E-NAMTILA

THE SYRIAN ELECTRONIC ACADEMIC DATABASE

Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin

Mirna Ahmad Shaddoud 1*; Asma Khalil 2; Ioannis Kotaridis 3; Hussam Hag Husein 4; Romulus Costache 5,6,7

1, Geography Department, Faculty of Arts and Humanities, Tartous University, Tartous, Syria

2, Institute of Hydraulic Engineering and Water Resources Management, Vienna University of Technology, Karlsplatz 13/223, 1040 Vienna, Austria

3, Aristotle University of Thessaloniki, Faculty of Engineering, School of Civil Engineering, Lab. of Photogrammetry – Remote Sensing, 54124 Thessaloniki, Greece

4, Institute of Geography, FAU Erlangen Nürenberg University, Erlangen, 91052, Germany

5, National Institute of Hydrology and Water Management, 013686, Bucharest, Romania

6, Danube Delta National Institute for Research and Development, Tulcea, Romania 7, Department of Civil Engineering, Transilvania University of Brasov, 500152, Brasov, Romania

E-mail:
mirnashaddoud@tartous-univ.edu.sy

Received: 10/01/2025
Acceptance: 12/05/2025
Available Online: 15/05/2025
Published: 01/07/2025

DYSONA – Applied Science
Download this article

 

Manuscript link
http://dx.doi.org/10.30493/DAS.2025.499154

Abstract

Flash floods are among the most significant natural hazards, occurring across various temporal and spatial scales. Assessing and mapping flash flood risks is a critical component of sustainable hydrological management, particularly in regions prone to recurrent flooding. Western Syria is exposed to annual flash floods, leading to casualties and significant infrastructure damage. This study integrates morphometric analysis with geospatial tools to assess flash flood risks, providing a valuable approach for data-scarce region like Syria. The research focuses on the Abu Al Ward River Basin, employing 18 morphometric parameters categorized into linear, areal, and topographic dimensions. These include parameters such as stream order (U), streams number (Nu), streams length (Lu), mean bifurcation ratio (MRb), weighted mean bifurcation ratio (WMRb), length of overland flow (Lg) for linear parameters. Areal parameters encompass area (A), drainage density (Dd), stream frequency (Fs), basin texture (Rt), form factor (Ff), and circulatory ratio (Rc). Topographic parameters include basin relief (R), relief ratio (Rr), relative relief (Rh), ruggedness number (Rn), basin slope (Bs), and slope index (SI). The findings indicate that 52.50% of the study area is at very high to high flash flood risk (SW5, SW6 and SW7), flowed by 6.88% at moderate risk (SW1). Low to very low risk areas (SW2, SW3 and SW4) comprise 40.62% of the region. These results offer actionable spatial insights to enhance flash flood risk management strategies in the Abu Al-Ward River Basin, supporting the sustainability of critical natural resources, including soil and water.

Keywords: Flood risk, Flash floods, Morphometric analysis, Eastern Mediterranean

Introduction

Flash flood risk is one of the most critical hydrological challenges affecting ecosystems [1][2]. The severity of flash floods is often exacerbated by prolonged drought periods, which amplify their impact [3][4]. Temporal and spatial variability in precipitation and rainfall intensity are key drivers influencing the occurrence and magnitude of flash floods [5][6]. This risk is particularly acute in developing countries within the Eastern Mediterranean, where the frequency and severity of flash floods are on the rise [7-9]. Many of these countries face significant challenge due to the absence of robust hydrological monitoring systems, comprehensive prevention plans, and effective rapid response strategies to mitigate flash flood risk [10][11].

Flash flood maps serve as essential tools for the spatial assessment of potential hazards, offering reliable insights for risk management [12]. In this context, morphometric analysis provides a comprehensive approach to evaluating natural hazards, enabling the development of effective mitigation strategies [13][14]. This method has been widely applied in assessing various risks, including soil erosion [15], flood risk [16], surface runoff [17], identifying water harvesting sites [18], and groundwater resource locations [19]. Composite ranking method such as the Compound Factor (CF) approach [20][21] and Davis’s classification system [22] are frequently used to quantify flash flood hazards based on morphometric parameters. Advanced techniques like the Multi-Criteria Decision Analysis (MCDA) and the Analytical Hierarchy Process (AHP) further enhance hazard assessments [23][24]. Remote sensing (RS) data play a critical role in these analyses, providing Digital Elevation Models (DEM) as foundational datasets for morphometric evaluation [25]. Integrating RS data with Geographic Information Systems (GIS) enables precise morphometric measurement and the generation of detailed flash flood hazard maps [26][27]. These maps assist decision makers and planners in developing river basin management strategies [28] and offer valuable insights for mitigating the severity of future flash flood risks [29][30].

