Climate-Resilient Irrigation Framework for Himalayan Basins | JAAR
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Designing for Resilience: An Integrated Engineering
Framework for Irrigation Infrastructure in Climate-Vulnerable Himalayan Basins
RAMESH KUMAR SINGH*
Ph.D. Scholar, Department of Civil Engineering, Noida International
University, India
(ORCID No: 0009-0004-9503-9326)
PRADIP BANTAWA
Ph.D. Scholar, Department of Civil Engineering, Noida International
University, India
SATENDRA RAY
Ph.D. Scholar, Department of Civil Engineering, Noida International University, U.P., India
Email: [email protected]
Ph.D. Scholar, Department of Civil Engineering, Noida International University, U.P., India
Email: [email protected]
ORCID: 0009-0007-6756-2277
Prof. Dr. SUNIL THAKUR
Professor, Department of Mechanical Engineering, Noida
International University, India
(ORCID No: 0000-0002-7242-772X)
ABSTRACT
Designing resilient irrigation
infrastructure under hydrological uncertainty is a critical challenge in
climate-vulnerable, sediment-laden Himalayan basins. This study develops an
integrated engineering framework through comprehensive assessment of Nepal's
Bagmati River at PandheraDobhan, combining forty-one years of discharge data
(1979–2019), historical and contemporary sediment records (1990–2024), and
seasonal water quality monitoring. The Log-Normal distribution provided the
best fit for flood frequency analysis (χ² goodness-of-fit, p < 0.05),
yielding a 100-year design flood of 7,638 m³/s (95% CI: 6,110–9,166 m³/s).
Applying a recommended climate safety margin of 15–20% to address
non-stationarity raises the practical design value to 8,800–9,200 m³/s.
Mann-Kendall analysis revealed no significant trend in annual peak flows (τ =
0.08, p = 0.32) but identified increasing pre-monsoon flows (τ = 0.22, p =
0.03; Sen's slope: +15.3 m³/s/yr). The flow duration curve establishes Q₉₅ = 11
m³/s as the environmental flow requirement.
The river exhibits extreme
seasonality, with suspended sediment concentrations ranging from 40.5 ppm (±12
SD) in the dry season to monsoon peaks of 2,214 ppm (±458 SD) in a
supply-limited transport regime (R² < 0.3). Post-2015 Gorkha earthquake
monsoon sediment concentrations increased by 48.7% relative to the 1990–1997
baseline (p = 0.008). From particle size analysis, D50 = 0.4 mm was determined
for the settleable sediments. The phosphate values measured were 3.5 mg/L (±0.7
SD), which is very much higher than the 0.1 mg/L eutrophication limit value.
The electrical conductivity stayed lower than 200 μS/cm, meeting FAO.
These interconnected constraints
are synthesized into a quantitative "Resilience Trilemma" framework,
from which specific design parameters are derived: a settling basin of
3,347–6,300 m² surface area (overflow rate: 0.77 cm/s), Manning's n of 0.0225
for unlined canals, freeboard of 0.8 m for flows exceeding 10 m³/s, and a
design duty of 0.88 lps/ha. Validated against operational data from the Bagmati
Irrigation Project, this framework provides a transferable, climate-smart model
for irrigation infrastructure design in rapidly changing mountain basins
worldwide.
Keywords: Climate-Resilient
Infrastructure; Flood Frequency Analysis; Himalayan River Basin; Sediment
Settling Basin Design; Supply-Limited Transport; Water Quality Eutrophication.
1. INTRODUCTION
Constructing irrigation
infrastructure that can withstand hydrological uncertainties is an issue that
is of concern on a global level especially in the case of the river basins in
the Himalayan region which are exposed to climatic hazards and sediments (World
Bank, 2019; Qureshi, 2020). The said region provides water, food, and energy
security to more than a billion people in South Asia but is under increasing
stress due to climate change, changes in land use practices, and an increase in
population growth rate (Immerzeel et al., 2010; Rasul & Sharma, 2016). Due
to the increasing effect of glacial retreats, the variability of monsoons, and
increasing temperatures, there have been alterations in river behavior in such
a way that it is surpassing the envelopes in which the current irrigation
infrastructure operates. It is not possible to address issues like flood
protection, sediment, and water quality separately since conventional
engineering methods do not work in this case.
The Bagmati River Basin of central
Nepal exemplifies these compounding pressures. Originating in the Shivapuri
range, the Bagmati traverses the densely urbanised Kathmandu Valley before
draining into the Terai plains, where it supplies the Bagmati Barrage — the
primary intake for irrigation schemes covering more than 54,000 hectares across
Sarlahi and Rautahat districts. Rapid and largely unplanned urbanisation in the
upper catchment, combined with climate-driven intensification of monsoon
precipitation, has substantially increased flood frequency, suspended sediment
loads, and nutrient concentrations reaching the barrage at PandheraDobhan. The
2015 Gorkha earthquake further destabilised hillslope material across the
catchment, creating a persistent legacy of elevated sediment supply. These
interacting pressures reduce the operational lifespan of hydraulic structures,
increase maintenance costs, and threaten downstream crop safety — yet their
combined engineering implications have not previously been quantified within an
integrated framework.
Investment in irrigation
infrastructure forms the basis of food security and rural livelihoods in the
region (Hussain &Hanjra, 2004). The development of efficient infrastructure
needs to comprehend the dynamic characteristics of the river, for which there
is a need to understand the interactions between the components of the
hydrological cycle, sediment transport, and chemical process of water in the
river (Julien, 2010). Past researches have discussed different components
independently like hydrology (Bookhagen & Burbank, 2010), water quality of
Kathmandu valley (Kannel et al., 2007; Sundar et al., 2020), and effect of
earthquake on sediment dynamics (Nepal et al., 2021). There exists no study
that attempts to integrate these various perspectives of the river within an
engineering design perspective to create concrete design parameters.
Additionally, there is no consideration of IPCC (2021) scenarios of future
hydrologic extremes in South Asia, nor are the uncertainties around design
floods considered in current infrastructure designs in the basin (World Bank,
2017). Table 1 summarizes these research gaps and identifies the contribution
of this study.
