Flooding is a global issue and is becoming a prime concern of research comprehensively. Flooding enriches grounds with minerals and sediments transported by water. These sediments increase the fertility of the soil and replace long-standing with new soil [1
]. Floods are a great natural way to recharge groundwater [1
]. Despite such benefits, when they cause human and economic loss, they are viewed as “catastrophes”. For better flood management researchers around the globe are dealing with procedures to utilize the flood water and control loss of assets. These studies presented structural and non-structural management of flood. The structural management considers physical measures including the construction of dams, leaves, floodwalls, and elevated buildings, cleaning of water bodies, and flood proving properties [3
]. The second possible solution is non-structural, which includes planning for disaster, flood plain zoning, and early warning systems. These measures cannot completely utilize flood resources, this is the explanation integrated water resource management (IWRM) is standing out enough to be noticed [4
Flash floods are a potential source of freshwater. However, flash floods are seldom considered as source of water due to the unavailability of management resources. Flash floods are different from traditional riverine floods in their extent and properties [5
]. These floods last for a short time but are intense in the extent of destruction they cause. Resources from these floods cannot be as proficiently saddled as those from riverine floods.
Whereas, in the last few decades’, water consumption is rapidly increasing all over the world due to the increase in a population [12
]. To supply reliable water resources, new water reservoirs have to be built to meet the fast-growing demands of water. Dams are the most important resources for the management of future water scarcity and a significant investment to provide essential services for the social communities [13
]. Traditionally, dam suitability analysis is conducted using decision-making techniques. However, with the integration of remote sensing (RS) and geographical information systems (GIS), different techniques are evolving as the most appropriate approaches for dam site selection. The recent development in satellite RS has increased the power to investigate the terrain characteristics and hydrologic parameters. The integration of RS and GIS enhance the adaptability of joining the spatial data (geomorphology, topography, and geology) with numerical models and decision-making schemes including fuzzy logic, Boolean logic, weighted overlay, analytic hierarchy process (AHP), multi-criteria evaluation, and artificial intelligence [16
]. Dam site selection was performed in the Greater Zab region of Iraq using AHP and fuzzy logic techniques. Another contemporary study in Sweden utilizes weighted overlay analysis on different layers (rainfall, evapotranspiration, geological, and geomorphological thematic maps) for dam site selection [18
]. Further studies have also been conducted for dam suitability analysis using multi-criteria analysis [18
]. Sayl et al. [19
] integrates RS and GIS technique to estimate physical variable of dams (elevation-area-volume curve) in western desert of Iraq. Pandey et al. [20
] process overlay analysis under Integrated Mission for Sustainable Development (IMSD) guidelines for dam site suitability in Karso, Hazirbagh, India. In a study Syst et al. [21
] analyze soil conservation services curve number (SCS-CN) equation with compound weighted index (CWI) and multi criteria evaluation techniques in Sao-Francisco and Nile catchments to identify suitable locations for dam construction.
The primary ecological issue in the watershed zones is soil erosion (SE) which essentially influences the dam adequacy. SE accelerated by deforestation, overgrazing, and improper cultivation of land. Among the different factors, approximately 84% of SE is caused by water and wind [19
]. However, the average soil loss estimated due to water is more than 2000 t-km−2
Worldwide, 0.5% to 1% of sedimentation every year influences the capacity limit of reservoirs. The expanded deforestation and destructing man-made exercises everywhere on the world anticipated that by 2050 most of the dams will lose their half of capacity [24
]. In Asia, sedimentation has covered approximately 40% of the total storage of reservoirs [25
]. The developing countries are also at high risk because sedimentation affects the long-term sustainability of storage structures. Iran is suffering from an annual average SE of 24 t-ha−1
]. Approximately 30 to 32.8 Mha (million hectares) area is affected by SE through the water in India. In Pakistan, 16Mha land is affected by soil loss through different processes, and approximately 70% of soil loss 11.2Mha is categorized as erosion by water. Sedimentation in the three main reservoirs of Pakistan (Tarbela, Mangla, and Chashma) is going to reduce their storage capacities by over 40% in the coming years. Different studies show that SE has drastically affected the storage capacities of existing dams and reservoirs in Pakistan [26
]. The production capacity of the Warsak dam in Pakistan has a 70% decreased due to SE [26
Global trends show that more than 20 billion tons of sediment yield are accumulated in the ocean from the rivers [28
