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Morphometric analysis of suswa river basin using geospatial techniques  †.

1. Introduction

2. materials and methods, 2.1. study area, 2.2. materials and methods, 3. results and discussion, 3.1. linear aspects, 3.2. areal aspects, 3.3. relief aspects, 3.5. aspect, 3.6. drainage density, 4. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Mani, A.; Kumari, M.; Badola, R. Morphometric Analysis of Suswa River Basin Using Geospatial Techniques. Eng. Proc. 2022 , 27 , 65. https://doi.org/10.3390/ecsa-9-13225

Mani A, Kumari M, Badola R. Morphometric Analysis of Suswa River Basin Using Geospatial Techniques. Engineering Proceedings . 2022; 27(1):65. https://doi.org/10.3390/ecsa-9-13225

Mani, Ashish, Maya Kumari, and Ruchi Badola. 2022. "Morphometric Analysis of Suswa River Basin Using Geospatial Techniques" Engineering Proceedings 27, no. 1: 65. https://doi.org/10.3390/ecsa-9-13225

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• Published: 28 August 2024

Global insights on flood risk mitigation in arid regions using geomorphological and geophysical modeling from a local case study

• Adel Kotb   ORCID: orcid.org/0000-0002-8188-3188 1 ,
• Ayman I. Taha   ORCID: orcid.org/0000-0003-4526-1784 2 ,
• Ahmed A. Elnazer   ORCID: orcid.org/0000-0002-7338-0935 3 &
• Alhussein Adham Basheer   ORCID: orcid.org/0000-0001-5283-9201 1  

Scientific Reports volume  14 , Article number:  19975 ( 2024 ) Cite this article

Metrics details

• Environmental sciences
• Natural hazards

This research provides a comprehensive examination of flood risk mitigation in Saudi Arabia, with a focus on Wadi Al-Laith. It highlights the critical importance of addressing flood risks in arid regions, given their profound impact on communities, infrastructure, and the economy. Analysis of morphometric parameters ((drainage density (Dd), stream frequency (Fs), drainage intensity (Di), and infiltration number (If)) reveals a complex hydrological landscape, indicating elevated flood risk. due to low drainage density, low stream frequency, high bifurcation ratio, and low infiltration number. Effective mitigation strategies are imperative to protect both communities and infrastructure in Wadi Al-Laith. Geophysical investigations, using specialized software, improve the quality of the dataset by addressing irregularities in field data. A multi-layer geoelectric model, derived from vertical electrical sounding (VES) and time domain electromagnetic (TDEM) surveys, provides precise information about the geoelectric strata parameters such as electrical resistivity, layer thicknesses, and depths in the study area. This identifies a well-saturated sedimentary layer and a cracked rocky layer containing water content. The second region, proposed for a new dam, scores significantly higher at 56% in suitability compared to the first region’s 44%. The study advocates for the construction of a supporting dam in the second region with a height between 230 and 280 m and 800 m in length. This new dam can play a crucial role in mitigating flash flood risks, considering various design parameters. This research contributes to flood risk management in Saudi Arabia by offering innovative dam site selection approaches. It provides insights for policymakers, researchers, and practitioners involved in flood risk reduction, water resource management, and sustainable development in arid regions globally.

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Introduction.

Floods have long been recognized as one of the most devastating natural disasters, posing significant threats to communities worldwide 1 . In the Kingdom of Saudi Arabia (KSA), a region characterized by arid landscapes and sporadic rainfall, floods can have catastrophic consequences 2 . This paper aims to address the multifaceted issue of flood risks and their profound impact on the communities of KSA 3 , 4 . Furthermore, it underscores the critical importance of mitigating these risks through the judicious selection of dam sites, emphasizing the utilization of geophysical and geomorphological modeling techniques 5 .

Floods in KSA, while infrequent, are nonetheless devastating when they occur due to the arid nature of the region 6 . These events can lead to loss of life, damage to infrastructure, disruption of livelihoods, and economic losses 7 . Understanding the dynamics of flood risks is essential for safeguarding the well-being of KSA’s communities and ensuring the sustainable development of the region 8 . One pivotal approach to mitigating the impact of floods in KSA is through the strategic placement of dams 9 . These structures play a vital role in flood control, water resource management, and supporting agricultural activities 10 . Therefore, the selection of appropriate dam sites is paramount to the overall flood risk reduction strategy.

In this context, this paper centers its focus on the application of geophysical and geomorphological modeling techniques, specifically within the unique setting of Wadi Al-Laith in KSA 11 . Wadi Al-Laith, characterized by its intricate topography and hydrological features, serves as an exemplary case study to demonstrate the efficacy of these innovative approaches in dam site selection (Fig.  1 ). To contextualize our research, we present a comprehensive review of previous studies related to flood risks and dam site selection within the KSA region 12 . These studies provide valuable insights into the historical context and existing methodologies employed in flood risk management. Acknowledging the limitations and challenges of existing approaches is fundamental to driving innovation in flood risk mitigation 13 . By critically evaluating past strategies, we can identify areas where geophysical and geomorphological modeling can enhance the accuracy and effectiveness of dam site selection 14 , 15 .

location map of the study area, ( a ) spatial location of Saudi Arabia (red) relative to the world (gray) created by map chart, https://www.mapchart.net/world.html , ( b ) spatial location of Wadi Laith (green) relative to Makkah governorate (yellow) in Saudi Arabia created by map chart, https://www.mapchart.net/asia.html , ( c ) spatial location of Wadi Laith [created using 26 .

This study’s objective is toestablish a holistic framework for enhancing flood risk mitigation strategies in the region and contribute to the ongoing discourse on flood risk management in KSA by exploring innovative approaches to dam site selection, particularly through a promising solution of the application of geophysical and geomorphological modeling 16 , 17 . It endeavors to offer recommendations that can advance the planning and selection of optimal locations for new dams, as well as evaluate the performance and efficiency of existing dams 18 , 19 . Ultimately, this research is dedicated to ensuring the protection of both the communities and critical infrastructure within the Kingdom of Saudi Arabia (KSA).

The primary aim of this paper is to comprehensively address the multifaceted issue of flood risks in the Kingdom of Saudi Arabia (KSA), highlighting the unique challenges posed by the region’s arid landscapes and sporadic rainfall. The paper emphasizes the catastrophic consequences floods can have on communities, infrastructure, livelihoods, and the economy within KSA, while also considering global implications. It underscores the critical importance of mitigating flood risks through the judicious selection of dam sites, advocating for the use of advanced geophysical and geomorphological modeling techniques to enhance decision-making processes. Recognizing the devastating impact of floods in KSA despite their infrequency, the study promotes the strategic placement of dams as essential for flood control, sustainable water resource management, and supporting agricultural activities.

The paper specifically focuses on Wadi Al-Laith as a case study to illustrate the efficacy of geophysical and geomorphological modeling techniques in dam site selection. This area’s intricate topography and hydrological features serve as an exemplary setting for showcasing innovative flood risk mitigation strategies that could potentially inform similar efforts globally. To provide a comprehensive context, the paper conducts a thorough review of previous studies related to flood risks and dam site selection within KSA, aiming to offer insights into historical contexts, existing methodologies, and challenges faced in flood risk management.

Moreover, the study aims to contribute to the global discourse on flood risk management by exploring innovative approaches to dam site selection that improve accuracy and effectiveness through advanced modeling techniques. By establishing a holistic framework for enhancing flood risk mitigation strategies in KSA, the paper seeks to provide recommendations that can advance the planning and selection of optimal dam locations and evaluate the performance of existing infrastructure. Ultimately, the research aims to protect communities and critical infrastructure in KSA and beyond, thereby improving global resilience to floods and promoting sustainable development practices worldwide.

Area under investigation

Wadi Al-Laith, located in the Kingdom of Saudi Arabia (KSA), is a distinctive geographical feature within the western region of the country 20 . It is characterized by a variety of unique geographical attributes that shape its landscape and hydrology (Fig.  1 ).

Wadi Al-Laith can be described as a wadi, which is a typically dry riverbed or valley that experiences sporadic and often intense flash floods during the rare rainfall events in the arid region of KSA 21 . The geographical features of Wadi Al-Laith include a meandering topography with a pronounced channel that can expand dramatically during flood events. The valley exhibits a narrow and winding path, surrounded by rocky terrain and outcrops, with the nearby presence of limestone formations 22 .

The region’s hydrology is further influenced by its proximity to the Red Sea and the surrounding mountain ranges, which can contribute to localized weather patterns and rainfall variability 23 . Due to its geological composition and topographical characteristics, Wadi Al-Laith becomes particularly susceptible to flash flooding, making it a pertinent area for studying flood risk mitigation.

Wadi Al-Laith has witnessed several historical flood events, which have had significant repercussions for the surrounding communities and infrastructure 14 , 24 . These flood events are typically associated with the sporadic but intense rainstorms that occasionally occur in the region. Over the years, these floods have resulted in loss of life, damage to property, disruption of transportation networks, and agricultural losses. These historical flood events serve as poignant reminders of the urgent need to develop effective flood risk mitigation strategies in the area 20 , 21 , 25 .

Wadi Al-Laith assumes paramount importance as a case study for flood risk mitigation and dam site selection for several compelling reasons. Firstly, the unique topographical and geological characteristics of the region, such as the presence of limestone formations and rocky outcrops, make it an ideal testing ground for assessing the effectiveness of mitigation measures, including the strategic placement of dams. Secondly, the historical flood events in Wadi Al-Laith provide valuable data and insights into the vulnerabilities and risks associated with flash floods in arid regions, which can inform the development of targeted mitigation strategies. Thirdly, the lessons learned from Wadi Al-Laith can be extrapolated to other wadis and flood-prone areas within KSA and similar arid regions globally, making it a crucial reference point for policymakers, researchers, and practitioners engaged in flood risk management.

Briefly, Wadi Al-Laith in KSA serves as an exemplary study area for comprehensively examining the geographical characteristics, historical flood events, and the imperative role it plays in advancing flood risk mitigation and dam site selection strategies. The insights gained from this case study have the potential to enhance the resilience of communities and infrastructure in arid regions, safeguarding them against the adverse impacts of flash floods.

