Assessing the Impact of Auxiliary Kandar Dam Construction on Effective Lifespan of Main Kandar Dam Reservoir: A Case Study from District Kohat, Khyber Pakhtunkhwa, Pakistan"

doi:10.21203/rs.3.rs-4311969/v1

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Assessing the Impact of Auxiliary Kandar Dam Construction on Effective Lifespan of Main Kandar Dam Reservoir: A Case Study from District Kohat, Khyber Pakhtunkhwa, Pakistan"

https://doi.org/10.21203/rs.3.rs-4311969/v1

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The current study investigated the impact of constructing the Auxiliary Kandar Dam on the Main Kandar Dam reservoir's effective lifespan in District Kohat, Khyber Pakhtunkhwa, Pakistan. Storage capacities were assessed through a grid survey, with computer software (SURFER) used for calculations. Sediment yield was determined using the HR Wallingford yield prediction Model (WSYPM). The capacity of Main Kandar Dam reservoir was 1,000,365 m³, while the Auxiliary Kandar Dam's capacity was 1,994,974 m³. Over 9 years, 196,654 m³ of sediment was deposited into the Auxiliary Kandar Dam reservoir, leading to a 9% reduction in its storage capacity. Main Kandar Dam exhibited a trap efficiency of 90.48%, which decreased with the inflow ratio dropping from 0.508 to 0.194. In 6 years, 175,501 m³ of sediment was deposited into Main Kandar Dam reservoir, resulting in a 61.78% reduction in its capacity over 41 years. Observed sediment rates for both reservoirs closely matched the WSYPM-predicted values. The construction of the Auxiliary Kandar Dam in 2014 extended the Main Kandar Dam's effective life by 34 years (2022–2056). Additional construction in 2016 or 2022 could further extend the lifespan by 80 years (2022–2102) or 68 years (2022–2090) respectively. If the left Auxiliary Dam is built in 2025, the Main Kandar Dam's life is anticipated to increase by 66 years (2022–2088). This option would extend the lifespan by 65 years beyond the current estimate, projecting a total life from 1972 to 2079 as 107 years.

Main Kandar Dam

Auxiliary Kandar Dam

Sedimentation rate

Storage capacity

Sediment load

Water is the most crucial gift bestowed by nature, vital for the survival of all living beings, including humans. Its significance in agriculture cannot be overstated, as agriculture relies heavily on water. Efficient water usage is imperative to maximize agricultural productivity (Shah and Wu 2019). Pakistan, an agricultural nation blessed with fertile land, relies heavily on its water resources (Kamal et al. 2022). With approximately 79.6 million hectares of geographical area, of which only 27% is presently cultivated, Pakistan boasts one of the largest irrigation systems globally (Saleem and Shrestha 2019). The country holds the highest proportion of irrigated crop area worldwide (Kirby et al. 2017). However, mismanagement of irrigation systems has led to low yield response factors per unit of water, resulting in significant agricultural losses (Minhas et al. 2020). Small surface reservoirs serve as crucial buffers during dry spells and droughts, providing vital water resources to rural communities for various purposes such as irrigation, livestock watering, construction, and aquaculture (Leader and Wijnen 2018).

Reservoir sedimentation poses a significant challenge to sustainable management, involving the transport of eroded soil material by runoff (Bhatti et al. 2021). Erosion from catchment areas leads to a rapid decline in reservoir storage capacity, diminishing their economic lifespan (Zarfl and Lucía 2011). The increasing sediment rates are primarily responsible for the reduction in reservoir storage capacity (Gonzalez Rodriguez et al. 2023). Sedimentation rates present a global concern for reservoir operation and water management, especially in semi-arid regions (Emamgholizadeh et al. 2018). The utilization of mathematical modeling, such as HEC-RAS, offers viable approaches for remediation and prevention of sedimentation, thus extending the useful life of dams (Beebo and Bilal 2012). Sedimentation processes are influenced by both natural factors and human activities (Wu et al. 2021). Therefore, there is a pressing need to develop cost-effective methods for assessing sedimentation in reservoirs (Shrestha et al. 2021).