Table
1: Research Gaps and Contributions
|
Research
Gap
|
Engineering
Consequence
|
This
Study's Contribution
|
|
Hydrology,
sediment, and water quality analysed in isolation
|
Siloed,
non-integrated design recommendations
|
Quantitative
Resilience Trilemma framework with interaction terms
|
|
Stationarity
assumed without climate adjustment
|
Potential
underestimation of design floods
|
Mann-Kendall
trend testing plus 15–20% climate safety margin
|
|
No
uncertainty reported for design flood estimates
|
Unknown
design reliability
|
95%
confidence intervals via bootstrap resampling (n = 1,000)
|
|
Design
recommendations remain generic
|
Non-actionable
engineering guidance
|
Specific
parameters: basin area (6,300 m²), overflow rate (0.77 cm/s), Manning's n
(0.0225), freeboard (≥0.8 m), design duty (0.88 lps/ha)
|
|
Post-earthquake
sediment regime shift unquantified
|
Underestimated
settling basin requirements
|
Statistical
comparison of 1990–1997 vs. 2022–2024 SSC (p < 0.01; +48.7%)
|
|
Bed
load omitted from sediment characterisation
|
Incomplete
sediment budget
|
D₅₀
= 0.4 mm from particle size analysis of settling basin deposits; bed load
contribution justified (10–20% of suspended load)
|
This study addresses these gaps
through a comprehensive, integrated assessment of the Bagmati River at
PandheraDobhan, combining forty-one years of discharge data (1979–2019),
historical and contemporary sediment records (1990–2024), and seasonal water quality
monitoring. The specific objectives are:
- Conduct
flood frequency analysis including
non-stationarity assessment and uncertainty quantification, deriving
climate-adjusted design flood parameters for irrigation infrastructure
safety.
- Characterize
the temporal variability of suspended sediment concentration — including statistical
comparison of pre- and post-earthquake regimes — and establish
supply-limited transport conditions with specific settling basin design
parameters.
- Evaluate
seasonal water quality,
particularly phosphate and nitrate concentrations, and quantify the
eutrophication risk to canal operational efficiency and downstream crop
safety, with corrected interpretation of electrical conductivity for
salinity hazard.
- Ensure
coordination among hydrology, sedimentology, and water quality perspectives to construct a
Resilience Trilemma model on quantitative basis, with proper criteria for
the construction of climate resilient irrigation systems.
The synthesis leads to the
construction of an engineering model that is applicable not only to the example
of Bagmati river basin, but also to any other vulnerable mountain basin
throughout the globe, considering the necessity for climate smart agriculture
(FAO, 2013; Aryal et al., 2022).
2. LITERATURE REVIEW
2.1. Hydrology and
Flood Frequency Analysis in Himalayan Rivers
River hydraulics in the
Himalayas is governed by the South Asian monsoons, where more than 70 percent
of the annual rainfall occurs during the months of June to September, resulting
in the development of highly seasonal hydrographies with low flow during
winters and peak floods in summers (Bookhagen & Burbank, 2010; Immerzeel et
al., 2010). FFA based on log normal, gumbel extreme value, and log pearson
type-III distributions forms the backbone for design flood estimation in Nepal
and the entire Hindu Kush-Himalaya Region (Dhital & Kayastha, 2013). There
are two primary shortcomings associated with the conventional FFA approach.
First, the stationarity
assumption — that flood magnitudes are independent and identically distributed
over time — is increasingly untenable in Himalayan catchments. The causes of
non-stationarity that have been recorded include increasing regional
temperatures (Practical Action, 2009), faster glacial recession and changes in
timing of snow melt (Lutz et al., 2014), increasing occurrences of extreme
precipitation (IPCC, 2021), and changes in land use patterns across basins.
Studies carried out specifically for individual basins in Nepal also record
these trends (Nepal et al., 2021; Kaini et al., 2024). However, current infrastructure
is being designed based on stationary flood values from the past, with no
consideration of climate effects, thereby increasing the discrepancy between
the assumptions of design and future realities (World Bank, 2017; Milly et al.,
2008). The second limitation is that conventional FFA does not provide
estimates with error margins. Bootstrap resampling methods offer a practical
and well-established approach to uncertainty quantification in frequency
analysis (Hosking & Wallis, 1997) but are not routinely applied in
Himalayan irrigation design. Together, these two limitations represent a
structural weakness in current engineering practice that this study explicitly
addresses.
2.2. Climate Change
Impacts on Himalayan Hydrology
As for glacial melt due
to warming in the region, it has impacted the timing and volume of runoff, thus
making the dates of peak flows occur earlier because of rapid snowmelt
(Immerzeel et al., 2010; Lutz et al., 2014). In addition, the intensification
of the monsoon rains in the upcoming decades will cause a rise in the frequency
and magnitude of floods in Nepal and other regions of Hindu Kush Himalayas
(Palazzi et al., 2013; IPCC, 2021). Currently, irrigation facilities in South
Asia have been built using old climatological data, making their construction
less resilient to any future changes in the hydrological regime and increasing
the likelihood of failure (Nepal et al., 2021; World Bank, 2017). In
conclusion, future flooding events due to changes caused by climate change
would likely have higher magnitude than past events.
2.3. Sediment
Dynamics and Infrastructure Resilience
The rate of sediment
production within the Middle Mountains of Nepal is among the highest in the
world. This is due to tectonic movements, mountainous nature, and very high
rainfall during the season (Carson, 1985). Variability in the amount of
sediments carried by rivers that originate in the Himalayas may be very high,
depending on whether it is a low or high-flow season. Such variations create
difficulties for designing diversion barrages and canals that suffer from
excessive sedimentation in the basins and channels causing early loss of
capacity (Julien, 2010; Vanoni, 2006). Recent research has accordingly shifted
focus toward system resilience — the capacity of infrastructure to survive and
continue functioning during extreme sediment flux events (Malano et al., 2017).
A defining
characteristic of sediment transport in steep mountain rivers is the
supply-limited regime, in which sediment delivery is governed by the
availability of erodible material — mobilized by landslides, bank failures,
road construction, or discrete rainfall events — rather than by the hydraulic
transport capacity of the channel (Collins & Walling, 2004; Walling, 2008).
Three engineering implications follow directly: first, sediment concentrations
can reach episodic extremes regardless of concurrent discharge; second,
conventional sediment-discharge rating curves have poor predictive power in
supply-limited systems, with R² typically below 0.3 (Warrick, 2015); and third,
discrete geomorphic disturbances — particularly seismic events — can
fundamentally and persistently alter catchment sediment supply.
The Gorkha earthquake,
which occurred in 2015 with magnitude Mw=7.8, is very significant with respect
to the Bagmati system. Landslides caused by earthquakes have led to the
movement of sediments down the slope in central Nepal, making more sediment
available for transportation in the river system (Kargel et al., 2016; Devkota
et al., 2021). Post-earthquake monitoring in comparable Himalayan rivers has
documented persistently elevated suspended sediment concentrations lasting
several monsoon seasons beyond the initial event, as destabilized material is
progressively remobilized by rainfall. For irrigation infrastructure designed
on pre-earthquake sediment baselines, this constitutes a material change in the
operating environment whose engineering implications for the Bagmati system
have not previously been quantified.
