Evaluation of Morphometric Parameters Studies in Middle-West Part of Kushtia District, Bangladesh, Using Remote Sensing and GIS Techniques ()

Khan M. Nasir Uddin^{*}, Md. Nozibul Haque^{}

Department of Electrical and Electronic Engineering, Islamic University, Kushtia, Bangladesh.

**DOI: **10.4236/gep.2023.111014
PDF
HTML XML
82
Downloads
474
Views
Citations

Department of Electrical and Electronic Engineering, Islamic University, Kushtia, Bangladesh.

This study finds 1D, 2D and 3D morphometric parameters of the middle-west
part of Kushtia district, Bangladesh to implement groundwater potential. For this
purpose, the SRTM (DEM) data were used to compute different parameters in GIS
environment. The values of 1D parameters like stream order, stream length and
mean bifurcation ratio was calculated as 6, 1774.72 km and 2.08 respectively.
The computed values of drainage density (0.01 - 23.06 km/km^{2}),
stream frequency (1 - 5.64 per km^{2}), drainage texture (0.25 - 0.70
km/km^{4}), length of overland flow (0.02 - 45.05 km^{2}/km),
constant of channel maintenance (0.04 -
90.04 km^{2}/km), circularity ratio (0.39 - 0.84), form factor (0.35),
elongation ratio (0.62), relief ratio (0.00 - 1.81) and ruggedness number (0.04
- 214.72) disclose the morphometrical conditions of the study area. The results
revealed from this study on drainage morphometry can be a great assistance for
understanding the hydro-geomorphological character of the area.

Keywords

Share and Cite:

Uddin, K. and Haque, M. (2023) Evaluation of Morphometric Parameters Studies in Middle-West Part of Kushtia District, Bangladesh, Using Remote Sensing and GIS Techniques. *Journal of Geoscience and Environment Protection*, **11**, 211-231. doi: 10.4236/gep.2023.111014.

1. Introduction

Quantitative analysis of the earth geometry well known as morphometry is frequently used in hydro-geomorphological analysis like the assessment of groundwater potential, groundwater management and basin management. R.E. Horton pioneered the hydrologic and hydro-morphometric analysis of basin and provided a rational and systematic place (Brinson, 1993). Smith (1950), Miller (1953), Schumm (1956), Strahler (1964), Mueller (1968) and many other researchers followed him.

Morphometric analysis requires measurement of 1D, 2D and 3D features using traditional methods (Horton, 1945; Strahler, 1957, 1964). In the last few decades, many GIS software evolved in such a way that millions of data analyses and data representation are done rapidly and cost effectively. Remote sensing data is used in GIS software in such a way that this pair became one of the strongest tools for natural resource survey and management. Using these tools, high accuracy was obtained by Moore et al. (1991) when he extracted information from DEM and analyzed for morphometric parameters in the riverine areas. Later different riverine areas of India were researched to find morphometric parameters successfully by using DEM and satellite image data (Nautiyal, 1994; Srivastava, 1997; Nag, 1998; Srinivasa Vittala et al., 2004; Sreedevi et al., 2005, 2009, 2012; Banerjee et al., 2015; Asode et al., 2016).

Significant, reliable and high accuracy results were also obtained by Sreedevi et al. (2005, 2009), Avinash et al. (2011), Altaf et al. (2013), Rao et al. (2015), and Prakash et al. (2016a, 2016b). Kumar Rai et al. (2017) found that the morphometric study with the aid of GIS software was cheaper and highly acceptable when compared to other conventional methods. So far, no morphometric analysis has been carried out in and around the area using remote sensing techniques and GIS. In this study, SRTM DEM data were used in GIS environment to evaluate 1D, 2D and 3D morphometric parameters to find groundwater potential.

2. Methodology

SRTM DEM data set (30 m resolution) was used for computing 1D, 2D and 3D morphometric parameters collected from http://earthexplorer.usgs.gov. The data set coupled with ArcGIS 10.2.1 software used here to carry out the analysis. These parameters have been calculated for identifying groundwater recharge potentiality of the study area. Flowchart of the methodology is shown in Figure 1.