Geological settings

Wadi Al Lith, situated in the western region of Saudi Arabia, boasts a distinctive geological landscape characterized by its diverse features (Fig.  2 ). The prevailing geological composition of this area primarily consists of sedimentary rocks, prominently marked by the presence of extensive limestone formations 27 . These limestone formations are integral components of the sedimentary sequence affiliated with the Arabian Platform, with origins traceable to the Cretaceous and Paleogene epochs 26 , 28 . Specifically, the study area within Wadi Al-Lith assumes the form of a valley stream typified by a thin sedimentary layer, the close proximity of hard rock strata to the surface, and rocky outcrops flanking the valley’s margins 29 . Notably, in select regions, sediment thickness within the valley gradually increases until it interfaces with the underlying hard rock formations.

Geological map of the area under investigation and its surroundings. [Created using 34 .

The geological framework of the Wadi Al-Lith catchment area comprises four primary rock units, as detailed by 27 , 30 .

Quaternary, encompassing sand, gravel, and silt deposits: yhis unit exhibits the predominant presence of eolian sand-dune formations and sheet sand and silt deposits, with sand deposits covering a substantial portion of the region.

Late- to post-tectonic granitic rocks: represented by various plutonic rock types, including diorite, tonalite, granodiorite, and monzogranite, alongside serpentinite to syenite formations.

Lith suite, Khasrah complex, diorite, and gabbro: constituting a suite of mafic to intermediate plutonic rocks.

Baish and Baha groups: comprising rocks such as basalt–dacite and biotite-hornblende-schist-amphibolite.

Additionally, Wadi Al-Lith encompasses volcanic rocks, notably basalt and andesite, remnants of ancient volcanic activity 2 . These volcanic formations are associated with the Red Sea rift system, a significant geological phenomenon that has profoundly influenced the region’s topographical characteristics 31 .

Structurally, the geology of the Wadi Al-Lith region is shaped by faulting and folding processes. Underlying the sedimentary rocks is the Arabian Shield, a Precambrian-age basement complex 31 . Characterized by its rugged and mountainous terrain, this geological foundation contributes significantly to the diverse topography evident in the area 27 , 32 .

The presence of a multitude of rock types and geological structures within Wadi Al-Lith holds significant implications for water resources and the occurrence of flash floods. Impermeable rock formations, such as limestone, can expedite surface runoff during intense precipitation events, augmenting the susceptibility to flash floods 27 , 32 . Consequently, a profound comprehension of the geological attributes of the region assumes paramount importance in facilitating effective water resource management and the implementation of appropriate mitigation measures aimed at mitigating the impact of flash floods 31 , 32 .

Methodology

The hydrogeological method in this study primarily involves using hydrological models to predict and map regions prone to flash floods. The geophysical methods employed include electrical resistivity sounding (VES) and time-domain electromagnetic (TDEM) methods to investigate subsurface layers. Combining hydrogeological and geophysical methods offers a comprehensive understanding of the factors influencing flash floods. Hydrological models derived from detailed morphometric and land cover analyses are augmented with subsurface information obtained from geophysical measurements. This integrated approach allows for more accurate predictions of flash flood-prone areas by considering both surface characteristics and subsurface conditions, ultimately enhancing flood risk mitigation strategies.

Hydrogeological method

In this study, hydrological models assume a pivotal role in the anticipation and mapping of flash flood-prone regions. The hydrological models used in this study are advanced and multifaceted, incorporating: (a) morphometric analysis which are utilizing parameters like drainage density, stream frequency, and rainage intensity, (b) topographic data derived from high-resolution topographic maps, (c) land cover data (integrated using the ASTER GDEM dataset), (d) subsurface information (enhanced with data from geophysical methods), and e) GIS Software: ArcGIS 10.4.1(for comprehensive data analysis).

These models work together to predict specific locales susceptible to flash floods, considering both surface and subsurface characteristics, to provide a holistic approach to flood risk mitigation in arid regions like the Kingdom of Saudi Arabia. These models find their genesis in morphometric analyses, which entail a comprehensive examination of the terrain's spatial characteristics and configurations. Topographic maps, boasting a horizontal posting resolution of approximately 30 m at the equatorial belt, serve as the primary data source for these morphometric inquiries. This level of detail facilitates an exhaustive comprehension of the landscape’s morphology and its ensuing influence on the hydrological patterns governing water flow.

To bolster the precision of the hydrological models, supplementary data regarding land cover is incorporated into the analytical framework. The research team leverages the ASTER Global Digital Elevation Model (GDEM) Version 3 33 , a dataset that furnishes a worldwide digital elevation model of terrestrial regions. This dataset boasts a spatial resolution of 1 arcsecond, equating to approximately 30 m on the ground. By integrating this land cover information into the hydrological models, the research endeavor accommodates pertinent factors such as vegetation types, soil compositions, and land use patterns, all of which exert substantial influences on the hydrological dynamics across the landscape.

Subsequently, hydrological models are brought into action to predict the specific locales susceptible to flash floods. These models simulate the water’s flow trajectory predicated on the amalgamation of topographic particulars and land cover attributes. In so doing, these models pinpoint areas where the confluence of terrain features and land cover characteristics renders them predisposed to the occurrence of flash floods. To further bolster the predictive capacity of these models, subsurface information procured through geophysical measurements is incorporated.

For the comprehensive analysis of data, including morphometric assessments, ArcGIS 10.4.1 software 34 is employed. This software platform facilitates data visualization, manipulation, and morphometric analyses, enabling a detailed exploration of the study area’s pertinent parameters. Key morphometric parameters essential to this study are presented in Table 1 , encompassing metrics such as drainage density (Dd), stream frequency (Fs), drainage intensity (Di), and infiltration number (If). These parameters, as outlined by 35 , 36 , form the cornerstone of the morphometric analyses undertaken in this investigation.

Geophysical methods

Geophysical methods, including electrical resistivity sounding (VES) and time-domain electromagnetic (TDEM) methods, are employed to investigate subsurface layers. The number of measurements were 157 VES and the same number of TDEM have been conducted in the same place to cover the whole area under investigation (Fig.  3 a). VES measures subsurface electrical resistivity at various points, yielding insights into subsurface composition and properties. In contrast, TDEM employs electromagnetic pulses to assess subsurface characteristics. These geophysical measurements inform the development of subsurface models.

( a ) Geographical distribution of VES and TDEM soundings’ site in the area under investigation [created using 26 , ( b ) example of VES no. 1 interpretation [extracted from 51 , ( c ) example of TDEM sounding no. 1 interpretation [extracted from 52 .

Geoelectrical method

Geoelectrical surveys, also known as the “DC method,” entail injecting direct electric current into the ground using surface-based current and voltage electrodes. The current’s direction is alternated to mitigate natural ground interference.

The vertical electrical sounding (VES) technique, utilizing continuous direct current (DC), is widely employed for groundwater exploration. It gauges values influenced by water content in rocks; higher values are characteristic of unsaturated rocks, while lower values indicate saturation, with salinity influencing measurements 37 .

The method of measuring ground electrical resistance relies primarily on Ohm's law, which states that the electric current flowing through a conductor is directly proportional to the voltage across it Eq. ( 1 ).

Ground electrical resistance is measured in accordance with Ohm’s law, where electric current is injected into the ground via two conductive electrodes (A and B) 38 , 39 Eqs. ( 2 ), ( 3 ).

The apparent electrical resistance (ρa) is determined by dividing the product of the potential difference (∆V) by the current strength (I) and multiplying it by a geometric constant (K), which varies based on the distance between the current and voltage electrodes. This process is conducted using the Schlumberger configuration, which allows for deeper measurements compared to other configurations 40 , 41 .

Simultaneously, the potential difference across two additional electrodes (M and N) within the ground is measured. Apparent electrical resistance (ρa) is calculated by dividing the product of potential difference (∆V) by current strength (I) and multiplying by a geometric constant (K), contingent on the electrode distance. The Schlumberger configuration is employed for deeper measurements Eqs. ( 2 ),( 3 ) 42 .

The geoelectrical survey in the study area was performed using the ARES II/1 43 device, manufactured in the Czech Republic, which has a high capacity to transmit a current of up to 5 A, a voltage of 2000 V, and a capacity of up to 850 W, enabling measurements to be taken until reaching the solid base rocks.

Time domain electromagnetic method (TDEM)

TDEM relies on electromagnetic induction principles, creating a varying magnetic field and measuring induced electrical currents in the subsurface.

A transmitter coil carrying a strong current generates a changing magnetic field penetrating the subsurface. This field induces secondary electrical currents (eddy currents) in conductive materials beneath the surface, resulting in secondary magnetic fields. Upon deactivating the transmitter coil, the eddy currents decay, and the associated magnetic fields diminish. A receiver coil captures changes in the magnetic field over time, known as the decay curve or decaying electromagnetic response, providing subsurface resistivity distribution insights 44 .

Key equations utilized in TDEM include Faraday’s law of electromagnetic induction, Maxwell’s equations Eq. ( 4 ), governing electromagnetic wave propagation, and Ampere’s law, accounting for electric currents and the displacement current.

where ( ∇  × B) is the curl of the magnetic field vector (B), (μ 0 ) is the permeability of free space, a fundamental constant, (J) is the electric current density, and (∂E/∂t) is the rate of change of the electric field vector (E) with respect to time. This equation relates magnetic fields to electric currents and the displacement current (the term involving ∂E/∂t), which accounts for the changing electric field inducing a magnetic field 45 , 46 .

The Cole–Cole model represents complex electrical conductivity in subsurface materials, incorporating parameters (σʹ, σʹʹ, and α) to account for frequency-dependent conductivity Eq. ( 5 ).

where the complex conductivity (σ*) and angular frequency (ω) and (j) is the imaginary unit (√(− 1)) 40 , 41 .

Inversion algorithms, based on forward modeling and optimization techniques, interpret TDEM data and construct subsurface resistivity models. The inversion process involves comparing predicted data with measured data and adjusting the resistivity model to minimize discrepancies. Iterations continue until a satisfactory match is achieved, yielding the best-fitting resistivity distribution. These methodologies enable the estimation of subsurface properties, valuable in groundwater exploration, mineral assessment, and geological formation characterization 47 . Figure  3 b, c illustrates an example of these interpretations.