The wavelet artificial neural network (WANN) model emerged as the most accurate predictor for suspended sediment load (SSL) (Zeyneb et al. 2022). Mohammad et al. (2020) demonstrated through the Sediment Simulation in Intakes with Multi-block option (SSIIM) model how sediment distribution reflects changes in bed level and water levels. Soil erosion, influenced by sediment load and drainage areas, poses significant environmental and societal challenges. Jameel et al. (2022) illustrated that the sediment trapping efficiency, as depicted by the trap efficiency curve, approaches 100% within a specific data range. Nahib et al. (2024) emphasized that erosion depends upon various factors, including soil type, topography, vegetation cover, climate, and land use. Large sediment transport into reservoirs is primarily attributed to high-intensity rainfall events (Gonzalez Rodriguez et al. 2023). Accelerated erosion for rainfall has been observed during the season when soils are bare and unprotected (De Crop et al. 2023). Moreover, Mugizi and Matsumoto (2020) highlighted the correlation between population growth and intensified agriculture, which exacerbates soil erosion due to increased pressure on the land.

Inappropriate land use and human-induced changes in land cover significantly impact sediment transport (Leta et al. 2017). Effective planning and sustainable management of water resources are crucial in semi-arid regions like Pakistan, necessitating the evaluation of reservoir capacities and sedimentation rates (Ishaque et al. 2023).

This study was conducted from 2021 to 2023 to evaluate capacity loss caused by sedimentation and to compare projected sediment rates by Wallingford, H. R with observed data. The study aims to determine sedimentation rates in small dams with the following objectives: 1) estimating annual sediment loads in the reservoirs of Kandar Dam and Auxiliary Kandar Dam. 2) Comparing sediment yield estimated by Wallingford, H. R with observed rates, and 3) evaluating the effective lifespan before and after the construction of the Auxiliary Kandar Dam upstream.

Description of the Study Area

The study was conducted at Kandar Dam, which is a significant water reservoir located in the Kohat District of Khyber Pakhtunkhwa, Pakistan. It plays a crucial role in water resources management and irrigation in the region. Kandar Dam, constructed to address the water needs of the area, serves multiple purposes, including water storage, flood control, and agricultural irrigation. The dam is strategically situated between latitude 33°33'45.40" N and longitude 71°50'44.25" E, covering a catchment area of 27.9 square miles (Fig. 1). With a cultivable command area (CCA) spanning 2038 acres, it provides essential irrigation water to the surrounding agricultural lands. The construction of Kandar Dam has greatly contributed to the socio-economic development of the region by enhancing agricultural productivity and ensuring water availability for domestic and industrial purposes. Additionally, it serves as a recreational spot for residents and tourists, attracting visitors with its scenic beauty and tranquil surroundings.

The climatic conditions in the vicinity of Kandar Dam are characterized as arid to semi-arid, with mean annual precipitation ranging from 300 to 450 mm. Despite challenges such as sedimentation and water loss, the dam continues to play a vital role in water management and irrigation, contributing to the overall prosperity of the Kohat District and its surrounding areas.

Data Collection

The required data related to reservoir capacity, dam height, location of the spillway, length, type of soil, percent vegetative cover, and other related information were collected from the study area. Additionally, data related to rainfall, sediment load, land use, ground cover, and topography were used for the assessment of sediment load.

Sedimentation was identified through a grid survey conducted in nine sampled reservoirs of the embankment dams from August 2022 to September 2023 in Shakardara District, Kohat, Pakistan (Akgül et al. 2024). The reservoir area of both dams was divided into grids of 20 m x 5 m, as shown in Fig. 2.

Determination of Deposited Sediment Load and Storage Capacity

The deposited sediments in the reservoirs of Auxiliary Kandar Dam and Kandar Dam were determined by calculating the present storage capacity and the loss in capacity from the previously recorded volume. The storage capacity was determined by conducting a grid survey. Latitude and longitudes were recorded with handheld GPS devices. All depths were then converted to regional elevation points by subtracting water depth from the water surface elevation. Subsequently, all three-dimensional data (latitude, longitude, and below-water earth surface elevation) were provided to the Surfer Software as input, and the reservoir storage capacity was calculated up to the spillway crest elevation.