The investigation was carried out on an area of greater Kushtia district of Bangladesh. It has an international border with India and located in the northern side of the southwest part of Bangladesh. This study comprised three Upazilas (Sub-districts) namely, Mirpur, Bheramara and eastern parts of Daulatpur upazilla under Kushtia district covering 539.82 km^{2} areas within geographical coordinates of 23˚45'08'' - 24˚07'52''N and 88˚51'53'' - 89˚06'18''E as shown in Figure 2. It consists of several villages, two Upazila towns. The Ganges (Padma) river and its distributary, the Hisna are the main surface water sources here.

The Ganges is flowing in the extreme north-northwest sides of the study area, whereas the Hisna is flowing through the center from the northwest corner to the southwest. Mostly the deltaic silt formed this area. The northern side is formed by alluvial sands whereas the southern is by deltaic sands.

Figure 1. Flow chart of the methodology.

2.1. 1D Parameters

Stream Order (*S _{u}*): In order to find out stream order in this study the hierarchical ordering method of Strahler (1957) was utilized. The water body branching level is generally denoted by a positive whole number.

Figure 2. Location map of the study area.

Stream Number (*N _{u}*): It is also an integer which indicates streams population for a particular stream order. In 1945, Horton informed that stream numbers reduce with increasing stream orders. Generally large stream number indicate maximum drainage in an area meaning higher runoff and less suitable for groundwater recharge.

Stream Length (*L _{u}*): Physical drainage length of water bodies in an area is known as stream length. Shorter streams generally found to be more stepper than that of longer streams which are mainly flat in nature. It was calculated in GIS environment according to Horton (1945).

Mean Stream Length (*L _{m}*): Streams of a specific order can have different lengths. Averaged value of which is mean stream length given in Equation (1). This unitless parameter indicates components’ characteristic size of drainage network.

${L}_{m}=\frac{{L}_{u}}{{S}_{u}}$ (1)

Stream Length Ratio (*R _{l}*): This unitless parameter was initially introduced by Horton (1945). This ratio is obtained by dividing entire stream lengths of two consecutive streams in descending orders as shown in Equation (2).

${R}_{l}=\frac{{L}_{u}}{{L}_{u-1}}$ (2)

Here, the numerator and denominator are the stream length in descending orders.

Bifurcation Ratio (*R _{b}*): Horton (1945) introduced this drainage parameter. It is found by dividing stream numbers of two consecutive orders given by the Equation (3).

${R}_{b}=\frac{{N}_{u}}{{N}_{u+1}}$ (3)

where *N _{u}* and

Rho Coefficient (*q*): This is a very important parameter indicating the storage capacity of a drainage network (Horton, 1945), hence the groundwater potential. Mathematically, it can be obtained by dividing stream length ratio by bifurcation ratio which is ultimately unitless given in Equation (4).

$q=\frac{{R}_{l}}{{R}_{b}}$ (4)

Higher the value of *q*, higher chance of flooding in that area and very good change for groundwater recharge.

2.2. 2D Parameters

Drainage Density (*D** _{d}*): Sum of stream lengths per unit area is known as drainage density (Horton, 1945) given in the Equation (5). It is very important parameter for drainage analysis of an area.

${D}_{d}=\frac{L}{A}$ (5)

where entire length of streams and unit area are denoted by *L* and *A* respectively. Areas with lower density are good for groundwater recharge potential and flooding.

Stream Frequency (*F _{s}*): It is defined as the population of streams per unit area (Horton, 1945) as mentioned in Equation (6).

${F}_{s}=\frac{N}{A}$ (6)

*N* indicates entire population of streams in area *A*. Lower stream frequency is good for better groundwater recharge.

Drainage Texture (*D _{t}*): This parameter is formulated as the product of

${D}_{t}={D}_{d}\times {F}_{s}$ (7)

Lower drainage texture indicates the higher infiltration and lower run-off.

Constant of Channel Maintenance (*C*): This parameter was introduced by Schumm (1956), which is the reciprocal of drainage density given in Equation (8).

$C=\frac{1}{{D}_{d}}$ (8)

The constant indicates the area required per kilometer long streams of all orders. Larger value of *C* is better for groundwater recharge.