By combining hydrological models derived from topographic and land cover data with the subsurface model obtained from geophysical measurements, a comprehensive understanding of the factors affecting the occurrence of flash floods can be achieved. This integrated approach allows for more accurate prediction of locations vulnerable to flash floods, as it takes into account surface characteristics and subsurface conditions.

In a clearer and more summarized sense, the hydrological models used in this study are derived from detailed morphometric studies based on topographic maps and land cover data. ASTER’s Global Digital Elevation Model (GDEM) version 3 is used to obtain land cover information. These models, along with subsurface information obtained through geophysical measurements and interpretation using VES and TDEM methods, contribute to predicting locations vulnerable to flash floods through a more comprehensive and accurate understanding of the contributing factors.

Hydrogeological modeling

In this study, a comprehensive analysis of the study area’s topography, hydrology, and precipitation patterns was conducted using various geospatial data sources and techniques. The digital elevation model (DEM) played a central role in extracting valuable insights.

The DEM was employed to delineate the drainage network within the study area, specifically focusing on the Wadi Lith watershed (Fig.  4 a). By assessing stream orders within this watershed, a significant observation emerged. It was noted that as the stream order increased, the number of associated stream segments decreased. Notably, the first-order stream (SU1) displayed the highest frequency, indicating that lower-order streams are more prevalent in the area. This observation underscores the heightened susceptibility of Wadi Lith to drainage-related hazards (Fig.  4 b).

( a ) Digital elevation map of the area under investigation, ( b ) drainage network map of the area under investigation. Created using 34 .

The DEM dataset yielded critical information concerning the topography and hydrology of the study area. Elevation data, flood flow directions, and identification of vulnerable regions were among the key findings derived from the DEM analysis. The elevation levels captured by the DEM ranged from 0 to 2663 m within the study area (Fig.  4 a).

The researchers employed ArcGIS software to generate three essential maps using the DEM data: slope, aspect, and hill shade maps to gain a deeper understanding of the topographic features. These maps provided distinct perspectives on the terrain’s characteristics. The slope map (Fig.  5 a) vividly illustrated the steepness of the rocks in the study area, with higher slope values indicating more pronounced inclinations. The aspect map (Fig.  5 b) revealed that slopes predominantly faced southward within the study area. Furthermore, the hill shade map (Fig.  5 c), employing shading techniques, effectively portrayed the topographical features of hills and mountains. It accentuated relative slopes and mountain ridges, notably highlighting the valley of Al-Lith as particularly susceptible to flood hazards (Table 2 ).

( a ) Slope map of the area under investigation, ( b ) aspect map of the area under investigation, ( c ) Hill shade map of the area under investigation. [created using 34 .

Monthly precipitation data (Table 3 ) were scrutinized to understand the precipitation patterns in the Al-Lith area. The analysis revealed that the average annual precipitation in the area amounted to approximately 9.3 mm. Notably, January, November, and December were identified as the months with the highest recorded rainfall levels, as per data sourced from climate-data.org. The combination of these factors suggests that while Al-Lith typically experiences low annual precipitation, the region is highly susceptible to flash floods during specific months which are January, November, and December. This primary flood risk occurs due to significantly higher precipitation levels during these months, where rainfall is significantly higher. The last historical floods happened in November 2018 and December 2022.

As a combined result of the above, this study harnessed the power of the DEM to conduct an in-depth analysis of the study area's drainage network, stream orders, and topographical features. ArcGIS software facilitated the creation of informative slope, aspect, and hill shade maps, shedding light on the terrain’s characteristics and emphasizing flood vulnerabilities in Al-Lith Valley. Furthermore, the examination of monthly precipitation data unveiled the region’s average annual rainfall patterns, highlighting specific months of heightened precipitation (Table 4 ). These integrated findings contribute to a comprehensive understanding of the study area's hydrological and topographic dynamics, which are crucial for flood risk assessment and mitigation efforts.

Morphometric parameters analysis

In the assessment of the study area’s morphometric characteristics, several key parameters were examined to gain valuable insights into its drainage network and hydrological behavior.

Drainage density (Dd)

Drainage density (Dd) serves as a fundamental metric, calculated as the total length of streams within a drainage basin divided by its area (A). In the present research region, a notably low drainage density of 1.19 km −1 is observed, indicative of a scarcity of streams relative to the area’s expanse. This characteristic can be primarily attributed to the presence of erosion-resistant, fractured, and rough rock formations that facilitate accelerated water flow within the wadi 26 .

Stream frequency (Fs)

Stream frequency (Fs) signifies the abundance of streams within a specific area, quantified as the number of streams per unit area. In the studied domain, the stream frequency is calculated to be 3.32 km 2 , revealing a relatively low stream density. This implies a scarcity of streams per square kilometer, a phenomenon influenced by factors such as modest relief, permeable subsurface materials, and a heightened capacity for infiltration. These conditions collectively contribute to the profusion of streams within the region 48 , 49 .

Bifurcation ratio (Rb)

The bifurcation ratio (Rb) provides insights into the branching pattern within a watershed’s stream network. It is computed as the ratio of the number of streams of a given order to the number of streams of the order directly above it. The mean bifurcation ratio (Mbr) in the study area is determined to be 1.96, signifying a notable degree of branching within the watershed’s stream network 49 .

Infiltration number (If)

The infiltration number (If) represents a comprehensive metric evaluating the infiltration capacity of a watershed, factoring in both drainage density and stream frequency. In the research region, the calculated infiltration number is 3.95, categorizing it as exhibiting low infiltration numbers and high runoff potential. This observation underscores the area’s propensity for high runoff rates due to its limited infiltration capacity 49 .

Flood risk assessment and site suitability

The interplay of drainage density, stream frequency, bifurcation ratio, and infiltration number impart significant insights into the watershed's characteristics and hydrological behavior. Notably, the low drainage density, low stream frequency, high bifurcation ratio, and low infiltration number in the study area collectively contribute to elevated flood risk and heightened potential for runoff. This assessment underscores the imperative necessity for the implementation of effective flood mitigation measures within the region.

Furthermore, a holistic approach was applied by 50 involving the interrelationship of bifurcation ratio, drainage frequency, and drainage density to evaluate the basin’s hazard potential. Based on this analysis, the studied basin is identified as having a considerable likelihood of experiencing flash floods.

Briefly, the comprehensive analysis of morphometric parameters reveals critical insights into the study area’s hydrological behavior and flood risk. The observed characteristics necessitate diligent attention to flood risk mitigation strategies and effective management practices within the region.

Geophysical data processing and interpretation

In the aftermath of an extensive field survey conducted within the study area, a meticulous and structured data processing sequence is enacted. This sequence encompasses several crucial steps geared toward enhancing data consistency and reliability.

Data quality assessment

The initial phase of data processing revolves around the generation of apparent resistance curves employing the field data. These curves serve the pivotal function of identifying and rectifying any irregularities, with particular emphasis on anomalies encountered during the onset of electrical and electromagnetic tests. Aberrant readings undergo rigorous scrutiny and, where necessary, are expunged from the dataset to elevate the overall precision and fidelity of the information.

Utilization of data processing software

Subsequently, specialized data processing software tools come into play, specifically the “Interpex 1DIV” 51 and “ZondTEM1D” 52 programs. These meticulously designed programs take on the responsibility of processing data originating from electrical probes. The dataset encompasses critical information, including electrical resistance, and, in applicable scenarios, resistance and inductive polarization. The primary probe data collected from the study site serves as the foundational data set for this comprehensive processing (Fig.  3 b, c).

Development of a multi-layers model

The third phase in the data processing continuum is marked by efforts to streamline the representation of multi-layered data into a more coherent and manageable form. This procedure necessitates the amalgamation of groups of closely associated resistance values into unified composite resistance layers. The primary objective is to streamline the dataset’s complexity while preserving its intrinsic geoelectric attributes and characteristics.

Characterization of geoelectric layers

The ultimate stage of data processing culminates in the meticulous characterization of geoelectric layers. This encompasses the precise determination of electrical resistivity values, layer thicknesses, and the depths of the discrete geoelectric strata. These defined parameters offer a comprehensive understanding of the geological and geophysical attributes of the study area.

Geophysical insights

The geophysical investigation, with a specific focus on the vicinity proximate to the groundwater dam and the Wadi Al-Leith water station within Wadi Al-Laith, has yielded valuable insights. The primary aim was to harness the dam’s influence on nearby wells, thus mitigating the necessity for extensive station-to-well extensions. Concurrently, the presence of a fractured layer and the heterogeneous topography of the solid base rocks were meticulously documented.

The amalgamated findings underscore the existence of a substantial and adequately saturated sedimentary layer at select locations, coexisting alongside a cracked rocky layer harboring a discernible water content. It is pertinent to note that the predominant characteristic across the valley’s expanse is the prevalence of a notably thin sedimentary layer, characterized by limited water saturation (Fig.  6 ). It is clear from the interpretations that the depth of groundwater in the investigation area ranges from 0.5 to 14 m (Fig.  6 a), and the thickness of the layer containing the water ranges between 0.3 and 33.63 m (Fig.  6 b). The inference of the presence of groundwater was confirmed by an actual review of the results of the electrical resistance values, which ranged from 33.9 to 145 Ω.m (Fig.  6 c).

( a ) Depth map to groundwater bearing layer, ( b ) thickness map of groundwater bearing layer, ( c ) resistivity distributions map of groundwater bearing layer, ( d ) map of hypothetical score calculation by geophysical weighted decision matrix [created using 26 .

In summation, the comprehensive geophysical investigation has unveiled the coexistence of well-saturated sedimentary layers and fractured rocky substrates across the study area. These findings constitute a pivotal resource for groundwater assessment and the judicious utilization of resources within the Wadi Al-Laith region.

Matrix of comparative assessment of dam site suitability

Matrix of the effective geoelectrical model for dam site suitability.

Matrices have been mentioned, as one of the means of evaluating the preference for identifying areas, in many studies that deal with environmental and water assessment processes for proposing or evaluating areas for constructing dams, such as 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 . The matrices differed in many of them depending on the parameters used and the data available (Tables S1 and S2 supplementary information documents). In this research, a somewhat unique matrix was designed based on the availability of data and the amount of correlation and complementarity between them.