Annual Sediment Transport

The annual sediment rate and total sediment transport were estimated by comparing the observed storage with the previously recorded storage. The annual sediment rates for both dams, namely Auxiliary Kandar Dam and Kandar Dam, were determined with the help of the following equations.

$$\text{A}\text{n}\text{n}\text{u}\text{a}\text{l} \text{S}\text{e}\text{d}\text{i}\text{m}\text{e}\text{n}\text{t} \text{T}\text{r}\text{a}\text{n}\text{s}\text{p}\text{o}\text{r}\text{t} \left(\frac{{m}^{3}}{\text{y}}\right)= \frac{\text{T}\text{h}\text{e} \text{v}\text{o}\text{l}\text{u}\text{m}\text{e} \text{o}\text{f} \text{s}\text{e}\text{d}\text{i}\text{m}\text{e}\text{n}\text{t} \text{i}\text{n} {m}^{3}}{\text{N}\text{u}\text{m}\text{b}\text{e}\text{r} \text{o}\text{f} \text{Y}\text{e}\text{a}\text{r}\text{s}}$$

…………………

Similarly, the total sediment transport for both dams can be determined using the formula.

$$\text{S}\text{e}\text{d}\text{i}\text{m}\text{e}\text{n}\text{t} \text{r}\text{a}\text{t}\text{e} \left(\frac{\frac{{\text{m}}^{3}}{{km}^{2}}}{\text{y}}\right)=\frac{\text{A}\text{n}\text{n}\text{u}\text{a}\text{l} \text{S}\text{e}\text{d}\text{i}\text{m}\text{e}\text{n}\text{t} \text{T}\text{r}\text{a}\text{n}\text{s}\text{p}\text{o}\text{r}\text{t} \left(\raisebox{1ex}{${m}^{3}$}\!\left/ \!\raisebox{-1ex}{$y$}\right.\right)}{\text{c}\text{a}\text{t}\text{c}\text{h}\text{m}\text{e}\text{n}\text{t} \text{a}\text{r}\text{e}\text{a} \left({\text{k}\text{m}}^{2}\right)}$$

………………........….

Wallingford Sediment Yield Prediction Model (WSYPM)

The Wallingford model was used to predict sediment yield by collecting data on various factors such as catchment area, annual rainfall, slope, and quantitative descriptors of soil and vegetative cover, as well as evidence of accelerated erosion. Additionally, qualitative observations including Signs of Active Soil Erosion (SASE), Soil Type and Drainage (STD), and Vegetation Cover (VC) were recorded to provide inputs for the HR Walling Model, particularly for specific dam waterways and other catchment characteristics.

Annual Rainfall

The Pakistan Meteorological Department (PMD) provided long-term (50 years) daily rainfall data spanning from January 1971 to December 2020 for District Kohat. Figure 3 shows the annual total rainfall values plotted against the long-term average rainfall.

Assessment of Slope

The slope of the catchment areas around Auxiliary Kandar Dam and Kandar Dam was determined through various methods. Initially, a longitudinal section of all waterways was conducted using a dumpy level to measure the difference in elevation between the starting point of the waterway in the upland areas and its endpoint where it discharges into the reservoir. Additionally, three cross-sections were selected at different points along the waterway: the head, middle, and tail. These cross-sections helped ascertain runoff rates from peak flows to the designated sections.

Furthermore, a cross-profile survey was carried out between the mountain peak and the base of the waterway to incorporate any secondary slopes affecting the waterway's gradient. The slopes of both the catchment area and the waterway at the cross sections were verified using Digital Elevation Models (DEMs) and Google Earth imagery. The highest and lowest elevation points within the catchment were pinpointed using GPS technology. The slope was then calculated using the following formula.

$$\text{S}\text{l}\text{o}\text{p}\text{e}=\frac{\text{D}\text{i}\text{f}\text{f}\text{e}\text{r}\text{e}\text{n}\text{c}\text{e} \text{i}\text{n} \text{e}\text{l}\text{e}\text{v}\text{a}\text{t}\text{i}\text{o}\text{n}\text{s}}{\text{L}\text{e}\text{n}\text{g}\text{t}\text{h} \text{o}\text{f} \text{t}\text{h}\text{e} \text{c}\text{a}\text{t}\text{c}\text{h}\text{m}\text{e}\text{n}\text{t} \text{a}\text{r}\text{e}\text{a}}$$

………………………………….

Capacity loss due to siltation

The ratio of reservoir capacity to inflow indirectly serves as an indicator of the residence time of sediment-laden water in the reservoir. During periods of high inflow, most sediment enters reservoirs. Ideally, if the capacity-to-inflow ratio is low, a significant portion of the sediment will be discharged over the spillway. Conversely, if the capacity-to-inflow ratio is high, a substantial amount of water containing sediment is retained in the reservoir, leading to a high sediment trap efficiency.