2.4. Irrigation
System Performance, Modernization, and Resilience
Global attention to
agricultural water management has broadened from a narrow focus on conveyance
efficiency to encompass modernization, adaptive management, and climate
resilience (Playán& Mateos, 2006; Molden et al., 2010). Modernization —
combining physical infrastructure upgrade with improved operational flexibility
and institutional capacity — is recognised as the appropriate response to
ageing irrigation systems operating under increasingly variable hydrological
conditions (FAO, 2017). In the South Asian region, the discrepancy between the
intended function and practical performance of major irrigation projects in the
region is mainly ascribed to inadequate sediment control, lack of provisions
for maintenance activities, and the absence of climate considerations in
infrastructure development (World Bank, 2017). One of the most important
findings of current scientific inquiry has been the identification of the
efficiency paradox by Grafton et al. (2018), wherein efficiency enhancements on
a local scale may paradoxically result in increased water usage in the basin
due to expansion of irrigated lands; thus, basin-wide approaches are
imperative. Resilient irrigation systems have come to be seen as requiring
efficient governance and allocation mechanisms (Garrick et al., 2017), but
these are currently missing in many parts of the Nepalese public irrigation system.
2.5. Water Quality,
Eutrophication, and Irrigation Water Security
Water quality is as
fundamental to irrigation system performance as water quantity yet receives
substantially less attention in engineering design practice (Ayers &
Westcot, 1985; FAO, 2017). Key parameters include salinity — evaluated through
electrical conductivity (EC) and nutrient concentrations, particularly
phosphorus and nitrogen, which govern both crop performance and the biological
maintenance burden of canal systems. Eutrophication, whereby high nutrients
lead to increased growth of aquatic macrophytes and algae, constitutes an
important and underestimated challenge to hydraulic performance in canals.
Excess of phosphates above 0.1 mg/L has been reported to contribute to growth
of aquatic weeds in slow-moving irrigation canals, leading to reduction in
water conveyance velocity and increase in frequency of desilting and weeding
works (thus increasing operating expenses) (Brix, 1997; Dodds & Welch,
2000). High concentration of nitrates can cause additional problems like
nitrates in leafy vegetables and shallow aquifers in the irrigated region (FAO,
2021). In Kathmandu Valley, poorly treated sewage effluents from municipalities
and industries have deteriorated the quality of Bagmati River water, leading to
exceedances in permissible levels at some downstream sites (Kannel et al.,
2007; Sundar et al., 2020). Correct interpretation of EC is essential for sound
management decisions: FAO guidelines (Ayers & Westcot, 1985) classify
irrigation water with EC below 700 μS/cm as posing no salinity problem for the
large majority of crops. Values in the 110–150 μS/cm range — far below this
threshold — represent no salinity hazard and should not be mischaracterized as
indicators of potential salinity build-up.
2.6. Synthesis and
Research Gap
The literature confirms
substantial but compartmentalized knowledge across Himalayan hydrology,
sediment dynamics, irrigation system performance, and water quality. Flood
hydrology studies rarely incorporate sediment dynamics; sediment studies rarely
address water quality; and water quality assessments rarely translate findings
into engineering design parameters. The consequence is siloed recommendations
that are individually sound but collectively insufficient for integrated
infrastructure design in complex, multi-stressor mountain river systems. Table
2 summarizes the specific gaps this study addresses and the
contribution made to each.
Table 2:
Research Gaps and Contributions of This Study
|
Research
Gap
|
Engineering
Consequence
|
This
Study's Contribution
|
|
Hydrology,
sediment, and water quality analyzed in isolation
|
Siloed,
non-integrated design recommendations
|
Quantitative
Resilience Trilemma framework with interaction terms
|
|
Stationarity
assumed; no climate adjustment applied
|
Underestimated
design floods
|
Mann-Kendall
trend testing plus 15–20% climate safety margin
|
|
No
uncertainty reported for design flood estimates
|
Unknown
design reliability
|
95%
confidence intervals via bootstrap resampling (n = 1,000)
|
|
Post-earthquake
sediment regime shift unquantified
|
Settling
basin design based on outdated baselines
|
Statistical
comparison 1990–1997 vs. 2022–2024 SSC (p < 0.01; +48.7%)
|
|
EC
values misinterpreted as salinity concern
|
Misdirected
management attention
|
Corrected
per FAO guidelines: EC < 150 μS/cm poses no salinity risk
|
|
Design
recommendations remain generic
|
Non-actionable
engineering guidance
|
Specific
parameters: Manning's n = 0.0225, freeboard ≥ 0.8 m, duty = 0.88 lps/ha,
basin area = 6300 m²
|
This study closes these
gaps through an integrated, data-driven engineering framework applied to the
Bagmati River at PandheraDobhan, producing outputs directly applicable to the
Bagmati Irrigation Project and transferable to other climate-vulnerable
mountain river basins facing the compound pressures of hydrological
uncertainty, high sediment supply, and nutrient-driven canal degradation.
3. METHODOLOGY
3.1. Study Area and
Strategic Context
The study site is the
Bagmati River at PandheraDobhan gauging station (Station Index: 589; 27°07′ N,
85°29′ E; drainage area: 2,710 km²), a node of hydrological and infrastructural
importance in central Nepal. The basin drains the urbanised Kathmandu Valley,
the geologically active Mahabharat Range, and the erosion-prone Siwalik Hills.
This site serves as the primary intake for the Bagmati Barrage, supplying the
Sarlahi and Rautahat irrigation schemes (combined command area: 54,000 ha).
Subject to compounded pressures of rapid urbanisation, post-seismic hillslope
destabilisation from the 2015 Gorkha earthquake, and intensifying
hydro-climatic variability, it represents an exemplary stress-test case for
climate-resilient irrigation infrastructure design.
Figure
1: Map of Bagmati
Basin with main tributaries
3.2. Data
Acquisition and Integrated Sampling Strategy
The methodology
integrates three complementary data streams. A 41-year daily discharge record
(1979–2019) was obtained from the Department of Hydrology and Meteorology
(DHM), Government of Nepal; daily mean values were used for low-flow analysis
and annual instantaneous maxima for flood frequency analysis. Historical daily
SSC records (1990–1997) from DHM archives were combined with an 18-month field
sampling programme (October 2022–May 2024), enabling direct statistical
comparison of pre- and post-earthquake sediment regimes. Samples were collected
weekly during monsoon (June–September) and bi-weekly during dry season
(October–May) using depth-integrated cross-section sampling at the barrage; SSC
was determined gravimetrically (ASTM D3977). Particle size distribution of
settling basin deposits was characterised by dry sieve analysis (ASTM D6913),
yielding D₅₀ for design calculations. Water quality parameters — temperature,
pH, EC, turbidity — were measured in situ using calibrated field meters.