Length of Overland Flow (*L _{g}*): It is the measure of length of water over the ground surface before being concentrated into particular channels of streams. Mathematically it is half of

${L}_{g}=\frac{C}{2}=\frac{1}{2{D}_{d}}$ (9)

Circularity ratio (*R*_{c}): This ratio can be found by dividing area of study by a circle area having equal perimeter (Miller, 1953) given by the Equation (10).

${R}_{c}=\frac{4\pi A}{{P}^{2}}$ (10)

where perimeter of the circle is *P*. The ratio value close to unity means area is circular and less favorable for groundwater recharge.

Form Factor (*F _{f}*): The value of the parameter can be found by dividing area of study by the area made from the maximum length of the study area. Most cases

${F}_{f}=\frac{A}{{L}_{b}^{2}}$ (11)

where *L _{b}* is the length of the study area.

Elongation Ratio (*R _{e}*): This 2D parameter is defined as the ratio of a circle diameter formed by the area investigated to its maximum length (Schumm, 1956). Mathematically it can be written as Equation (12) below.

${R}_{e}=\frac{2\sqrt{\frac{A}{\pi}}}{{L}_{b}}$ (12)

More the value of this parameter more the area will be circular which is less favorable for groundwater recharge.

2.3. 3D Parameters

Absolute Relief (*R _{a}*): It is defined as elevation of given location. Generally, we obtain it from DEM data directly.

Relative Relief (*R _{r}*): Schumm (1956) used the formula given below in Equation (13) to find relative relief of an area. It is actually defined by the Equation (13):

${R}_{r}=H-h$ (13)

where, maximum and minimum elevation within the unit area are denoted as H and h respectively.

Relief Ratio (*R _{rr}*): Ratio of relative relief to the length of study area (Schumm, 1956) is known as relief ratio which is given in Equation (14).

${R}_{rr}=\frac{{R}_{r}}{{L}_{b}}$ (14)

Its lower value indicates lower gradient and favorable for groundwater recharge.

Ruggedness Number (*R _{n}*): Relative relief and drainage density product gives ruggedness number of the area of study (Strahler, 1958) as shown in Equation (15).

${R}_{n}={R}_{rr}\times {D}_{d}$ (15)

The low ruggedness value means less susceptible to soil erosion that results higher chance of groundwater recharge.

Different 1D, 2D and 3D morphometric parameters have been calculated for identifying groundwater recharge potentiality for the study area.

3. Results and Discussion

Quantitative analyses of earth geometry are immense assistance in managing and utilizing water resources properly. Remotely sensed data set were used to perform the morphometric analysis. The study area has been investigated for different morphometric characteristics by computing different 1D, 2D and 3D parameters. At first drainage pattern of the area was depicted using GIS software as shown in Figure 3.

3.1. 1D Parameters

In this investigation, seven 1D parameters have been calculated using different tools in GIS environment. Details of these parameters are discussed below:

3.1.1. Stream Ordering (*S _{u}*)

It is usual that streams of different size, shape and order flow in an area. It is seen that streams merged together to form bigger streams. So, it is important to know the order of a stream and how do it position in the stream’s hierarchy, and stream order is the way to know that (Horton, 1945; Strahler, 1957). Actually, morphometric analysis starts with the finding out of stream orders. It provides very important information regarding drainage network of an area. Strahler’s (1964) method for stream ranking was used here in GIS environment. It was found that there are 3420 streams of different ranks flowing as drainage network in the investigated area. Highest rank of the stream order is 6. Lower ranked streams mostly found in the relatively elevated regions compared to higher rank. Figure 4 showed the stream ordering of the area of study.

Figure 3. Drainage pattern of study area.

Figure 4. Stream order.

3.1.2. Stream Number (*N _{u}*)

In this investigation, the maximum number of streams is observed in the first-order and counted to 1745, whereas the minimum number of 81 streams is observed for 6^{th} order. Second order streams are 820. The third and fourth order was relatively close with numbers 374 and 318. Fifth order is counted to 82 and very close to the 6^{th} order. It is closely observed that stream numbers significantly decreasing with increasing stream orders. Table 1 and Figure 5 showed stream ordering and stream numbers. The first three as well as fifth stream orders show normal tendency of stream branching, but it was not found for the fourth and sixth stream orders. This type of stream branching results a poor drainage network, and often cause flooding or slow stream flow which makes the study area a good potential for groundwater recharge.