]. Thus, the estimation of SE and sediment yield is important for new dam site selections and existing dams for life and storage capacity calculations. Conventional methods to assess SE risk is expensive and time-consuming [16
]. The estimation of SE is improved with the development of the Revised Universal Soil Loss Equation (RUSLE) model [30
]. The model has different input parameters related to the topography, climate, and cropping systems. Integration of GIS and RS tools are handy in the development of environmental models and their advanced features of data storage, management, analysis, and display. The factors of RUSLE are generated using modern techniques of GIS and RS [17
]. The implementation of RUSLE for the estimation of SE based on the integration of GIS and RS was also used in different studies [33
Torrential flooding and erratic behavior of rainfall in western catchments of Dera Ghazi Khan have created a myth for disaster risk reduction strategies. The unplanned urbanization and arid nature of the area further limited the availability of freshwater resources. Suitable site identification for dam construction is the utmost need for torrential flood management and to meet the water demands of the area. The study aims to provide effective management of hill torrents’ flow, converting the disastrous energy into a useful source by identification of suitable sites for storage structures. To select a group of indicators that exceedingly affect the dam suitability, different literature was investigated. The selected indicators follow hydrologic and engineering investigations in the spatial domain. The methodology adopted is based on the relation of selected indicators with reservoir and dam wall suitability. Focusing on the main problem of the area, the study also utilizes the GIS and RS technique to quantify the sediment yield and calculating the life of proposed structures.
The mountain range of Suleiman with widespread from northeast to southeast of Pakistan is prone to flash floods. The frequent occurrence of low to medium intensity flash floods in the monsoon season makes these catchments more vulnerable as compared to the other parts of Pakistan. The seasonal erratic patterns of rainfall further restrict the usual cultivation of different crops due to the water-scarce nature of the area. The historical cropping level of the hill torrents also indicates that only a small percentage of flood flows during high floods are utilized for agriculture and the remaining flood flows damage canals and canal command area.
Implementation of IMPs (integrated management practices) and BMPs (best management practices) using modern techniques of hydrologic investigations have proven to be a viable method for the management of these areas through dam site suitability and soil loss estimation.
The present study adopts a new methodology for dam site selection using different morphometric datasets including SO, MrVBF, TRI, Slope, CD, VD, and GD. The methodology proves a strong dimension in the dam site selection. The selected parameters/indicators reflect the maximum possible set of rules defined in the literature [3
] for dam site suitability analysis. The index/indicator as a qualitative approach makes the methodology unique and reduce the user dependency for individual thematic layer generation. Validation of methodology was conducted with an existing dam (Gomal-Zem Dam) in the north of the Suleman mountain range. The adopted methodology identified the Gomal-Zem Dam in a very high suitable class. The designed methodology and selected sites are presented to Secretary and Additional Secretary PID (Punjab Irrigation Department), Pakistan, and found satisfactory. According to [62
], both dams are classified in the small dam category. Several studies [3
] identified suitable locations for the small dam, check dam, and percolation tank for water harvesting in Pakistan and India. For example, Jamali et al. 2014 [68
] present the solution for site suitability for DAM in northern Pakistan using modern techniques of GIS and RS with spatial multi-criterion analysis (SMCA). Singh et al. 2008 [67
] identify fourteen suitable sites for check dams using different thematic layers including; LULC, hydrologic soil group, slope, and DEM. The identification of suitable sites followed the guidelines provided by the Integrated Mission for Sustainable Development (IMSD). A latest research has been conducted in Iraq. This research utilized all possible variables including geological formation, soil type, fault line, tectonic line, altitude, slope, rainfall data, water discharge, land use/cover, road network, and material used for dam site selection [69
]. Contrarily, very few attempts had been made which utilizes specific indices for dam site suitability analysis. However, the designed methodology grouped certain indices which represent multiple criteria for dam site suitability analysis. The set of indices set well on the varied topography of the areas. The selected indicators cover the maximum set of rules in the literature cited above. The relation between different indicators with the reservoir and dam wall suitability makes the methodology more robust. The selected indicators are generalized and hence could be implemented in any other area.