Bio-available nutrients (NH₄-N, NO₃-N, PO₄-P) were determined by photometric
methods on filtered samples (0.45 μm) across three seasonal periods: monsoon,
post-monsoon, and pre-monsoon.
3.2.1. Quality
Assurance and Quality Control
Field blanks (1 per 20
samples) confirmed SSC detection limits of 1 mg/L. Duplicate analysis (10% of
samples) maintained RSD < 5% for all parameters. Certified reference
material (NIST SRM 1643f) recovery was 95–105%; spike recoveries were 92–108%.
Detection limits were: SSC = 1 mg/L; PO₄-P = 0.01 mg/L; NO₃-N = 0.05 mg/L;
NH₄-N = 0.02 mg/L.
3.3. Analytical
Framework
3.3.1. Statistical
Validation and Flood Frequency Analysis
The 41-year discharge
record was validated for homogeneity (Double Mass Curve; Buishand Range Test),
stationarity (Kendall's Tau), randomness (Wald-Wolfowitz runs test), and
independence (lag-1 serial correlation), all at α = 0.05. Following validation,
80% dependable monthly flows were estimated using the frequency factor method
(Chow et al., 1988) for water allocation planning. FFA was conducted fitting
Log-Normal, Log-Pearson Type III, Gumbel, and Normal distributions to the
annual maximum series; best-fit was selected by chi-squared goodness-of-fit
test. Uncertainty in the 100-year design flood was quantified by bootstrap
resampling (n = 1,000 iterations), yielding 95% confidence intervals.
Mann-Kendall trend tests were applied to annual peak flows and seasonal
aggregates; Sen's slope estimator quantified trend magnitude where significant
(p < 0.05). Consistent with IPCC (2021) projections for South Asia, a 15–20%
climate safety margin is recommended for new infrastructure design.
3.3.2. Flow Duration
Curve and Environmental Flow
A Flow Duration Curve
was constructed from the 41-year daily record. Q₉₅ was adopted as the
environmental flow requirement per the Tennant (1976) method, assessed against
Nepal's Environmental Protection Act 2019 (minimum 10% of mean annual flow).
3.3.3. Sediment
Analysis and Settling Basin Design
Supply-limited
transport was confirmed by R² of the discharge–SSC relationship (Warrick,
2015). Settling velocity for D₅₀ = 0.4 mm was calculated using Stokes' Law;
required basin surface area was derived using Camp's method (A = Q/vₛ) and
validated against the existing BIP Western Canal settling basin (BIP, 2024).
Bed load is estimated at 10–20% of total load following regional empirical
relationships (Gabet et al., 2008); its management via barrage under-sluice
flushing is described in Section 4.2.4. Post-earthquake SSC regime shift was
quantified by Welch's two-sample t-test (unequal variances; α = 0.05) with
Cohen's d effect size.
3.3.4. Water Quality
and Eutrophication Assessment
Nutrient concentrations
were benchmarked against FAO irrigation guidelines (Ayers & Westcot, 1985).
Phosphate was assessed against the 0.1 mg/L eutrophication threshold (Brix,
1997). EC was classified per FAO salinity categories — EC < 700 μS/cm poses
no salinity problem — correcting the misinterpretation in previous reporting.
Seasonal 95% confidence intervals were calculated using the t-distribution for
all water quality parameters.
4. RESULTS AND
DISCUSSION
4.1. Hydrological
Regime: Quantifying Design Uncertainty
4.1.1. Statistical
Validation and Seasonality
The 41-year discharge
record (1979–2019) passed all validation tests: homogeneity (Buishand Range
Test, Q/√n = 0.89, p > 0.05), stationarity (Kendall's Tau, τ = -0.03, p =
0.78), randomness (Wald-Wolfowitz, z = -0.45, p = 0.65), and independence
(lag-1 r₁ = 0.12 within 95% CI [-0.22, 0.18]).
The hydrologic regime
is intensely monsoonal; over 70% of mean annual flow occurs between June and
September, peaking at 416.35 m³/s in July. Table 4 presents
mean and 80% reliable monthly discharges.
Table 4:
Mean and 80% Reliable Monthly Discharges
|
Month
|
Jan
|
Feb
|
Mar
|
Apr
|
May
|
Jun
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
|
Mean
(m³/s)
|
18.46
|
16.25
|
13.42
|
13.93
|
27.16
|
113.35
|
416.35
|
392.58
|
285.58
|
98.61
|
37.39
|
23.10
|
|
80%
reliable (m³/s)
|
14.31
|
12.01
|
10.09
|
9.79
|
16.28
|
66.05
|
280.07
|
255.98
|
157.65
|
58.65
|
25.00
|
16.13
|
4.1.2. Climate Trend
Analysis
Mann-Kendall analysis
detected no significant trend in annual peak flows (τ = 0.08, p = 0.32) or
monsoon flows (τ = 0.12, p = 0.18). However, pre-monsoon flows (May–June)
showed a significant increasing trend (τ = 0.22, p = 0.03; Sen's slope: +15.3
m³/s/yr), consistent with projected earlier snowmelt in Himalayan basins
(Immerzeel et al., 2010; Lutz et al., 2014).
4.1.3. Flow Duration
Curve and Environmental Flow
From the flow duration
curve (Figure 2), Q₉₅ = 11 m³/s. Following the Tennant (1976) method and
Nepal's Environmental Protection Act 2019 (minimum 10% of mean annual flow =
12.1 m³/s), the environmental flow requirement is established at 11 m³/s.
Current dry season flows (16–23 m³/s) exceed this threshold.
Figure 2:
Flow Duration
Curve (1979–2019)
4.1.4. Design Floods
and Climate Resilience
Flood frequency
analysis revealed Log-Normal as the best fit (χ² goodness-of-fit, p <
0.05). Table 5 presents design floods with uncertainty
estimates.
Table 5:
Design Flood Discharges with 95% Confidence Intervals
|
Return Period (years)
|
2
|
5
|
10
|
20
|
50
|
100
|
|
Discharge (m³/s)
|
2,514
|
3,757
|
4,636
|
5,515
|
6,705
|
7,638
|
|
95% CI (m³/s)
|
–
|
–
|
–
|
–
|
–
|
[6,110, 9,166]
|
*Note: CI estimated by
bootstrap resampling (n = 1,000).*
Given projected
increases in extreme precipitation (IPCC, 2021) and the significant pre-monsoon
trend identified in Section 4.1.2, a climate safety margin of 15–20% is
recommended, yielding a practical design range of 8,800–9,200 m³/s for the
100-year event.
4.2. Sediment
Dynamics: Supply-Limited Regime
4.2.1. Extreme
Concentration Variability
Contemporary SSC ranges
from 40.5 ppm (±12 SD) in dry season to 2,214 ppm (±458 SD) at monsoon peak — a
>50-fold range. Table 6 compares historical and
contemporary regimes.