Davis’s method provides a precise ranking of river sub-basins according to a statistical relationship of morphometric characteristics [22][31], while the complex factor method prioritizes the values ​​of morphometric characteristics in ascending or descending order [20][21][32]. Both methods provide rapid assessments; however, Davis’s method ranks the basins in a more objective manner. Most of the literature on flash flooding in the Syrian coastal basin used the composite factor method in arranging hydrological priority [33], and the AHP method was used to identify the locations most at risk of flash flooding [34]. This paper focuses on the priority arrangement of flash floods in the Southern Syrian Coastal Basin using Davis’s method in a similar manner to its application in the Northern Syrian Coastal Basin [35]. This study focuses on developing a flash flood risk map for the Abu Al-Ward River Basin, which will serve as a critical resource for officials and planners. The map aims to guide the implementation of protective measures and the construction of additional water management infrastructure to reduce future risks effectively.

Material and Methods

Study area

The study area is located within the Abu Al-Ward River Basin, a sub-basin of the southern Kabir River Basin in the eastern Mediterranean region of Syria (Fig. 1 A). It is situated between latitudes of 34° 38′ 29″ and 34° 43′ 17″ N and longitude of 36° 5′ 25″ and 36° 17′ 51″ E, with an area of 91.05 km2. The study area is bounded by the Arous River to the north, which forms the northern border, and the southern Kabir River to the south, along with the Rawil River to the east. To the west, the area is bordered by the southern Kabir River and the Mediterranean (Fig. 1 B). The elevation within the basin varies between 41 meters and 582 meters above sea level. The river network comprises five distinct river orders. Notably, the Arous and Khalifa Rivers converge at the village of Al-Hasna, located at an elevation of 41 meters (Fig. 1 C).

The region experiences an annual rainfall ranging from 448.38 to 889.57 mm, with the average summer temperature ranging between 19°C and 23°C, and winter temperatures between 10°C and 14°C. This region has been heavily impacted by the ongoing conflict since 2011, resulting in the absence of regular hydrological monitoring and insufficient protective measures at the river basin level. The basin is characterized by frequent flash flood events, with notable occurrences on January 29, 2020, March 17, 2020 and January 13, 2024. According to official unpublished surveys, the 2024 flash flood caused extensive damages, submerging approximately 250 hectares of potato fields, 319 hectares of greenhouses, 68 hectares of citrus orchards, 166 hectares of wheat, and 58 hectares of green beans crops. Additionally, the event led to the tragic loss of four lives from a single family. Although a single dam is present in the upper parts of the basin, the area lacks a comprehensive flood management system.

Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin
Figure 1. Location of the study area in the southern coastal region of Syria (A and B) with a depiction of elevation (C). A flash flood event the study area (January 13, 2024) with evident damages to houses and agricultural properties (D, E, and F)

Data and software

The study area was delineated using RS data (DEM) (From Link) within a GIS environment in Arc map 10.5. Filling, flow direction, flow accumulation, and watershed delineation were then applied to the data. River orders were determined using the Strahler method with the GIS environment. River basins were classified according to rank, and concentration points were used to divide the study area into seven sub-basins (Fig. 2) [36][37]. The morphometric characteristics of each sub-basin were then determined (Table 1) and the basic measurements of the research area and each sub-basin were extracted in the GIS environment (Table 2).

Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin
Figure 2. Sub-basins of Al-Ward River basin 

Morphometric analysis

In this assessment, morphometric parameters including basic [38-43], linear [38][40][43-45], areal [38][40][45-47] , and topographic [40-44][48] were applied to produce a potential flash flood hazard map.Overall, 18 parameters were adopted to determine the degree of flash flood hazard, including linear (Stream order U, streams number Nu, streams length Lu, mean bifurcation ratio MRb, weighted mean bifurcation ratio WMRb, length of overland flow Lg) , areal (area A, drainage density Dd, stream frequency Fs, basin texture Rt, form factor Ff, circulatory ratio Rc),and topographic (basin relief R, relief ratio Rr, relative relief Rh, ruggedness no Rn, basin slope Bs, slope index SI) parameters (Table 1).

Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin
Table 1. The utilized morphometric parameters and their determination method
Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin
Table 2. Geometric morphometric measurements of the sub-basins

Prioritization of flash flood mapping

The method proposed by Davis [31] was employed to assess the degree of flash flood risk in the sub-basins of the study area. The following formulas were used:

Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin

Where Y is the degree of flash flood hazard. Ymax and Ymin represent the upper and lower limits of the proposed hazard scale. Xmax and Xmin correspond to the highest and lowest values ​​of each parameter. X is the estimated value of each parameter, located between the highest and lowest values. Sub-basins were classified according to the estimated hazard degree, which was assigned a final score ranging from 1 to 5.

The influence of each morphometric factor on the flash flood hazard score (H) was evaluated by calculating the Pearson correlation coefficient between each factor and the final hazard score weight (W). The flash flood risk levels in the sub-basins were categorized into five levels: 1. Very low risk, 2. Low risk, 3. Medium risk, 4. High risk, 5. Very high risk. The sum of the weights for each parameter was calculated, and the final risk level (H) was assigned based on the results. The flash flood risk map was then generated in a GIS environment in Arc map 10.5.

Results and Discussion

Linear parameters

The stream network was classified into five stream orders (U) according to Strahler’s method. The sub-basins of the fourth order included SW1; SW2; SW3; SW4 and SW5, while the sub-basins of the fifth order included SW6 and SW 7. In this context, the higher U indicates a large area of flow within the river basin. There is a direct relationship between U, flow depth, and flash flood risk [49][50]. The total number of channels (Nu) in the study area was estimated at 599, with a total stream length (Lu) of 219.33 km. The Nu ranged from 27 channels with a stream length (Lu) value of 10.66 km in SW3 to 178 channels with Lu value of 55.42 km in SW6, as shown (Table 3). Both Nu and Lu reflect the interaction between precipitation and geological structures [51]. These parameters are associated with the presence of impermeable rocks, low permeability, higher surface runoff potential, and increased flash flood risk [18][52]. The Sub-basins SW6, SW7, and SW4 were classified as having higher flash flood risk based on to Nu and Lu. The Mean bifurcation ratio (MRb) ranged from 1.71 in SW4 to 4.18 in SW7, while the WMRb ranged from 1.8 in SW1 to 2.56 in SW7 (Table 4).

Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin
Table 3. Stream order measurements
Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin
Table 4. Characteristics of bifurcation ratios

The bifurcation ratio (Rb) reflects the shape of the river network, which influences the volume of generated surface runoff [53]. Low Rb values indicate high discharge and long concentration time during rainstorms, which are associated with higher flash flood risk [37][54]. Consequently, sub-basins SW4, SW1, SW2 are expected to have high flash flood risk due to their low MRb and WMRb values.

The length of overland flow (Lg) values ranged from 1 in SW4 to 1.5 in SW5 (Table 5). Low Lg values indicate rugged terrain, fast surface runoff, and higher flood risk [55]. Based on Lg values, higher flash flood risk is expected in SW4, SW2, and SW6. Therefore, linear parameters suggest that the most vulnerable sub-basins to flood risk are SW6, SW4, and SW1, respectively. U, Lu, and Nu were found to be the most influential factors in determining flood risk (Fig. 4). The high flood risk in SW6 and SW7 can be attributed to rapid peak flow, low permeability geological structures, and high hydrological response.

Areal parameters

The area (A) reflects the sequence of hydrological processes, from the formation of flow to peak flow and its subsequent dispersion [56]. A larger basin area indicates a greater hydrological response, which correlates with a higher flash flood risk [52]. The area of the sub-basins ranged from 4.07 km2 in SW3 to 25.78 km2 in SW4.

Sub-basins SW4, SW6 and SW7 were classified as more susceptible to a high hydrological response (Table 6). Drainage density (Dd) values ranged from 2 in SW4 to 3.12 in SW5 (Table 5). Dd reflects the combined influence of geological structures, land cover, and topographic slope orientation [38][46]. High Dd values indicate low infiltration rates and a higher volume of surface runoff [57]. Therefore, SW5, SW7 and SW3 sub-basins were classified as more hydrologically responsive based on their Dd values.

Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin
Table 5. Results of morphometric measurements in the Abu Al-Ward River sub-basins

The values of Stream frequency (Fs) ranged from 5.67 in SW2 to 7.69 in SW7. High Fs values are associated with increased surface runoff, hills with low permeability rock structures, and higher flash flood risk [58][59]. Based on Fs, sub-basins SW7, SW6, and SW3 were classified as higher risk (Table 6). Basin texture (Rt) values varied from 1.6 in SW3 to 4.8 in SW7 (Table 5). Rt in the study area is classified as predominantly rough [60], which indicates the presence of a low permeability surface, influenced by soil and rocks characteristics [61]. Sub-basins SW7, SW4, and SW6 were identified as more susceptible to flash flood risk based on their Rt vales.

Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin
Table 6. Hydrological response risk score in Abu Al-Ward River sub-basins

Form factor (Ff) values ranged from 0.18 in SW4 and SW6 to 0.38 in SW1, while the values of the circulatory ratio (Rc) ranged from 0.12 in SW6 to 0.35 in SW1. According to Ff and Rc, sub-basins with more elongated shapes tend to have lower runoff, longer concentration times, and consequently lower flash flood risks [17][62]. The sub-basins considered the riskiest based on Ff and Rc are SW1, SW7, and SW2. Based on the areal parameters, the sub-basins most exposed to the flash flood risk are SW7, SW1, SW5, SW4 and SW6. The areal parameters with highest influence on flash flood risk were Rt, Fs, and A (Fig. 4). This observation is mainly attributed to low permeability rock generating higher surface runoff, which in turn increase the flash flood risk.

Topographic parameters

The basin relief (R) values in the study area ranged from 138 in SW1 to 335 in SW6 (Table 5). High R values indicate accelerated morphodynamic processes on slopes, increased runoff hazard, earlier rapid peak flow, and higher flood hazard [63][64]. According to R values, the sub-basins of SW6 and SW5 were considered more hazardous (Table 6). The values of relief ratio (Rr) ranged from 0.013 in SW4 to 0.043 in SW5 (Table 5). High Rr values are indicative of large volumes of accelerated runoff, severe erosion, and a greater amount of sediment loss [65]. Based on Rr values, the sub-basins of SW5, SW3, and SW2 were classified as higher hazard zones (Table 6).

The values of the relative relief index (Rh) ranged from 0.38 in SW4 to 1.21 in SW5. High Rh values indicate higher runoff and a greater flash flood hazard [66]. According to Rh, the sub-basins of SW5, SW1and SW3 were classified as more vulnerable to flash flooding. The ruggedness number (Rn) values ranged from 0.32 in SW1 and SW4 to 0.76 in SW6 (Table 5). High Rn values indicate faster peak flow, shorter concentration time, and a higher hydrological response [65]. Based on Rn values, the sub-basins of SW6, SW5 and SW7 were considered more vulnerable to flash flooding (Table 6).

The values of basin slope (Bs) ranged from 0.74 in SW4 to 2.46 in SW5, while slope index (SI) ranged from 0.009 in SW4 to 0.34 in SW3. These differences are attributed to the effect of geological structures and precipitation along the channels. High values of Bs and SI indicate steeper slopes, larger surface runoff volumes, greater flow peaks in the hydrograph, and a higher runoff risk [65]. SW5 and SW3 are expected to encounter higher flash flood according to Bs and SI (Table 6). Based on the topographic indicators, the sub-basins most exposed to flash flood risk are SW6, SW5 and SW3. The most influential factors are Rn, R (Fig. 4). This can be explained by dominant influence of slope direction and high terrain in SW6, compared to the average basin slope and slope degrees in other sub-basins.

Flash flood hazard map

In this assessment, 18 morphometric parameters were used to determine the degree of flash flood hazard based on the method of Davis [31]. Rn, R, and U were the parameters with the highest positive influence over flash flood risk, while SI, Lg, MRb, and WMRb, recorded the most negative influences according to importance analysis (Fig. 4). The weights (W) for each parameter were assigned individually, and a final hazard degree (H) was given for each parameter, ranging from 1 to 5, as shown in Table 6. The sub-basins were ranked according to the final hazard degree in the following order: SW6, SW5; SW 7, SW1, SW2; SW 4 and SW3.

Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin
Figure 4. The importance of morphometric parameters

The Figure 5 shows the potential flash flood hazard map based on the morphometric analysis and prioritization. The hazard degree was classified as follows: Very low hazard in SW3 with an area of 4.07 km2 (4.47%). Low hazard in SW2 and SW4 with an area of 32.92 km2 (36.15%). Moderate hazard in SW1 with an area of 6.26 km2 (6.88%). High hazard in SW5 and SW7 with an area of 22.89 km2 (25.14%). Very high hazard in SW6 with an area of 24.91 km2 (27.36%). The map shows that the southern and western sub-basins (SW5, SW6, and SW7) are the most vulnerable to flash flood risk, mainly due to their increased ruggedness (R) and relief number (Rn). On the other hand, the northern and eastern basins were found to be less vulnerable to flash flood risk due to their high bifurcation and decreased ruggedness.

Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin
Figure 5. Flash flood hazard map in the Abo Al-Ward River Basin

Conclusion

The morphometric prioritization method applied in flash flood hazard mapping is a reliable and efficient approach for the sustainable management of river basins. This method is particularly valuable in areas where flash flooding occurs frequently. This study aimed to develop a flash flood hazard map for the Abu Al-Ward River Basin in western Syria, based on morphometric analysis and utilizing 18 linear, area, and topographic parameters. The results indicated that the SW6 basin is the most vulnerable to flash flooding, which highlights the need for prompt action and the adoption of reliable hazard maps in Abu Al-Ward River Basin. The map can assist in identifying potential sites for water collection and storage in the SW6 basin, which could help to reduce the flash flood risk in SW7.