Figure 5. Steam order and stream number.

Table 1. Stream order (*S _{u}*), stream number (

3.1.3. Stream Length (*L _{u}*)

GIS environment profoundly used to calculate and measure stream length in the area of study and tabulated in Table 2. It showed different stream lengths for different stream orders. Surface runoff characteristics significantly influenced by stream length which actually consider as an important hydrological parameter. Smaller streams are found in areas with steep slope. Flatter plain provides opportunity to have longer stream lengths (Strahler, 1964). Stream length of 1031.90 km measured in the first order found to be maximum among the total extracted lengths of 1774.72 km. Sixth order streams have the minimum length of 23.95 km. Among others second, third, fourth and fifth order streams occupied 405.61 km, 162.86 km, 117.97 km and 32.42 km respectively. It is closely observed that stream lengths shrank with increasing stream order (Figure 6).

Figure 6. Steam order and stream length.

Table 2. Stream order (*S _{u}*), stream length (

3.1.4. Mean Stream Length (*L _{m}*)

The characteristics of an area are revealed from mean stream length and have significant influence on the surface. It can be found by different component analysis of drainage network (Strahler, 1964). It was calculated using Equation (1). It revealed that *L _{m}* values confined in the 0.59 to 0.30 range. The

3.1.5. Stream Length Ratio (*R _{l}*)

With the help of Equation (2) this parameter has been calculated and tabulated in Table 2. Highest and lowest value of this parameter were 0.74 and 0.27 observed for sixth order and fifth order stream respectively, the average being 0.42. Higher value of *R _{l}* indicates the abnormality in drainage network. Abnormalities are found in between stream 4 and stream 3 lengths as well as in streams 6 and stream 5. These types of drainage network often cause very low drainage water movement, which facilitates a good chance for water to percolate.

3.1.6. Bifurcation Ratio (*R _{b}*)

It is very important morphometric parameter which can predict flood prone zones (Prabhakaran & Raj, 2018). Using Equation (3), this parameter has been estimated and shown in Table 1. Highest and lowest value of the parameter was 3.88 and 1.01 found for fifth order and sixth order stream respectively, whereas the average value was 2.08. Lower mean bifurcation ratio means the area is flat or rolling surface more likely to be affected by the flood and highly favorable for groundwater recharge. Higher bifurcation ratio is seen near areas near close to rivers.

3.1.7. Weighted Mean Bifurcation Ratio (*R _{bwm}*)

Proposed method of Schumm (1956) was used here to calculate this parameter. The *R** _{bwm}* found in this study is 2.12 (Table 1). It is close to average value of bifurcation ratio. Low value of this parameter indicates areas with very low slope and often affected by flood.

3.1.8. Rho Coefficient (*q*)

It is considered to be a vital parameter in morphometric analysis of an area. Here, it was calculated using Equation (4) and tabulated in Table 1. Higher the value of *q*, the more is the storage in the drainage network which in turn can cause flooding. Parameter value confined in between 0.06 and 0.73. The zones having lower slope and faulty drainage pattern with higher stream order facilitate low water current. Hence, it makes a greater scope of flooding and groundwater recharge.

3.2. 2D Parameters

3.2.1. Drainage Density (*D _{d}*)

It is one of the most significant morphometric parameters of an area. Groundwater recharge potentiality exclusively depends on this factor as well. It indicates how closely drainage channels are distributed in an area. Its value depends on many surface and sub-surface parameters. Low permeability of subsoil materials, flat or very small steepness of lands and high vegetation results very small drainage density (Nag, 1998). Low drainage density values provide higher chance of flooding and groundwater recharge hence good groundwater potentiality. High relief, small vegetation and higher permeability provide good reasons for higher drainage density. The *D _{d}* value of the area ranging from 0.01 to 23.06 km/km

3.2.2. Stream Frequency (*F _{s}*)

Here Equation (6) was used to calculate this parameter. *F _{s}* values of this study are in the range of 1.00 - 5.64 no. of streams per km

Figure 7. Drainage density.

Figure 8. Steam frequency.