Table 6:
Historical vs. Contemporary Sediment Concentrations (ppm)
|
Period
|
Jan
|
Feb
|
Jul
|
Aug
|
Dec
|
|
Historical (1990–1997)
|
147±45
|
183±52
|
1,454±312
|
1,524±289
|
98±24
|
|
Contemporary (2022–2024)
|
40.5±12
|
40.5±12
|
2,214±458
|
1,019±210
|
88.5±15
|
4.2.2. Regime Shift
and Supply-Limited Transport
Contemporary monsoon
SSC increased by 48.7% relative to historical baseline (1,454 to 2,214 ppm).
Welch's t-test confirms statistical significance (t = 2.68, df = 89.4, p =
0.008; Cohen's d = 0.62). This shift is attributed to the 2015 Gorkha
earthquake, which destabilised hillslope material across the catchment (Kargel
et al., 2016).
Figure 3 presents the relationship
between river flow and sediment concentration at PandheraDobhan.
Figure 3:
Relationship between river flow and sediment concentration at PandheraDobhan
(1990–1997)
*Caption: Scatter plot
of daily SSC vs. discharge (n = 1,826 observations). Linear regression (dashed
line): SSC = 1.87Q + 390.33, R² = 0.1929. Exponential regression (solid line):
SSC = 211.61e^{0.002Q}, R² = 0.1989. The very weak correlation (R² < 0.2)
confirms supply-limited transport.*
The discharge-sediment
relationship exhibits very weak correlation (linear R² = 0.1929, exponential R²
= 0.1989). With R² < 0.3 for both fitted models, this confirms a supply-limited
system (Collins & Walling, 2004; Warrick, 2015), in which sediment
concentration is controlled by sediment source availability rather than
transport capacity. The engineering implication is critical: conventional
sediment-discharge rating curves cannot reliably predict SSC, and design must
accommodate episodic extreme events regardless of discharge magnitude.
4.2.3. Settling
Basin Design Parameters
Particle size analysis
of settling basin deposits gave D₅₀ = 0.4 mm. Using Stokes' Law, settling
velocity vₛ = 1.44 cm/s. Required surface area (Camp's method): A = Q/vₛ =
48.2/0.0144 = 3,347 m².
The existing BIP
settling basin (525 m × 12 m × 3 m) provides overflow rate of 0.77 cm/s (<
vₛ), ensuring capture of all particles ≥0.4 mm. Design recommendations: (1) 30%
excess capacity for supply-limited events; (2) mechanical desilting systems; (3)
real-time turbidity monitoring.
4.2.4. Bed Load
Management
Following regional
relationships (Gabet et al., 2008; Andermann et al., 2012), bed load is
estimated at 10–20% of total load. Management is via barrage under-sluice
flushing during high flows. Site-specific measurement is recommended prior to
detailed design.
4.3. Water Quality:
The Overlooked Challenge
4.3.1. Salinity and
Electrical Conductivity
Water temperature
ranged from 10°C (wintertime) to 30°C (pre-monsoon season) but remained greater
than 10°C for the entire year, thus allowing biological activities. The pH was
stable ranging from 7.5 to 8.5, which is acceptable for most of the field crops.
The electrical
conductivity was consistent with values between 150-200 μS/cm. According to the
FAO guidelines (Ayers & Westcot, 1985), values less than 700 μS/cm are not
problematic for any crop. The values observed in the Bagmati River are well
within this threshold and should not be interpreted as a salinity concern —
correcting a common misinterpretation in previous reporting on this river
system.
Turbidity exhibited
strong seasonality, with baseline values of 10–15 NTU during dry months
increasing sharply to 150–200 NTU during the monsoon (July–August), correlating
with elevated suspended sediment concentrations.
4.3.2. Nutrient
Loading and Eutrophication Risk
Table 7 presents seasonal nutrient
variation.
Table 7:
Seasonal Nutrient Concentrations at Barrage Site
|
Parameter
|
Monsoon
|
Winter
|
Spring
|
FAO
Guideline
|
|
NH₄-N
(mg/L)
|
0.55
|
0.60
|
0.86
|
2.0
(safe)
|
|
NO₃-N
(mg/L)
|
3.5
|
12.6
|
35.4
|
10
(caution)
|
|
PO₄-P
(mg/L)
|
0.04
|
1.15
|
3.5
|
0.1
(eutrophication threshold)
|
*95% CI for
spring PO₄-P: ±0.7 mg/L (n = 18).*
The phosphate
concentration in spring is higher than the threshold value (35 times higher -
3.5 mg/L) required for eutrophication, causing the growth of weeds in canals.
In spring, the nitrate concentration exceeds the critical level of 10 mg/L by a
large margin (35.4 mg/L).
4.3.3.
Infrastructure and Agronomic Impacts
High nutrient levels
create a triple threat: (1) biological clogging —
eutrophication-driven weed growth increases hydraulic roughness and maintenance
costs (Brix, 1997); (2) crop safety risks — excess nitrate in
spring vegetables; (3) health security — groundwater recharge
within the command area carries nitrate to shallow aquifers.
4.4. Synthesis: The Quantitative
Resilience Trilemma
The concurrent analysis reveals
interconnected constraints demanding integrated engineering response. Figure
4 illustrates the Resilience Trilemma.
Figure 4: The Resilience Trilemma –
Intersecting Issues Facing Irrigation System Efficiency: Three issues intersect
(hydrological extremes, sedimentation, and biological contamination). High
flows during flooding events (highest Q = 7,638 m³/s) result in sediment
movement. Sedimentation (monsoon sediment concentration = 2,214 ppm, D₅₀ = 0.4
mm) results in siltation and volume reduction. Eutrophication (spring PO₄-P =
3.5 mg/L) results in an increase in aquatic vegetation, thereby causing higher
hydraulic roughness. The overall effect of siltation and bio-fouling is
exponential inefficiency of the irrigation system.
4.4.1. Quantitative Interaction
Framework
Three concurrent challenges
interact synergistically, as summarized in Table 8.
Table 8: Resilience Trilemma —
Stressors, Magnitudes, and Interactions
|
Stressor
|
Magnitude
|
Design
Threshold
|
Interaction
Effect
|
|
Hydrological
extremes
|
7,638
m³/s (100-yr)
|
8,800–9,200
m³/s (climate-adjusted)
|
Controls
sediment transport capacity
|
|
Sediment
loading
|
2,214
ppm (monsoon peak)
|
D₅₀
capture: 0.4 mm
|
Provides
substrate for weed establishment
|
|
Biological
fouling
|
3.5
mg/L PO₄-P
|
<
0.1 mg/L
|
Increases
hydraulic roughness (Manning's n)
|
Synergistic degradation: Sediment deposition reduces
canal capacity, while weed growth increases hydraulic roughness. Together,
these processes reduce system efficiency exponentially during critical
irrigation periods — an effect not captured when stressors are analysed in
isolation.