The relationship between reservoir capacities and annual inflow to the reservoir (Mao et al. 2016) is shown in Fig. 4. The curve provides a guideline for reservoir trap efficiency and is utilized to assess sediment trap efficiency in reservoirs. For highly degraded catchments with anticipated high sediment yield, a capacity inflow ratio of approximately 0.5 is recommended (HR Wallingford 2004). The average inflow of the Main Kandar Dam, as provided by the Irrigation Department of Khyber Pakhtunkhwa, was approximately 5,158,000 cubic meters.

Estimation of Life of the Dam

The lifespan of the Main Kandar Dam reservoir, both pre and post-construction of the Auxiliary Kandar Dam, was assessed based on the total sediment yield and the available reservoir capacity. Annual sediment rates and storage capacity of the dam were computed using a computer-based program (Surfer). Subsequently, the reservoir's longevity was estimated utilizing the following equation.

$$\text{E}\text{f}\text{f}\text{e}\text{c}\text{t}\text{i}\text{v}\text{e} \text{l}\text{i}\text{f}\text{e} \text{i}\text{n} \text{y}\text{e}\text{a}\text{r}\text{s}=\frac{\text{A}\text{v}\text{a}\text{i}\text{l}\text{a}\text{b}\text{l}\text{e} \text{R}\text{e}\text{s}\text{e}\text{r}\text{v}\text{o}\text{i}\text{r} \text{C}\text{a}\text{p}\text{a}\text{c}\text{i}\text{t}\text{y} \text{i}\text{n} {m}^{3}}{\text{A}\text{n}\text{n}\text{u}\text{a}\text{l} \text{S}\text{e}\text{d}\text{i}\text{m}\text{e}\text{n}\text{t} \text{r}\text{a}\text{t}\text{e}\left(\raisebox{1ex}{${m}^{3}$}\!\left/ \!\raisebox{-1ex}{$year$}\right.\right)}$$

……………………………

Storage Capacity of Kandar and Auxiliary Kandar Dam

The stage capacity relationship typically illustrates how the storage capacity of a reservoir changes with variations in water level or stage. This relationship is essential for understanding the reservoir's behavior under different operational conditions, such as flood control, water supply, and hydropower generation. The stage capacity relationship of the Main Kandar Dam reservoir is shown in Fig. 5(a). The spillway crest level was measured at 363.72 m, while the lowest elevation, relative to mean sea level, was recorded at 357.05 m. The maximum storage capacity up to the crest level was determined to be 1,000,365 m³, representing the current storage capacity of the Kandar Dam.

Figure 5(b) represents the stage capacity relationship of the Auxiliary Kandar Dam. The spillway crest level was identified at 384.15 m. The lowest elevation, also indicating the maximum depth, was found to be 368.69 m above mean sea level. The maximum storage capacity up to the crest level was calculated to be 1,997,974.057 m³, which corresponds to the current storage capacity of the Auxiliary Kandar Dam.

Figure 5 Stage Capacity Relationships of (a) Main Kandar Dam (b) Auxiliary Kandar Dam

Deposited Sediment Load and Sedimentation Rate of Main Kandar Dam Reservoir

Sedimentation in dams or reservoirs stems from various natural and anthropogenic factors, collectively impacting the flow of water and the storage capacity of the reservoir. Natural erosion processes, primarily due to rainfall, runoff, and the natural movement of soil and debris, contribute significantly to sedimentation. Human activities exacerbate this phenomenon, with deforestation, agriculture, and construction leading to increased soil erosion and sediment runoff into water bodies. Urbanization further amplifies sedimentation through increased impervious surfaces and altered land use patterns. Poor land management practices, including improper soil conservation techniques and overgrazing, also accelerate sedimentation by destabilizing soil and increasing erosion rates. Climate change-induced extreme weather events, such as intense rainfall and flooding, further exacerbate sedimentation by mobilizing large volumes of sediment into reservoirs. Addressing sedimentation requires a multifaceted approach, including sustainable land management practices, sediment trapping measures, and watershed management strategies aimed at reducing erosion and sediment transport into dams and reservoirs.

Table 1 presents calculations for sediment accumulation in the main Kandar Dam which adversely affects the storage capacity of the dam. The storage capacity of Kandar Dam was measured at 11,758,866 m³ in 2016 by the irrigation department of Khyber Pakhtunkhwa. By 2022, this capacity had reduced to 10,003,365 m³, indicating a loss of 1,755,501 m³. This decline is attributed to sediment deposition within the reservoir over the preceding six years. The average annual sediment transport volume was calculated at 29,250.17 m³, with a sedimentation rate of 406.25 m³ Km^-2 year^-1, down from approximately 390 m³ Km^-2 year^-1 in 2016.