3.2.3. Drainage Texture (*D _{t}*)

It denotes relative positioning of drainage network. Smith (1950) classified drainage texture to 5 categories based on drainage density. In this study, *D _{t}* values were calculated using Equation (7) and depicted in Figure 9. The parameter varied in between 0.25 to 7.70, and it lies in the range of very coarse to moderate coarse based on drainage density. It is revealed from the results that it followed a very closer drainage texture pattern.

3.2.4. Constant of Channel Maintenance (*C*)

This morphometric parameter was calculated using Equation (8) and represented in Figure 10. The *C* values of this area are in the range of 0.04 to 90.09 km^{2}/km. In most of the areas *C* value is below 0.24 m and next channel length is as much as 28.25 m covers almost entire area. Areas with lower *C* values mean quick water discharge hence less favorable for groundwater recharge and vice versa.

3.2.5. Length of Overland Flow (*L _{g}*)

The calculated values of *L _{g}* using Equation (9) are shown in Figure 11. It is seen that

Figure 9. Drainage texture.

Figure 10. Constant of channel maintenance.

Figure 11. Length of overland flow.

3.2.6. Circulatory Ratio (*R _{c}*)

The estimated circulatory ratio of the area using Equation (10) is shown in Figure 12. Here, *R _{c}* values varied from 0.39 to 0.84. Low

3.2.7. Form Factor (*F _{f}*)

This morphometric parameter measures different types of erosional process, movements of sediments, flood formation and corridor of flood. For a perfect circle *F _{f}* value is 1, when it is nearing zero it means elongated area. Here it was calculated using Equation (11) and found its value as 0.31 which indicates the area slightly elongated in shape. Hence, flood probability is high as transport rate is low. This area is favorable for groundwater recharge potential.

3.2.8. Elongation Ratio (*R _{e}*)

Generally, *R _{e}* values lie between 0.6 to 1 depending on different climatic and geologic types (Rudraiah et al., 2008). Equation (12) was used to calculate this parameter, and its value is 0.62 for the area studied. So, this area is moderately elongated. It provides relatively larger time to travel from one side to another of the study area, which in turn preferable for groundwater recharge.

Figure 12. Circulatory ratio.

3.3. 3D Parameter

3.3.1. Absolute Relief and Relative Relief

Absolute relief and relative relief are 3D morphometric parameters of an area. Absolute relief was readily available from SRTM (DEM) data. It was presented in Figure 13. The relative relief was estimated using Equation (13) with the help of GIS software and depicted in Figure 14. Areas with low relative relief increase the probability of surface water body, flooding and groundwater recharge.

3.3.2. Relief Ratio (*R _{r}*)

Overall steepness of an area is described by the relief ratio, a key indicator of entire erosional process of an area. Relief ratio calculated using Equation (14) for this study is found to be 0 1.81 (Figure 15). It is highly connected with the hydrologic character of the study area and erosional process. This value is high near rivers whereas the remaining areas are mostly flat indicating the favorability for groundwater recharge.

3.3.3. Ruggedness Number (*R _{n}*)

This morphometric parameter mostly used to measure undulation of surface topography (Selvan et al., 2011). This parameter was calculated using Equation (15). Ruggedness number of the area studied ranges from 0.04 to 214.72 as shown in Figure 16. When drainage density is high with high relief of a basin, the ruggedness number of that river basin will also be high (Chow, 1964). High *R** _{n}* value is observed in the riverine area where dominant part is below the value 25.24 spreading over the area.

Figure 13. Absolute relief.

Figure 14. Relative relief.

Figure 15. Relief ratio.

Figure 16. Ruggedness number.

4. Conclusion

The morphometric analysis provides very useful information to evaluate surface water resource conservation, and their management. It can be applied to even smaller areas. The evolved drainage is dendritic in nature. The highest number of streams is found for lower order occupying most drainage lengths. The lower value for weighted mean bifurcation ratio increases the chance of flooding and groundwater recharge. Moderately elongated shape of the area was verified by form factor, circulatory ratio and elongation ratio values, which in turn provide high groundwater potential.

This study also showed efficient use of GIS techniques coupled with SRTM (DEM) data to evaluate 1D, 2D and 3D morphometric parameters which might be of great help for planners and decision-makers to develop sustainable strategies for water resource management.