References

  1. Badenko V, Badenko N, Nikonorov A, Molodtsov D, Terleev V, Lednova J, Maslikov V. Ecological aspect of dam design for flood regulation and sustainable urban development. MATEC Web Conf. 2016;73:03003. DOI
  2. Podgornov NS, Davydov RV, Zotov DK, Antonov VI, Maslikov VI, Maslikova EI, Chusov AN, Cheremisin AV. Socio-ecological consequences during the construction of a multistage system of flood control facilities on side tributaries. J. Phys.: Conf. Ser. 2021;1942:012059. DOI
  3. Khansalari S, Ranjbar-Saadatabadi A, Fazel-Rastgar F, Raziei T. Synoptic and dynamic analysis of a flash flood-inducing heavy rainfall event in arid and semi-arid central-northern Iran and its simulation using the WRF model. Dyn. Atmos. Oceans. 2021;93:101198. DOI
  4. Prokešová R, Horáčková Š, Snopková Z. Surface runoff response to long-term land use changes: Spatial rearrangement of runoff-generating areas reveals a shift in flash flood drivers. Sci. Total Environ. 2022;815:151591. DOI
  5. Czigány S, Pirkhoffer E, Nagyváradi L, Hegedűs P, Geresdi I. Rapid screening of flash flood-affected watersheds in Hungary. Z. Geomorphol. Suppl. Issues. 2011;55:1-13. DOI
  6. Schumacher RS. Heavy Rainfall and Flash Flooding. Oxford Res. Encycl. Nat. Hazard Sci. 2017. DOI
  7. Tarolli P, Borga M, Morin E, Delrieu G. Analysis of flash flood regimes in the North-Western and South-Eastern Mediterranean regions. Nat. Hazards Earth Syst. Sci. 2012;12:1255-65. DOI
  8. Diakakis M, Priskos G, Skordoulis M. Public perception of flood risk in flash flood prone areas of Eastern Mediterranean: The case of Attica Region in Greece. Int. J. Disaster Risk Reduct. 2018;28:404-13. DOI
  9. Tichavský R, Koutroulis A, Chalupová O, Chalupa V, Šilhán K. Flash flood reconstruction in the Eastern Mediterranean: Regional tree ring-based chronology and assessment of climate triggers on the island of Crete. J. Arid Environ. 2020;177:104135. DOI
  10. Ali K, Bajracharyar RM, Raut N. Advances and Challenges in Flash Flood Risk Assessment: A Review. J. Geogr. Nat. Disasters. 2017;7:195. DOI
  11. Amirmoradi K, Shokoohi A. River Flash Flood Economical Loss and its Uncertainty in Developing Countries. Water Resour. Manag. 2023;38:81-105. DOI
  12. Subraelu P, Ahmed A, Ebraheem AA, Sherif M, Mirza SB, Ridouane FL, Sefelnasr A. Risk Assessment and Mapping of Flash Flood Vulnerable Zones in Arid Region, Fujairah City, UAE-Using Remote Sensing and GIS-Based Analysis. Water. 2023;15:2802. DOI
  13. Syed NH, Rehman AA, Hussain D, Ishaq S, Khan AA. Morphometric Analysis to Prioritize Sub-Watershed for Flood Risk Assessment in Central Karakoram National Park Using Gis/Rs Approach. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2017;IV-4/W4:367-71. DOI
  14. Mahmood S, Rahman AU. Flash flood susceptibility modeling using geo-morphometric and hydrological approaches in Panjkora Basin, Eastern Hindu Kush, Pakistan. Environ. Earth Sci. 2019;78:1. DOI
  15. Singh WR, Barman S, Tirkey G. Morphometric analysis and watershed prioritization in relation to soil erosion in Dudhnai Watershed. Appl. Water Sci. 2021;11:83. DOI
  16. Taib H, Hadji R, Bedri K, Defaflia N, Hamed Y, Gentilucci M, Barbieri M, Pambianchi G. Morphometric analysis and risk assessment of flash floods in the Atlas chain of eastern Algeria and the Algerian-Tunisian borders. Euro-Mediterr. J. Environ. Integr. 2024. DOI
  17. Shaikh M, Yadav S, Manekar V. Application of the Compound Factor for Runoff Potential in Sub-watersheds Prioritisation Based on Quantitative Morphometric Analysis. J. Geol. Soc. India. 2022;98:687-95. DOI
  18. Musaed H, El-Kenawy A, El Alfy M. Morphometric, Meteorological, and Hydrologic Characteristics Integration for Rainwater Harvesting Potential Assessment in Southeast Beni Suef (Egypt). Sustainability. 2022;14:14183. DOI
  19. Choudhari PP, Nigam GK, Singh SK, Thakur S. Morphometric based prioritization of watershed for groundwater potential of Mula river basin, Maharashtra, India. Geol. Ecol. Landsc. 2018;2:256-67. DOI
  20. Memon N, Patel DP, Bhatt N, Patel SB. Integrated framework for flood relief package (FRP) allocation in semiarid region: a case of Rel River flood, Gujarat, India. Nat. Hazards. 2019;100:279-311. DOI