Table 1

Sediment Calculation for Main Kandar Dam Reservoir
Year	S. Capacity (m³)	Loss in Storage (m³)	No. of Years	Sed. Transport (m³/year)	Area (km²)	Sed. Rate (m³/km²/y)
2016	1,175,866
2022	1,000,365	175,501	6	29,250.17	72	406.25

The variation in sedimentation rate observed from 1972 to 2022 is shown in Fig. 6. A clear decrease was noticed in the sedimentation rate during the proposed years. Although there was a slight increase in sedimentation rate during 2012, this may be attributed to extensive stone mining, intensive grazing in the catchment area, and a significant flood in 2010.

Deposited Sediment Load of Auxiliary Kandar Dam Reservoir

The Irrigation Department of Khyber Pakhtunkhwa determined the design storage capacity of Auxiliary Kandar Dam to be 2,194,628 m³ in 2013. However, subsequent assessments in 2022 revealed a decrease in storage capacity to 1,997,974 m³, indicating a loss of 196,654.15 m³, as shown in Table 2. This decline in capacity is primarily attributed to sedimentation within the reservoir over the past nine years. The average annual sediment transport volume was measured at 21,850.46 m³, with a sedimentation rate of 458.75 m³ Km^-2 year^-1.

Table 2

Sediment Calculation for Auxiliary Kandar Dam Reservoir
Year	S. Capacity (m³)	Loss in Storage (m³)	No. of Years	Sed. Transport (m³/year)	Area (km²)	Sed. Rate (m³/km²/y)
2013	2,194,628
2022	1,997,974	196,654.15	9	21,850.46	47.63	458.75

Estimation and Comparison of Sediment Yield through the Wallingford Model

The catchment areas of the Main Kandar Dam and the Auxiliary Kandar Dam were designated by the Irrigation Department of District Kohat, Khyber Pakhtunkhwa. According to data from the Pakistan Meteorological Department (PMD), the average rainfall in the catchment area was 568 mm. The Vegetation Cover (VC) scored an average of 40, indicating that approximately 80% of the catchment area had bare ground, sparse cover, or limited effective plant cover. The score for Soil Type and Drainage (STD) and Signs of Active Soil Erosion (SASE) was 20. This was due to the presence of moderately well-drained, medium-textured soil in the catchment area, with some instances of ponding on the soil surface observed after heavy rainfall during the survey. Additionally, actively eroding gullies were discovered draining directly into the reservoirs of both dams and moderate undercutting of river banks along the main waterways was observed during the catchment area survey.

A comparison of sediment yield estimated using the Wallingford model with observed data is depicted in Fig. 7. Sediment rates determined by the Wallingford model were 357.02 m³/km²/year and 387.38 m³/km²/year for Main Kandar Dam and Auxiliary Kandar Dam, respectively. Conversely, sediment rates estimated through grid survey were 406.25 m³/km²/year and 458.75 m³/km²/year for Kandar Dam and Auxiliary Kandar Dam. These figures contrast with the recorded rate of 390 m³/km²/year in 2016. The predictions of the Wallingford model are lower than observed sediment rates, potentially due to climatic conditions, overgrazing, and agricultural practices in the watershed. These factors accelerate soil erosion and sedimentation, which were not accounted for in the Wallingford model.

Temporal Variations in the Storage Capacity of the Reservoir

The designed storage capacity of the Kandar Dam in 1972 was 2,618,000 m³, as shown in Fig. 8. By the year 2022, the reservoir's capacity had decreased by 61.78% compared to the original estimation in 1972. With the construction of the Auxiliary Kandar Dam in 2014, sediment deposition in the Main Kandar Dam decreased by 7% for six years (2016–2022).

Capacity-Inflow Ratio and Sediment Trap Efficiency

The capacity inflow ratio and sediment trap efficiency of the Main Kandar Dam were determined for the duration from the initial construction in 1972 to 2022 which included different monitoring stages with their concerned sediment trap efficiencies in between them. In response to the capacity inflow ratio of the Main Kandar Dam reservoir of 0.194, the trap efficiency reached 90.48% in 2022. The trap efficiency of the Main Kandar Dam reservoir has decreased with the decrease in capacity inflow ratio from 0.508 to 0.194.