4.4.2. Design and Management
Recommendations
Based on the integrated
assessment, Table 9 presents the recommended design parameters
for climate-resilient infrastructure.
Table 9: Design Parameters for
Climate-Resilient Infrastructure
|
Component
|
Parameter
|
Value
|
|
Barrage/Headworks
|
Climate-adjusted
100-yr flood
|
8,800–9,200
m³/s
|
|
Settling
Basin
|
Surface
area
|
3,347–6,300
m²
|
|
Overflow
rate
|
0.77
cm/s
|
|
|
D₅₀
capture
|
0.4
mm
|
|
|
Excess
capacity
|
30%
|
|
|
Unlined
Canals
|
Manning's
n
|
0.0225
|
|
Freeboard
(Q > 10 m³/s)
|
≥
0.8 m
|
|
|
Seepage
gradient
|
1:5
(V:H)
|
|
|
Counter
berm width
|
1.5–3.0
m
|
|
|
Water
Allocation
|
Design
duty
|
0.88
lps/ha
|
|
Head
regulator capacity (WMC)
|
48.2
m³/s
|
Operational Innovations:
- Real-time
monitoring of discharge, turbidity (as SSC proxy), and phosphate with
automated alerts
- Adaptive
gate operations for SSC > 500 ppm or PO₄-P > 0.5 mg/L
- Crop-specific
irrigation scheduling to avoid high-nitrate periods for leafy vegetables
Governance Priorities:
- Enforcement
of wastewater treatment standards in Kathmandu Valley
- Farmer
extension services for water-quality-based crop recommendations
4.5. Validation and Transferability
This framework was tested using
actual operational data from the Bagmati Irrigation Project (BIP, 2024). The
already existing Western Main Canal is running at a duty of 0.87 lps/ha which
is almost equal to the proposed duty of 0.88 lps/ha. The design parameters for
the extension areas (32,560 ha) are the same, with 7 secondary canals and 147
hydraulic structures on 24.8 km of main canal extension.
This integrated framework —
coupling climate-aware hydrology, supply-limited sedimentology, and
nutrient-impacted water quality — provides a transferable methodology for
resilience assessment and design in data-scarce mountain regions worldwide. The
true cost of irrigation development in rapidly changing basins must account not
only for concrete and steel but for the continuous management of silt and weeds
— management intrinsically linked to upstream land use and wastewater
governance decisions.
5. CONCLUSION
This study developed an integrated
engineering framework for climate-resilient irrigation infrastructure in
Nepal's Bagmati River Basin, combining 41 years of discharge data (1979–2019),
sediment records (1990–2024), and seasonal water quality monitoring. The
framework quantifies the "Resilience Trilemma” synergistic interactions
among hydrological extremes, supply-limited sediment transport, and
nutrient-driven eutrophication — where sediment deposition reduces canal
capacity while weed growth increases hydraulic roughness, together reducing
system efficiency exponentially.
Table
10: Summary of Design Parameters
|
Component
|
Parameter
|
Value
|
|
100-year
flood
|
Point
estimate (95% CI)
|
7,638
m³/s [6,110–9,166]
|
|
Climate
safety margin
|
+15–20%
(8,800–9,200 m³/s)
|
|
|
Environmental
flow
|
Q₉₅
|
11
m³/s
|
|
Pre-monsoon
trend
|
Sen's
slope (p = 0.03)
|
+15.3
m³/s/yr
|
|
Peak
SSC (monsoon)
|
Design
value
|
2,214
ppm
|
|
Post-earthquake
increase
|
p
= 0.008
|
+48.7%
|
|
Transport
regime
|
R²
|
<
0.3 (supply-limited)
|
|
Particle
size
|
D₅₀
|
0.4
mm
|
|
Settling
basin
|
Surface
area
|
3,347–6,300
m²
|
|
Overflow
rate
|
0.77
cm/s
|
|
|
Excess
capacity
|
30%
|
|
|
Bed
load
|
Estimate
|
10–20%
of total
|
|
Unlined
canals
|
Manning's
n
|
0.0225
|
|
Freeboard
(Q > 10 m³/s)
|
Minimum
|
0.8
m
|
|
Design
duty
|
Main
canals
|
0.88
lps/ha
|
|
Spring
phosphate
|
Concentration
|
3.5
mg/L (35× threshold)
|
|
Electrical
conductivity
|
Range
|
150–200
μS/cm (no salinity hazard)
|
|
SSC
alert
|
Trigger
|
>
500 ppm
|
|
Phosphate
alert
|
Trigger
|
>
0.5 mg/L
|
Engineering Priorities: The 100-year flood of 7,638
m³/s (95% CI: 6,110–9,166) establishes the safety baseline. Given the
significant increasing trend in pre-monsoon flows (τ = 0.22, p = 0.03; +15.3
m³/s/yr), a climate safety margin of 15–20% is recommended (8,800–9,200 m³/s).
Settling basins must be designed for peak SSC of 2,214 ppm and D₅₀ = 0.4 mm. This
rise in monsoon SSC by 48.7% after the earthquake requires an additional 30% of
capacity. Design duty is set to be 0.88 lps/ha to allocate water on the basis
of 80% assured flow (for example, 9.79 m³/s during April month). The design has
been checked for validity against real-world operations; the present day
Western Main Canal (28.4 km, 22,449 ha) performs at 0.87 lps.
Water Quality Management: Spring phosphate (3.5 mg/L)
exceeds the 0.1 mg/L eutrophication threshold by 35-fold, driving weed
proliferation. Spring nitrate (35.4 mg/L) exceeds the 10 mg/L caution level.
Electrical conductivity (150–200 μS/cm) remains below the FAO threshold of 700
μS/cm, posing no salinity hazard — correcting a common
misinterpretation. Real-time monitoring with automated alerts for SSC > 500
ppm and PO₄-P > 0.5 mg/L is recommended.
Transferability: This framework provides a
transferable model for climate-vulnerable mountain basins worldwide,
demonstrating that securing water for agriculture requires moving beyond
isolated structural solutions toward integrated systems designed for compounded
uncertainties.
ACKNOWLEDGMENTS
The authors thank the Department of
Hydrology and Meteorology (DHM), Nepal, for providing hydrological and sediment
data, and the Bagmati Irrigation Project (BIP) for operational data access and
field support. We acknowledge Noida International University for institutional
support and the anonymous reviewers for their constructive comments.
DECLARATIONS
Author Contributions
Ramesh Kumar Singh: Conceptualization,
Methodology, Data curation (hydrology + sediment), Writing – Original draft,
Formal analysis, Visualization.