In the comprehensive assessment of the geoelectric model of sublayers as an effective parameter in the suitability matrix for both the first and second regions, a series of parameters were carefully considered, each assigned a weight percentage to reflect its relative importance in the decision-making process. These parameters encompassed critical aspects of the geoelectrical model of sublayers and related factors, including layer resistivity (ρ), layer thickness (h), layer geometry, layer boundaries, electrode configuration, data quality and error estimation, inversion algorithm, geological constraints, and hydrogeological properties (Tables S3 and S4 supplementary information documents).

The weighted decision matrices for both regions were constructed by evaluating the effectiveness of each parameter for its effective power in site suitability. A hypothetical score calculation was then performed by multiplying the weight percentage by the effectiveness score for each parameter and summing these values for each region (Table 5 , Fig.  6 d). The results revealed that the second region excelled in suitability, achieving an impressive score of 60%, whereas the first region scored lower at 40%. This suggests that the second region is significantly more favorable for dam construction, as determined by the geoelectrical model of sublayers and its associated suitability parameters.

Matrix of dam site suitability

In the evaluation of suitable locations for building a dam within the first and second regions, a set of parameters and their respective weightings were considered. These parameters included bifurcation ratio (Mbr), aspect, slope, hill shade of the study area, annual average precipitation, stream length (Lu), drainage density (Dd), stream frequency (Fs), drainage intensity (Di), infiltration number (If), flood possibilities, and the geoelectrical model of sublayers (Table 6 ). Each parameter was assigned a weight percentage reflecting its relative importance in the decision-making process. Subsequently, weighted decision matrices were created for both regions, where the quality of each parameter was assessed for each location.

The hypothetical score calculation was performed by multiplying the weight percentage by the quality score for each parameter and summing these values for each region. Based on this analysis, the first region, where the old dam was located, received a suitability score of 44%, while the second region scored higher at 56%, suggesting that the second region may be a more suitable option for building a dam according to the specified criteria (Fig.  7 ).

Map of hypothetical score calculation by hydrogeological and geophysical weighted decision matrix. Created using 26 .

Evaluating dam site suitability

The assessment conducted through matrix analysis has yielded valuable insights into the suitability of potential dam sites in the specified regions. These findings are rooted in a meticulous evaluation of various parameters and their weighted contributions to the overall suitability score. In this context, the first region emerged with a suitability score of 44%, while the second region demonstrated a notably higher score of 56%. This discrepancy in scores underscores a critical distinction between the two regions in terms of their potential for dam construction (Fig.  7 ).

The higher score awarded to the second region suggests that it may hold distinct advantages when measured against the specific criteria used for evaluation. These criteria, which include factors like bifurcation ratio (Mbr), aspect, slope, hill shade of the study area, annual average precipitation, stream length (Lu), drainage density (Dd), stream frequency (Fs), drainage intensity (Di), infiltration number (If), flood possibilities, and the geoelectrical model of sublayers depended on geoelectrical properties, geological constraints, and hydrogeological considerations, collectively indicate a higher level of suitability for dam construction in the second region. This implies that the second region offers a more promising and feasible prospect for establishing a dam infrastructure, aligning closely with the predefined objectives and prerequisites of the project. As such, the findings of this analysis provide a compelling rationale for considering the second region as the preferred choice for future dam construction endeavors.

Parameters of proposed dam

Although it is impossible to completely eliminate the risk of flash floods, there are a variety of strategies to lessen it. For example, it is possible to identify the areas that are most vulnerable to the hazard by analyzing the drainage system, hydrologic modeling, and the local geology. Dams and canals are suggested solutions to the issue in addition to assisting in collecting and replenishing water for various reasons.

The Al-Lith earthen dam in the study area collapsed on November 23, 2018, as a result of repeated rainstorm events in the upper part of Wadi Al-Lith in western Saudi Arabia 64 . An old Al-Lith dam was built as an altocumulus dam to solve this issue. Its height terminates at the earth's surface and its goal is to store groundwater to supply the wells dug above this dam. To supply a purification plant next to the old dam, a number of wells needed to be sunk at the top of the old dam (Fig.  8 ).

Map of the calculated storage-capacity volume of the proposed dam which is suggested for the area under investigation. Created using 34 .

Based on the morphological analysis of the watershed and to reduce the risk of flash flooding 50 , the study of work suggests improving the proposed dam so that it can have a storage capacity of about 38,187,221.4 m 3 and an area behind the dam of about 3,567,763.9 m 2 . Additionally, it may advocate building a supporting dam around 5 km south of the old Al-Lith Dam. Geologically, the site of the proposed and projected new Dam will be constructed on the two wadi sides with hard rock of quartz–diorite and no faults. The newly proposed dam will have a storage capacity of 114,624,651.1 m 3 , and its size will be 5,104,646.8 m 2 (Fig.  8 ). According to GIS analysis, if the elevation map of the study area ranges from 122 to 617 m, the suggested proposed dam should measure between 230 and 280 m in height and 800 m in length.

The hydrogeological modeling conducted in this study leverages Digital Elevation Model (DEM) data to delineate the drainage network of Wadi Lith, revealing key insights into the region's susceptibility to flood hazards. The DEM analysis underscores the dominance of first-order streams (SU1) in the area, indicating a heightened vulnerability to drainage-related issues. The slope, aspect, and hill shade maps generated using ArcGIS further enhance our understanding of the region’s topography. The slope map highlights areas of steep inclinations, the aspect map shows a predominance of south-facing slopes, and the hill shade map vividly portrays the valley’s topographical features, emphasizing the Al-Lith Valley’s susceptibility to floods.

The analysis of morphometric parameters offers a comprehensive understanding of the drainage characteristics and flood risks within the study area. Drainage density (Dd) shows a value of 1.19 km −1 , the low drainage density indicates a scarcity of streams, attributed to erosion-resistant rock formations that facilitate rapid water flow, contributing to flood risk. Stream Frequency (Fs) shows at 3.32 km 2 , the relatively low stream frequency suggests limited stream presence, influenced by modest relief and high infiltration capacity. The bifurcation ratio (Rb) shows a mean value of 1.96 reflecting significant branching within the stream network, crucial for understanding flood dynamics. Infiltration number (If) illustrates the low infiltration number of 3.95 highlights a high runoff potential, underlining the area’s vulnerability to flash floods. These parameters collectively indicate an elevated flood risk and necessitate effective mitigation strategies.

The geophysical investigation, focusing on the area around the groundwater dam and Wadi Al-Leith water station, reveals the coexistence of well-saturated sedimentary layers and fractured rocky substrates. This duality is crucial for groundwater assessment and highlights the potential for utilizing these resources effectively. The identified groundwater depths (0.5–14 m) and layer thicknesses (0.3–33.63 m) are significant for planning water extraction and management strategies.

The matrix analysis for dam site suitability compares two regions, considering various hydrological, geological, and geoelectrical parameters. The geoelectrical model illustrates that the second region scores higher (60%) compared to the first (40%), indicating better suitability for dam construction based on geoelectrical properties. Overall suitability containing factors like bifurcation ratio, aspect, slope, and precipitation illustrates that the second region again scores higher (56%) versus the first (44%). This comprehensive evaluation suggests that the second region is more favorable for dam construction due to its advantageous geoelectrical and topographical characteristics.

Considering the historical collapse of the Al-Lith Dam in November 2018 and December 2022, the study proposes improvements to the dam structure to enhance its storage capacity and flood mitigation capability. The proposed dam should have a storage capacity of approximately 114,624,651.1 m 3 , with a height of 230–280 m and a length of 800 m. This strategic enhancement aims to bolster the region's flood resilience and water management efficiency.

The integrated hydrogeological, geophysical, and morphometric analyses provide a holistic understanding of the flood risks and water management challenges in Wadi Al-Lith. The proposed mitigation strategies, including the construction of a new dam, are grounded in comprehensive geospatial and geophysical data, ensuring their effectiveness in enhancing the region’s flood resilience and water resource management. This study underscores the importance of leveraging advanced geospatial techniques and comprehensive data analysis for effective flood risk mitigation in arid regions.

The study offers a comprehensive evaluation of flood risk mitigation strategies in Wadi Al-Laith, Kingdom of Saudi Arabia (KSA), emphasizing the critical need to address flood risks in arid regions due to their severe impact on communities, infrastructure, livelihoods, and the economy.

By using the hydrological analysis, the investigation of the morphometric parameters revealed low drainage density, low stream frequency, a high bifurcation ratio, and a low infiltration number, indicating elevated flood risk and high runoff potential in Wadi Al-Laith. These characteristics highlight the need for effective flood risk management to protect communities and infrastructure.

By using geophysical investigation, data processing used specialized software 51 , 52 to process electrical and electromagnetic probe data, ensuring accuracy by correcting field data irregularities. The “multi-layer model” was developed by consolidating resistance values and providing detailed information on electrical resistivity, layer thicknesses, and depths of geoelectric strata. Findings include a well-saturated sedimentary layer and a cracked rocky layer with water content, though a thin, less saturated sedimentary layer is predominant. The study area was divided into two regions for dam construction, with the proposed new dam site scoring 56% in suitability, higher than the old dam sites at 44%.

The study indicates the encouragement and support of combining hydrogeological and geophysical data to offer a thorough understanding of factors contributing to flash floods, including topography, drainage characteristics, and subsurface properties.

Long-term implications of constructing dams have environmental Impacts like (1) dams significantly alter natural water flow, which can impact downstream ecosystems. By regulating water flow, dams can reduce the frequency and severity of floods, but they may also reduce sediment transport, affecting riverine habitats and delta formations. (2) The creation of a reservoir can lead to the submersion of land, affecting local flora and fauna. In arid regions like Wadi Al-Laith, this could disrupt unique desert ecosystems (3) Stagnant water in reservoirs can lead to reduced water quality, promoting the growth of algae and affecting aquatic life.

Also, the long-term implications of constructing dams have a morphological response like (1) the dam will trap sediments, leading to sediment accumulation in the reservoir. This can reduce the dam’s storage capacity over time and necessitate periodic dredging. (2) downstream of the dam, reduced sediment supply can lead to channel erosion, altering the geomorphology of the riverbed and potentially impacting infrastructure and habitats.