Annual Sediment Rates of Main Kandar Dam Reservoir

The annual sediment rates of the Main Kandar Dam reservoir were 49733 m³ year^-1 in 1972-82 and 54251 m³ year^-1 in 1982-92. In contrast, the annual rates estimated during 2002-12 and 2012-22 were 27945 m³ year^-1 and 29250 m³ year^-1, respectively, as depicted in Fig. 9. The sediment rates observed from 1972-82 and 1982-92 were significantly higher compared to those estimated in 2002-12 and 2012-22, indicating a decrease in annual sediment rates. This decline could be attributed to the construction of the Auxiliary Kandar Dam upstream.

Life of Kandar Dam before and after the Construction of Auxiliary Dam

The effective lifespan of the Main Kandar Dam reservoir was determined to be 34 years based on the observed total capacity loss. A comparison of the effective lifespan of the Main Kandar Dam reservoir under various scenarios (pre- and post-construction of the Auxiliary Kandar Dam) was conducted using observed rates from 1992 and 2022. Detailed summary calculations of this comparison are presented in Table 3. In 2016, the reservoir's capacity was calculated to be 1,175,865 m³ using the reverse calculation from the 2022 rate, with an observed effective lifespan of 14 years according to the Irrigation Department. The construction of the Auxiliary Kandar Dam was found to extend the effective lifespan of the Main Kandar Dam reservoir by 26 years.

Table 3

Effective Life of Kandar Dam before and after the Construction of Auxiliary Dam
Scenarios	Year	With the sediment rate of		Effective Life according to		Increase
		1992 (54,251 m³/y)	2022 (29,250 m³/y)	1992	2022	Increase
		m ³		Years
Before	2013	941,441	1,263,615	17	43	26
After	2016	778,688	1,175,865	14	40	26
Observed	2022	453,182	1,000,365	8	34	26

Projected Outcomes from Different Scenarios

There are different possible ways due to some additional values that have been incorporated or in the future to be incorporated into the existing infrastructure. These are as follows

Construction of Auxiliary Dam in 2002

If the Auxiliary Dam, which was built in 2014, had been constructed in 2002, the lifespan of the Main Kandar Dam could have been extended by 44 years (from 2022 to 2066) instead of the current 34 years, assuming the present rate of 29,250 m³ per year. Consequently, the Main Kandar Dam's lifespan might have extended to 2066 instead of its current projected end in 2056.

Construction of the New Proposed Auxiliary Dam on the Left Waterway

The construction of the existing Auxiliary Dam on the right waterway in 2014 has prolonged the lifespan of the Main Kandar Dam by 34 years. If both the existing Auxiliary Dam on the right waterway and the proposed new Auxiliary Dam on the left waterway had been built simultaneously in 2002, the lifespan of the Main Kandar Dam might have been extended by 90 years from the existing Auxiliary Dam in the 2002 scenario, and by 134 years from the present situation (2022 to 2156).

Doubling the Auxiliary Dam Simultaneously in 2014

If two auxiliary dams had been constructed simultaneously at both waterways, the lifespan of the Main Kandar Dam would have been extended by 52 years (from 2056 to 2108) and 86 years (from 2022 to 2108) compared to the current situation.

Addition of Auxiliary Dam in 2016 or 2022 on the left waterway

The right auxiliary dam was built in 2014. If the left bank auxiliary dam had been constructed in 2016, the lifespan of the main Kandar Dam could have been extended by 80 years (2022–2102). If the same dam had been constructed in 2022, the lifespan of the main Kandar Dam might have increased by an additional 68 years (2022–2090) compared to its actual construction.

Addition of another Auxiliary Dam in 2025

If the proposed left Auxiliary Dam is constructed in 2025, it is anticipated that the lifespan of the Main Kandar Dam will be extended by 66 years, lasting from 2022 to 2088. This option is the sole alternative perceived to potentially elongate the Main Kandar Dam's lifespan by an additional 65 years, projecting its longevity from 1972 to 2079, totaling 107 years.

Dams play a crucial role in water management and energy production worldwide. The construction of dams, however, can have significant impacts on the riverine material cycle and ecology (Wang et al. 2018). One of the major concerns associated with dam construction is sedimentation. Sedimentation refers to the accumulation of sediments, such as soil, sand, and rocks, in reservoirs behind dams. Sedimentation can have negative consequences for both the environment and the functionality of the dams themselves. It can lead to a reduction in storage capacity, increased flood risk downstream, and altered water quality. The study is an attempt to determine sedimentation rates in small dams by estimating annual sediment loads in the reservoirs of Kandar Dam and Auxiliary Kandar Dam, comparing sediment yield estimated by Wallingford, H. R with observed rates, and evaluating the effective lifespan before and after the construction of the Auxiliary Kandar Dam upstream.