The efficacy of the designed structure is analyzed by annual average SE estimates. The estimation of SE was necessary because the mountain range of Koh e Suleman is prone to soil erosion due to its varied topography and barren nature of the land cover. The RUSLE equation involves R-rainfall, K-soil erodibility, LS-length slope, C-landcover management, and P-support practice factors to estimate the annual average soil loss of Sanghar torrent. The erratic behavior of rainfall mostly adopting sudden surge from cloud bursts and thunderstorm categorize the episodic nature of streams which remains active in monsoon season (July, August, and September) as shown in Table 2
. The high variation in topography and sandy nature increase the soil loss probability in the study area. The SE results using the RUSLE equation shows an average soil loss of 75 t-ha−1
. The SY estimates using SDR and SE results show approximately 298,073 tons and 318,000 tons of annual average sediment yield will feed the dam-A and dam-B respectively. The SY results substantiate 87 y and 90 y lives of dam-A and dam-B at a height of 150 ft and 200 ft, respectively. The validation of methodology with limited records of Vidor shows sufficient accuracy of results. The average QOBSERVE and QRUSLE sediment record of Vidor torrent for the monsoon season of 2016 were 7925 t-day−1
and 7455 t-day−1
Focusing on the global climate change scenarios, if the frequency of events per year increases dramatically, it will increase the annual soil loss of the Sanghar catchment. The increased SE would decrease the associated dam life. The selected sites have the potential of upraising the dam height up to 385 ft and 325 ft for Dam-A and Dam-B, respectively. The Dam-B with a much higher capacity of 839 million m3
is considered as the main dam for controlling the flash flood peaks. However, Dam-A could be beneficial in series to enhance the life of Dam-B. The strategy is flexible and could be implemented for climate change adaptation schemes. The enriched literature proves the applicability and efficacy of the RUSLE equation. The latest research was conducted by [23
] for soil loss estimation using the RUSLE model on the Chitral river catchment in the North of Pakistan. Another study on Rawal Dam catchment in the North of Punjab province, Pakistan, was conducted by [70
] and found GIS and RS techniques suitable for SE estimates (R2 = 0.76). Kusimi et al. 2015 [71
] studied the effect of uncontrolled land use activities on SE in the Pra River, Ghana using the RUSLE equation. Djoukbala et al. 2018 [72
] also evaluate the reliability and effectiveness of the RUSLE equation with the integration of GIS in Wadi El-Ham Algeria and found satisfactory results.
Pakistan is facing a shortage of water for several years, primarily because of the increase in population and mismanagement of accessible water resources. The water war scenario with neighboring countries accentuate the existing drastic nature of water shortage. There is average annual potential of 23 billion m3
in D G Khan’s hill torrent water resources of the country that has not yet been used to its productive potential [73
]. To overcome the water shortage of the country climate change adaptation strategies are by far the most suitable practices that has been implemented around the globe. The structural management of flash flood by dam construction also fulfils the crop water requirement (CWR) in the piedmont plains of the area.
The study highlights the existing potential of hill torrents in Pakistan. The results promote the use of spate irrigation to improve the cropping intensity of the area. According to Ahmad et al., 2016 [73
], the benefit cost ratio of spate irrigation for piedmont plains of D G Khan is higher than canal and ground water. Therefore, the study concludes the efficient utilization of hill torrents for spate irrigation through the construction of small dam that would manage the flash flood water in environmentally friendly way. Further studies should incorporate the CWR calculation which would help in the modelling, demarcation and management of cultural command areas in the downstream of selected dam sites.
The adopted methodology confirms the applicability of IMPs in flash flood and erosion prone areas for the better management of natural hazards. The generated results substantiate effectiveness and reliability of RDSA technique for dam site suitability analysis and RUSLE for annual SE estimates. The study concludes the following testimonials:
RDSA technique classified total of 269 box-units in very high to very low classes for reservoir and dam wall suitability.
Qualitative analysis using RDSA technique results in two suitable dam sites (Dam-A and Dam-B) for the management of flash flood water.
Quantitative analysis reveals maximum possible capacity of 364 million m3 and 838 million m3 of Dam-A and Dam-B, respectively.
Soil loss estimation using RUSLE method results in average annual SE of 75 t-ha−1y−1.
At sub-catchment level LS, R, percentage of sand and silt concentrations show significant relation with SE.
SDR and SE based annual average sediment of 298,073 tons and 318,000 tons will feed the Dam-A and Dam-B, respectively
SY results substantiate approximate lives of 87 and 90 years for Dam-A and Dam-B at height of 150 ft and 200 ft, respectively.
The changing behavior of climate over few decades causes flash flood scenarios more frequent in Pakistan. The proposed sites have the potential to enhance the storage capacity of dams to overcome the long-term forecasted climate change scenarios. The dam wall height of proposed sites can be increased to maximum of 384 ft and 325 ft for Dam-A and Dam-B, respectively.