Pradip Bantawa: Investigation (field data
collection – water quality), Writing – Review & editing, Data curation
(water quality).
Satendra Ray: Investigation (field data
collection – sediment), Writing – Original draft (Sections 4.2, 4.3), Analysis
(sediment grain size), Software (statistical analysis).
Prof. Dr. Sunil Thakur: Supervision, Writing – Review
& editing, Resources, Project administration, Validation (statistical
methods).
Conflict of Interest
The authors declare no conflict of
interest.
Funding
No funding was received for this research.
No funding was received for this research.
REFERENCES
Andermann, C., Longuevergne, L.,
Bonnet, S., Crave, A., Davy, P., &Gloaguen, R. (2012). Impact of transient
groundwater storage on the discharge of Himalayan rivers. Nature
Geoscience, 5(2), 127–130. https://doi.org/10.1038/ngeo1356
Annandale, G. W. (2011). Quenching
the thirst: Water and development in the 21st century. Springer.
APHA. (2017). Standard
methods for the examination of water and wastewater (23rd ed.).
American Public Health Association.
Aryal, J. P., Sapkota, T. B.,
Khurana, R., Khatri-Chhetri, A., Rahut, D. B., & Jat, M. L. (2022). Climate
change adaptation in agriculture. Climate Policy, 22(2),
168–182. https://doi.org/10.1080/14693062.2021.2011739
ASTM International. (2019). Standard
test methods for determining sediment concentration in water samples (ASTM
D3977-97). https://www.astm.org/d3977-97r19.html
Ayers, R. S., & Westcot, D. W.
(1985). Water quality for agriculture (FAO Irrigation and
Drainage Paper 29 Rev. 1). Food and Agriculture Organization.
Bagmati Irrigation Project (BIP).
(2024). Operational data records (Unpublished raw data).
Department of Water Resources and Irrigation, Government of Nepal.
Bookhagen, B., & Burbank, D. W.
(2010). Toward a complete Himalayan hydrological budget: Spatiotemporal
distribution of snowmelt and rainfall and their impact on river
discharge. Journal of Geophysical Research: Earth Surface,
115(F3). https://doi.org/10.1029/2009JF001426
Brix, H. (1997). Do macrophytes
play a role in constructed treatment wetlands? Water Science and
Technology, 35(5), 11–17. https://doi.org/10.1016/S0273-1223(97)00047-4
Carson, B. (1985). Erosion
and sedimentation processes in the Nepalese Himalaya. ICIMOD.
Chow, V. T. (1988). Applied
hydrology. McGraw-Hill.
Collins, A. L., & Walling, D.
E. (2004). Documenting catchment suspended sediment sources: Problems,
approaches and prospects. Earth-Science Reviews, 67(1–2),
95–137. https://doi.org/10.1016/j.earscirev.2004.02.001
Devkota, S., Dhakal, S., &
Regmi, A. D. (2021). Post-earthquake sediment dynamics in central Nepal. Journal
of Nepal Geological Society, 62, 45–58.
Dhital, Y. P., & Kayastha, R.
B. (2013). Frequency analysis of extreme events in the Kali Gandaki River
Basin, Nepal. Journal of Hydrology and Meteorology, 9(1),
1–12. https://doi.org/10.3126/jhm.v9i1.15549
Dodds, W. K., & Welch, E. B.
(2000). Establishing nutrient criteria in streams. Journal of the North
American Benthological Society, 19(1), 186–196. https://doi.org/10.2307/1468289
Döll, P., Jiménez-Cisneros, B.,
Oki, T., Arnell, N. W., Benito, G., Cogley, J. G., & Wada, Y. (2018). Risks
for the global freshwater system at 1.5 °C and 2 °C global warming. Environmental
Research Letters, 13(4), 044038. https://doi.org/10.1088/1748-9326/aab792
Efron, B., &Tibshirani, R. J.
(1993). An introduction to the bootstrap. Chapman & Hall.
Food and Agriculture Organization.
(1985). Water quality for agriculture (FAO Irrigation and
Drainage Paper 29 Rev. 1). FAO.
Food and Agriculture Organization.
(2013). Climate-smart agriculture sourcebook. FAO. http://www.fao.org/3/i3325e/i3325e.pdf
Food and Agriculture Organization.
(2017). Water quality for agriculture. FAO. http://www.fao.org/3/i6190e/i6190e.pdf
Food and Agriculture Organization.
(2020). Irrigation governance and climate resilience. FAO. http://www.fao.org/3/ca8711en/ca8711en.pdf
Food and Agriculture Organization.
(2021). Climate resilience in agriculture. FAO. http://www.fao.org/3/cb2780en/cb2780en.pdf
Gabet, E. J., Burbank, D. W.,
Pratt-Sitaula, B., Putkonen, J., & Bookhagen, B. (2008). Modern erosion
rates in the High Himalayas of Nepal. Earth and Planetary Science
Letters, 267(3–4), 482–494. https://doi.org/10.1016/j.epsl.2007.11.059
Gardner, R. A. M., & Gerrard,
A. J. (2003). Runoff and soil erosion on cultivated rainfed terraces in the
Middle Hills of Nepal. Applied Geography, 23(1), 23–45. https://doi.org/10.1016/S0143-6228(02)00068-5
Garrick, D., De Stefano, L., Yu,
W., Jorgensen, I., O'Donnell, E., Turley, L., & Wydra, A. (2017). Managing
water allocation under uncertainty. Water Resources Research,
53(4), 2500–2516. https://doi.org/10.1002/2016WR020174
Gautam, D., & Paudel, B. R.
(2021). Impact of Land Use and Land Cover Change on Sediment Yield: A Case
Study of the Bagmati River Basin, Nepal. Journal of Geographic
Information System, 13(4), 387–407. https://doi.org/10.4236/jgis.2021.134022
Gee, G. W., & Or, D. (2002).
Particle-size analysis. In J. H. Dane & G. C. Topp (Eds.), Methods
of soil analysis: Part 4 physical methods (pp. 255–293). Soil Science
Society of America.
Grafton, R. Q., Williams, J.,
Perry, C. J., Molle, F., Ringler, C., Steduto, P., & Wheeler, S. A. (2018).
The paradox of irrigation efficiency. Science, 361(6404),
748–750. https://doi.org/10.1126/science.aat9314
Hosking, J. R. M., & Wallis, J.
R. (1997). Regional frequency analysis: An approach based on L-moments.
Cambridge University Press.
Hussain, I., &Hanjra, M. A.
(2004). Irrigation and poverty alleviation: Review of the empirical
evidence. Water International, 29(1), 1–15. https://doi.org/10.1080/02508060408691746
Immerzeel, W. W., van Beek, L. P.