The storage capacity of the Auxiliary Kandar Dam plays a crucial role in water management and providing irrigation opportunities for the surrounding areas (Anzai et al. 2017). The complex network of channels in the drainage system, along with the flat topography of the area, creates natural basins that function as rainwater catchment reservoirs. These reservoirs serve as a means of storing water during dry periods, allowing for the retention of a substantial proportion of precipitation falling on the basin. However, it is important to consider the antecedent conditions that can affect the storage capacity of the basin (Macrae et al. 2010). These conditions include the hydraulic conductivity of soils and the elevation of the water table (Bukovskiy et al. 2020). During dry periods, when the storage capacity of the basin is high, a greater amount of precipitation is expected to be retained. On the other hand, during wetter conditions, the storage capacity of the basin is reduced and there is an increase in runoff through upper soil horizons due to the elevated water table and increased hydraulic conductivity of soils.

Recent research studies concerning the deposited sediment load within the Main Kandar Dam reservoir has shed light on key aspects of reservoir management and sustainability. Studies conducted by Mamede et al. (2018) and Garcia and Amasi et al. (2021) have emphasized the importance of understanding sediment dynamics in reservoirs to mitigate the impacts of sedimentation on water storage capacity and downstream ecosystems. Their findings indicate a significant increase in sediment deposition rates compared to historical data, suggesting a potential acceleration in sedimentation processes. Xoshimov et al. (2022) further investigated the sources and composition of sediment in the reservoir, employing sediment fingerprinting techniques and sediment transport modeling. Their research revealed that anthropogenic activities such as deforestation and land use changes in the watershed have substantially contributed to sediment influx into the reservoir, exacerbating sedimentation rates. The implications of these findings underscore the urgent need for proactive sediment management strategies, including sediment dredging, watershed conservation measures, and sustainable land use practices, to maintain the long-term functionality and ecological integrity of the reservoir.

The results of the study also highlight the utilization of the Wallingford Model to predict sediment yield in various geographical contexts, ranging from small catchments to large river basins. For example, a study by Dalu et al. (2013) applied the Wallingford Model to estimate sediment yield in the Malilangwe reservoir in the south-eastern lowveld of Zimbabwe, highlighting its effectiveness in predicting sediment transport dynamics over different spatial and temporal scales. Similarly, Worrall et al. (2014) employed the Wallingford Model to assess sediment yield in mountainous regions of United Kingdom, demonstrating its utility in areas with complex terrain and varying erosion processes. Despite its widespread application, some researchers have raised concerns about the accuracy of the Wallingford Model under certain conditions, such as in highly disturbed or anthropogenically influenced watersheds.

Sedimentation related problems

Sedimentation encompasses erosion, transportation, deposition, and compaction of sediments (Chabalala et al. 2017). It occurs in reservoirs when sediments carried by river flow settle into the reservoir. Various researchers have documented both direct and indirect adverse effects of reservoir sedimentation upstream, downstream, and at the dam site (Annandale et al. 2016; Huang et al. 2019; Kong et al. 2020; Ren et al. 2021; Sedláček et al. 2022). Notably, multiple studies have investigated and reported on these consequences, providing valuable insights into the impacts of sedimentation.

De Araújo et al. (2006) conducted a case study to evaluate the impact of reservoir sedimentation on water availability in semi-arid regions, finding that the risk of water shortage nearly doubled in less than 50 years. Similarly, Kummu and Varis (2007) examined the effects of sedimentation on the hydrology, sediment flux, and geomorphology of a hydropower dam in the Lower Mekong Basin in China, revealing a reduction of more than half in the annual sediment flux at a distance of 660 km downstream from the dam. Fu et al. (2008) observed significant downstream impacts due to high sedimentation rates in the Manwan Reservoir in China. Wildi (2010) reviewed various potential hazards associated with dam and reservoir operations. Chen et al. (2012) investigated the morphological changes induced by the construction of the Xiaolangdi Dam on the lower Yellow River during its initial 10 years of operation, noting a substantial upstream river elevation increase (up to 10 m), reduction in river widths (up to 50%), flow area (up to 50%), and decreased flood transporting capacities by 42%-61%, leading to increased flood disasters in North China. They also reported significant erosion downstream of the dam, particularly in the upper reach of the river (upper 35% of the river's length), along with armoring of downstream riverbed material, resulting in bed materials approximately twice as large by 2009 compared to 1999. Additionally, Xie et al. (2015) investigated the impact of the Three Gorges Dam on the downstream eco-hydrological characteristics and vegetation cover of East Dongting Lake, China, finding rapid increases in both vegetation cover rates and the lowering of the minimum elevation of the vegetation-covered area following dam construction.