While acknowledging the potential long-term environmental implications, the decision to propose dam construction is based on a comprehensive assessment of the specific context of Wadi Al-Laith a recommended advice for building an 800 m-long auxiliary dam with a height of 230–280 m, utilizing quartz–diorite rock. Our analysis of morphometric parameters indicates a high flood risk due to low drainage density, low stream frequency, high bifurcation ratio, and low infiltration number. A strategically placed dam can significantly mitigate these risks. Additionally, the selected dam site in the second region, utilizing sturdy quartz–diorite rock without faults, provides a stable foundation for the proposed structure, ensuring its long-term stability and effectiveness. The proposed auxiliary dam, with a detailed design considering height, diameter, relief holes, surface inclinations, and well placements, aims to enhance flood resilience while addressing the specific hydrological and geological conditions of the area.

In addition to proposing dam construction, our study considered several non-structural and nature-based solutions to mitigate flood risk in Wadi Al-Laith, The study underscores the need for a holistic approach to enhance water resource management and support agriculture, and flood risk mitigation in arid regions like KSA, where infrequent but devastating floods can occur. A holistic approach to flood risk mitigation in arid regions like Wadi Al-Lith in the Kingdom of Saudi Arabia should combine structural and non-structural measures to address both immediate flood threats and long-term resilience, considering the unique hydrological and climatic conditions. Key strategies include (1) integrated watershed management, involving catchment area analysis, land use planning, and soil and water conservation; (2) structural measures, such as building dams, flood channels, and retention basins; (3) non-structural measures, including advanced flood forecasting, community engagement, and sustainable water management policies; (4) geophysical and hydrological monitoring through continuous data collection and geophysical surveys; (5) ecosystem-based approaches, such as restoring natural floodplains and promoting green infrastructure; and (6) adaptive management and research to allow flexibility in strategies and support ongoing research. By integrating these measures, advanced monitoring, and active community involvement, a holistic approach can significantly enhance flood resilience in arid regions like Wadi Al-Lith, addressing immediate risks and building long-term sustainability and adaptability to climate change.

The research contributes to flood risk management discourse in KSA by presenting innovative approaches to dam site selection using geophysical and geomorphological modeling. While our study acknowledges the potential long-term environmental implications of dam construction, it also highlights the necessity of such infrastructure in the specific context of Wadi Al-Laith to ensure effective flood risk mitigation. It offers valuable insights and recommendations to protect communities and infrastructure in arid regions prone to flash floods, promoting sustainable development. Findings can guide policymakers, researchers, and practitioners in KSA and similar arid regions globally.

Data availability

All data generated or analyzed during this study are included in this mnuscript.

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Acknowledgements

Special thanks to Dr. Nihal Adel ([email protected]), Associate Professor of English, Department of English Language, Faculty of Al-Alsun, Minya University, Egypt, for reviewing the linguistic, grammar, and scientific moral context of the current research.

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All authors contributed to all sections and work stages, field measurements, data collection and measurements using geophysical equipment and reviewed the manuscript. A. K. wrote the theoretical part, research methods, removed the deficiencies that appeared after the interpretation, and strengthened the main parts of the research, wrote the summary and conclusions part, reviewed the research parts, maintained a reduction in the percentage of plagiarism, made tables and arranged the forms to match the idea and form of the research, prepare files to confirm the journal requirements and then submitted the research to the journal after approval rest of the authors. A. I. T. developed the field work plan and acquired the data. A. A. E. contributed to the data interpretation, reviewed the research and arranged its parts. A. A. B wrote the text of the manuscript, developed the field work plan with the first and second authors, coordinated the text, wrote the summary and conclusions part with the first author, reviewed the research parts, maintained a reduction in the percentage of plagiarism with the first author, made tables and arranged the forms to match the idea and form of the research with the first author.

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Kotb, A., Taha, A.I., Elnazer, A.A. et al. Global insights on flood risk mitigation in arid regions using geomorphological and geophysical modeling from a local case study. Sci Rep 14 , 19975 (2024). https://doi.org/10.1038/s41598-024-69541-x

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• DOI: 10.1007/s41207-024-00617-w
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30 References

Evaluation of relative tectonic activity in a semiarid basin: analysis of geomorphic indices and morphometric parameters in the meskiana watershed, integrated geospatial analysis for identifying regions of active tectonics in the saharian atlas, an review analysis of methodology and calculation fundamentals, erosion patterns, drainage dynamics, and their environmental implications: a case study of the hammamet basin using advanced geospatial and morphometric analysis, the geoenvironmental factors influencing slope failures in the majerda basin, algerian-tunisian border, hydrogeological investigation of karst aquifers using an integrated geomorphological, geochemical, gis, and remote sensing techniques (southern mediterranean basin—tunisia), empirical graphical and numerical model for the schematization of underground mining operations in the heterogeneous rock masses, case of boukhadra mine, ne algeria, differentiating nitrate origins and fate in a semi-arid basin (tunisia) via geostatistical analyses and groundwater modelling, geospatial modelling for sub-watershed prioritization in western himalayan basin using morphometric parameters, integrating gravity data for structural investigation of the youkous-tebessa and foussana-talah transboundary basins (north africa), watershed prioritization for soil erosion mapping in the lesser himalayan indian basin using pca and wsa methods in conjunction with morphometric parameters and gis-based approach, related papers.

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Morphometric analysis for prioritizing sub-watersheds of Murredu River basin, Telangana State, India, using a geographical information system

• Padala Raja Shekar 1 &
• Aneesh Mathew 1  

Journal of Engineering and Applied Science volume  69 , Article number:  44 ( 2022 ) Cite this article

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The Murredu watershed in Telangana State was chosen for the morphometric and land use/land cover (LULC) analysis in this current study. Geographical information system (GIS) and remote sensing (RS) techniques can estimate the morphometric features and LULC analysis of a catchment. A total of fourteen sub-watersheds (SWs) were created from the watershed (SW 1 to SW 14), and sub-watersheds were prioritized based on morphometric and LULC features. Evaluation of various morphometric characteristics such as linear aspects, relief aspects, and aerial aspects has been carried out for every sub-watershed to prefer ranking. Four parameters were utilized for the LULC analysis to rank and prioritize sub-watersheds. The sub-watersheds were categorized into three groups as low, medium, and high, for soil and water conservation priority based on morphometric and LULC analysis. Using morphometric analysis, higher priorities have been assigned to SW 12 and SW 1, while using LULC analysis, higher priorities have been assigned to SW 9 and SW 11. SW 10 and SW 13 are the most common sub-watersheds that fall within the same priority while using morphometric and LULC analysis. The coefficient of regression results reveals that stream length and stream order, and also stream number and stream order, have a strong association. The deployment of soil and water conservation measures may be conducted in the high-priority sub-watersheds.

Introduction

Morphometric characteristics are a mathematical and quantitative study of the Earth’s surface arrangement, as well as the shape and magnitude of its landforms [ 3 , 10 , 34 ]. A watershed is a section of land where rainwater contributes to a common location [ 11 ]. The study of watersheds is crucial for preventing soil erosion, conserving water, and ensuring long-term growth. Techniques like geographical information system (GIS) and remote sensing are powerful tools for analyzing the river basin’s hydraulic process [ 57 ].

The size, drainage, shape, and land use pattern of a watershed determine its classification. The many forms of watersheds are mini-watersheds (one to hundred hectares), micro-watersheds (hundred to thousand hectares), milli-watersheds (thousand to ten thousand hectares), sub-watersheds (ten thousand to fifty thousand hectares), and macro-watersheds (greater than fifty thousand hectares). Morphometric characteristics are a helpful process for analyzing watersheds as it shows the relationship among many features of a catchment like a stream order, stream length, etc. Watershed protection has drawn attention towards the safety of natural resources such as soil and water [ 14 ].

Various scientists have used traditional methods to analyze various watershed characteristics [ 13 , 16 , 17 , 18 , 45 , 50 , 52 , 53 , 54 ], and nowadays, remote sensing and GIS tools have been widely used for watershed analysis [ 2 , 7 , 4 , 5 , 6 , 21 , 32 , 36 , 37 , 41 , 43 , 44 , 47 , 49 , 51 , 58 ]. Morphometric characteristics provide a quantitative catchment report, which is valuable in studies like watershed prioritization, hydrologic modeling, natural resource conservation, etc. [ 49 ].

Extracting drainage features from the shuttle radar topography mission (SRTM) digital elevation model (DEM) has become a more popular, accurate, faster, and cost-effective way of conducting catchment studies [ 22 , 31 ]. Morphometric analysis is a quantitative catchment analysis that reveals the drainage features and development of soil erosion, surface runoff, groundwater infiltration capacity, groundwater potential, etc. [ 42 ].

A systematic analysis is essential for the configuration of a catchment, and its stream courses involve relief aspects, linear aspects, and aerial or shape aspects of the catchment [ 54 ]. Linear aspects involve the stream length, the number of streams, the bifurcation ratio, the mean stream length ratio, the stream frequency, the stream length ratio, the stream density, the drainage texture, the drainage intensity, the length of the overland flow, and the RHO coefficient. Relief features contain watershed relief, relief ratio, relief relative, ruggedness number, maximum elevation, and minimum elevation. Also, the areal features consist of circulation ratio, watershed area, perimeter, form factor ratio, basin length, elongation ratio, lemniscate ratio, and compactness coefficient [ 54 ].

According to scientific studies, morphometric features of a river basin play a significant role in prioritizing sub-watersheds [ 24 ]. Sediments, nutrients, and pollutants will be deposited and collected by the water flowing into and out of the basin [ 35 ]. They can have a significant impact on the river basin’s onsite and offsite ecosystem. As a result, studying the drainage basin process has the potential to help for a better understanding of how water moves through the hydrologic cycle. Implementing watershed management is crucial for achieving sustainable land and water resource use, as well as mitigating increasing pollutants’ impacts [ 18 , 40 , 38 ]. For the present study, the most relevant quantitative morphometric characteristics have been chosen and applied. Morphometric characteristics can be divided into three categories such as linear, relief, and areal aspects. These have been utilized to prioritize more susceptible sub-watersheds since they have a direct or indirect relationship with peak flow, runoff, and soil erosion hazards [ 33 , 18 , 48 , 46 , 41 ].