  21. Kotinas VA. Prioritization of Flash Flood-Prone Areas in Small Coastal Basins around the Mediterranean Using Geomorphological Variables. J. Geogr. Environ. Earth Sci. Int. 2021;25:1-11. DOI
  22. Farhan Y, Ayed A. Assessment of Flash-Flood Hazard in Arid Watersheds of Jordan. J. Geogr. Inf. Syst. 2017;9:717-51. DOI
  23. Akay H, Baduna Koçyiğit M. Flash flood potential prioritization of sub-basins in an ungauged basin in Turkey using traditional multi-criteria decision-making methods. Soft Comput. 2020;24:14251-63. DOI
  24. Ramdani RS, Fehdi C, Gueraidia NEH, Gueraidia S, Ramdani rayene sirine. Flood Susceptibility Mapping using GIS-AHP method and morphometric analysis in the El Malabiod Watershed N.E of Algeria. Res. Sq. Prepr. 2024. DOI
  25. Sangle AS, Yannawar PL. Morphometric analysis of watershed using GIS and RS: a review. Int. J. Eng. Res. Technol. 2014;3:499-502.
  26. Abdelgawad AG, Helal E, Sobeih MF, Elsayed H. Flood hazard mapping using a GIS-based morphometric analysis approach in arid regions, a case study in the Red Sea Region, Egypt. Appl. Water Sci. 2024;14:130. DOI
  27. Sahu SR, Rawat KS. Monitoring flash flood hazard zone using morphometric parameters and GIS techniques. AIP Conf. Proc. 2024;3072:040006. DOI
  28. Alarifi SS, Abdelkareem M, Abdalla F, Alotaibi M. Flash Flood Hazard Mapping Using Remote Sensing and GIS Techniques in Southwestern Saudi Arabia. Sustainability. 2022;14:14145. DOI
  29. Schumann G, Bates PD, Apel H, Aronica GT. Global flood hazard mapping, modeling, and forecasting: Challenges and perspectives. In Global Flood Hazard: Applications in Modeling, Mapping, and Forecasting. 2018:239-44. DOI
  30. Petroselli A, Florek J, Młyński D, Książek L, Wałęga A. New Insights on Flood Mapping Procedure: Two Case Studies in Poland. Sustainability. 2020;12:8454. DOI
  31. Davis JC, Sampson RJ. Statistics and data analysis in geology. New York: Wiley; 1986.
  32. Altaf F, Meraj G, Romshoo SA. Morphometric Analysis to Infer Hydrological Behaviour of Lidder Watershed, Western Himalaya, India. Geogr. J. 2013;2013:1-14. DOI
  33. Abdo HG. Evolving a total-evaluation map of flash flood hazard for hydro-prioritization based on geohydromorphometric parameters and GIS-RS manner in Al-Hussain river basin, Tartous, Syria. Nat. Hazards. 2020;104:681-703. DOI
  34. Abdo HG, Zeng T, Alshayeb MJ, Prasad P, Ahmed MF, Albanai JA, Alharbi MM, Mallick J. Multi-criteria analysis and geospatial applications-based mapping flood vulnerable areas: a case study from the eastern Mediterranean. Nat. Hazards. 2025;121:1003-31. DOI
  35. Shaddoud MA, Costache R, Kotaridis I, Fereshtehpour M, Kuriqi A. Flash flood prioritization assessment using morphometric analysis in the coastal region of the Eastern Mediterranean. DYSONA Appl. Sci. 2025;6:172-85. DOI
  36. Abdo HG, Almohamad H, Al Dughairi AA, Karuppannan S. Sub-basins prioritization based on morphometric analysis and geographic information systems: a case study of the Barada river basin, Damascus countryside governorate, Syria. Proc. Indian Natl. Sci. Acad. 2023;89:376-85. DOI
  37. Najia F, Bouchta EF, Mohamed M, Brahim B. Evaluation of morphometric parameters and prioritization of the Oued Joumouaa watershed. Ecol. Environ. Conserv. 2021;27:S403-19.
  38. Horton RE. Erosional development of streams and their drainage basins; hydrophysical approach to quantitative morphology. Geol. Soc. Am. Bull. 1945;56:275. DOI
  39. Gregory KJ, Walling DE. Drainage basin form and process: a geomorphological approach. Edward Arnold Publishers Ltd. 1973.
  40. Schumm SA. Evolution of Drainage Systems and Slopes in Badlands at Perth Amboy, New Jersey. Geol. Soc. Am. Bull. 1956;67:597. DOI
  41. Melton MA. An analysis of the relations among elements of climate, surface properties, and geomorphology. Def. Tech. Inf. Cent. 1957. DOI
  42. Strahler AN. Dynamic basis of geomorphology. Geol. Soc. Am. Bull. 1952;63:923. DOI
  43. Strahler AN. Quantitative analysis of watershed geomorphology. Eos Trans. AGU. 1957;38:913-20. DOI
  44. Strahler AN. Quantitative geomorphology of drainage basin and channel networks. In Handbook of applied hydrology. 1964.