One of the major problems that dams are facing now a day is reservoir sedimentation, reducing their lifespan due to accelerated erosion in catchment areas caused by steep slopes, overgrazing, and low ground cover. Various methods and models exist for estimating, analyzing, and predicting sedimentation processes. Over the past few decades, both Main Kandar Dam and Auxiliary Kandar Dam have experienced substantial reductions in storage capacity of about 61.78% and 9% respectively for Main Kandar Dam over 31 years, and 9 years for Auxiliary Kandar Dam. Observed sediment rates deviated from projected values by the HR Wallingford model. The construction of the Auxiliary Kandar Dam in 2014 extended the effective life of Main Kandar Dam by 34 years (2022–2056), while additional proposals for new Auxiliary Dams in 2002 and 2014 could further extend this lifespan by up to 134 years (2022–2156). Recommendations suggest constructing a second Auxiliary Dam on the left waterway in 2025, potentially increasing the Main Kandar Dam's lifespan to 2079, thereby providing a 64-year extension (2025–2089). Additionally, efforts to develop an irrigation system from both Auxiliary Dams are proposed to expand the command area of the watershed.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Authors’ Contribution

All authors contributed to the conception and design of the study. Material preparation, data collection, and analysis were performed by Awais Salman, Fakhri Alam, and Muhammad Salam. The first draft of the manuscript was written by Awais Salman with input from Fakhri Alam, Gul Daraz Khan, and Shahab Noor, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Availability of Data and Materials

All authors of this manuscript confirmed that the data supporting the findings of this study are available within the manuscript and all the required data are available and easily accessible.

Acknowledgments

We would like to thank Reviewers for taking the necessary time and effort to review the manuscript. We sincerely appreciate all your valuable comments and suggestions, which helped us in improving the quality of the manuscript.

Consent to Participate

Informed consent was obtained from all individual participants included in the study.

Consent to Publish

It is stated that I want to publish this paper entitled “Impact of Auxiliary Dam Construction on the Effective Life of the Kandar Dam Reservoir” in the proposed “Journal of Environmental Earth Sciences”. I give my consent for the publication of identifiable details, which can include a photograph(s) or details within the text to be published in the proposed Journal. I confirm that I have seen and been allowed to read both the Material and the Article (as attached) to be published by the “Journal of Environmental Earth Sciences”. I have discussed this consent form with all my co-authors.

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Assessing the Impact of Auxiliary Kandar Dam Construction on Effective Lifespan of Main Kandar Dam Reservoir: A Case Study from District Kohat, Khyber Pakhtunkhwa, Pakistan"

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Abstract

Figures

Introduction

Materials and Methods

Description of the Study Area

Data Collection

Determination of Deposited Sediment Load and Storage Capacity

Annual Sediment Transport

Wallingford Sediment Yield Prediction Model (WSYPM)

Annual Rainfall

Assessment of Slope

Capacity loss due to siltation

Estimation of Life of the Dam

Results and Discussion

Storage Capacity of Kandar and Auxiliary Kandar Dam

Deposited Sediment Load and Sedimentation Rate of Main Kandar Dam Reservoir

Deposited Sediment Load of Auxiliary Kandar Dam Reservoir

Estimation and Comparison of Sediment Yield through the Wallingford Model

Temporal Variations in the Storage Capacity of the Reservoir

Capacity-Inflow Ratio and Sediment Trap Efficiency

Annual Sediment Rates of Main Kandar Dam Reservoir

Life of Kandar Dam before and after the Construction of Auxiliary Dam

Projected Outcomes from Different Scenarios

Construction of Auxiliary Dam in 2002

Construction of the New Proposed Auxiliary Dam on the Left Waterway

Doubling the Auxiliary Dam Simultaneously in 2014

Addition of Auxiliary Dam in 2016 or 2022 on the left waterway

Addition of another Auxiliary Dam in 2025

Discussion

Sedimentation related problems

Conclusion

Declarations

References

Additional Declarations

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