The status of the catchment’s land use/land cover (LULC) is another crucial factor to consider when prioritizing sub-watersheds [ 18 , 19 , 39 ]. The most influential factor and indicator of environmental degradation, including a catchment, is LULC changes. Several researchers have explored and used LULC analysis in catchment prioritizing [ 25 , 55 ]. Increased slope gradient irregularly enhanced soil erosion rates under various LULC scenarios, which were determined to be greatest at a particular critical degree of slope [ 59 ]. Changes in the catchment’s LULC have been recognized as the principal cause of environmental change, resulting in accelerated soil erosion, and are primarily anthropogenic [ 25 ]. RS and GIS techniques can represent various LULC categories through classification procedures [ 1 , 9 , 12 , 15 , 20 , 23 , 26 , 29 , 56 ]. RS and GIS techniques have been used in catchment prioritizing [ 28 ], which is a basic prerequisite for planners and policymakers to design management schemes that consider the immensity of the catchment area [ 19 ].

The objectives of the current study are to prioritize sub-watersheds depending on the morphometric characteristics of each sub-watersheds and also to prioritize sub-watersheds using LULC analysis of each sub-watersheds. Also, the study aims to locate the most common sub-watersheds that fall within the same priority by utilizing both morphometric and LULC analyses.

Murredu catchment is located in Telangana State. Murredu River is the sub-tributary of the Godavari River, as shown in Fig. 1 . Murredu watershed is located between longitudes 80° 20′ 0′′ and 80° 50′ 0′′ East and latitudes 17° 10′ 0′′ and 17° 50′ 0′′ North. It has a total area of 1593.33 km 2 . The hottest months of the year are usually March to June. The watershed’s rainy season is from July to September. In November, the weather turns cool and stays that way until February. The monsoon arrives in June and lasts until September. The Murredu River basin’s altitude ranges from 57 to 784 m above sea level, according to the SRTM digital elevation model.

Geographical map of the Murredu River basin

According to the World Geologic Maps of the United States Geological Survey (USGS), the study area has two types of significant rocks. Lower Triassic to Upper Carboniferous and undivided Precambrian are the geological age of two rocks. Sedimentary (Lower Triassic to Upper Carboniferous) and metamorphic rocks (undivided Precambrian) are the type of rocks that were observed in the research area. The undivided Precambrian-Metamorphic Rock occupies the majority of the current study’s area. The drainage pattern of the catchment is dendritic to sub-dendritic. The geological and drainage network of the study area is shown in Fig. 2 .

Geological and drainage network of the study area

The SRTM DEM was used for the watershed delineation in this current study. It can be downloaded from USGS Earth Explorer. DEM has a resolution of 30 m. The quantitative morphometric characteristics were performed to examine fourteen sub-watersheds of the Murredu catchment. Table 1 shows the data that was used in this research.

Figure 3 shows the processing of DEM, including fill, flow direction, flow accumulation, stream definition, stream to features, etc. Using ArcGIS 10.4.1 software, sub-watersheds (SW 1 to SW 14) are categorized based on the length of the stream, stream order, stream number, etc. Three groups of morphometric features were studied and categorized; they were linear, relief aspect, and aerial aspect. These features are determined using various empirical methods shown in Table 2 . Linear parameters of the Murredu river basin (SW 1 to SW 14) were calculated and presented in Table 3 . After getting all the morphometric values, the next step is to find the rank of individual parameters in each sub-watershed. The sub-watershed having the maximum value in the relief and linear characteristics has been ranked as first, while the second maximum value has been ranked as second, the third maximum value has been ranked as third, and so on. The sub-watershed having the minimum value in the areal or shape characteristics has been ranked as first, while the second minimum value has been ranked as second, the third minimum value has been ranked as third, and so on. After getting all ranks for individual parameters in each sub-watershed, the next step is to find the compound parameter value for each sub-watershed. To arrive at the compound parameter value, all the ranks in SW1 are added together and divided by the number of characteristics (the present study area consists of 20 characteristics) and repeat the procedure for other sub-watersheds. Following the calculation of compound values, the sub-watersheds were categorized into three classes high, medium, and low. The high priority has been given to the sub-watersheds with the very low compound value, denoted by the number 1 (high). The medium priority has been given to the sub-watershed with the next low compound parameter value, denoted by the number 2 (medium). The low priority has been given to the sub-watershed with the lowest compound parameter value, denoted by the number 3 (low). The high priority signifies the sub-watershed having the highest risk of runoff, peak flow, and soil erosion [ 18 , 33 ].

Methodology of the morphometric analysis

Results and discussion

The quantitative morphometric measurements give information on the catchment’s hydrological features. There are fourteen sub-watersheds in the Murredu catchment. By examining multiple criteria like the basin’s linear aspect, aerial aspect, and relief aspect, the morphometric analysis was utilized to prioritize sub-watersheds (Murredu). The details of various parameters are discussed below.

Basic parameters of river basin

Area of the watershed (a).

The area of the watershed can directly reflect the overall volume of water. It is one of the important parameters because a watershed’s overall area is projected into the horizontal plane. It is denoted by “A.” The overall area of the watershed is 1593.33 km 2 . In the present study, the largest and smallest sub-watershed areas are 230.95 km 2 (SW 8) and 25.79 km 2 (SW 2), respectively.

The perimeter of a watershed (P)

Watershed’s outer boundary that encloses its area is defined as the watershed perimeter [ 21 ] and is designated by P . The total perimeter of the watershed is 314 km. Out of the fourteen Murredu basins, the largest and smallest sub-watershed perimeters are 164.32 km (SW 8) and 45.46 km (SW 9), respectively.

Watershed length (L b )

The major dimension among the essential parameters of the major drainage channel is the watershed length [ 33 ]. It is denoted by L b . In the current research, the longest length of the sub-watersheds is at SW 8 (and is 28.87 km), while the shortest is at SW 2 (8.31 km).

Relief (B h )

Catchment relief is described as the elevation variation between the maximum value and outlet value on the perimeter of the catchment and is denoted by B h [ 52 ]. In this current study, SW 13 has the maximum relief (0.66), and SW 9 has the minimum relief (0.13).

Stream order (U)

According to Strahler [ 54 ], the order of stream is termed as the calculation of the position of a stream in the hierarchy of streams. The smallest finger type, as well as any unbranched tributaries, is termed first stream order. Two first stream orders are combined to generate a second stream order. Following that, the second stream order combines the third, and so on. The letter U is used to represent stream order. Figure 4 depicts the representation of each sub-watershed and its drainage network. The Murredu catchment consists of fourteen sub-watersheds, in that 5th order for SW 9, SW11, and SW13; 4th order for SW 1, SW 3, SW 4, SW 5, SW 6, SW 7, S.W 8, SW 10, and SW 12; and 3rd order for SW 2 and SW 14. The catchment has a dendritic to sub-dendritic drainage structure.

Sub-watersheds and drainage networks

Stream number (N u )

In a given catchment, the number of streams is defined as the number of streams in each sequence of that catchment [ 17 ] and is denoted by the symbol N u . SW 9 (256) and SW 2 (20), respectively, have the highest and lowest stream numbers in this study.

Stream length (L u )

Stream length is defined as the mean length of the stream of each of the dissimilar orders in a catchment. As a result, the length of the stream is greater in a first-order stream, and also it increases as stream order increases [ 17 ]. It is designated by L u . In the present research, the lengths of the largest and smallest of the stream are SW 13 (160 km) and SW (28 km), respectively.

Linear aspects

Bifurcation ratio (r b ).

According to Schumm [ 45 ], the bifurcation ratio is termed as the proportion of the number of streams of any given order to the number of streams of the next higher order. It was indicated by R b . In the current study, SW 9 (16) has the maximum bifurcation ratio, and SW 2 has the minimum (8.33).

Mean stream length (L sm )

It is defined as the ratio of the length of the stream to the number of streams [ 17 ] and is denoted by L sm . In the current study, the maximum (20.97) and minimum (3.72) mean stream lengths are SW 12 and SW 9, respectively.

Stream length ratio (R l )

It is defined as the ratio of the given order’s average stream length to the next smaller order’s mean stream length [ 17 ]. R l is the symbol for it. SW 9 (3.05) and SW 2 (1.5) had the highest and lowest stream length ratio values, respectively, in the current study.

According to Horton [ 17 ], the stream length and number of unique orders in a drainage basin are linked by two fundamental rules. The foremost is the law of stream numbers that describes the link between the given order’s stream number and its stream order in terms of an inverted geometric series with the bifurcation ratio as the base. Figure 5 shows a strong correlation between stream order and stream number with better coefficients of determination ranging from SW 4 (0.975) to SW 6 (0.999).

Order of streams and the number of streams

The second is the law of stream length, which is the mean length of a particular order in terms of stream order, the average length of first-order streams, and stream length ratio. This rule is expressed as a direct geometric series. Figure 6 shows a strong correlation between stream order and stream length with coefficients of determination ranging from SW 14 (0.603) to SW 7 (0.996).

Order of streams and the stream length

Mean bifurcation ratio

Strahler [ 53 ] utilized a weighted average ratio of bifurcation generated by multiplying the ratio of bifurcation for every consecutive set of patterns by the overall number of streams occupied in the ratio and taking the average of the combination of these results to arrive at a more representative bifurcation number. SW 1 has the highest value, whereas SW 13 has the lowest value in this study.

Stream frequency (F s )

Stream frequency is defined as the number of stream segments of all orders per unit catchment area, according to Schumm [ 45 ]. It is denoted by F s . In the current study, the higher stream frequency is at SW 9 and the lower stream frequency is at SW 8.

Drainage density (D d )

According to Schumm [ 45 ], drainage density is defined as the proportion of the overall length of the stream segments of all orders to the catchment area projected on the horizontal surface. It is indicated by D d . In this study, drainage density is higher at SW 9 and lower at SW 8.

Drainage texture (D t )

It is defined as the total number of streams per perimeter of the catchment, according to Schumm [ 45 ], and is denoted by the symbol D t . In the current study, drainage texture is maximum at SW 9 and is minimum at SW 2.

Length of the overland flow (L o )

The highest value of the length of the overland flow indicates greater surface runoff and the lowest value of the length of the overland flow indicates shorter surface runoff, according to Schumm [ 45 ]. It is denoted by L o . The length of the overland flow is higher at SW 8 and lower at SW 9.