Acknowledgements

This research is financed by the Ministry of Science and Technology (MOST), Bangladesh.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

[1] |
Altaf, F., Meraj, G., & Romshoo, S. A. (2013). Morphometric Analysis to Infer Hydrological Behaviour of Lidder Watershed, Western Himalaya, India. Geography Journal, 2013, Article ID: 178021. https://doi.org/10.1155/2013/178021 |

[2] |
Asode, A. N., Sreenivasa, A., & Lakkundi, T. K. (2016). Quantitative Morphometric Analysis in the Hard Rock Hirehalla Sub-Basin, Bellary and Davanagere Districts, Karnataka, India Using RS and GIS. Arabian Journal of Geosciences, 9, Article No. 381. https://doi.org/10.1007/s12517-016-2414-x |

[3] |
Avinash, K., Jayappa, K. S., & Deepika, B. (2011). Prioritization of Sub Basins Based on Geomorphology and Morphometric Analysis Using Remote Sensing and Geographic Information System (GIS) Techniques. Geocarto International, 26, 569-592. https://doi.org/10.1080/10106049.2011.606925 |

[4] |
Banerjee, A., Singh, P., & Pratap, K. (2015). Morphometric Evaluation of Swarnrekha Watershed, Madhya Pradesh, India: An Integrated GIS-Based Approach. Applied Water Science, 7, 1807-1815. https://doi.org/10.1007/s13201-015-0354-3 |

[5] | Brinson, M. M. (1993). A Hydrogeomorphological Classification for Wetlands. Technical Report, US Army Corps of Engineers, Waterways Experiment Station. |

[6] | Chow, V. T. (1964). Handbook of Hydrology. McGraw Hill. |

[7] |
Horton, R. E. (1945). Erosional Development of Streams and Their Drainage Basins. Bulletin of the Geological Society of America, 56, 275-370. https://doi.org/10.1130/0016-7606(1945)56[275:EDOSAT]2.0.CO;2 |

[8] |
Kumar Rai, P., Narayan Mishra, V., & Mohan, K. (2017). A Study of Morphometric Evaluation of the Son Basin, India Using Geospatial Approach. Remote Sensing Applications: Society and Environment, 7, 9-20. https://doi.org/10.1016/j.rsase.2017.05.001 |

[9] | Miller, V. C. (1953). A Quantitative Geomorphic Study of Drainage Basin Characteristics in the Clinch Mountain Area, Virginia and Tennessee (pp. 389-402). Colombia University. |

[10] |
Moore, I. D., Grayson, R. B., & Ladspm, A. R. (1991). Digital Terrain Modelling: A Review of Hydrological, Geomorphological and Biological Applications. Hydrological Processes, 5, 3-30. https://doi.org/10.1002/hyp.3360050103 |

[11] |
Mueller, J. E. (1968). An Introduction to the Hydraulic and Topographic Sinuosity Indexes. Annals of the Association of American Geographers, 58, 371-385. https://doi.org/10.1111/j.1467-8306.1968.tb00650.x |

[12] |
Nag, S. (1998). Morphometric Analysis Using Remote Sensing Techniques in the Chaka Sub-Basin, Purulia District, West Bengal. Journal of the Indian Society of Remote Sensing, 26, 69-76. https://doi.org/10.1007/BF03007341 |

[13] |
Nautiyal, M. D. (1994). Morphometric Analysis of a Drainage Basin Using Aerial Photographs: A Case Study of Khairkuli Basin, District Dehradun, U.P. Journal of the Indian Society of Remote Sensing, 22, 251-261. https://doi.org/10.1007/BF03026526 |

[14] |
Prabhakaran, A., & Jawahar Raj, N. (2018). Drainage Morphometric Analysis for Assessing form and Processes of the Watersheds of Pachamalai Hills and Its Adjoinings, Central Tamil Nadu, India. Applied Water Science, 8, Article No. 31. https://doi.org/10.1007/s13201-018-0646-5 |

[15] | Prakash, K., Mohanty, T., Singh, S., Chaubey, K., & Prakash, P. (2016a). Drainage Morphometry of the Dhasan River Basin, Bundelkhand Craton, Central India Using Remote Sensing and GIS Techniques. Journal of Geomatics, 10, 21-132. |

[16] | Prakash, K., Singh, S., & Shukla, U. K. (2016b). Morphometric Changes of the Varuna River Basin, Varanasi District, Uttar Pradesh. Journal of Geomatics, 10, 48-54. |