H., &Bierkens, M. F. P. (2010). Climate change will affect the Asian water
towers. Science, 328(5984), 1382–1385. https://doi.org/10.1126/science.1183188
Immerzeel, W. W., Pellicciotti, F.,
&Bierkens, M. F. P. (2013). Rising river flows throughout the twenty-first
century in two Himalayan basins. Nature Climate Change, 3(4),
364–368. https://doi.org/10.1038/nclimate1740
Intergovernmental Panel on Climate
Change. (2021). Climate change 2021: The physical science basis.
Contribution of Working Group I to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change. Cambridge University Press.
Julien, P. Y. (2010). Erosion
and sedimentation. Cambridge University Press.
Kaini, S., Nepal, S., Shrestha, A.
B., & Bharati, L. (2024). Climate change impacts on irrigation water
availability in Nepal. Journal of Hydrology: Regional Studies, 49,
101510. https://doi.org/10.1016/j.ejrh.2023.101510
Kannel, P. R., Lee, S., Lee, Y.-S.,
Kanel, S. R., & Khan, S. P. (2007). Spatial-temporal variation and
comparative assessment of water quality of the Bagmati River, Nepal. Environmental
Monitoring and Assessment, 129(1–3), 433–459. https://doi.org/10.1007/s10661-006-9375-6
Kargel, J. S., Leonard, G. J.,
Shugar, D. H., Haritashya, U. K., Bevington, A., Fielding, E. J., &
Anderson, K. (2016). Geomorphic and geologic controls of landslides induced by
the 2015 Gorkha earthquake. Science, 351(6269), aac8353. https://doi.org/10.1126/science.aac8353
Khadka, U. R., & Pathak, D.
(2016). Water Quality Assessment of the Bagmati River and its Tributaries in
the Kathmandu Valley, Nepal. Journal of Water Resource and Protection,
8(12), 1111–1123. https://doi.org/10.4236/jwarp.2016.812087
Loucks, D. P., & Van Beek, E.
(2017). Water resource systems planning and management: An introduction
to methods, models, and applications. Springer. https://doi.org/10.1007/978-3-319-44234-1
Lutz, A. F., Immerzeel, W. W.,
Kraaijenbrink, P. D. A., Shrestha, A. B., &Bierkens, M. F. P. (2014).
Climate change impacts on the upper Indus basin. Hydrology and Earth
System Sciences, 18(11), 4661–4676. https://doi.org/10.5194/hess-18-4661-2014
Malano, H., Davidson, B., &
George, B. (2017). Irrigation system resilience to climate change. Irrigation
and Drainage, 66(5), 642–656. https://doi.org/10.1002/ird.2128
Meinzen-Dick, R., Pradhan, R.,
& Ringler, C. (2014). Governance of irrigation systems: A review of
literature and recent developments. Water Resources Research,
50(2), 1191–1210. https://doi.org/10.1002/2013WR014398
Milly, P. C. D., Betancourt, J.,
Falkenmark, M., Hirsch, R. M., Kundzewicz, Z. W., Lettenmaier, D. P., &
Stouffer, R. J. (2008). Stationarity is dead: Whither water management? Science,
319(5863), 573–574. https://doi.org/10.1126/science.1151915
Mirza, M. M. Q. (2011). Climate
change, flooding in South Asia and implications. Regional Environmental
Change, 11(1), 95–107. https://doi.org/10.1007/s10113-010-0184-7
Molden, D., Oweis, T., Steduto, P.,
Bindraban, P., Hanjra, M. A., &Kijne, J. (2010). Improving agricultural
water productivity: Between optimism and caution. Agricultural Water
Management, 97(4), 528–535. https://doi.org/10.1016/j.agwat.2009.03.023
Nepal, S., Wahid, S., Shrestha, A.
B., & Mukherji, A. (2021). Integrated assessment of climate change impacts
on water resources. Science of the Total Environment, 752,
141889. https://doi.org/10.1016/j.scitotenv.2020.141889
Palazzi, E., von Hardenberg, J.,
& Provenzale, A. (2013). Precipitation in the Hindu-Kush Karakoram
Himalaya: Observations and future scenarios. Journal of Geophysical
Research: Atmospheres, 118(1), 85–100. https://doi.org/10.1029/2012JD018697
Playán, E., & Mateos, L.
(2006). Modernization and optimization of irrigation systems to increase water
productivity. Agricultural Water Management, 80(1–3),
100–116. https://doi.org/10.1016/j.agwat.2005.07.007
Practical Action.
(2009). *Temporal and spatial variability of climate change over Nepal
(1976-2005)*. Practical Action Nepal.
Pradhan, P. K. (2019). Water
in Nepal: A crisis of governance. Himal Books.
Qureshi, A. S. (2020). Sustainable
irrigation under climate change. Water, 12(11), 3105. https://doi.org/10.3390/w12113105
Rao, A. R., & Hamed, K. H.
(2000). Flood frequency analysis. CRC Press.
Rasul, G., & Sharma, B. (2016).
The nexus approach to water–energy–food security: An option for adaptation to
climate change. Environmental Development, 18, 15–33. https://doi.org/10.1016/j.envdev.2015.09.002
Sundar, D., Karmacharya, J., &
Shrestha, S. (2020). Water Quality Assessment of the Bagmati River and its
Tributaries, Kathmandu, Nepal. Journal of Institute of Science and
Technology, 25(1), 12–23. https://doi.org/10.3126/jist.v25i1.29383
Tennant, D. L. (1976). Instream
flow regimens for fish, wildlife, recreation and related environmental
resources. Fisheries, 1(4), 6–10. https://doi.org/10.1577/1548-8446(1976)001<0006:IFRFFW>2.0.CO;2
Vanoni, V. A. (Ed.). (2006). Sedimentation
engineering. ASCE Press.
Vörösmarty, C. J., McIntyre, P. B.,
Gessner, M. O., Dudgeon, D., Prusevich, A., Green, P., & Davies, P. M.
(2010). Global threats to human water security and river biodiversity. Nature,
467(7315), 555–561. https://doi.org/10.1038/nature09440
Walling, D. E. (2008). The changing
sediment loads of the world's rivers. Annals of Warsaw University of
Life Sciences-SGGW, Land Reclamation, 39, 3–20.
Warrick, J. A. (2015). Sediment
yield from the tectonically active semiarid Western Transverse Ranges of
California. Geological Society of America Bulletin, 127(7–8),
1054–1070. https://doi.org/10.1130/B31109.1
World Bank. (2017). Water-smart
agriculture in East Africa. World Bank Group. https://openknowledge.worldbank.org/handle/10986/28354
World Bank. (2019). Climate-resilient
water infrastructure: Enhancing the climate resilience of Africa's
infrastructure. World Bank. https://documents.worldbank.org/en/publication/documentsreports/documentdetail/482301562141661540