Drainage intensity (D i )

According to Faniren [ 13 ], drainage intensity is defined as the ratio of stream frequency to drainage density. It is denoted by D i . In this current study, the drainage intensity is higher and lower at SW 9 and SW 7, respectively, and shown in Fig. 7 .

Morphometric analysis of twenty sub-watersheds

RHO coefficient (ρ)

RHO coefficient is a proportion between the stream length ratio and the bifurcation ratio, according to Horton [ 17 ]. It is designated by ρ . In this current study, the RHO coefficient is higher and lower at SW 9 and SW 14, respectively.

Infiltration number (I f )

It is defined as the combination of stream frequency and drainage density, according to Faniran [ 13 ], and is denoted by I f . In the current study, SW 9 has a higher infiltration number and SW 8 has a lower infiltration number.

Constant of channel maintenance (c cm )

This property defines the number of units of catchment surface needed to support one unit of route length. In other terms, it is the number of square kilometers of catchment surface area required to support one linear kilometer of stream segment. It was first proposed by Schumm in 1956 [ 45 ], who defined the channel maintenance constant as the reverse of drainage density. In the current study, SW 8 has a higher constant of channel maintenance and SW 9 has a lower constant of channel maintenance.

Areal aspect

Circulatory ratio (r c ).

According to Miller [ 30 ], it is termed as the proportion of the area of a catchment to the area of the circle with an equal circumference as the catchment’s perimeter. It is indicated as R c . Its ratio indicates the shape of the catchment. In the current study, SW 5 has a higher circulatory ratio and SW 8 has a lower circulatory ratio.

Elongation ratio (R e )

It is defined as the proportion of the diameter of a circle covering the equal area as the catchment to the minimum length of the catchment, as per Schumm [ 45 ]. It is denoted by R e . In this current study, SW 2 has a higher elongation ratio and SW 8 has a lower elongation ratio.

Form factor (F f )

Form factor is defined as the proportion of catchment area to the square of catchment length, according to Horton [ 17 ]. It is denoted by F f . In this present study, SW 2 has a higher form factor and SW 8 has a lower form factor.

Lemniscate ratio (K)

It is used to calculate the catchment’s slope [ 8 ]. It is denoted by K . In this present study, SW 8 has a higher lemniscate ratio and SW 2 has a lower lemniscate ratio.

Shape index (S b )

The shape index is the reciprocal of the form factor. It was first proposed by Horton [ 16 ]. It is denoted by the symbol S b . In this present study, SW 8 has a higher shape index and SW 2 has a lower shape index.

Compactness coefficient (C c )

According to Horton [ 17 ], the compactness coefficient is termed as the proportion of the catchment’s perimeter to the circumference of an equivalent circular area and is indicated as C c . In this present study, SW 8 has a higher compactness coefficient and SW 5 has a lower compactness coefficient.

Relief aspect

Relief ratio (r h ).

According to Schumm [ 45 ], the relief ratio is termed as the proportion of the maximum catchment relief ( B h ) to the minimum catchment length which is parallel to the primary catchment line and is denoted by R h . In this current study, the higher value of the relief ratio is at SW 2 and the lower value of the relief ratio is at SW 13.

Relative relief (R hp )

The perimeter and watershed are used to determine relative relief [ 27 ]. R hp is the symbol for it. SW 2 has the higher value, whereas SW 8 has the lower value in this study.

Ruggedness ratio (R n )

According to Strahler [ 53 ], the ruggedness ratio is used to measure the surface unevenness or roughness. It is the combination of drainage density and maximum catchment relief and is denoted by R n . In this study, the higher value and lower value have been identified at SW 13 and SW 14, respectively.

Hypsometric analysis

The relative proportion of the catchment areas below or above a specific height is represented by the hypsometric curve for a catchment. The hypsometric integral is defined as the area below the hypsometric curve [ 52 , 45 ], and it has been used to determine the stage of development of a catchment, along with the hypsometric curve. The catchment is split into three phases such as old, mature, and young. The value of the hypsometric integral in the old stage is less than 0.3, the mature stage is between 0.3 and 0.6, and the youthful stage is greater than 0.6. The hypsometric integral is shown in Table 4 .

Morphometric sub-watershed prioritization and ranking

For this analysis, the most relevant quantitative morphometric characteristics are chosen and applied. Morphometric characteristics can be divided into three categories (linear features, relief features, and areal features). These have been utilized to prioritize more susceptible sub-watersheds since they have a direct or indirect relationship with peak flow, runoff, and risk of soil erosion [ 17 , 18 , 48 , 46 ].

Soil erosion is directly relevant to the linear and relief characteristics such as mean bifurcation ratio, drainage density, stream frequency, drainage texture, relief, ruggedness number, and so on [ 18 , 33 ]. The maximum value of linear and relief characteristics in a catchment indicates the most erodible soil. Consequently, the sub-watershed with the maximum value in the relief and linear characteristics is ranked first, while the second maximum value is ranked as second, the third maximum value is ranked as third, and so on.

The areal characteristics such as circularity ratio, shape index, compactness coefficient, elongation ratio, form factor, and lemniscate ratio have an indirect relationship with soil erosion [ 18 , 33 ]. The most erodible soil in a catchment is the soil with the minimum areal characteristic value. Hence, sub-watershed having the lowest areal characteristics values will be ranked first, the second lowest areal characteristic values will be ranked as second, the third lowest areal characteristic values will be ranked as third, and so on.

For linear and relief parameters, the maximum value is given a ranking of 1, and the next maximum value is given a ranking of 2, and so on. In the case of areal parameters, the minimum value was given a ranking of 1, followed by the next minimum value is given a ranking of 2, and so on.

After assigning a ranking based on each parameter, the ranking values for all fourteen sub-watersheds were averaged to arrive at a compound parameter value. Table 5 shows the results of ranking for all fourteen sub-watersheds. Sub-watershed 1 has a compound value of 5.75 if all the ranks in SW1 are added together and divided by 20 characteristics. The procedure has been repeated for other sub-watersheds (from SW 2 to SW 14) and presented in Table 6 .

Following the calculation of compound values, the sub-watersheds were categorized into three groups, high (≥ 5.05 to < 6.5), medium (≥ 6.5 to < 8), and low (≥ 8 to < 9.5). The sub-watershed with the minimum compound value represents as rank 1 category, SW having the next minimum compound value represents as rank 2 category, and so on. The sub-watersheds with the compound value in the range of ≥ 5.05 to < 6.5 have been specified as high priority. The sub-watershed with the compound value in the range of ≥ 6.5 to < 8 has been chosen as a medium priority. The sub-watersheds with the compound value in the range of ≥ 8 to < 9.5 have been specified as a slow priority. Among 14 sub-watersheds, SW 12 and SW 1 are falling within high priority; SW 2, SW 3, SW 4, SW 5, SW 6, SW 9, and SW 13 fall within a medium priority; and SW 7, SW 8, SW 10, SW 11, and SW 14 fall within a low priority. This means that the sub-watersheds with the highest priority have the greatest danger of runoff, peak flow, and soil erosion risk [ 18 , 33 ].

The final priority map of sub-watersheds in the Murredu catchment is shown in Fig. 8 . SW 12 and SW 1 are the most vulnerable sub-watersheds to land degradation, and they are more vulnerable to soil erosion and runoff. As a result, the findings will help in better planning and the management of the Murredu catchment.

Priority of sub-watersheds based on morphometric analysis

Land Use/Land Cover (LULC) analysis

Prioritization of LULC of sub-watersheds was based on LULC data of the year 2020 from Sentinel-2 imagery. LULC has a resolution of 10 m. LULC categories include eight primary classes such as grass, flooded vegetation, water, trees, crops, scrub/shrub, built-up area, and bare ground. Figure 9 depicts the LULC map of the research area. Table 7 shows the details of the various LULC categories. The following classes are the LULC criteria that were considered for prioritizing sub-watersheds.

Study area’s LULC cover map

SW 14 has the highest percentage of land with trees (55.48%), while SW 7 has the lowest percentage of trees (5.40%). Sub-watersheds with a smaller percentage of trees have been given a high rank, while those with a higher percentage of trees have been given a low rank.

SW 11 has the highest percentage of land with crops (79.97%), while SW 1 has the lowest percentage of crops (18.22%). Sub-watersheds with a small percentage of crops were given a high rank, while those with a high percentage of crops were given a low rank.

Scrub/shrub

SW 5 has the highest percentage of scrub/shrub (41.53%), while SW 11 has the lowest percentage of scrub (7.63%). Sub-watersheds with a lower percentage of scrub/shrub have a high rank, whereas those with a larger percentage of scrub/shrub have a low rank.

Built-up area

SW 9 has the highest percentage of land with the built-up area (25.80%), while SW 4 has the lowest percentage of built-up area (0.31%). Sub-watersheds with a larger percentage of the constructed area have a low rank, while sub-watersheds with a smaller percentage of the built-up area have a high rank.

For the built-up area parameter, the maximum value was given a ranking of 1, and the next maximum value was given a ranking of 2, and so on. In the case of trees, crops, and scrub/shrub parameters, the minimum value was given a ranking of 1, followed by the next minimum value is given a ranking of 2, and so on.

The compound parameter method of averaging values was applied for sub-watershed prioritization. Table 8 shows the results of the ranking of all fourteen sub-watersheds. All the ranks in SW1 are added together and divided by four characteristics, and then the compound parameter has been computed as 8. The procedure has been repeated for the remaining sub-watersheds from SW 2 to sw14, as shown in Table 9 .

Following the calculation of compound values, the sub-watersheds were categorized into three groups, high (≥ 4 to < 6), medium (≥ 6 to < 8), and low (≥ 8 to < 10). The sub-watershed with the minimum compound value represents as rank 1 category, SW having the next minimum compound value represents as rank 2 category, and so on. The sub-watersheds with the compound value in the range of ≥ 4 to < 6 have been specified as a high priority. The sub-watershed with the compound value in the range of ≥ 6 to < 8 has been chosen as a medium priority. The sub-watersheds with the compound value in the range of ≥ 8 to < 10 have been specified as low priority. Among four sub-watersheds, SW 9 and SW11 are falling within a high priority; SW 7, SW 8, SW 12, SW 13, and SW 14 fall within a medium priority; and SW 1, SW 2, SW 3, SW 4, SW 5, SW 6, and SW 10 fall within a low priority. Figure 10 shows the priority of sub-watersheds based on LULC analysis.