[17] |
Rao, L., Ansari, Z., Sadiq Mirza, M., & Yusuf, A. (2015). Morphometric Studies Using Remote Sensing and GIS Techniques in Bah Tehsil, Agra District, Uttar Pradesh. Journal of the Geological Society of India, 85, 197-205. https://doi.org/10.1007/s12594-015-0206-7 |

[18] |
Rudraiah, M., Govindaiah, S., & Vittala, S. S. (2008). Morphometry Using Remote Sensing and GIS Techniques in the Sub-Basins of Kagna River Basin, Gulburga Basin District, Karnataka, India. Journal of the Indian Society of Remote Sensing, 36, 351-360. https://doi.org/10.1007/s12524-008-0035-x |

[19] |
Schumm, S. (1956). Evolution of Drainage Systems and Slopes in Badlands at Perth Amboy, New Jersey. Geological Society of America Bulletin, 67, 597-646. https://doi.org/10.1130/0016-7606(1956)67[597:EODSAS]2.0.CO;2 |

[20] | Selvan, M. T., Ahmad, S., & Rashid, S. M. (2011). Analysis of the Geomorphometric Parameters in High Altitude Glacierised Terrain Using SRTM DEM Data in Central Himalaya, India. ARPN Journal of Science and Technology, 1, 22-27. |

[21] |
Smith, K. G. (1950). Standards for Grading Texture of Erosional Topography. American Journal of Science, 248, 655-668. https://doi.org/10.2475/ajs.248.9.655 |

[22] |
Sreedevi, P. D., Owais, S., Khan, H. H., & Ahmed, S. (2009). Morphometric Analysis of a Watershed of South India Using SRTM Data and GIS. Journal of the Geological Society of India, 73, 543-552. https://doi.org/10.1007/s12594-009-0038-4 |

[23] |
Sreedevi, P. D., Sreekanth, P. D., Khan, H. H., & Ahmed, S. (2012). Drainage Morphometry and Its Influence on Hydrology in an Semi Arid Region: Using SRTM Data and GIS. Environmental Earth Sciences, 70, 839-848. https://doi.org/10.1007/s12665-012-2172-3 |

[24] |
Sreedevi, P. D., Subrahmanyam, K., & Ahmed, S. (2005). Integrated Approach for Delineating Potential Zones to Explore for Groundwater in the Pageru River Basin, Cuddapah District, Andhra Pradesh, India. Hydrogeology Journal, 13, 534-543. https://doi.org/10.1007/s10040-004-0375-8 |

[25] |
Srinivasa Vittala, S., Govindaiah, S., & Honne Gowda, H. (2004). Morphometric Analysis of Sub-Watersheds in the Pavagada Area of Tumkur District, South India Using Remote Sensing and GIS Techniques. Journal of the Indian Society of Remote Sensing, 32, 351-362. https://doi.org/10.1007/BF03030860 |

[26] |
Srivastava, V. K. (1997). Study of Drainage Pattern of Jharia Coalfield (Bihar), India, through Remote Sensing Technology. Journal of the Indian Society of Remote Sensing, 25, 41-46. https://doi.org/10.1007/BF02995417 |

[27] |
Strahler, A. N. (1957). Quantitative Analysis of Watershed Geomorphology. Eos, Transactions American Geophysical Union, 38, 913-920. https://doi.org/10.1029/TR038i006p00913 |

[28] |
Strahler, A. N. (1958). Dimensional Analysis Applied to Fluvially Eroded Landforms. Geological Society of America Bulletin, 69, 279-300. https://doi.org/10.1130/0016-7606(1958)69[279:DAATFE]2.0.CO;2 |

[29] | Strahler, A. N. (1964). Quantitative Geomorphology of Drainage Basins and Channel Networks, Section 4-11. In V. T. Chow (Ed.), Handbook of Applied Hydrology. McGraw Hill. |

Journals Menu

Contact us

+1 323-425-8868 | |

customer@scirp.org | |

+86 18163351462(WhatsApp) | |

1655362766 | |

Paper Publishing WeChat |

Copyright © 2024 by authors and Scientific Research Publishing Inc.

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.