  45. Strahler AN. Revisions of Horton’s quantitative factors in erosional terrain. Trans. Am. Geophys. Union. 1953;34:345.
  46. Horton RE. Drainage-basin characteristics. Eos Trans. AGU. 1932;13:350-61. DOI
  47. Potter PE. A Quantitative Geomorphic Study of Drainage Basin Characteristics in the Clinch Mountain Area, Virginia and Tennessee. J. Geol. 1957;65:112-3. DOI
  48. Verstappen HT. Applied geomorphology: geomorphological surveys for environmental development. Elsevier; 1983.
  49. Youssef AM, Pradhan B, Hassan AM. Flash flood risk estimation along the St. Katherine road, southern Sinai, Egypt using GIS based morphometry and satellite imagery. Environ. Earth Sci. 2010;62:611-23. DOI
  50. Alqahtani F, Qaddah AA. GIS digital mapping of flood hazard in Jeddah-Makkah region from morphometric analysis. Arab. J. Geosci. 2019;12:6. DOI
  51. Mahmood S, Rahman AU. Flash flood susceptibility modelling using geomorphometric approach in the Ushairy Basin, eastern Hindu Kush. J. Earth Syst. Sci. 2019;128:4. DOI
  52. Abdelkader MM, Al-Amoud AI, El Alfy M, El-Feky A, Saber M. Assessment of flash flood hazard based on morphometric aspects and rainfall-runoff modeling in Wadi Nisah, central Saudi Arabia. Remote Sens. Appl. Soc. Environ. 2021;23:100562. DOI
  53. Abdelkareem M. Targeting flash flood potential areas using remotely sensed data and GIS techniques. Nat. Hazards. 2016;85:19-37. DOI
  54. Nadhim Al-neama S, Yang S, Muneer Yahya B. Evaluation of surface run-off potential of basins in Nineveh governorate, Iraq based on morphometric analysis, using RS and GIS. Mater. Today Proc. 2022;60:1753-68. DOI
  55. Kumar V. Prioritization of Sub-Watersheds Based on Morphometric Analysis of Drainage Basin-A Case Study of Medkhali River Basin in Lower Siwalik Basin, India. Int. J. Multidiscip. Approach Stud. 2017;4:4.
  56. Al-Saady YI, Al-Suhail QA, Al-Tawash BS, Othman AA. Drainage network extraction and morphometric analysis using remote sensing and GIS mapping techniques (Lesser Zab River Basin, Iraq and Iran). Environ. Earth Sci. 2016;75:18. DOI
  57. Shah SA, Shah NA, Ullah S, Alam MM, Badshah H, Ullah S, Mumtaz AS. Documenting the indigenous knowledge on medicinal flora from communities residing near Swat River (Suvastu) and in high mountainous areas in Swat-Pakistan. J. Ethnopharmacol. 2016;182:67-79. DOI
  58. Morisawa ME. Quantitative Geomorphology of Some Watersheds in the Appalachian Plateau. Geol. Soc. Am. Bull. 1962;73:1025. DOI
  59. Patel DP, Dholakia MB, Naresh N, Srivastava PK. Water Harvesting Structure Positioning by Using Geo-Visualization Concept and Prioritization of Mini-Watersheds Through Morphometric Analysis in the Lower Tapi Basin. J. Indian Soc. Remote Sens. 2011;40:299-312. DOI
  60. Smith KG. Standards for grading texture of erosional topography. Am. J. Sci. 1950;248:655-68. DOI
  61. Mishra AK, Rai SC. Geo-hydrological inferences through morphometric aspects of the Himalayan glacial-fed river: a case study of the Madhyamaheshwar River basin. Arab. J. Geosci. 2020;13:13. DOI
  62. Singh S, Singh MC. Morphometric analysis of Kanhar river basin. Natl. Geogr. J. India. 1997;43:31-43.
  63. Altaf S, Meraj G, Romshoo SA. Morphometry and land cover based multi-criteria analysis for assessing the soil erosion susceptibility of the western Himalayan watershed. Environ. Monit. Assess. 2014;186:8391-412. DOI
  64. Bhat MS, Alam A, Ahmad S, Farooq H, Ahmad B. Flood hazard assessment of upper Jhelum basin using morphometric parameters. Environ. Earth Sci. 2019;78:2. DOI
  65. Kaliraj S, Chandrasekar N, Magesh NS. Morphometric analysis of the River Thamirabarani sub-basin in Kanyakumari District, South west coast of Tamil Nadu, India, using remote sensing and GIS. Environ. Earth Sci. 2014;73:7375-401. DOI
  66. Ali U, Ali SA. Analysis of drainage morphometry and watershed prioritization of Romushi-Sasar catchment, Kashmir Valley, India using remote sensing and GIS technology. Int. J. Adv. Res. 2014;2:5-23.

Cite this article:

Shadoud, M. Ahmad, Khalil, A., Kotaridis, I., Husein, H. H., Costache, R. Morphometric analysis for flash flood hazard mapping: A case study of the Abu Al-Ward River Basin. DYSONA – Applied Science, 2025;6(2): 398-410. doi: 10.30493/das.2025.499154