Priority of sub-watersheds based on LULC analysis

The quantitative analysis of morphometric factors will be used in the development of catchment, river basin prioritizing for soil conservation, and also for water conservation. Morphometric descriptors are simple techniques for defining catchment processes that can be used to compare catchment characteristics and for a better understanding of the geological history of the catchment. According to the data, SW 9 and SW11 have the highest priority, and SW 1, SW 2, SW 3, SW 4, SW 5, SW 6, and SW 10 have the lowest priority among sub-watersheds. The results of morphometric and LULC analysis were compared to determine the most common sub-watersheds associated with each priority. According to morphometric study and LULC analysis, two sub-watersheds, SW 10 and SW 13, are the common sub-watersheds that fall within a low and medium priority, respectively.

Conclusions

GIS and remote sensing approaches have been used for morphometric and LULC research over the Murredu catchment area. Twenty parameters of morphometric and four parameters of LULC have been calculated and scientifically analyzed in this current study. The results of morphometric analysis-based prioritization showed that the SW 12 and SW 1 sub-watersheds are of high priority. The results of the LULC analysis-based prioritizing showed that the SW 9 and SW11 sub-watersheds are of high priority. Comparing morphometric and LULC analysis, the common sub-watersheds falling within the same priority are SW 10 and SW 13. The deployment of soil and water conservation measures may be conducted in the high-priority sub-watersheds. As a result, effective land and water management strategies should be planned for each sub-watershed based on their sensitivity rankings.

Availability of data and materials

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Land use/land cover

Sub-watersheds

Geographical information system

Remote sensing

Shuttle radar topography mission

Digital elevation model

United States Geological Survey

Environmental Systems Research Institute

Stream order

Stream length

Stream number

Stream length ratio

Bifurcation ratio

Mean stream length

Mean stream length ratio

Stream frequency

Drainage density

Drainage texture

Length of overland flow

RHO coefficient

Drainage intensity

Infiltration number

Constant of channel maintenance

Maximum elevation

Minimum elevation

Relief ratio

Relative relief

Ruggedness number

Area of watershed

Perimeter of watershed

Basin length

Circulatory ratio

Elongation ratio

Form factor

Lemniscate ratio

Shape index

Compactness coefficient

Sum of rankings

Total number of parameters

Compound parameter

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Acknowledgements

The authors would like to thank the anonymous reviewers for their instructive comments, which helped to improve this paper. In addition, the authors wish to thank the US Geological Survey (USGS) for making available the satellite data. Finally, the authors also want to thank ESRI for providing land use land cover data.

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Shekar, P.R., Mathew, A. Morphometric analysis for prioritizing sub-watersheds of Murredu River basin, Telangana State, India, using a geographical information system. J. Eng. Appl. Sci. 69 , 44 (2022). https://doi.org/10.1186/s44147-022-00094-4

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Morphometric Analysis of River Drainage Basin/Watershed using GIS and RS: A Review

2017, International Journal for Research in Applied Science & Engineering Technology (IJRASET)

Morphometry is the measurement and mathematical analysis of the earth's surface, shape, and dimension of the land forms. Morphometric analysis requires measurement of linear aspects, aerial aspect and slope of the drainage basin. In all 28 literatures, the researchers analyses the morphometric study for watershed management and prioritization of watershed using morphometric analysis through geoinformatics technology. We focus on matter of fact that is methodology, adopted, raw data used as input and process to study sustainable watershed management. The content of this review paper divided in to three sections namely Introduction, Methodology, and analysis, Conclusion followed by references.

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Sub-watershed prioritization has gained due importance in the recent time for management of natural resources at a watershed level especially in the perspective of planning and management of watersheds. Analysis of morphometric parameters (linear, areal, relief and shape aspects) is usually the core investigation outline for prioritization of sub-watersheds. The current study makes an effort to prioritize sub-watersheds of Kiknari nala watershed situated in Mandla district of Madhya Pradesh, India by executing morphometric analysis using the techniques of remote sensing and GIS. Different morphometric parameters such as bifurcation ratio (Rb), drainage density (Dd), stream frequency (Fs), texture ratio (Rt), relief ratio (Rh), form factor (Ff), circulatory ratio (Rc) and elongation ratio (Re) for each sub-watershed was calculated using standard formulas and ranks were allocated so as to achieve values of compound parameter. In the present study, suitable soil and water conservation measures should be adopted primarily for SW – 2 having highest priority rank followed by SW – 1.

IAEME Publication

Doddaballapur district comprises of about 12micro watershed which contains several mini watershed .The study area includes Bashettihalli mini watershed 77°33'0''E to 77°35'0''E latitude and 13°14'30''N to 13°17'30''N longitude. The study involves the morphological analysis, which includes the various methods of exploring the mathematical relationships between various stream attributes. There is a scarcity of waterin the study area hence in order to overcome the problem a detailed analysis of catchment characteristics is being presented in the paper. Hence for the study high resolution IRS LISS III image is used and its processed in Erdas imagine software for planning of watershed development. Different Morphometric analysis provides the explanation of physical characteristics of the watershed which are useful for the areas of land use planning, soil conservation, terrain elevation and soil erosion.

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Flash Flood Susceptibility Assessment Using Morphometric Characteristics and Geospatial Technology in Waya Watershed, Volta River Basin, Ghana

20 Pages Posted: 30 Aug 2024 Publication Status: Under Review

Bismark Mensah-Brako

University of Ghana - Ho Technical University

Francis Ampiaw

Richard kotei, philip kayku.

Drainage watershed is a significant hydrological unit required for sustainable management of soil and water resources for sustainable food production systems. Drainage morphometric characteristics are essential indicators to ascertain surface runoff generation, erosional characteristics and flash flood susceptibility of any watershed. In Waya watershed, lives and properties have been severely destroyed as a result of flash floods. Farmland and food crops have been swept off and several physical infrastructures and investments destroyed. Many farming households hardly recover from devastating effects of flash floods leading to poverty with its other socio-economic impacts.  Present study aimed at assessing flash flood susceptibility of Waya Watershed and its sub-watersheds using geospatial technologies and morphometric characteristics which is envisaged to serve as baseline data for sustainable flood mitigation planning and management strategies. The drainage morphometric characteristics were determined using the Advanced Spaceborne Thermal Emission and Reflection Radiometer DEM (30 m) in GIS 10.7 environment. The Morphometric compound ranking method was applied to prioritize the susceptibility of sub-watersheds to flash flood events in Waya watershed. The results of the morphometric analysis revealed that Waya Watershed is a seventh order drainage system with a dendritic to sub-dendritic drainage pattern and elongated shape. Seventy-eighty (78.00) percent of total streams were found to be 1st order streams which indicated that Waya watershed and its sub-watersheds are prone to flash flood events. The mean bifurcation ratio (4.48) and form factor (0.20) are an indicative of structural control on stream development, higher level of surface runoff and high flash flood potential. The stream frequency (3.27- 4.14), drainage density (2.24-2.51), drainage texture (4.97-7.92), infiltration number (8.05-10.22) and relief ratio (3.69 -16.44 m) revealed a presence of homogenous geological formation, high discharge rate, higher runoff discharge and flash floods. Watershed relief (553 m), relative relief (194.4), ruggedness number (1.36) and mean slope (10.31 %) are indicative of undulating topography, high potential energy to move water down the slope, high sediment transportation and high erosional characteristics. The results further showed that seven sub-watersheds (SW1, SW5, SW6, SW9, SW8, SW10 and SW12) constituted 63 % of the total area of the watershed are classified as high to very high susceptibility to flash flood for which sustainable soil and water conservation measures are required to mitigate the risk of flood and soil erosion.  The study recommends good amount of investment in the development of Inland Valley Rice and Wetland Rice Production Structures as sustainable soil and water conservation measures to mitigate flash flood as well as to enhance sustainable rice production in the area.

Keywords: Watershed, flash flood, geospatial technology, morphometric characteristics, flood susceptibility

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Bismark Mensah-Brako (Contact Author)

University of ghana - ho technical university ( email ).

P. O.Box HP 217 Department of Marketing Ho Ghana

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Analysis of morphometric characteristics and prioritization of micro watersheds of Karamnasa River Basin using remote sensing & GIS technique

• Kumar, Sumit
• Kumar, Dhiraj
• Chandola, V. K.
• Sonkar, Niraj Kumar
• Dwivedi, Anuj Kumar
• Ojha, C. S. P.

Morphometric analysis of watershed using remote sensing and GIS—a case study of Nanganji River Basin in Tamil Nadu, India

• Original Paper
• Published: 12 March 2019
• Volume 12 , article number  202 , ( 2019 )

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• Pandian Mangan 1 ,
• Mohd Anul Haq 1 &
• Prashant Baral 1  

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Morphometric analysis of a river basin is essential to identify and assess seasonal changes in drainage basin characteristics, understand the groundwater potential, and address issues related to management of soil erosion due to flash floods during the high flows. Nanganji River Basin is one of the least studied seasonal river basins in India which carry substantial flows during the monsoon period. In this study, morphometry of Nanganji River Basin, located in the central Tamil Nadu prairies, has been studied using remote sensing and GIS. The interrelationship between the various morphometric factors of the basin has been studied using a correlation matrix. Factor analysis has been applied to group the individual morphometric parameters into a smaller number of factors. Further, these factors have been studied in relation to the sub-basins to understand the existing relation between the factors and the sub-basins. Finally, the study identifies environmental issues of the Nanganji River Basin mostly related to the river flow regime which widens significantly during the monsoon months.

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Acknowledgements

We are very grateful to IBM Corporation for providing online version of IBM SPSS Statistics for the necessary computations.

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Pandian Mangan, Mohd Anul Haq & Prashant Baral

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Mangan, P., Haq, M.A. & Baral, P. Morphometric analysis of watershed using remote sensing and GIS—a case study of Nanganji River Basin in Tamil Nadu, India. Arab J Geosci 12 , 202 (2019). https://doi.org/10.1007/s12517-019-4382-4

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Received : 15 February 2018

Accepted : 22 February 2019

Published : 12 March 2019

DOI : https://doi.org/10.1007/s12517-019-4382-4

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