C. and K.D.; funding acquisition, S.S. All authors have read and agreed to the published version of the manuscript.

Funding

National Priority Area Research, Excellence Research Grant (ERG); (Grant No: TU-NPAR-077/78-ERG-05), Research Directorate, The Office of the Rector, Tribhuvan University, Kathmandu, Nepal.

Data Availability Statement

Data is contained within the article. The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Acknowledgments

The authors would like to acknowledge the Tribhuvan University, Office of the Rector, Research Directorate, for research grant support under the National Priority Area Research, Excellence Research Grant (ERG) (Grant N: TU-NPAR-077/78-ERG-05). We also acknowledge local authorities, organizations, FGD, KII, and participants who provided their valuable time and data and information to the authors.

Conflicts of Interest

The authors declare no competing or conflicting interests.

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Figure 1. Conceptual framework (Adopted from Chin, 2006 [19]).
Figure 1. Conceptual framework (Adopted from Chin, 2006 [19]).
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Figure 2. Location of the study area.
Figure 2. Location of the study area.
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Figure 3. Sinuosity of Manohara (1996–2023).
Figure 3. Sinuosity of Manohara (1996–2023).
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Figure 4. Manohara River course shift between 2003 and 2023.
Figure 4. Manohara River course shift between 2003 and 2023.
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Figure 5. (ah): Manohara River course 2003–2023. (a)—upstream section: Salinadi area, (b)—Changunarayan area, (c)—Brahmakhel area, (d)—Mulpani area, (e)—Kandaghari, (f)—Gothataar area, (g)—Sinamangal/Airport area, and (h)—downstream Shankhamul area.
Figure 5. (ah): Manohara River course 2003–2023. (a)—upstream section: Salinadi area, (b)—Changunarayan area, (c)—Brahmakhel area, (d)—Mulpani area, (e)—Kandaghari, (f)—Gothataar area, (g)—Sinamangal/Airport area, and (h)—downstream Shankhamul area.
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Figure 6. Flood hazard risk zones along the Manohara River.
Figure 6. Flood hazard risk zones along the Manohara River.
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Figure 7. Built-up growth between 2006 and 2016, and 2011 and 2021.
Figure 7. Built-up growth between 2006 and 2016, and 2011 and 2021.
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Figure 8. Land use change from 2003 to 2023.
Figure 8. Land use change from 2003 to 2023.
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Figure 9. Natural processes and anthropogenic activities along Manohara. Photo credit: 1 Laxmi Manandhar, 2024; 2 Nirisha Adhikari, 2025; 3 The Rising Nepal, August 2022.
Figure 9. Natural processes and anthropogenic activities along Manohara. Photo credit: 1 Laxmi Manandhar, 2024; 2 Nirisha Adhikari, 2025; 3 The Rising Nepal, August 2022.
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Figure 10. Flood vulnerability along Manohara Squatter. Photo credit: My Republica, August 2022.
Figure 10. Flood vulnerability along Manohara Squatter. Photo credit: My Republica, August 2022.
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Table 1. Sinuosity index (SI) value.
Table 1. Sinuosity index (SI) value.
YearCenterline Length (km)SI Value
199622.601.59
200325.621.80
200625.841.82
200926.351.85
201126.021.83
201322.861.61
201623.561.66
202122.481.58
202320.611.45
Notes: Source: Calculated using derived length from the river shapefile of 1996–2023.
Table 2. Water surface area of Manohara 2003–2023.
Table 2. Water surface area of Manohara 2003–2023.
YearWater Surface AreaDeviation from Mean Area
200371.806−0.068
200671.8880.014
200971.724−0.150
201171.081−0.793
201371.815−0.059
201671.8780.004
202171.831−0.043
202371.9710.097
mean area71.749
Notes: Source: Calculated using river polygon layers 2003–2023.
Table 3. Discharge calculation for Manohara and its tributaries for a 100-year return period.
Table 3. Discharge calculation for Manohara and its tributaries for a 100-year return period.
RiverCatchment Area (km2)Peak Discharge (m3/s)
Manohara (Station 1)194.84907.76
Manohara (Station 2)72.65422.42
Hanumante (Station 1)76.89441.33
Hanumante (Station 2)21.24165.57
Salinadi31.88224.80
Mahadevkhola8.283.01
Notes: Source: Authors’ calculation.
Table 4. Interrelationship between built-up growth and river course change.
Table 4. Interrelationship between built-up growth and river course change.
Spatial Intersection YearBuilt-Up Expansion in the Shifted River Course of the Preceding YearBuilt-Up% Against the Water Surface Area of the Later YearNo Change in
River Course
Area Coverage
Preceding-LaterArea Ha% CoverageArea Ha%
2003–200617.5023.3430.3742.30
2006–201110.0414.1314.8320.63
2011–201610.7615.012.2217.20
2016–202113.7119.0916.9323.55
2021–202313.9319.3638.6053.74
Notes: Source: Author’s calculation using spatial overlays.
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Shrestha, S.; Chapagain, P.S.; Dahal, K.; Adhikari, N.; Shrestha, P.; Manandhar, L. Urban Growth and River Course Dynamics: Disconnected Floodplain and Urban Flood Risk in Manohara Watershed, Nepal. Water 2025, 17, 2391. https://doi.org/10.3390/w17162391

AMA Style

Shrestha S, Chapagain PS, Dahal K, Adhikari N, Shrestha P, Manandhar L. Urban Growth and River Course Dynamics: Disconnected Floodplain and Urban Flood Risk in Manohara Watershed, Nepal. Water. 2025; 17(16):2391. https://doi.org/10.3390/w17162391

Chicago/Turabian Style

Shrestha, Shobha, Prem Sagar Chapagain, Kedar Dahal, Nirisha Adhikari, Prajjwal Shrestha, and Laxmi Manandhar. 2025. "Urban Growth and River Course Dynamics: Disconnected Floodplain and Urban Flood Risk in Manohara Watershed, Nepal" Water 17, no. 16: 2391. https://doi.org/10.3390/w17162391

APA Style

Shrestha, S., Chapagain, P. S., Dahal, K., Adhikari, N., Shrestha, P., & Manandhar, L. (2025). Urban Growth and River Course Dynamics: Disconnected Floodplain and Urban Flood Risk in Manohara Watershed, Nepal. Water, 17(16), 2391. https://doi.org/10.3390/w17162391

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